Quantification of Health Commodities: RMNCH - Supplement Forecasting Consumption of Select Reproductive, Maternal, Newborn, and Child Health Commodities

Publication date: 2016

Quantification of Health Commodities: RMNCH Supplement Forecasting Consumption of Select Reproductive, Maternal, Newborn, and Child Health Commodities Updated June 2016 Quantification of Health Commodities RMNCH Supplement 2 JSI Research & Training Institute, Inc., and Management Sciences for Health This manual represents the combined efforts of JSI Research & Training Institute, Inc. and the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program, funded by US Agency for International Development and implemented by Management Sciences for Health. This document is made possible in part by the generous support of the American people through the US Agency for International Development (USAID), under the terms of cooperative agreement number AID-OAA-A-11-00021. The contents are the responsibility of Management Sciences for Health and do not necessarily reflect the views of USAID or the United States Government. Support for this work was also provided by the United Nations Children’s Fund (UNICEF). The views expressed by the authors do not necessarily reflect the view of UNICEF. UNICEF and JSI Research & Training Institute, Inc. (JSI) shall have the right to duplicate, use, or disclose the data to the extent provided in the agreement. This restriction does not limit UNICEF’s right to use information contained in these data if it is obtained from another source without restriction. About SIAPS The goal of the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program is to assure the availability of quality pharmaceutical products and effective pharmaceutical services to achieve desired health outcomes. Toward this end, the SIAPS result areas include improving governance, building capacity for pharmaceutical management and services, addressing information needed for decision-making in the pharmaceutical sector, strengthening financing strategies and mechanisms to improve access to medicines, and increasing quality pharmaceutical services. About JSI JSI Research & Training Institute, Inc. (JSI) is a U.S.-based health care consulting firm committed to improving the health of individuals and communities worldwide. Our multidisciplinary staff works in partnership with host-country experts, organizations, and governments to make quality, accessible health care a reality for children, women, and men around the world. JSI’s headquarters are in Boston, Massachusetts, with U.S. offices in Washington, D.C.; Atlanta, Georgia; Burlington, Vermont; Concord, New Hampshire; Denver, Colorado; Providence, Rhode Island; and San Francisco, California. JSI also maintains offices in more than 40 countries throughout the developing world. Quantification of Health Commodities RMNCH Supplement 3 Recommended Citation This report may be reproduced if credit is given to SIAPS and JSI. Please use the following citation. JSI and SIAPS. 2015. Quantification of Health Commodities: RMNCH Supplement Forecasting Consumption of Select Reproductive, Maternal, Newborn and Child Health Commodities. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. Submitted to the United Nations Children’s Fund by JSI, Arlington, VA: JSI Research & Training Institute, Inc. This work is based on Quantification of Health Commodities developed by the USAID | DELIVER PROJECT and is modeled on other “Companion Guides” written by the Project for ARVs, HIV Test Kits, Laboratory Commodities, and Contraceptives, and on the Manual for Quantification of Malaria Commodities published by the Strengthening Pharmaceutical Systems Program. Parts of this document were originally published in: USAID | DELIVER PROJECT, Task Order 4. 2011. Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4 and USAID | DELIVER PROJECT, Task Order 1. 2008. Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 1 They are reprinted with permission. Systems for Improved Access to Pharmaceuticals and Services Center for Pharmaceutical Management Management Sciences for Health 4301 North Fairfax Drive, Suite 400 Arlington, VA 22203 USA Telephone: 703.524.6575 Fax: 703.524.7898 E-mail: siaps@msh.org Website: www.siapsprogram.org JSI Research & Training Institute, Inc. 1616 Fort Myer Drive, 16th Floor Arlington, VA 22209 USA Tel +1 703 528 7474 Fax +1 703 528 7480 www.jsi.com Quantification of Health Commodities RMNCH Supplement 4 Contents 5 Summary . 7 Acronyms . 9 Acknowledgments . 11 Section 1. Introduction . 13 Section 2. Forecasting Algorithms . 23 Section 2.1 Forecasting Algorithms for Family Planning Products . 24 Emergency Contraceptive Pills . 25 Female Condoms . 40 Contraceptive Implants. 51 Section 2.2. Forecasting Algorithms for Maternal Health Products . 66 Magnesium Sulfate . 67 Misoprostol . 74 Oxytocin . 83 Section 2.3. Forecasting Algorithms for Newborn Health Products . 91 Antenatal Corticosteroids . 92 Chlorhexidine . 99 Antibiotics for possible severe bacterial infection in newborns . 106 Neonatal Resuscitation Commodities . 116 Section 2.4. Forecasting Algorithms for Child Health Products . 131 Amoxicillin . 132 Zinc and Oral Rehydration Salts . 144 Section 3: Tools and Resources for Quantification . 156 Tools and Resources for Quantification . 158 Glossary . 167 Annexes . 169 Annex A. Flow of Data in Quantification . 170 Annex B: Types of Data Used for Forecasting Consumption of Health Commodities . 171 Contents 6 Summary 7 This guide will assist program managers, service providers, and technical experts when conducting a quantification of commodity needs for the 13 reproductive, maternal, newborn, and child health commodities prioritized by the UN Commission on Life-Saving Commodities for Women and Children. This quantification supplement should be used with the main guide—Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement. * This supplement describes the steps in forecasting consumption of these supplies when consumption and service data are not available; after which, to complete the quantification, the users should refer to the main quantification guide for the supply planning step. * USAID | DELIVER PROJECT, Task Order 4. 2014. Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. Summary 8 Acronyms 9 ACS antenatal corticosteroids ANC antenatal care ARI acute respiratory infection Beta-AC betamethasone acetate Beta-PO4 betamethasone phosphate Beta betamethasone CH child health CHERG Child Health Epidemiology Reference Group CHW community health worker COC combined oral contraceptive CPR contraceptive prevalence rate CSO Civil Society Organization CYP Couple-Years of Protection Dexa dexamethasone DHS Demographic and Health Survey DT dispersible tablet EC emergency contraception ECP emergency contraceptive pill EML Essential Medicines List EMLc Essential Medicines List of Children FP family planning FSW female sex worker GBV gender-based violence HBB Helping Babies Breathe HMIS health management information system iCCM Integrated community case management ICEC International Consortium for Emergency Contraception IDPIG International Drug Price Indicator Guide (MSH publication) IM intramuscular IU international units IV intravenous JSI JSI Research & Training Institute, Inc. LAPM long acting and permanent methods LARC long acting reversible contraception LMIS logistics management information system MCH maternal and child health MEC Medical Eligibility Criteria (WHO publication) MH maternal health MICS multiple indicator cluster survey MNCH maternal, newborn, and child health MSH Management Sciences for Health MWRA married women of reproductive age NAC National AIDS Council or Commission or Control program NGO nongovernmental organization OC oral contraceptive ORS oral rehydration salts OTC over the counter PAC post-abortion care PE/E pre-eclampsia and eclampsia PPH postpartum hemorrhage Acronyms 10 PSBI possible severe bacterial infection RSD respiratory distress syndrome RH reproductive health RHS Reproductive Health Survey RHSC Reproductive Health Supplies Coalition RMNCH reproductive, maternal, newborn, and child health SIAPS Systems for Improved Access to Pharmaceuticals and Services [Program] SOH stock on hand SRH sexual and reproductive health STG standard treatment guideline STI sexually transmitted infection TFR total fertility rate UNCoLSC United Nations Commission on Life-saving Commodities for Women and Children UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund USAID United States Agency for International Development WHO World Health Organization WRA women of reproductive age Acknowledgments 11 Authors: JSI: Ellie Bahirai, Jane Feinberg, Alexis Heaton SIAPS: Jane Briggs, Reem Ghoneim, Rima Shretta, Beth Yeager PATH: Fay Venegas The authors would like to thank the following individuals for their valuable contributions: Kabir Ahmed (UNFPA), Laila Akhlaghi (JSI), Claudia Allers (JSI), Mags Beksinska, (University of the Witwatersrand), Malia Boggs (USAID), Martha Brady (Population Council), Neal Brandes (USAID), Tracey Brett (MSI), Siobhan Brown (PATH), Patricia Coffey (PATH), Carmela Cordero (EngenderHealth), Jean-Bernard Delbarre (HRA Pharma Company’s Foundation), Bidia Deperthes (UNFPA), Nel Druce (DfID), Suzanne Diarra (MSH/ SIAPS) Maxine Eber (PSI), Michael Egharevba (JSI), Laura Frye (Gynuity), Om Garg (Cupid Ltd), Nancy Goh (CHAI), Rehana Gubin (Jhpiego), Lisa Hedman (WHO), Tara Herrick (PATH), Steve Hodgins (Save the Children), Tony Hudgins (JSI), Saskia Husken, (UAFC), Roy Jacobstein (EngenderHealth), Monica Kerrigan (BMGF), Damien Kirchhoffer (CHAI), Koen Kruytbosch (Merck), Barbara Lamphere (JSI), Victor Lara (PSI), Ashley Latimer (PATH), Nilza LoForte (USAID | DELIVER PROJECT), Trisha Long (JSI), Richard Lowe (VSI), Vicky MacDonald (Abt Associates), Joe McCord (JSI), Mutsumi Metzler (PATH), Glenn Milano (USAID), Nicola Moore (CHAI), Golam Mohammad Kibria (SIAPS), Beatrice Mutali (Merck), Jovith Ndahinyuka (USAID | DELIVER PROJECT), Keith Neroutsos (PATH), Elizabeth Obaje (USAID | DELIVER PROJECT), Andualem Oumer (SIAPS/MSH). Chris Purdy (DKT International), Manjari Quintanar Solares (PATH), Kate Rademacher (FHI360), Greg Roche (JSI), Suzy Sacher (JSI), Joel Segre (BMGF), John Skibiak (RHSC), Cary Spisak (JSI), Laurentiu Stan (JSI), Markus Steiner (FHI360), Eric Takang (JSI), John Townsend (Population Council), Karma Tshering (UNFPA), Morgan Van Dyke (PATH), Annette Velleuer (Bayer), Hans Vemer (Jhpiego), Donna Vivio (USAID), Steve Wall (Save the Children), Jayne Waweru (JSI), Elizabeth Westley (ICEC), Jillian Zemanek (PATH), Rabson Zyambo (USAID | DELIVER PROJECT) In addition, the authors extend special thanks to the Helping Babies Breathe program, the American Academy of Pediatrics, and the Ministries of Health of Uganda and Tanzania for providing valuable input and insights contributing to the material about neonatal resuscitation equipment. Acknowledgments 12 Quantification of Health Commodities RMNCH Supplement 13 Section 1 | Introduction 14 The United Nations Commission on Life-Saving Commodities for Women and Children (the Commission), a part of the Every Woman, Every Child movement, aims to increase access to 13 life-saving commodities in 50 of the world’s poorest countries. The Commission identified and endorsed an initial list of 13 overlooked reproductive, maternal, newborn, and child health (RMNCH) commodities that, if more widely accessed and properly used, could save the lives of more than 6 million women and children per year.1 These 13 commodities have diverse characteristics: some are new products that are in the process of being introduced at scale and some are products that have been in use for many years but are under-used or not available when needed or in the recommended formulation. However, one commonality shared by all is the need to increase access to these commodities among the women and children who need or want them. A major component of access is availability and to ensure availability, accurate estimates of supply requirements are needed. At the global level, this information can inform both donors’ plans for procurement and manufacturers’ plans for production. At the national level, this information is also essential for budgeting, resource mobilization, and planning for procurement and supply chain operations. Currently, accurate estimates of need are unavailable for many of the 13 commodities at either the global or national levels. Therefore, many of the Commission’s work plans have included activities related to collecting this information through market sizing or quantification exercises. The Commission’s 2012 report also notes that improved quantification efforts are needed as part of supply chain improvement. This guide provides practical guidance on estimating the quantities of supplies needed by programs as part of a national quantification exercise. While this guidance was developed primarily for public sector and nongovernmental program (NGO) programs, the methodology presented could also be relevant for forecasting of commodity needs for the private sector. Since many terms related to quantification and forecasting were used in the work plans of the Commission working groups and technical resource teams in different ways, the following working definitions were agreed upon to delineate the focus of the activities and to attempt to harmonize vocabulary across all Commission activities. These definitions are consistent with those used in the general quantification guide, Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement. Quantification answers the question, “How much should be procured and when should it be delivered?” Quantification includes both forecasting and supply planning. It is the process of estimating the quantities and costs of the products required for a specific health program (or service), and determining when the products should be delivered to ensure an uninterrupted supply for the program. Quantification takes into account the expected demand for commodities, unit costs, existing stocks, stock already on order, expiries, lead time, minimum and maximum stock levels, and shipping costs. Using this information, the total commodity requirements and costs for the program are calculated and compared with the available financial resources to determine the final quantities to procure. The two sub-processes of quantification, forecasting and supply planning, are defined as follows: Section 1 | Introduction 15 x Forecasting answers the question: “How much is needed, in quantities, to meet the health demand of the population?” Forecasting is the process of estimating the quantities of products that will actually be dispensed or used to meet the health needs of the targeted population during a specific future period of time. Forecasting can be based on historical consumption (quantities dispensed or used), services, morbidity and/or demographic data, and assumptions about future demand, program plans, and performance. When historical data are unavailable or unreliable, assumptions will also be needed to estimate program performance and product consumption. x The supply plan is the final output of the quantification, and details the total product quantities and costs required to fill the supply pipeline to ensure optimal procurement and delivery schedules, taking into account lead times, minimum and maximum stock levels, and desired arrival dates of shipments. For definitions of additional terms related to forecasting and supply planning, please consult the Glossary at the end of this document. This guide will assist program managers, service providers, and technical experts involved in quantification of RMNCH commodities with detailed guidance on best practice demographic and morbidity-based forecasting methodologies, in order to improve the quality of national- level forecasts of life-saving commodities when consumption and services data are not available. This document serves as a supplement to and should be used in conjunction with Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement produced by the USAID | DELIVER PROJECT and updated in 2014(hereafter referred to as Quantification of Health Commodities). This document is not meant to provide general guidance on managing maternal and child health or family programs, nor does it offer programmatic guidance on selecting or administering the products used in a country. Rather, this guide will assist stakeholders to— x Gather and analyze the data needed to prepare the forecast x Build forecasting assumptions to account for data gaps, programmatic considerations, and environmental factors x Organize the data and assumptions to be able to calculate the quantities of each product expected to be consumed by clients during the forecast period. We recommend preparing annual estimates for a two-year forecast period. The outputs of the forecasting methodologies outlined within this document should not be used directly for procurement. The supply planning step is where estimated needs are compared with existing stocks, pending shipments, available budgets, product shelf life, and other critical inputs to plan procurement and shipment schedules. Once the forecast is prepared, the quantification team should refer to the original Quantification of Health Commodities for guidance on supply planning. For each of the 13 priority commodities, this document provides information and guidance on— x Product description, indications, and considerations for use Section 1 | Introduction 16 x Types of data needed for forecasting and potential sources of those data x Building the forecasting assumptions and calculating forecasted consumption using a forecasting algorithm x Incorporating product- and program-specific considerations into the forecasting assumptions x Additional products, consumables or equipment required This guide also includes general considerations for forecasting for these commodities, references, and an inventory of tools. In the weeks and months before a quantification exercise for any of the 13 Commission commodities, facilitators and technical staff should review the relevant sections of this document to inform data collection and exercise planning. During the quantification exercise, this guide can serve as a reference to participants to explain applied methodologies. The quantification team will need to adapt the sample forecasting algorithms to fit the country context and the scope of the quantification being undertaken. This guide is intended to help program managers, service providers, and technical experts use what they know about the products they manage and the programs they are implementing to estimate the quantities of products that will be needed to serve their programs’ clients in a given time period. The programmatic examples are meant to illustrate the process of building the forecasting assumptions based on programmatic planning decisions and best estimates of expected demand and use of products, but will need to be adapted by the quantification team for the local scope and context. Because there may not be reliable historical consumption or services data to allow forecasting for programs, the forecasting methodology will be based on many assumptions. According to Quantification of Health Commodities: Contraceptive Companion Guide, “If you do not have historical consumption or services data – for example, when a new program or new services are to be implemented, or when a new contraceptive method or product will be introduced—forecasting…becomes an assumptions-driven exercise that requires inputs from a broad range of key stakeholders. You should draw informed assumptions from research data; from experiences from other countries; and from the knowledge and experience of program managers, implementing partners, service providers, and technical experts. The forecasting assumptions and results should be formulated, agreed upon, and vetted by key decision-makers, implementers, and service providers who will be responsible for managing and providing the specific…services and products.” There may be a need to account for data that are missing or of questionable quality, such as unreliable, outdated, or incomplete data. How severely accuracy is affected and how this influences decisions will depend upon the seriousness of the data problems, but should be noted. These limitations do not mean that quantification cannot be performed with less-than-perfect data. However, limitations do require a closer review of the available data, assumptions, and results and an understanding of the deficiencies, the application Section 1 | Introduction 17 limitations, and the risks—financial and otherwise—of using such assumptions, data, and results. Therefore, forecasts should be frequently reviewed and revised as more data becomes available—to either validate the assumptions that were made or revise them and make adjustments to the forecast and supply plan as needed. We recommend that a range of people form a quantification team or coordination committee, particularly for the forecasting portion of the exercise. The coordination committee can include program representatives from both the public and private sectors familiar with the products and plans, logistics and warehousing staff, procurement staff, pharmacy unit staff, technical experts, and donors/funders.2 In addition, members (or at least one member) of the quantification team should be comfortable using MS Excel™ or other software applications used to manage the forecasting data and calculations. The figure below from Quantification of Health Commodities illustrates the steps in quantification—guidance on forecasting for the 13 Commission products is represented in the “Preparation” and “Forecasting” boxes. (For another view of the quantification process, including the inputs and outputs for each step, refer to annex A.) Users of this guide should refer to Quantification of Health Commodities to prepare supply plans for each product. Quantification cannot be a one-time event; it is a recurring process. Supply plans should be monitored closely and forecasts updated regularly as new/better information becomes available to check all inputs and assumptions used and revise as needed. This is particularly true for new or emerging programs/products where historical data is weak and forecasts are heavily based on assumptions to predict demand/use. Section 1 | Introduction 18 Source: USAID | DELIVER PROJECT. Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement The choice of forecasting methodology will be dictated by the type and quality of the data available to the quantification team. Types of data include— x Consumption data (or proxy consumption data) x Services data Section 1 | Introduction 19 x Morbidity data and/or demographic data x Program targets Please refer to annex B for a description of each type of data and related forecasting methodology, and to the Quantification of Health Commodities for a detailed review of data types and the merits of using different methodologies. For family planning products, the sources, strengths, and challenges associated with each type are further discussed in the Quantification of Health Commodities: Contraceptive Companion Guide. Using data on actual consumption of products is the standard for well-established products and programs where historical consumption data are reliable and available and viewed as representative of future program needs. The consumption-based methodology is covered thoroughly in Quantification of Health Commodities, Quantification of Health Commodities: Contraceptive Companion Guide (for family planning products),3 and Quantification of Health Commodities: Community Case Management Products Companion Guide (for child health products).4 In many countries consumption data may exist but with limitations, in which case we would strongly recommend conducting multiple forecasts and comparing the outputs; this too is covered in the main guide. Since not all programs capture, report, or otherwise have visibility into consumption data, this guide is meant to offer forecasting possibilities when consumption data are limited or when programs are introducing or scaling up new or less-used products. The nature of the 13 overlooked or under-used commodities prioritized by the Commission suggests that they are not currently used or available in sufficient quantities to achieve their maximum health impact, so historical data would in many cases underestimate their potential demand. The potential data items and possible sources of those data are detailed in the forecasting algorithms for each product. A caveat: Quantification of Health Commodities notes that demographic- and morbidity- based estimates are often used to estimate the total unmet need for a service or treatment in a program or country without taking into consideration program capacity, or the actual volume of services provided or quantities of products used. Therefore, demographic and morbidity-based forecasts may represent the uppermost bounds of the potential drug requirements for a program. This upper limit estimate should be tempered with realistic assumptions of service provision/uptake as program planners use these methodologies in the absence of reliable consumption or services data. If the same product appears in different forms in the country (e.g., different brands or designs) such that the quantification team believes that programmatic efforts or other drivers of use might affect different brands or designs unequally, it might be necessary to break the forecast down by brand/design so that separate assumptions can be applied to each. Similarly, brands may be procured from different vendors. Depending on the product, the brand choices may be driven by health programs, providers, or client preferences. Programs managing different brands may also have different plans for demand creation, provider capacity building, provision of equipment to facilities, or assignment of mobile units for more complex procedures, , etc. Therefore, the quantification team may need to build separate assumptions about growth (or decline) by brand. Section 1 | Introduction 20 Utilization of related services offered by the public and private sectors may differ slightly and this can affect estimates. If there is more than one programmatic source (e.g., public sector, social marketing, private clinic) providing these commodities in the country, it will likely be necessary to break out the estimated number of clients by source of supply—at minimum to specify the number of clients that will be served or cases that will be treated by the sources included in the forecasting exercise. For instance, if the public sector is the only program considered in the quantification, then you need only calculate the number of clients to be served or cases to be treated by that sector; clients or cases to be treated in other sectors should be excluded. The 13 Commission products fall into four categories: family planning, maternal health, newborn health, and child health. Due to the demographic/morbidity-based forecasting methodology covered in this guide, it is important to take into account the characteristics and usage patterns for each product. The products are listed below; detailed sections for each product follow. The Commission prioritized three family planning products: emergency contraceptive pills, female condoms, and contraceptive implants. There are a number of existing guidance documents on forecasting for contraceptive methods. Quantification of Health Commodities: Contraceptive Companion Guide is an important resource. In addition, the Forecasting Guide for New and Underused Methods5 discusses assumption-building for forecasting when there is no trend data, and thus is a particularly relevant source of information for the three family planning products on the Commission list. Users of this guide are strongly encouraged to refer to these resources. The three maternal health products are oxytocin and misoprostol for preventing or treating postpartum hemorrhage, and magnesium sulfate for eclampsia and severe pre-eclampsia in pregnancy. The four newborn health products are antenatal corticosteroids (ACS) for Respiratory Distress Syndrome for preterm babies, chlorhexidine for newborn cord care, injectable antibiotics for newborn sepsis, and resuscitation equipment for newborn asphyxia. The three child health products are amoxicillin for pneumonia, and oral rehydration salts (ORS) and zinc for diarrhea. For additional information about quantification of child health products administered at the community level, please refer to Quantification of Health Commodities: Community Case Management Products Companion Guide developed by the Supply Chains for Community Case Management (SC4CCM) project. Section 1 | Introduction 21 1 UN Commission on Life-Saving Commodities for Women and Children. Commissioners’ Report, September 2012. 2 JSI Research & Training Institute, Inc. 2014. Guidance and Resources for Inclusion of Reproductive, Maternal, Newborn, and Child Health (RMNCH) Commodities in National Commodity Supply Coordination Committees. Arlington, Va: JSI Research & Training Institute, Inc., for the UN Commission on Life-Saving Commodities for Women and Children, Supply and Awareness Technical Reference Team 3 USAID | DELIVER PROJECT, Task Order 4. 2011. Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. 4 JSI Research & Training Institute, Inc. 2012. Quantification of Health Commodities: Community Case Management Products Companion Guide. Arlington, Va.: Supply Chains for Community Case Management (SC4CCM). 5 Institute for Reproductive Health, Georgetown University (IRH/GU), John Snow Inc. (JSI), and Population Services International (PSI) for the Reproductive Health Supplies Coalition (RHSC). 2012. A Forecasting Guide for New & Underused Methods of Family Planning: What to Do When There Is No Trend Data? Washington, DC: IRH/GU, JSI, and PSI for the RHSC. Section 1 | Introduction 22 Quantification of Health Commodities RMNCH Supplement 23 This section provides a detailed description of each product and factors to consider when estimating the quantities needed to meet program/client needs. It also includes a forecasting algorithm for each product to guide the assumptions-building process to arrive at the quantity of product needed. For each product, this section provides information and guidance on— x Product description, indications, and considerations for use x Types of forecasting data needed and potential data sources x Building the forecasting assumptions and calculating the forecasted consumption using a forecasting algorithm x Incorporating product- and program-specific considerations into the forecasting assumptions x Information on additional products, consumables, or equipment required Quantification of Health Commodities RMNCH Supplement 24 Section 2.1 | Emergency Contraceptive Pills 25 Emergency contraceptive pills (ECPs) are typically progestin-only oral contraceptives indicated for use to prevent pregnancy after unprotected or inadequately protected sex. Applicable circumstances could be when no contraceptive was used, a contraceptive was used incorrectly, or a contraceptive was used but was immediately observed to have failed.1 Most ECPs can be taken up to five days after unprotected intercourse, though their effectiveness decreases the longer after unprotected sex they are taken. ECPs do not work if a woman is already pregnant, as they work primarily by preventing or delaying ovulation. Three regimens of oral contraceptives are packaged and labeled specifically for emergency contraception (EC): x 1 tablet of levonorgestrel 1.5 mg or 2 tablets of levonorgestrel 0.75 mg x 1 tablet of ulipristal acetate 30 mg x 1 tablet of mifepristone 10–25 mg (not widely available) The Commission specifically mentions the levonorgestrel-only formulations on its list of life- saving commodities. In developing countries, the levonorgestrel-only formulations are the most widely available form of ECPs. This forecasting guidance covers the levonorgestrel- only formulations, although the methodology could also apply for the other ECP regimens if those products were managed by a country program. Certain types of ordinary combined oral contraceptives can also be used as EC (known as the “Yuzpe regimen”). The following forecasting algorithm does not consider the Yuzpe regimen, as those pills are reported and resupplied through combined oral contraceptive supplies. Insertion of an intrauterine device (IUD) is the most effective form of emergency contraception but is not the focus of this guidance. ECPs are safe for all women of reproductive age (including adolescents and older women during the peri-menopausal period). In addition to IUD, they are the only post-coital method a woman can use to prevent pregnancy after unprotected sex or method failure; however, efficacy depends on correct dose and use by the end user. Most efficacy estimates for levonorgestrel ECPs suggest that they prevent between 59% and 95% of expected pregnancies.2 EC is important not only for women who have had no control over their exposure to sex, as in the case of sexual violence, but also for couples who find themselves in need of contraception after unprotected sex (including method failure). Demand for ECPs is unpredictable because ECPs are not typically used for routine or continuous use as a family planning method. Furthermore, use is heavily contingent on client and provider awareness. The population that uses ECPs is likely a subset of the total population interested in using—or already using—a modern method of contraception. For example, if a woman is using a condom and it breaks, if she forgets to take her pill, or if she receives her injection late, she would know immediately that her short-acting method had failed. If she knew about ECPs, she could use it as a back-up method. However, a woman using a long-acting method would not necessarily know immediately if her method failed; long-acting methods are also typically less likely to fail and, therefore, users of long-acting methods are less likely to use ECPs. In addition, ECPs may also be used as part of post- Section 2.1 | Emergency Contraceptive Pills 26 rape care and in refugee and humanitarian crisis settings,3 as well as for other women not using a method. Knowledge continues to be an important barrier to uptake, ECP is often one of the least known, least available, and least used modern family planning methods in developing countries. Many countries still do not include emergency contraceptive pills on their national essential medicines list (NEML). The Contraceptive Security Indicators compiled for 2013 indicate that 25 out of 43 surveyed countries (58%) have ECPs on their NEMLs.4 It appears that countries are increasingly recognizing the importance of this method and adding it to their respective lists when updates take place. For example, according to a 2011 survey, Rwanda and Senegal added ECPs to their NEMLs during their latest list revision.5 Uptake in the public versus private/commercial sectors has been different in some countries, leading to challenges for public sector/government forecasting and procurement. According to the 2013 CS Indicators, 55% of surveyed countries managed ECPs in the public sector, 73% in NGO sector, 36% in the social marketing sector, and 93% in the commercial sector. In surveyed countries, ECPs are offered on average in two out of these four sectors. In Kenya, for example, the commercial sector market for ECPs is vibrant and sales are high, but public sector distribution has lagged. Reasons for this slow uptake in the public sector may include that women prefer the speed and privacy offered by private pharmacies and are willing to pay for it, and that public sector procurement has not often been accompanied by appropriate training and orientation of public clinic staff or demand generation activities among women. In addition, ECPs may be offered via traditional as well as nontraditional outlets such as hospital emergency rooms, refugee and internally displaced persons camps, pharmacies, prisons, and schools. Access and availability can be influenced by issues such as licensing and registration of products, and whether clients are able to obtain the method without a prescription. Source: A Forecasting Guide for New & Underused Methods of Family Planning6 Because ECP is a new method for many public sector programs, emergency contraceptive pills can be difficult to forecast because of a lack of routine reliable consumption and other data. To the extent possible, we recommend that real sources of data or examples from past quantification exercises be used as the foundation to build assumptions. Estimates should be realistically aligned with programmatic plans and capacity for introducing or expanding provision of ECPs in a given sector, especially if EC is well established in other sectors. For instance, the private commercial sector plays a strong/established role in EC provision in some countries; quantification teams should use caution in extrapolating commercial sector demand for ECPs to the public sector. The quantification team will need to decide which data and evidence-based assumptions best fit its country or program situation. Thus not all of the types of data mentioned below may be applicable or needed for every country or forecasting exercise. Section 2.1 | Emergency Contraceptive Pills 27 See table 1 for possible sources of this data. It is critical to document all data and assumptions that are used in forecasting so that others can review, understand, and also update or revise data and assumptions as better information becomes available. This documentation can also serve as a reference for future forecasts or adjustments. The standard forecasting methodology using demographic data involves estimating the number of users of the method, (stratified by brand and by source if relevant) and multiplying by the method-specific Couple-Years of Protection (CYP) factor. The CYP factor is the estimated number of doses required to protect a couple from pregnancy for one year. However, since ECP is not commonly used as a primary contraceptive method for annual protection as very few women in Africa who have ever used EC use it more than once,7 the quantification team may choose to instead estimate the number of women experiencing an episode requiring ECPs and convert to quantities required by multiplying by one dose (pack) per episode (or other conversion factor based on dispensing protocols in the country). Data Source Limitation Forecasting Total population National census data, US Census Bureau International Database,8 DHS May be outdated (true of any listed data source); may need to apply estimated annual growth rate to project to forecast years Percentage of population that women comprise Census data, DHS, Reproductive Health Survey (RHS) May be outdated (true of any listed data source); may need to apply estimated annual growth rate to project to forecast years x Target population o Percentage of women of reproductive age (WRA), i.e., women at risk for pregnancy o Contraceptive prevalence rate (CPR) (modern methods) o Percentage of WRA reporting ever use of ECPs o Percentage of modern method users using short-term contraceptive methods o Percentage of WRA experiencing unmet need for contraception o Percentage of WRA not using contraception o Incidence of rape (or rates of gender-based violence) o Short-term method failure rates o Percentage of women aware of EC o Percentage of women with access to EC o Health services-seeking behavior x Product mix (brands/formulations managed and their proportional share) x Source mix (the sources of supply and their proportional share) x Dispensing protocols, (i.e., how many ECPs are dispensed per episode requiring EC) x Other estimates of likelihood of use/repeat use of EC x Programmatic changes that would affect demand for or consumption of ECPs (change in dispensing protocols, increase in service provision, demand generation activities, changes in the number of providers trained and number of facilities equipped to offer the method, increase in number of women willing to seek ECP) Section 2.1 | Emergency Contraceptive Pills 28 Data Source Limitation Number or percentage of women who are of reproductive age (15–49) Census data, DHS, RHS May be outdated (true of any listed data source); may need to apply estimated annual growth rate to project to forecast years Contraceptive prevalence rate (CPR) (modern methods) Family health surveys, DHS, RHS, national health surveys May be outdated (true of any listed data source); may need to apply estimated annual growth rate to project to forecast years Short-term method prevalence (female condoms, male condoms, oral contraceptives, injectables) Family health surveys, DHS, RHS, national health surveys May be outdated (true of any listed data source); may need to apply estimated annual growth rate to project to forecast years Short-term method failure rates Contraceptive technology9 Contraceptive efficacy may differ from US standard Unmet need DHS or similar surveys Data may be underestimated ECP ever use DHS (DHS between 2009 and 2014 do not include ever use of ECP) or similar surveys Data may be underestimated Incidence of rape or GBV DHS, country studies Data may be underestimated Awareness of emergency contraception DHS or similar surveys Data may be underestimated WRA with access to health services DHS, SARA (services availability and readiness assessment), country studies Data may be unavailable or outdated WRA likely to seek EC (health services-seeking behavior) Behavioral studies, Key informants Data is not always available or reliable, and may differ by product Product mix MoH Reports, LMIS records, Facility records, DHS, multiple indicator cluster survey (MICS) May not be representative if product is newly introduced Source mix (percentage of share of public sector, social marketing sector, etc.) Key informants/Social Marketing, DHS Data may be incomplete ECP dispensing protocols /quantity of ECPs dispensed per episode National formulary, essential medicines list, standard treatment guidelines, WHO recommended guidelines, MoH, surveys Non-adherence by provider could skew forecast CYP MEASURE Evaluation PRH Family Planning and Reproductive Health Indicators Database10 CYP factor for ECP is 20 doses, which may overestimate quantities needed if WRA use ECPs only for episodic, and not annual, protection. Programmatic plans Programs managing ECPs or working with current/potential users Program targets do not always align realistically with program and system capacity; May be anecdotal and not accurately reflect reality of introducing a new product Section 2.1 | Emergency Contraceptive Pills 29 1. Determine the scope of the quantification 2. Calculate target population estimates for women who are likely to need and use emergency contraceptive pills 3. Estimate product/brand mix 4. Estimate source mix 5. Calculate the estimated quantity of ECP doses to be consumed per year in the forecast period Each step is explained in detail below. We recommend preparing annual forecasts for a two- year period. Clarify whether the quantification will cover the product needs for all programs and sectors in the country, or a subset of the channels through which ECPs are provided. Clarify at what levels of the health system ECPs are managed. Estimate the number of women of reproductive age (WRA) between ages 15 and 49 who are at risk for needing ECP (including those experiencing a short-term method failure, those not using a modern contraceptive method, and if relevant, those receiving ECP as part of post-rape care), who are aware of ECP, have access to it, and will seek treatment. In some cases, the quantification team may deem it worth the effort to disaggregate WRA into different groups based on reason for using ECP because demand is distinct by reason, or because assumptions about awareness, access, and treatment-seeking behavior might be different based on each reason for use. For example, secondary analysis of DHS or other data may provide the quantification team with the basis for assumptions about differing use of ECPs based on WRA age, marital status, level of education, income, or other characteristics. x WRA in the country/program catchment area. To estimate the population of WRA (if this information is not already available from a reliable data source), review census data and multiply the number of women in the population by the percent of women who are of reproductive age. If census data is outdated, you may need to adjust the total population for growth by applying the annual population growth rate up to and through the years of the forecast and base further calculations on these to obtain the number of WRA in each year of the forecast. The example in this section applies this method for estimating the total population based on census data from a previous year. x WRA at risk for pregnancy. To estimate the number of WRA at risk for pregnancy, multiply the number of WRA by the combined proportion of WRA in union (sometimes called “currently married”) and WRA who are unmarried but sexually active, if these data are available. The quantification team may also choose to consider non-sexually active women in the target population since women who report not being sexually active may still be at risk for pregnancy due to rape (and thus might use ECPs as part of post-rape care) – see the bullet below for “Remaining women not using or not in need of a modern method.” Section 2.1 | Emergency Contraceptive Pills 30 Disaggregating WRA WRA using a long-acting or permanent method of contraception are highly unlikely to use ECPs. Women using short-acting methods such as condoms (male and female), oral contraceptives, and injectables might use ECPs if they suspect they did not use their method properly or their method failed. Women with unmet need might elect to use ECPs if they knew about them and had access to them. Women not using any method (even if they do not express unmet need) might use ECPs in the case of rape. Thus the quantification team might choose to break down WRA by these groups. See the sample forecasting algorithm for a visual depiction of these separate flows. Note: in countries with a high prevalence of use of traditional contraceptive methods, the quantification team could choose to use total CPR (rather than only modern methods CPR) and break out traditional methods users. Otherwise, in the sample algorithm described here, women using traditional methods are taken into account in the calculations for women at risk of pregnancy due to rape. x Contraceptive use o Women using a modern method. Multiply the number of WRA at risk for pregnancy times the percentage of women who report using a modern method of contraception. o Women with unmet need for contraception. Multiply the number of WRA at risk for pregnancy times the percentage of WRA with unmet need (depending on the group (women in union, sexually active women, or both) for which unmet need data are available). These are the women who are not using another method and may choose to use ECPs if they have unprotected intercourse. (Note: for the sample algorithm, these women are included in the flow at “need for ECP” and filtered by awareness of EC, access to EC, and likelihood of seeking treatment. The quantification team could instead choose to assume might use ECP at the rate of “ever use” of ECPs, and next include it in the flow at treatment- or health services-seeking). o Remaining women not using or not in need of a modern method. Multiply the number of WRA at risk for pregnancy times 100 minus the sum of the percentage of women who report using a modern method of contraception and the percentage with unmet need. WRA x (100 – [% CPR + % Unmet Need]) Add to these the number of WRA not considered “at risk for pregnancy,” as they should be included in the women that, though they do not express unmet need or may not be sexually active, may use ECPs in case of rape. x Method mix o Some women using short-term methods may elect to use ECP if their primary method fails. To calculate the number of WRA using short-term methods, multiply the number of WRA using a modern method times the percentage of contraceptive users using each short-term method: - Male condoms - Female condoms - Oral contraceptives (all brands and presentations) - Injectables (all brands and presentations) Note: if you have data on modern method use in terms of % of WRA using each method, be sure to adjust this percentage so it represents the % of modern Section 2.1 | Emergency Contraceptive Pills 31 contraceptive users using each method. For example, if 5% of WRA are using implants in a country where mCPR is 45%, then the % of users using implants is 5/45 = 11%. x Method failure. To calculate the number of short-term method users experiencing method failure, multiply the number of WRA using each short-term method times the method-specific failure rate. (Long-acting method users may not know immediately if their method failed; long-acting methods are also typically less likely to fail and, therefore, users of long-acting methods are less likely to use ECPs.) Note: if the quantification team has chosen to break out traditional methods users in a previous step, it could apply estimated failure rates for traditional methods and include that in the calculation at this step. x Post-rape care. In countries with high rates of sexual violence that dispense ECP as part of post-rape care, or if ECP is only available for post-rape care, the quantification team might elect to consider this group of WRA in the forecast. Estimates of the number of women seeking ECP for this purpose may depend on reported cases of sexual violence, the age distribution of cases, and the proportion of survivors seeking care. If data on incidence of rape are not available, the quantification team might choose to use data on the proportion of women at risk of gender-based violence as a proxy. Sources of such data might include organizations that provide post-rape care and/or work with refugee camps or statistics on violence, if available. For this calculation, multiply the remaining WRA not using a modern method by the percent of WRA who are likely to experience rape or gender-based violence. Add to this the number of WRA not in union or not sexually active, as they might choose to use ECPs in case of rape. Note: In the sample algorithm, use of ECP for this reason is only included in the flow of WRA not using a modern method and not experiencing unmet need. The assumption is that use of ECP by women using a modern method or with unmet need, including for reasons of rape, is already captured in the algorithm. x Awareness of EC. In many countries, low levels of awareness of EC may have a significant impact on the number of women who actually seek EC, even if they need it. The quantification team may consider factoring in the awareness of EC as another variable. DHS data on awareness of ECP may be available. In addition, consider current and planned demand generation interventions that are expected to increase awareness of EC by interviewing the Ministry of Health (MoH) and social marketing organizations that might be able to provide this data. For this calculation, multiply the sum of the number of women experiencing unmet need, the number of women experiencing method failure and the number of women needing post-rape care by the percent of women who are aware of emergency contraception. See the sample algorithm for a visual depiction of this step. x Access to EC. The quantification team may elect to factor in likely access to EC, such as the percentage of WRA needing EC who live in urban areas which infers that they will more likely have access. In urban settings, knowledge of EC may be higher and the population may have more disposable income to be able to purchase ECPs, meaning pharmacies/drug shops in urban settings may be more motivated to keep a stock of ECPs.11 This point may be especially relevant in settings where there are public sector user fees or if the forecast includes the social marketing sector. Another Section 2.1 | Emergency Contraceptive Pills 32 option would be to consider the proportion of women attending antenatal care as a proxy for access. To calculate this, multiply the number of women who need EC and are aware of its availability by the percentage of women who have access. See the sample algorithm for a visual depiction of this step. x Treatment or health services-seeking. Another critical factor to refine the target population is to estimate the percentage of women aware, with access, who will actually seek EC. There may be studies in the country about health services-seeking behaviors, but in the absence of these types of data, the quantification team may need to make an educated guess about the proportion of women in need who will actually seek EC. If the quantification team believes rates of treatment-seeking might differ by reason for use, conduct interviews with advocacy groups that work with victims of post-rape care and/or refugee and crisis camps on use of EC to estimate frequency of use in these situations. For this calculation, multiply the number of WRA needing EC, who are aware and have access, by the estimated percentage who will seek treatment. See the sample algorithm for a visual depiction of this step. Determine the percentage of the target population that obtains ECPs from different supply sources such as the public, social marketing, NGO, and private sectors. Your calculations should include those sectors relevant to the scope of the quantification. Take into consideration current “share” and whether the quantification team expect that the “share” of the total ECP supply that women will access by source will change in the forecast period, e.g., due to programmatic plans or campaigns, removal of regulatory barriers. When consumption, services, or survey data (like the DHS) are not available, interviews with social marketing organizations and the private sector will be useful in determining an estimate of current source mix. If EC is being introduced for the first time in a program and there is no available data, information about the experience of the same or like- products (including earlier generations of a product) in similar markets/countries may be useful.12 That said, particularly in countries where commercial sector provision of ECPs is well-established, use caution in using commercial sector demand as basis for assumptions about potential program growth or marketing of a new brand of ECPs in other sectors. Multiply the number of WRA by brand times the proportion accessing EC from each source (sector) of supply. The sample algorithm puts the source mix step before brand mix; the quantification team will need to determine the proper sequence, if multiple brands are managed in the country, and/or the same brands are managed by more than one source (sector) of supply. To figure out how many users of each different ECP the program will need to serve, you will need to know how many types (different brands or formulations) of ECPs are offered, and have data on the product mix (the proportion of the total ECP supply made up by each brand or formulation) or make assumptions about it. If only one brand/formulation of EC is managed by the program participating in the forecasting exercise, you can Section 2.1 | Emergency Contraceptive Pills 33 assume that 100% of ECP needs will be covered by that type, and you can skip this step. For countries where multiple brands or formulations of ECPs are managed, multiply the number of WRA (needing EC, are aware, have access, will seek EC) times the proportion each brand makes up of the total. See the sample algorithm for a visual of this step. Convert the number of women who will use ECPs to the quantities of each product that will be needed by multiplying the number of WRA (by brand and sector of supply) by the quantity of each product needed per episode. See the sample algorithm for a visual depiction of this step. The following sample algorithm, in Figure 1, illustrates a country scenario in which the public, social marketing, and private sectors all manage ECPs. The scope of the forecast includes the public and social marketing sectors, each of which manage one brand of ECPs. Section 2.1 | Emergency Contraceptive Pills 34 Section 2.1 | Emergency Contraceptive Pills 35 A1 Proportion of WRA in union/sexually active A2 Proportion of WRA not in union/sexually active A3 Unmet need for contraception A4 Contraceptive prevalence rate (modern methods) A5 Percentage of women neither using a modern contraceptive method nor reporting unmet need for contraception: 100 - (% CPR + % unmet need) A6,7,8,9 Method mix (% of modern method users, using each short-term method) A10 Incidence of rape A11 Method-specific failure rates (% of users experiencing short-term method failure in a year, by method) A12 Percentage of WRA aware of ECP A13 Percentage of WRA with access to ECP A14 Percentage of WRA who will seek treatment A15 Percentage of users accessing EC from public sector A16 Percentage of users accessing EC from social marketing sector A17 Percentage of brand mix of ECPs in public sector A18 Percentage of brand mix of ECPs in social marketing sector A19 Conversion factor (quantity of doses required per episode) Figure 1 illustrates a scenario of steps to follow when forecasting for ECP for the prevention of pregnancy in women of reproductive age. The final result is the total estimated quantities of ECPs that are expected to be dispensed to clients in each year of the forecast period. This alone should not be used for procurement. In addition to this figure, other data will be used during the supply planning step. Refer to the original Quantification of Health Commodities for guidance on the supply planning step. None required. Levonorgestrel-only ECPs appear in the World Health Organization (WHO) Essential Medicines List (EML).13 As of October 2013, WHO had prequalified Gedeon Richter’s two-pill levonorgestrel ECP and FamyCare’s one- and two-pill levonorgestrel ECPs. Several ECPs are also approved by other stringent regulatory authorities, such as the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). In addition, a number of manufacturers are producing generic equivalents of ECPs. Some are currently going through the WHO prequalification process and being procured by international organizations and country governments.14 Access and availability of ECPs are influenced by a number of issues including licensing, registration, cost, whether clients are able to obtain the method without a prescription, and hours and geographical convenience of facilities to ensure that clients can access EC within five days after unprotected sex. Levonorgestrel emergency contraceptive pills are registered for sale and distribution in over 140 countries. Even in countries where no dedicated product has been registered, EC may sometimes be supplied with a special import license, and Section 2.1 | Emergency Contraceptive Pills 36 women can always use a higher dose of regular birth control pills for EC, as mentioned. The following site compiles data on the status of EC in many countries— www.emergencycontraception.org.15 Country X would like to estimate the quantities of emergency contraceptive pills to be consumed by clients of its public sector RH/FP program as well as a social marketing program over the next two years. Available data (all DHS data are from “current year”) x Total population as of current year (Population Reference Bureau): 16,000,000 x Population growth rate (PRB): 3.1% x Percentage of population who are women (DHS): 51 x Percentage of women who are of reproductive age (DHS): 44.3 x Percentage of WRA using a modern method of contraception (CPR) (DHS): 42 x Percentage of WRA using male condom (DHS): 2.70 x Percentage of WRA using female condom (DHS): 0.10 x Percentage of WRA using oral contraceptives (DHS): 1.90 x Percentage of WRA using injectables (DHS): 19.20 x Percentage of WRA experiencing unmet need for contraception (DHS): 27 x Percentage of clients accessing ECP by source (DHS: public sector: 82, social marketing: 15 x Percentage of WRA aware of EC (DHS): 35 Assumptions the quantification team agreed upon for the forecast period timeframe x No projected change in the proportion of the population that is women x No projected change in the proportion of women that are of reproductive age x All WRA are at risk of pregnancy x Estimated percentage of annual increase in CPR (due to increases in long-acting methods): 1 x No projected change from current year in short-term method mix as % of WRA x No projected change in unmet need x Estimated percentage of annual increase in awareness of EC: 1 x Estimated percentage of urban WRA (more likely to have access): 15 x Percentage treatment-seeking (women having access and need who will seek ECPs): 20 x Health services-seeking behavior not differentiated among e.g. age groups or purposes for seeking ECP x Percentage product (brand) mix and source mix: Brand A (public sector): 15; Brand B (social marketing sector): 60 (i.e., 25% is commercial sector, which is not considered in this example) x Product/Source mix unchanged in the forecast period x Conversion factor for episodic use: 1 dose/treatment required per episode (box 2 continued on following page) Section 2.1 | Emergency Contraceptive Pills 37 Input Current year Forecast year 1 Forecast year 2 1. Population pop. growth rate 3.1% 16,000,000 16,496,000 17,007,376 2. Number of women in the population % of pop. that is women 51.0% 8,160,000 8,412,960 8,673,762 3. Women of Reproductive Age (WRA) % of women that are 15-49 44.3% 3,614,880 3,726,941 3,842,476 4. CPR (modern methods) est. annual CPR increase 1.0% 42.0% 43.0% 44.0% 5. WRA using a modern method of contraception 1,518,250 1,602,585 1,690,690 6. Method mix - converted from % of WRA to % of contraceptive users male condom 2.7% 6.4% 6.3% 6.1% female condom 0.1% 0.2% 0.2% 0.2% oral contraceptives 1.9% 4.5% 4.4% 4.3% injectables 19.2% 45.7% 44.7% 43.6% 7. Number of method users m condom 97,602 100,627 103,747 f condom 3,615 3,727 3,842 ocs 68,683 70,812 73,007 inj 694,057 715,573 737,755 8. WRA with unmet need unmet need 27.0% 976,018 1,006,274 1,037,469 9. Remaining WRA not using modern contraception 100-(%CPR+ %unmet need) 1,120,613 1,118,082 1,114,318 10. WRA experiencing short-term method failure m condom failure rate 18.0% 17,568 18,113 18,674 f condom failure rate 21.0% 759 783 807 oc failure rate 9.0% 6,181 6,373 6,571 inj failure rate 6.0% 41,643 42,934 44,265 11. Unprotected WRA at risk for pregnancy due to rape incidence of GBV (proxy for rape) 14.0% 156,886 156,532 156,005 12. Total WRA with a need for ECP (total items 8 + 10 + 11) 1,199,056 1,231,009 1,263,791 13. Awareness of ECP est. annual increase in awareness 1.0% 35.0% 36.0% 37.0% 14. Number of WRA with a need, who are aware 419,669 443,163 467,602 15. Number of WRA with a need, who are aware, who have access % urban dwellers (proxy for access to ECP) 15.0% 62,950 66,474 70,140 (box 2 example continued on following page) Section 2.1 | Emergency Contraceptive Pills 38 The final result for each year represents the forecast demand for ECPs required for client consumption. The next step is to conduct supply planning to take into account existing stocks, quantities on order, other supply chain considerations, and available funding to determine the quantities of contraceptives required for procurement. Refer to the original Quantification of Health Commodities for guidance on the supply planning step. Input Current year Forecast year 1 Forecast year 2 16. total WRA who will seek ECP likelihood of seeking ECP 20.0% 12,590 13,295 14,028 17a. Number of WRA seeking ECP using brand A (public sector % brand A (public sector) 15.0% 1,889 1,994 2,104 17b. Number of WRA seeking ECP, using brand B (social marketing sector) % brand B (social marketing sector) 60.0% 7,554 7,977 8,417 18a. Estimated annual consumption (quantities of product) - brand A (public sector conversion factor for episodic use (1 dose per episode) 1 1,889 1,994 2,104 18b. Estimated annual consumption (quantities of product) - brand B (social marketing sector) 7,554 7,977 8,417 Section 2.1 | Emergency Contraceptive Pills 39 1 International Consortium for Emergency Contraception, Emergency Contraceptive Pills: Medical and Service Delivery Guidelines. Third Edition, 2012. New York: ICEC. Available at http://www.cecinfo.org/custom-content/uploads/2013/06/Medical-and-Service-Delivery-Guildelines- English-June-20131.pdf. 2 International Consortium for Emergency Contraception (ICEC), Emergency Contraception: Questions and Answers for Decision-Makers, 2013. New York: ICEC. Available at http://www.cecinfo.org/custom-content/uploads/2013/04/QandAforDecisionmakers20131.pdf. 3 Reproductive Health Response in Conflict (RHRC) Consortium. Emergency Contraception for Conflict-Affected Settings:A Reproductive Health Response in Conflict Consortium Distance Learning Module. 2008. Available at http://www.rhrc.org/resources/general_fieldtools/er_contraception/ec_brochure_english.pdf. 4 USAID | DELIVER PROJECT, Task Order 4. 2013. Contraceptive Security Indicators Data 2013. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. Available at http://deliver.jsi.com/dlvr_content/resources/allpubs/factsheets/CSIndiData2013.xlsx 5 USAID | DELIVER PROJECT, Task Order 4. 2012. Contraceptive Security Brief. Emergency Contraceptive Pills: Supply Chain Considerations. Arlington, Va.: USAID | DELIVER PROJECT. 6 Institute for Reproductive Health, Georgetown University (IRH/GU), John Snow Inc. (JSI), and Population Services International (PSI) for the Reproductive Health Supplies Coalition (RHSC). 2012. A Forecasting Guide for New & Underused Methods of Family Planning: What to Do When There Is No Trend Data? Washington, DC: IRH/GU, JSI, and PSI for the RHSC. 7 Morgan, G., Keesbury, J., & Speizer, I. Emergency contraceptive knowledge and use among urban women in Nigeria and Kenya. Stud Fam Plann. 2014 March; 45 (1): 59-72. 8 United States Census Bureau . International Programs. http://www.census.gov/population/international/data/idb/informationGateway.php 9 Trussell, J. Contraceptive Efficacy. In Hatcher RA, Trussell J, Nelson AL, Cates W, Kowal D, Policar M. Contraceptive Technology Twentieth Revised Edition. New York, NY: Ardent Media, 2011. 10 Measure Evaluation PHR. Family Planning and Reproductive Health Indicators Database. http://www.cpc.unc.edu/measure/prh/rh_indicators/specific/fp/cyp 11 International Consortium for Emergency Contraception (ICEC). Emergency Contraception: How far have we come? What's new? What's next? 2011. Final Report on Online Discussion Forum, held March 2nd-16th. New York: ICEC. Available at http://www.cecinfo.org/custom- content/uploads/2012/12/ICEC-IBP-Online-Forum-on-EC-REPORT.pdf. 12 Institute for Reproductive Health, Georgetown University (IRH/GU), John Snow Inc. (JSI), and Population Services International (PSI) for the Reproductive Health Supplies Coalition (RHSC). 2012. A Forecasting Guide for New & Underused Methods of Family Planning: What to Do When There Is No Trend Data? Washington, DC: IRH/GU, JSI, and PSI for the RHSC. 13 World Health Organization (WHO). WHO Model List of Essential Medicines, 18th Edition. Geneva: April 2013. Available at http://apps.who.int/iris/bitstream/10665/93142/1/EML_18_eng.pdf. 14 USAID | DELIVER PROJECT, Task Order 4. 2012. Contraceptive Security Brief. Emergency Contraceptive Pills: Supply Chain Considerations. Arlington, Va.: USAID | DELIVER PROJECT. 15 International Consortium for Emergency Contraception (ICEC), Emergency Contraception: Questions and Answers for Decision-Makers, 2013. New York: ICEC. Available at http://www.cecinfo.org/custom-content/uploads/2013/04/QandAforDecisionmakers20131.pdf. Section 2.1 | Female Condoms 40 Female condoms are barrier devices that are inserted inside the vagina before sexual intercourse to prevent unintended pregnancy and reduce the transmission of the human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs). Female condoms are the only woman-initiated method providing dual protection against unintended pregnancy as well as transmission of HIV or other STIs. Female condoms do not require a prescription or clinician involvement beyond initial insertion training. Women of all ages can use the female condom; however, it is particularly attractive to women who experience side effects from hormonal methods; high-risk behavior groups, such as female sex workers and other women with multiple sexual partners; people who want to protect themselves from STIs, HIV, and unintended pregnancy; men who dislike the use of male condom; women who cannot negotiate the use of male condoms; and people who are allergic to latex (some female condoms are latex-free). Female condoms may be used in conjunction with the IUD, hormonal methods, and sterilization, but never with a male condom. Studies provide important evidence that the female condom is complementary to the male condom and contributes to increased cumulative protected sex (i.e. female condoms do not simply substitute for male condoms that would be used,; they contribute to greater total condom use of both male and female condoms). Female condoms are not as well-known and are used much less than male condoms.1 They are classified as “underutilized” by the Reproductive Health Supplies Coalition’s Caucus on New and Underutilized Methods. Because demand for and use of female condoms are low, existing consumption or distribution data are a poor predictor of future demand or use. Female condoms have a significantly higher per-unit cost than male condoms. Both male and female condoms may be artificially differentiated between condoms procured for family planning programs versus condoms procured for HIV and STI prevention programs. Since male and female condoms prevent both pregnancy and transmission of HIV and STIs, this distinction is unnecessary and may actually hamper access to condoms. In addition, if there are stock-outs, users may obtain condoms from a different program. For example, a patient at an antiretroviral (ART) site might obtain condoms from a family planning counselor at the same hospital, or a family planning client may obtain condoms from the HIV testing and counseling service. Ultimately, while users may intend to use condoms for pregnancy prevention, prevention of disease transmission, or both, the users’ intention is not relevant for forecasting purposes. Accordingly, an appropriate quantity of female condoms needs to be available to users regardless of their purpose. There are also benefits to coordinated forecasting among programs (e.g., potential for more/better data on use and drivers of use can allow the quantification team to build better assumptions). Nevertheless it is possible to break the forecast down by program (e.g., at the “source mix” level) if that is needed for financial, reporting, or other programmatic reasons. Section 2.1 | Female Condoms 41 It makes sense for different programs to forecast their condom needs together; or at least share their data. This will help each program avoid duplication, minimize overstocking, and shortages in its forecast, and plan for the transfer of products between programs if there are stock-outs. If you cannot avoid having to provide a separate forecast for condoms for a family planning program versus an HIV and STI prevention program, distinguish which program needs the separate forecast and adjust the assumptions accordingly. In addition, having separate forecasts for condoms for different programs would require that all data be differentiated by program at the service delivery level. As with other contraceptive methods, historical consumption data are usually the best basis for forecasting needs, with the exception of programs that are scaling up, introducing new methods or products, or planning other initiatives that would significantly change consumption. Quantification of Health Commodities: Contraceptive Companion Guide covers logistics- based forecasting. Since demand for and use of female condoms is low in many developing countries, consumption or distribution data may be a poor predictor of future demand or use. This section thus provides a possible methodology for forecasting for female condoms when logistics data are not available or not considered predictive of future consumption. A caution on using demographic data for forecasting both male and female condoms is that the question about contraceptive use in the DHS is hierarchical; it will not reflect additional use of condoms for HIV and STI prevention if the user has already indicated the use of another contraceptive method. Be cautious when using demographic and behavioral data about the prevalence of high-risk behavior or frequency of unprotected sex acts for determining program targets. Estimates based on this type of data about potential users, while valid and useful for advocacy or goal setting, may significantly overestimate actual demand. Female condoms especially have a higher incidence of over-forecasting. 2 Program targets should align realistically with program capacity when estimating quantities; it is not advisable for programs to use targets as the basis for procurement. x Scope (regional, national, district; programs; sectors) x Target population o Population census data and rate of growth o Percentage or number of sexually active women (or women ages 15-59); if the forecast is for female condoms for family planning only, use percentage or number of women of reproductive age, 15-49) o Percentage or number of female sex workers (FSW) o Contraceptive prevalence rate (CPR) o Percentage of modern method users using female condoms o Percentage of women that used female condom in last sex act x Product mix (if more than one type/brand of female condoms is being quantified for) x Source mix (distribution or service delivery source and its proportional share) x Couple-Years of Protection (CYP) factor x Coital frequency (among women on average, among FSW) x Clients per year per FSW x Programmatic changes that would affect consumption of female condoms (changes in service provision or service delivery strategy, demand generation activities, changes in the number of providers trained, and number of facilities equipped to offer the method) Section 2.1 | Female Condoms 42 See table 2 below for possible sources of this data. All data and assumptions that are used in the process of forecasting must be documented. This makes it possible for others to review, understand, and update or revise data and assumptions as better information becomes available. This documentation can also serve as a reference for future forecasts or adjustments. The forecasting formula involves estimating the number of users of female condoms (may be further stratified by brand and by source), and then multiplying by the method-specific CYP factor or another estimate of annual quantities of female condoms needed to protect one user, to convert to quantities of product required. An alternative for converting from users to quantities of product required is to estimate the number of sex acts requiring a female condom and multiply by one female condom per act of intercourse. The quantification team will need to agree upon and document the assumptions it makes and attempt to assess the impact that these assumptions will have on the final forecast. To make the best estimate of future consumption, the team should try to build assumptions that are as accurate and as reasonable as possible. Data Point Source Limitation Total population; rate of population growth; percentage or number of women of reproductive age (15–49) Census data, DHS, RHS Data may be outdated and may need to be adjusted for the forecast years Number or percentage of female sex workers (FSW) Programs working with FSW, NACs, World Bank Data may not be representative Contraceptive prevalence rate Family health surveys, Reproductive Health Surveys, National Health Surveys, DHS, MICS Data quality is not always known, may be outdated Contraceptive use among FSW Programs working with FSW, DHS Data may not be representative, may be outdated Method mix (percentage currently using female condom or percentage women using condom in last sex act) DHS, MICS; could be estimated from MoH Reports, LMIS records, Facility records Not always complete, data quality is not always known, and may be outdated Coital frequency Sexual behavior surveys, DHS May not be available for country of interest; may be outdated; special analyses of data may be required to generate frequency Clients or sex acts per FSW per time period Programs working with FSW, NACs, World Bank Data may not be representative Couple-years of protection (CYP) factor MEASURE Evaluation PRH Family Planning and Reproductive Health Indicators Database3 CYP factor is 120 units Product mix Key informants, program records Program records may be incomplete or unavailable. Source mix, e.g., public sector Key informants/Social Marketing DHS May be anecdotal and not accurately reflect reality of introducing a new product Programmatic plans Programs managing female condoms or working with current/potential users (e.g. MOHs, NACs, NGOs) Program targets do not always align realistically with program and system capacity Section 2.1 | Female Condoms 43 1. Determine the scope of the quantification 2. Estimate the target population 3. Determine use of contraceptive method by the target population 4. Determine the number of women using female condoms 5. Determine product mix (if applicable) 6. Determine source mix 7. Adjust for programmatic changes 8. Estimate quantity of female condoms required per user per year Clarify whether the quantification will cover the product needs for all programs and sectors in the country, or a subset of the channels through which female condoms are provided, e.g. public sector, social marketing. Clarify at what levels of the health system female condoms are managed. In the following steps, be prepared to make adjustments based on assumptions about program changes that are happening or planned for the forecast period. Ascertain if there will be interventions to increase contraceptive use overall, and use of female condoms in particular. If so, what demand building interventions have been planned? How will they affect sub-populations, brands (product mix), or sources of supply (sector mix) differently? Considerations might include the scale and reach or geographical scope of these interventions. These assumptions may be different depending on the product (if more than one type of female condom is managed in the country by the programs participating in the quantification) or the client’s source of supply. x Sexually active women ages 15-59. To estimate the population of sexually active women (those who might use female condoms not only to prevent unintended pregnancy but also to reduce transmission of STIs or HIV), obtain census data and multiply the percent of the population that is women by the proportion between the ages 15-59. We generally recommend assuming that all women 15-49 in union (or “currently married”) as well as unmarried sexually active women are at risk for pregnancy, and all sexually active women 15-59 (married or unmarried) are at risk for STIs or HIV, though this may not be applicable in all contexts. (If the forecast is for female condoms for family planning only, use women of reproductive age (WRA) 15- 49 instead – in union, sexually active, or both, depending on the data available). If the census data are outdated, you may need to adjust for population growth by applying the annual population growth rate up to the year of the forecast; document your assumption. x Female sex workers or other sub-populations to disaggregate. If the quantification team determines that there is a population of female sex workers (FSW) or another sub-population (e.g., unmarried women, younger women) whose use of female condoms may differ substantially from use by women in general, the team may elect to disaggregate these women for the forecast. That is, the Section 2.1 | Female Condoms 44 quantification team may create different assumptions to estimate the commodity needs for this population. As background for any assumptions about the number of FSW and their female condom use, interview organizations that work with, or provide legal protection services to FSW, and review studies of their contraceptive/condom use. If provided with the percentage of women 15-59 who are FSW, multiply this percentage by the number of women 15-59 to arrive at the number of women who are FSWs. Subtract the number of WRA who are FSWs from the number of WRA in general so they are not double-counted. If the quantification team has elected to forecast female condom needs for all sexually active women 15-59, for all uses, skip this step. x Use of contraceptives among WRA. To obtain the number of women of reproductive age using a contraceptive method, multiply the number of WRA by the CPR. x Use of contraceptives among female sex workers. To obtain the number of sex workers using a contraceptive method, multiply the number of female sex workers by the CPR. Consider collecting CPR data from organizations that work with, train, or provide legal protection services to female sex workers (if available) since CPR for FSWs may be different from that of the general population. If data is available on the rate of female condoms used per client (or per number of clients seen), combine this step with the next as one frequency. Two methods for determining this step are frequency of female condoms used in the last sexual encounter or female condoms as a percentage of method mix. If there is data available on condoms used in the last sexual encounter, this would be preferable as it might provide a better estimate of female condoms used for any purpose (contraception, HIV or STI prevention). Multiply the number of women by the frequency of female condoms used in the last sexual encounter. (If the forecast is for female condoms for family planning only, multiply the number of women using a contraceptive method by the percent of CPR represented by female condoms). This calculation will determine the number of women using female condoms. Note: if using method mix data specified in terms of percent of WRA using female condoms, be sure to adjust so that the figure you use at this step represents the percentage of modern contraceptive method users using female condoms. For instance if CPR (% of WRA using a modern method) were 30% and % of WRA using female condoms were 1%, then % of modern method users using female condoms would be 1/30 = 3.3%. Since condoms (male or female) may be used in conjunction with other contraceptive methods, female condoms as percent of CPR may be difficult to determine and may not be fully accurate; i.e., condom use may not be recorded in demographic surveys if a survey respondent mentions using another modern method of contraception. Data on use of condoms in the last sexual encounter may be available in reports by organizations providing socially marketed condoms, HIV and AIDS surveys (data on female condom use for HIV prevention will be mainly based on study reports) or other census or demographic reports. Although these reports typically do not distinguish Section 2.1 | Female Condoms 45 between male and female condoms and assume the condom use is male, there may be some statistics available on use of female condoms. Advocacy groups working on educating potential users on use of condoms to determine the frequency of female condom use may also have data available. If no other data are available, you might estimate female condom use as a percentage of male condom use, based on the proportion that female condoms represent of all condom distribution, if those data are available. You might also reference the percent of female condom use per WRA in another country that has experience with this product and shares similar demographics and socio-cultural context with your country. You might also reference data on awareness of the method and access to services among WRA. If disaggregating FSWs from women in general, and evidence on FSW use of female condoms is available, multiply the number of FSW by the proportion using female condoms at last sexual encounter. If there is differentiation among female condoms in the country (e.g., different brands or designs) such that the quantification team believes that the effect of programmatic efforts or other drivers of use might affect different brands or designs unequally, it might be necessary to break the forecast down by brand/design so that separate assumptions can be applied to each. If all female condoms managed in the country are in essence substitutes, then this step can be skipped. Estimate the number of women accessing female condoms from different sources, such as public sector program or social marketing program. If the forecast covers both FP and HIV programs, which finance or manage these products separately such that the forecast end result needs to be separated into condoms for FP and condoms for HIV prevention, you can apply an assumption about the proportion of users served by the FP vs HIV program here. Note however that this allocation between programs for financing reasons can also be accomplished at the supply planning step (after forecasting). For this calculation, multiply the number of women using female condoms by the proportion of women that obtain product from each source that manages female condoms. If logistics data from the national program or survey data are not available, interviews with key informants may provide information." There are a number of options for converting “users of female condoms” to “quantities of female condoms required to meet users’ needs.” Coital frequency represents the frequency of intercourse per year and thus could be a proxy for the number of times condoms are used to prevent an unintended pregnancy, an STI or HIV. If available, this figure may be used to estimate the quantities of female condoms needed per user per year. Surveys on coital frequency are rare, but if there are HIV and AIDS or reproductive health and contraceptive surveys that ask about coital frequency—in particular frequency of protected sex acts—this is the preferred data to use for this calculation. If data on coital frequency is not available, then the CYP factor4 is the measure typically used to determine the quantity of a product required to protect one user (one couple) from unintended pregnancy for one year. Even when forecasting for all uses (not only family Section 2.1 | Female Condoms 46 planning), quantification teams may choose to use the CYP factor for this conversion if no other reliable conversion factor is available. x Sexually active women (age 15-59). Convert the number of women to quantities of product required by multiplying the number of women using female condoms (by brand and source, if applicable) by the CYP factor of 120 female condoms. If data are available, frequency of protected sex may be a better figure to use. Multiply the number of women using female condoms by the frequency of protected sex acts (annual). x Female sex workers. For female sex workers, determining the number protected sex acts for a period of time (such as in a week or in a month, then adjusted to be annual) would be a better figure to use than the CYP or the coital frequency of the average woman. This information might be available from local studies, key informant interviews with organizations that work with FSW, or a focus group discussion with FSW networks. For this calculation, convert the number of women to the quantity of products required by multiplying the number of FSW using female condoms by the number of protected sex acts per year. These calculations result in the quantity of product required to meet client needs for each year of the forecast period as shown in figure 2. Please refer to Quantification of Health Commodities for guidance on the supply planning step. Section 2.1 | Female Condoms 47 The sample algorithm (figure 2) illustrates the steps to follow when forecasting for female condoms for public sector and a social marketing program. A1 Percentage of women 15-59 in union, sexually active, or both A2 Percentage of women who are FSW A3 % of women 15-59 reporting female condom use at last sexual encounter A4 % of FSW reporting female condom use at last sexual encounter A5 Percentage sourcing female condoms from public sector (Note: if source mix is different among women in general and FSW, use different assumptions for the disaggregated groups) A6 Percentage sourcing female condoms from social marketing sector A7 Evidence-based estimate of coital frequency where female condom was used or method-specific CYP factor The final result is the estimated quantities of female condoms needed to meet client demand for each year of the forecast; however, this alone should not be used for procurement. In addition to this figure, other data will be used during the supply planning step. Refer to the original Quantification of Health Commodities for guidance on supply planning. Section 2.1 | Female Condoms 48 x Lubricant may be necessary with some brands. x Pelvic models are necessary at service delivery points for demonstration of proper insertion. A number of different female condoms are available on the market. As of June 2013, two female condom brands were prequalified by the WHO/United Nations Population Fund (UNFPA). Additional designs are under review or development. If programs in a country manage more than one type/brand of female condom that must eventually be purchased from different vendors, then the quantification should take this into account. That is, each type or brand of female condom must ultimately be treated separately in the calculation, so that the end result will allow the team to proceed to the supply planning step for each product separately. Section 2.1 | Female Condoms 49 Country X would like to estimate the quantities of female condoms to be consumed by clients of their public sector RH/FP and National AIDS Control programs and social marketing program over the next two years Available data includes (DHS data from current year): x Total population as of current year (Population Reference Bureau): 9,125,500 million x Population growth rate (DHS): 3.23% x Percentage of population that is women (DHS,): 51 x Percentage of women ages15-59) (DHS: 49% x Estimated proportion of female sex workers (FSW) (local study, a year old): 0.5% of urban women x Percentage of women using female condom at last intercourse: 0.2% x Percentage of clients accessing female condoms by source: public sector (DHS): 50; social marketing: 40 x CYP Factor: 120 Assumptions the quantification team agreed on: x The number of FSW is too small to warrant forecasting separately x There is no estimated change in the proportion of the population that is women or the proportion of women that are ages 15-59 x All sexually active women are at risk of pregnancy and STI/HIV transmission x Estimated annual percentage increase in percentage of women using female condom at last intercourse: %0.05 x Source mix remains stable x CYP factor is the best estimate currently available for the quantity of FC needed per user per year Input Current year Forecast year 1 Forecast year 2 1. Population Pop. Growth Rate 3.23% 9,125,500 9,420,254 9,724,528 2. Number of women in the population % of population that is women 51% 4,654,005 4,804,329 4,959,509 3. Number of women ages 15-59 % of women that are 15-59 49% 2,280,462 2,354,121 2,430,160 4. % of women using FC at last intercourse annual increase in % of women using FC 0.05% 0.20% 0.25% 0.30% 5. Number of women using female condoms 4,561 5,885 7,290 6a. WRA using female condoms from public sector source mix - public sector 50% 2,280 2,943 3,645 6b. WRA using female condoms from social marketing sector source mix - social marketing 40% 1,824 2,354 2,916 7a. Estimated annual consumption of female condoms - public sector Couple-Years of Protection Factor 120 273,655 353,118 437,429 7b. Estimated annual consumption of female condoms - social marketing sector 218,924 282,495 349,943 Section 2.1 | Female Condoms 50 1 USAID | DELIVER PROJECT, Task Order 4. 2011. Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. 2 Institute for Reproductive Health, Georgetown University (IRH/GU), John Snow Inc. (JSI), and Population Services International (PSI) for the Reproductive Health Supplies Coalition (RHSC). 2012. A Forecasting Guide for New & Underused Methods of Family Planning: What to Do When There Is No Trend Data? Washington, DC: IRH/GU, JSI, and PSI for the RHSC. 3 Measure Evaluation PRH. Family Planning and Reproductive Health Indicators Database. Couple- Years of Protection. http://www.cpc.unc.edu/measure/prh/rh_indicators/specific/fp/cyp 4 The RESPOND Project technical meeting. New Developments in the Calculation and Use of CYP and Their Implications for Evaluation of Family Planning Programs. September 8, 2011. New York: EngenderHealth (The RESPOND Project). Also available at http://www.cpc.unc.edu/measure/prh/rh_indicators/specific/fp/cyp. Accessed 30 October 2013. Section 2.1 | Contraceptive Implants 51 Contraceptive implants are a highly effective hormonal family planning method used by women of reproductive age to prevent pregnancy. The product is a small, flexible plastic matchstick-sized rod (or rods) inserted under the skin of a woman’s upper arm that releases a progestin hormone over the course of the implant lifespan (3-5 years). Based on the WHO medical eligibility criteria for contraceptive use (2009),1 implants are suitable for nearly all women. Please refer to the WHO criteria for the full list of contraindications. Insertion should be per the labeled indication. Furthermore, implants should be administered in a setting in which the client has received “adequate information in order to make an informed, voluntary choice of a contraceptive method.” Skills-based and knowledge-based training are required to ensure the implant is administered safely according to medical criteria guidelines and to ensure that the woman is informed about possible risks and side-effects (e.g., bleeding pattern changes). Insertion and removal of implants requires a minor surgical procedure, which should be undertaken by “appropriately trained personnel in adequately equipped and accessible facilities.” The Commission case study notes that with “appropriate training, a wide variety of health care providers can provide implants safely and effectively. These cadres of providers include physicians, midwives, nurses, nurse auxiliaries, clinical officers, and, depending on educational and professional standards in each country, physician’s assistants and associates.” There are examples of community-level provision of implants as well as provision via mobile clinics. Please refer the WHO recommendations Optimizing health worker roles to improve access to key maternal and newborn health interventions through task shifting2 for more information. Though the Commission explicitly includes two-rod 150 mg levonorgestrel implants on its product list, the Commission’s Technical Reference Group on contraceptive implants includes all implants in its work plan regardless of brand, presence of the formulation on the WHO EML, or WHO prequalification status.3 Accordingly all implants are considered in this guidance document as well. The Commission product case study notes that the two-rod 150 mg levonorgestrel implants are included in the WHO EML (2011) but the one-rod 68 mg etonogestrel implants are still not included. Table 3 summarizes characteristics of the implants currently available. Section 2.1 | Contraceptive Implants 52 4 Implanon NXT™a Jadelle® Sino-implant (II)®b Manufacturer Merck Sharp & Dohme B.V. Bayer Pharma AG Shanghai Dahua Pharmaceuticals Co., Ltd. Active ingredient and amount 68 mg etonogestrel 150 mg levonorgestrel 150 mg levonorgestrel Labeled duration of effective use 3 years 5 years 4 years No. of rods 1 2 2 Trocars disposable disposable disposablec Shelf life 5 years 5 years 4 years CYP5 2.5 3.8 3.2 a Implanon NXT™ is progressively replacing Implanon in all countries. b Sino-implant (II) is sold under various trade names by different distributors: as Zarin® by Pharm Access Africa, Ltd.; as Trust Implant® by DKT Ethiopia; as Femplant™ by Marie Stopes International; and as Simplant® by WomanCare Global. c With the exception of China and India, Sino-implant (II) is provided with a disposable trocar. One-rod implants from Merck and two-rod implants from Bayer have been prequalified under the WHO Prequalification of Medicines Programme.3 Implants are ideally stored at controlled room temperature of 20-25°C. For well-established implant programs where data are available on product consumption, a logistics- or trend-based forecast should be prepared. Services data that describe the number of clients using implants are another alternative, but may underrepresent current users since implants rarely require a visit to a provider after insertion. Please refer to Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement6 and Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies7 for thorough guidance and examples of consumption and services data-based forecasting methodologies. Note that if financing has been a limiting factor for procurement and provision of implants in the past, the recent price reductions for implants may also mean that historical consumption data are not a reliable predictor future consumption, even for well-established programs. In the absence of robust consumption or services data, estimates based on demographic data, program plans/targets, or service capacity may be used to estimate the quantities required. A forecast based on program targets or plans, service provider capacity, or demographic data will tend to overestimate the quantity required because these methodologies require multiple assumptions about actual demand. The more assumptions are made in forecasting, the higher the chance for error. In addition, program plans for scale up may not match available funding or service provider training. Thus the resources that would be required to meet program targets should be reviewed stringently. To avoid overestimates, be realistic in estimates of service provision and client demand. No matter what forecast method is used, monitoring stock levels and demand regularly and maintaining a flexible supply chain are important to allow program planners to act if either too few or too many products are in the pipeline. A discussion of these methodologies and an extensive example of using them for forecasting implants consumption for a new program are detailed in Quantification of Health Section 2.1 | Contraceptive Implants 53 Commodities: Contraceptive Companion Guide. A sample algorithm for demographic forecasting for an existing program that does not have reliable logistics or services data will be sketched out below. The Quantification of Health Commodities: RMNCH Supplement focuses on the demographic forecasting method, but for new or expanding programs, two additional forecasting methodologies may be relevant and could be used to triangulate or validate forecasts: program targets and services capacity methods. Quantification of Health Commodities: Contraceptive Companion Guide offers examples of both for methods when forecasting of implants: p. 44 for forecast based on program targets and p. 45 for forecast based on service capacity. Training on implant insertion and removal requires competency-based training that includes supervised practice, usually through a combination of simulations on model arms and supervised observation of live insertions/removals in the clinic setting. This means that even if not using the service capacity forecast methodology, the forecast needs to take into consideration the number and distribution of trained health providers. Table 4 shows the likely sources of data for each of the steps. All data and assumptions that are used in the process of forecasting should be documented. This makes it possible for others to review, understand, and to update or revise data and assumptions as better information becomes available. This documentation can also serve as a reference for future forecasts or adjustments. x Target population o Total population o Population growth rate o Percentage of population that is women o Percentage of women who are of reproductive age (WRA), i.e., women at risk for pregnancy o Contraceptive prevalence rate (CPR) o Method mix (proportion of CPR attributable to implants) o Product mix (proportion(s) of method mix by product/brand) o Source mix (proportion of method or product mix by service delivery source, e.g., public, NGO/social marketing, private sector) x Programmatic plans or changes that would affect consumption of implants such as increase in service provision, additional providers trained in counseling, and knowledge-based skills; a new cadre of providers such as CHWs authorized to insert; campaigns to expand provision of method, or constraints on service provision, such as number of trained providers or adequate facilities; new restrictions on who is authorized to insert) x Couple-Years of Protection (CYP) conversion factor by product/brand or estimated insertion and removal rates x Estimated number of insertions and removals a trained provider (or facility) will do in a given time period x Estimated wastage rate if wastage at the point of consumption is deemed to be material x Availability of medical instruments, expendable medical supplies, and infection prevention supplies required to provide contraceptive implants Section 2.1 | Contraceptive Implants 54 Data Source Limitation Total population National census data, DHS May be outdated; may need to apply estimated annual growth rate to project to forecast years Percent of population that is women DHS, census data, RHS Data quality is not always known, may be outdated Number or percent that are women of reproductive age (15–49) Census data, DHS, RHS Data quality is not always known, may be outdated Contraceptive prevalence rate, method mix DHS, MICS, RHS, national health surveys, census data Data quality is not always known, may be outdated; may only report CPR for WRA in union Product mix MoH reports, LMIS records, facility records, DHS, MICS, MoH or NGO program records, RHInterchange (myaccessrh.org/rhi-home) Not always complete, data quality not always known, may be outdated or not collected; shipment information by product/brand (from RHInterchange) is not a direct proxy for dispensed-to user information Source mix (Service provision source where client is provided with product) DHS, key informants e.g. NGOs Not always accurate or may have changed since survey was carried out Couple-Year of Protection (CYP) factor USAID-endorsed standard factors5,8 May not reflect country-specific continuation/discontinuation rate: CYP offers a proxy for global continuation rates, but continuation can vary dramatically by country and health system. CYP is affected by counseling, age, and intentions of the user and the availability of skilled providers for removal. Service provider capacity for appropriate counseling, insertion and removal procedures Program records (e.g., from sample sites), training records, research from other countries on number of insertions possible per day Research from other countries may not reflect country- or health service delivery-level possibilities or constraints. Data from sample sites may not be nationally representative. Program plans Program records, key informants Ensure that funding and appropriate human resources are available to support the program plans, and are in place before increases in consumption are forecast. Availability of required instruments/supplies MoH Reports, LMIS records, facility records, program records If equipment, instruments, or supplies are used for other purposes than insertion/removal of implants then their availability may not be guaranteed The demographic forecasting calculation typically involves the number of clients who will be users of implants in each year of the forecast period divided by the method/brand-specific CYP factor to determine the quantity of implants that would be needed to serve that number of clients. We present here a second option for converting from numbers of users to quantities of product. This second option may be more appropriate for newly instituted or growing programs and involves estimating the numbers of new insertions and reinsertions among implants users. Section 2.1 | Contraceptive Implants 55 If research indicates that wastage at the point of consumption (insertion) is significant e.g. products contaminated, damaged or discarded due to errors in insertion, then this can be built into the forecast. The total quantity needed for the forecast period can be used as the basis for calculating the quantities of equipment, instruments and supplies needed for insertion and removal procedures. For more on this, please refer to Quantification of Health Commodities: Contraceptive Companion Guide pages 35 and 51-52. 1. Determine scope of quantification—types of facilities, sectors (public, private, NGO, etc.) 2. Determine assumptions that will affect the target population that will use implants in the forecast period 3. Calculate the target population that will use implants in the forecast period 4. Estimate the number of implants clients by brand 5. Estimate the number of implants clients by source 6. Calculate the quantity of implants (sets) needed in the forecast period, by brand and source Clarify whether the quantification will cover the product needs for all programs and sectors in the country, or a subset of the channels through which implants are provided, e.g., public sector, social marketing. Survey data, for example from a DHS or MICS, can give planners an idea of the current situation regarding implant use, i.e., implants as a proportion of the contraceptive prevalence rate (CPR). If implants programs have existed for some years, it may even be possible to see a trend in implants use between two survey periods. Keep in mind that growth in use of implants has been rapid in many countries but as programs become established, increases may not be as dramatic. If implants programs are new or yet to be introduced, planners may need to do some educated guessing and come to consensus on figures to use in estimating the number of users. Quantification of Health Commodities: Contraceptive Companion Guide pages 33- 35 offers an example of the types of assumptions they may need to discuss and come to agreement on. For instance, they may need to consider the following questions and how these will affect the indicators and assumptions used in the coming steps: Demographic forecast: x Will planners use WRA in union or all WRA to represent current and potential users of contraceptive methods? Note: We recommend using all WRA since many unmarried WRA are sexually active, but this assumption may not be appropriate in all countries. x Will the population of WRA grow at the same rate as the overall population (if adjusting outdated population figures)? x What is the projected increase (or decrease) in CPR? x What is the projected increase (or decrease) in implants as a proportion of the method mix? (Will all methods increase or decrease by the same proportion or will some users switch from other methods to implants, for example?) Section 2.1 | Contraceptive Implants 56 x Is CYP a good proxy for continuation/discontinuation, or if not, what might the rates of insertion and removal be in the forecast period? Services capacity and program plans: x How many trained providers there are/how many will be trained (Is there funding for this training?) x Are there properly equipped facilities for training and for implants insertion/removal? x How many insertions and removals is it expected that providers will do?* When deciding how many insertions providers can do (per day, per month, etc.) consider what other duties the targeted providers must perform. Do their regular duties leave them time enough for the insertion/removal process? How many procedures might a provider realistically do within the limits of his or her other responsibilities each day? x What types of information, education, and communication or other demand-creation activities are planned? x How many new implants users does the program expect to serve? x How many users are expected to continue into the next year? How many new users will there be the next year? In addition, the program’s ability to offer implants will also depend on whether the implants and all the instruments and supplies needed for insertion are available when and where needed in the country. Planners will need to determine (or create an assumption about) whether the required medical instruments, expendable medical supplies, and infection prevention supplies will be available. Related, some countries elect to procure kits that include implants as well as the medical supplies required for insertion. The target population is the number of WRA who will be users of implants in the forecast period. This includes both new adopters and continuing users. The assumptions built in the previous step and their effect on the following data elements will guide calculation of this figure. x Total population of the country x Percentage who are women x Percentage who are of reproductive age x Percentage who use modern methods of contraception (CPR) – Note: if CPR data are only available for women in union, apply this proportion to women in union only; if the quantification team has elected to consider all WRA in the quantification, but CPR data are only available for women in union, discuss and reach consensus on an assumption about use of contraception among unmarried WRA. x Percentage who use implants (method mix) – Note: if using method mix data stated in terms of % of WRA using implants, be sure to adjust so that you use a figure that represents the % of contraceptive users who use implants. For example, if CPR (% of WRA using a modern method) is 30% and % of WRA using implants is 2.5%, then % of CPR due to implants is 2.5/30 = 8.3%. Please refer to the sample forecasting algorithm for a visual depiction of these steps. * Anecdotally, PSI reported that a dedicated family planning provider on a specific event day could do the following number of insertions: 10 (Zambia), 15 (Togo), 30 (Mali, with an assistant). On a regular service provision day (not a dedicated event), Togo reported 2 insertions per day. Also anecdotally, in 2012, MSI Uganda inserted 143,762 implants, primarily through 24 mobile outreach teams. Personal communication with Maxine Eber, PSI and Rehana Gubin, Jhpiego, September 2013. Section 2.1 | Contraceptive Implants 57 More than one implant brand may be used in the country. Since brands may be procured from different vendors, you will need to make separate estimates of the numbers of clients that programs will provide with each brand. In the case of implants, it may be likely that program or provider product selection or training decisions (rather than client preferences) are driving the demand for different brands. Perhaps the public sector has chosen to manage one brand while a social marketing organization offers another. In addition, survey data does not typically break down implants by brand, so data on current use by brand may not be representative (or predictive of future use). Thus it is quite possible that the quantification team will need to build separate assumptions about growth (or decline) by brand, if programs managing different brands also have different plans for demand creation, provider capacity building, equipping facilities, or devoting mobile units to implants procedures. If the product is newly introduced, you will also need to consider the magnitude of scale- up expected in the coming years (whether based on a target or on trends in demand) and build those assumptions into the estimated client numbers for future years of the forecast period. This calculation is based on the result from the previous step, using: x Percentage of WRA using each brand of implants x Percentage of WRA receiving their contraceptive methods from public/social marketing/private/other sector If there is more than one programmatic source (e.g., public sector, social marketing, private clinic) providing women with implants in the country and included in the forecasting exercise, it will also be necessary to segment the estimated number of clients by source—at minimum to specify the number of clients that will be served by the sources included the forecast (as determined in step 1). For instance, if public sector is the only program considered in the quantification, then you need only calculate the number of clients to be served by that sector. In theory, the only implant clients who require product in a given period are (1) new adopters and (2) clients who have reached the useful life of their implants and elect to have them removed and a new set inserted. To convert from the number of clients in a period to the quantity of products needed to serve them, you need to know what proportion of users are new insertions in the period, and what proportion of users who have had implants inserted in the period will have them removed and new ones inserted. Option 1: When using demographic data for forecasting, and in the absence of actual study data on discontinuation rates for a country (which may differ by brand), you can use the CYP factor as a proxy. The CYP is the quantity of product needed to protect a couple from pregnancy for one year. See table 4 for the CYP factors for each implant brand. Implants have a CYP factor greater than one because their useful life is longer than one year per item or set. That is, a single item or set can provide more than one year of protection from pregnancy. For example, if 100 women are users of Jadelle implants in a given year, the calculation is: Section 2.1 | Contraceptive Implants 58 100 users (i.e., couples) = 26.3 implants per year 3.8 years of protection per implant per couple Therefore, 27 sets of Jadelle will be needed to meet the insertion/reinsertion needs of 100 WRA using Jadelle implants, because some current users are in the middle of their use life and do not need a new set. Using the CYP factor to convert from users (where CPR includes all users at a given time no matter where they are in the use life of the product) accounts for this. Option 2: The CYP factor for implants takes into account the average duration of time that a woman uses the implant. For example, the CYP for the Jadelle implant is 3.8 years. This means that on average, a woman will use Jadelle for 3.8 years even though its duration of effective use is 5 years. Since the CYP is based on the average duration of use, it can also be used to estimate the percentage of women who are discontinuing the use of implants each year. This discontinuation rate can then be used to determine the number of users needing a new implant each year. The formula8 to determine the number of users who will need a new implant in year X is the following (based on the RESPOND/EngenderHealth’s Reality Check tool calculations): a. Number of users in the current year (year X) – number of users in the previous year = Net difference in the number of users b. Number of users in the previous year * 1/CYP (the discontinuation rate) = the number of users in the previous year who have discontinued use c. Net difference in the number of users (step a) + Number of users in the previous year who have discontinued use (step b) = Total number of users needing a new implant in year X This formula gives you an estimate of the number of users who are new to implants and will therefore need a new implant, and the number of users who have removed an old implant and who may need to reinsert a new implant. To find the number of implants needed in year X to meet this need, multiply the answer to the formula above (Total number of users needing a new implant in year X) x 1 implant per user. An example to illustrate: let’s say our demographic forecast for the public sector estimates 10,000 users of Jadelle in the current year, 12,000 users in forecast year 1, and 14,000 users in forecast year 2. Calculation for forecast year 1 (12,000 – 10,000) + (10,000 * 1/3.8 [0.263]) = 4,632 users (new and discontinuing/reinserting) needing a new Jadelle implant in forecast year 1 4,632 * 1 = 4,632 sets of Jadelle required to meet need in forecast year 1 Calculation for forecast year 2 (14,000 – 12,000) + (12,000 * 0.263) = 5,158 users (new and discontinuing/reinserting) needing a new Jadelle implant in forecast year 2 5,158 * 1= 5,158 sets of Jadelle required to meet need in forecast year 2 Section 2.1 | Contraceptive Implants 59 If you have country-specific representative data on implants continuation rates for your country (which may differ by brand), you may elect to use that information in place of the CYP factor in the above calculation to estimate the quantities of product needed to serve new and continuing (or discontinuing, for removals) users each year. Option 2 is a way to estimate the number of new users (new insertions) for each year of the forecast period as well as the number of removals/reinsertions to maintain the projected CPR due to implants. This makes it possible to use a 1:1 ratio of new insertions and reinsertions to sets of implants required to meet the product needs as well as estimate the quantities of instruments and supplies needed for the expected insertions and removals. Option 2 yields higher commodity needs than Option 1 and may be more appropriate for new/growing implants programs that are not yet well established with a stable number of users from year to year. Insertion and removal of implants are minor surgical procedures that require additional medical instruments, expendable medical supplies, and infection prevention supplies. As such, forecasting for implants must take into account not only the device (implant) itself, but also the quantities of instruments and supplies required for insertion or removal. As of this writing, disposable trocars or insertion devices for implants insertion are provided with all implants (with the exception of Sino-implant (II)® in China and India). Applicators/trocars and other expendable instruments or supplies should be disposed of per country guidelines for medical contaminated waste. Please see table 5 for a list of instruments and supplies for insertion and removal of hormonal implants. In addition to this list, for programs that are expanding and training new clinicians, Merck notes that training placebos (placebo implants) are available. Merck recommends a minimum of at least one placebo per trainee, noting that three is optimal. Furthermore, Merck recommends 10-15 training kits per master trainer (assuming that each master trainer trains between 10-15 health professionals per training session).† Instruments and Supplies Insertion Removal Expendable or Reusable Unique Implants (Implanon NXT™, Jadelle® or Sino-implant (II)) X Expendable (1) Trocar and cannula or pre-filled insertion applicator (As of this writing, all implants come with disposable trocar or applicator, with the exception of Sino-implant (II) in China and Indonesia) X Expendable † Personal communication with Koen C. Kruytbosch, Merck, 11-Mar-2014. Merck also notes that the current cost of Implanon NXT™ placebo is 4.5 USD and the cost of the training kit is around 55 Euros. Section 2.1 | Contraceptive Implants 60 Instruments and Supplies Insertion Removal Expendable or Reusable Indispensable (1) Scalpel, handle, #3, graduated in cm with blade (#11) X Reusable or expendable (handle) Expendable (blade) (1) Forceps, mosquito (5 inch or 12.7 cm, curved, delicate) X Reusable (1) Forceps, mosquito (5 inch or 12.7 cm, straight) X Reusable Common Light source (if no natural light at service site) X X Reusable (1) Clean tray X X Reusable (1) Cup, bowl or gallipot X X Reusable (1) Forceps, Rampley, sponge-holding, Straight (5.5 inch or 14 cm) X X Reusable Alcohol-based handrub or soap and water (for hand hygiene) X X Expendable Small towel (for hand drying if soap and water were used) X X Reusable (1) Sterile surgical drape, small (to rest the client’s arm on) X X Expendable (1) Sterile surgical drape, fenestrated* X X Expendable (1) Pair of sterile gloves X X Expendable Antiseptic solution, such as iodine X X Expendable Local anesthetic such as lidocaine, (without epinephrine, 1% or 2%) X X Expendable Distilled water to dilute lidocaine (if 2% lidocaine is used) X X Expendable (1) 5 ml syringe with 1.5 inch and 21 gauge needle X X Expendable Sterile gauze sponges X X Expendable Skin bandage or band-aid X X Expendable Arm bandage (to apply pressure to the incision) X X Expendable Drapes (for packing instruments) X X Expendable Bleach (for decontamination solution) X X Expendable Safety box for sharps disposal X X Expendable (once full) *According to Merck, sterile fenestrated drape is not required for Implanon insertion. Source: Adapted from Cagatay, Levent, Carmela Cordero, and Roy Jacobstein, 20139 and Quantification of Health Commodities: Contraceptive Companion Guide, 2011.10 A product is classified as “Unique” if it is used exclusively to provide that particular method of contraception A product is classified as “Indispensable” if it is essential to provide the method, without which the service cannot be rendered. A product is classified as “Common” if it has multiple uses across a variety of surgical procedures and techniques. Section 2.1 | Contraceptive Implants 61 As noted, there are currently three manufacturers/suppliers of hormonal implants. Recent efforts have achieved price reductions or volume-based discounts for Jadelle and ImplanonNXT for many countries. As of this writing, both USAID and UNFPA procure both Jadelle and ImplanonNXT. Sino-implant (II) is marketed under a variety of names by different distributors: as Zarin® by Pharm Access Africa, Ltd.; as Trust Implant® by DKT Ethiopia; as Femplant™ by Marie Stopes International; and as Simplant® by WomanCare Global.11 This sample algorithm illustrates the steps a quantification team might follow when forecasting consumption of hormonal implants. In this example, the quantification team must consider the quantities needed for more than one program, as well as more than one brand. Section 2.1 | Contraceptive Implants 62 Section 2.1 | Contraceptive Implants 63 A1 Percentage of WRA in union and sexually active A2 Contraceptive prevalence rate (modern methods) A3 Method mix (percentage of CPR attributable to implants) A4,5 Product/brand mix (percentage of users who use each brand) A6 Source mix (percentage of users who receive product by source of supply) – public sector A7 Source mix – social marketing sector A8,9 Brand-specific CYP factor (Option 1) OR Calculation of new + discontinuing/reinserting users * 1 set of implants per insertion (Option 2) The final result is the estimated annual demand for hormonal implants, by brand and source (sector), however, these figures should not be used for procurement. The forecast figures will be used along with other data during the supply planning step. Please refer to Quantification of Health Commodities for guidance on supply planning. Country X would like to determine how many implants are needed for its public sector and social marketing family planning programs for the next two years. Available data includes (all DHS data is from current year): x Total population as of current year (Population Reference Bureau): 16,000,000 o Percentage of population that is women (DHS): 51 o Percentage of women that are of reproductive age (DHS): 44.3 o Percentage of WRA using a modern method of contraception (CPR) (DHS): 42 o Percentage of CPR due to implants (DHS): 1 o Percentage of clients accessing implants by source (DHS): public sector: 82, social marketing: 15 Assumptions the quantification team agreed upon: x There is no projected change in the proportion of the population that is women x There is no projected change in the proportion of women that are of reproductive age x All WRA are at risk of pregnancy x Estimated percentage annual increase in CPR: 1 x Estimated CPR increase is the same regardless of implant brand or source of supply x Estimated percentage increase in implants as a proportion of CPR: 0.2 x Percentage product (brand) mix: ImplanonNXT—35%, Jadelle—65% x No projected change in the source mix from theDHS, applied the same to both brands x CYP is an accurate-enough reflection of local discontinuation rates (box 6 continued on following page) Section 2.1 | Contraceptive Implants 64 Input Current year Forecast year 1 Forecast year 2 1. Population Pop. Growth Rate 3.1% 16,000,000 16,496,000 17,007,376 2. Number of women in the population % of population that is women 51% 8,160,000 8,412,960 8,673,762 3. Women of Reproductive Age (WRA) % of women that are 15-49 44.3% 3,614,880 3,726,941 3,842,476 4. CPR est. annual increase in CPR 1% 42.0% 43.0% 44.0% 5. WRA using a modern method of contraception 1,518,250 1,602,585 1,690,690 6. Method Mix - implants est. annual increase in method mix due to implants 0.2% 1.0% 1.2% 1.4% 7. Implants users as proportion of all contraceptive method users 2.38% 2.79% 3.18% 8. Number of WRA using implants 36,149 44,723 53,795 9a. Number of WRA using ImplanonNXT product mix - Implanon 35% 12,652 15,653 18,828 9b. Number of WRA using Jadelle product mix - Jadelle 65% 23,497 29,070 34,967 10a. Number of WRA receiving ImplanonNXT from public sector source mix - public sector 82% 10,375 12,836 15,439 10b. Number of WRA receiving ImplanonNXT from social marketing source mix - social marketing 15% 1,898 2,348 2,824 10c. Number of WRA receiving Jadelle from public sector source mix - public sector 82% 19,267 23,838 28,673 10d. Number of WRA receiving Jadelle from social marketing source mix - social marketing 15% 3,525 4,361 5,245 11. Estimated annual consumption - OPTION 1 (# users/CYP factor) a. ImplanonNXT - public sector CYP factor - ImplanonNXT 2.5 4,150 5,134 6,176 b. ImplanonNXT - social marketing 759 939 1,130 c. Jadelle - public sector CYP factor - Jadelle 3.8 5,070 6,273 7,545 d. Jadelle - social marketing 928 1,148 1,380 12. Estimated annual consumption - OPTION 2 (# users forecast yr 1 - # users current yr) + (# users current yr/CYP factor) a. ImplanonNXT - public sector CYP factor - ImplanonNXT 2.5 * 6,611 7,738 b. ImplanonNXT - social marketing * 1,209 1,415 c. Jadelle - public sector CYP factor - Jadelle 3.8 * 9,641 11,108 d. Jadelle - social marketing * 1,764 2,032 Section 2.1 | Contraceptive Implants 65 1 World Health Organization (WHO). Medical eligibility criteria for contraceptive use. 4th ed. Geneva: WHO; 2010. 2 World Health Organization (WHO). Optimizing health worker roles to improve access to key maternal and newborn health interventions through task shifting. Geneva: WHO, 2012. http://www.optimizemnh.org 3 WHO - Health Systems and Services: Prequalification of Medicines Programme. http://apps.who.int/prequal/. WHO 2015. 4 Jacobstein R, Stanley H. Contraceptive implants: providing better choice to meet growing family planning demand. Glob Health Sci Pract. 2013;1(1):11-17. http://dx.doi.org/10.9745/GHSP-D-12- 00003. (Adapted and augmented from a table originally prepared by FHI360, USAID and the RESPOND Project ) 5 The RESPOND Project technical meeting. New Developments in the Calculation and Use of CYP and Their Implications for Evaluation of Family Planning Programs. September 8, 2011. New York: EngenderHealth (The RESPOND Project). Also available at http://www.cpc.unc.edu/measure/prh/rh_indicators/specific/fp/cyp. Accessed 30 October 2013 6 USAID | DELIVER PROJECT, Task Order 1. 2008. Quantification of Health Commodities: A Guide to Forecasting and Supply Planning for Procurement. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 1. 7 USAID | DELIVER PROJECT, Task Order 4. 2011. Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. 8 The RESPOND Project 2014. Reality Check: A planning and advocacy tool for strengthening family planning programs: Version 3. User’s Guide. New York, EngenderHealth. 9 The RESPOND Project. 2013. Instruments and Expendable Supplies Needed to Provide Long- Acting and Permanent Methods of Contraception. New York: EngenderHealth/The RESPOND Project. 10 USAID | DELIVER PROJECT, Task Order 4. 2011. Quantification of Health Commodities: Contraceptive Companion Guide. Forecasting Consumption of Contraceptive Supplies. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. 11 Caucus on New and Underused Reproductive Health Technologies, 2013. RHSC Product Brief: Contraceptive Implants. Brussels: July 2013. Quantification of Health Commodities RMNCH Supplement 66 Section 2.2 | Magnesium Sulfate 67 One of the most common, yet treatable, causes of maternal death and disability worldwide is pre-eclampsia/eclampsia (PE/E)—characterized by the rapid elevation of blood pressure during pregnancy, decreased kidney function, and disseminated intravascular coagulation. It is estimated that 2–8 percent of all pregnancies are complicated by preeclampsia; however, according to WHO, in Africa and Asia, nearly one-tenth of all maternal deaths are associated with hypertensive disorders of pregnancy, whereas one-quarter of maternal deaths in Latin America have been associated with those complications.1 Eclampsia can occur in the second half of pregnancy, during labor, or after the birth, and is more common in low- and middle-income countries than in high-income countries. The pathogenesis of eclampsia is partially understood: it is related to inflammation and endothelial damage, and to placental development. Approximately 5–8 percent of women with pre-eclampsia present with this condition (eclampsia) in developing countries.2 For hypertensive disorders of pregnancy, the second most common cause of maternal death, greater use of magnesium sulfate is clearly called for.3 Magnesium sulfate (MgSO4) is an anticonvulsant and is the safest and most effective option for the prevention and treatment of pre-eclampsia and life-threatening seizures of eclampsia According to a WHO survey, although 85% of countries have magnesium sulfate available, there are various socio-cultural and policy-based issues hindering its use. Some providers are hesitant to administer it because of perceived side effects. In addition, there are sometimes delays in the patient receiving the second dose during transfer to a higher level facility. WHO recommends magnesium sulfate for the prevention of eclampsia in women with severe pre-eclampsia in preference to other anticonvulsants.4 Magnesium sulfate is available in various formulations; the WHO recommended presentation is 50% weight/volume which is equivalent to 0.5 g in 1 mL.5 The product is administered for 24 hours after last convulsion or delivery, whichever occurs later. The duration of treatment depends on clinical progression. There is evidence that this product may be underutilized in some countries as providers may not be aware of magnesium sulfate as a treatment option, do not know how to administer it correctly, or are concerned about potential issues with toxicity and side effects to the patient.40,43 Current practices as well as plans to increase use of magnesium sulfate should be taken into account during forecasting. Country-level data on the number of pregnant women who develop PE/E are limited; therefore, there is often a need to use proxy data. Regardless of the presentation, providers will be required to calculate the correct amount of magnesium sulfate to administer according to the dosing regimen selected (Pritchard’s or Zuspan’s regimens). For the purposes of forecasting, the use of the product for 24 hours after start of administration is considered; however, many patients are treated longer for up to a total of 48 hours. In some settings, patients may receive a loading dose from a lower level facility and then be referred to a higher level facility for continued treatment. In some cases, the patient may only receive the loading dose or an incomplete regimen if the provider determines that the patient has improved and does not require further treatment. These considerations should be discussed with national experts during the forecasting exercise. Section 2.2 | Magnesium Sulfate 68 Quantification teams may find the following programmatic assumptions relevant for estimating the number of cases of PE/E and the quantity of product required to treat them. x Pre-eclampsia complicates 2%–8% of pregnancies;6,7 however, a proxy figure of 2% that will require treatment severe PE/E with magnesium sulfate is used as a global average. x Every health facility in which births are attended should have available stocks of magnesium sulfate to deal with emergency cases of PE/E. Table 6 shows the likely sources of data. All data and assumptions that are used in the process of forecasting should be documented. This makes it possible for others to review, understand, and to update or revise data and assumptions as better information becomes available. This documentation can also serve as a reference for future forecasts or adjustments. Data Source Limitation Forecasting Total population Census data, DHS, RHS, US Census Bureau International Database May be outdated; may need to apply estimated annual growth rate to project to forecast years Proportion of pregnant women DHS, health management information system (HMIS), national maternal morbidity and mortality surveys, special surveys DHS data usually an underestimate Proportion of facility- based deliveries/births DHS, HMIS, national maternal morbidity and mortality surveys, special surveys DHS data usually an underestimate Percentage of pregnant women who have severe pre-eclampsia or eclampsia HMIS, national maternal morbidity and mortality surveys, special surveys Data limited. Literature indicates that pre- eclampsia complicates 2%-8% of pregnancies; however, 2% is often used as a global average when country level figures are not available. Percentage of pregnant women with PE/E who are likely to be given MgSO4 HMIS, national maternal morbidity and mortality surveys, special surveys Data may be incomplete or underestimates x Target population x Total number of pregnant women in population x Total number of births at facilities o Number of pregnant women developing PE/E likely to be given magnesium sulfate for prevention and treatment among facility-based births x Standard or average treatment regimen, i.e., amount of magnesium sulfate needed to prevent or treat each case of PE/E x Programmatic issues that may affect consumption (e.g., training of providers in administration of magnesium sulfate or scale-up in use) Section 2.2 | Magnesium Sulfate 69 Data Source Limitation Dosage recommended WHO or national MNCH guidelines National essential medicine program, WHO, MoH, NMCP, surveys Providers may not always follow dosage recommended Guidelines may propose different medicines for the same condition; parenteral treatment duration varies between patients depending on clinical evolution; STGs not always used by health providers Programmatic factors Interventions/factors affecting future changes in demand (e.g. scale up plans) MNCH program If strategies to increase use or encourage facility-based delivery are underway, the forecast may fall short The forecasting formula involves multiplying the number of pregnant women developing PE/E who will receive magnesium sulfate for prevention or treatment by the average quantity of magnesium sulfate required for each case. The steps in this calculation are as follows: 1. Determine the scope of the quantification (e.g., types of facilities 2. Calculate the target population that will be given magnesium sulfate for the prevention and treatment of PE/E 3. Calculate the amount of magnesium sulfate needed for each case for the prevention and treatment of PE/E/establish standard or average treatment regimen 4. Calculate the quantity of magnesium sulfate needed for prevention and treatment of PE/E for the forecast period 1. The quantification team needs to determine what types of facilities are currently authorized to administer magnesium sulfate and how many of these facilities are to be supplied with the planned procurement. During this step, the team should also collect information on plans to scale-up use of magnesium sulfate and take these plans into consideration when preparing the forecast. If the forecast is only for public sector facilities, the total number of births at facilities should be multiplied by the percentage of births occurring in only public sector facilities. 2. The target population for which magnesium sulfate should be used depends on the national maternal, neonatal, and child health (MNCH) guidelines. It should be administered to both women who develop seizures due to eclampsia and women who develop a severe rise in blood pressure during pregnancy to prevent possible development of the life-threatening seizures of eclampsia8. Magnesium sulfate should be available at all levels of the health care system where deliveries occur. Ideally, data on the number of pregnant women that develop PE/E and will receive magnesium sulfate should be used. This can sometimes be obtained from health services data, national maternal morbidity and mortality surveys, or special surveys. However, in practice, in most countries these data are not routinely collected and often difficult to obtain. In the absence of these data, we recommend using a proxy figure of 2% of all pregnancies that might result in severe preeclampsia or eclampsia and require treatment with magnesium sulfate.9 Section 2.2 | Magnesium Sulfate 70 3. The amount of magnesium sulfate needed for each case depends on what is recommended in the national MNCH guidelines. Currently, there are two commonly used regimens of magnesium sulfate that can be used to manage preeclampsia and eclampsia: Pritchard Regimen (IV/IM) Zuspan Regimen (IV/IM) Loading dose 4 g in 20 mL (20% solution) administered IV over 15-20 minutes, followed by 5 g in 10 mL solution (50%) IM injection in each buttock. 4 g in 20 mL (20% solution) administered IV over 15-20 minutes Maintenance dose 5 g in 10 mL (50% solution) IM injection every 4 hours in alternate buttocks. 1g per hour IV infusion Duration 24 hours after last convulsion or delivery, whichever occurs later NOTE: If convulsions occur after the loading dose is given, administer 2g in 4mL (50%) IV over five minutes The WHO-recommended formulation is a 50% weight/volume solution which is equivalent to 0.5g / mL. Other common presentations include 1 g/2 mL (50%) and 5 g/10 mL (50%). The presentation(s) available in a country will determine the regimen that can be administered. Required Quantities: This will depend on the regimen most commonly used in the country. For the two most common regimens, assuming administration for 24 hours, the total amounts required are: Pritchard regimen: loading dose = 4 g+ 10 g; maintenance dose = 30 g. Total = 44 g Zuspan regimen: loading dose = 4 g; maintenance dose = 24 g. Total = 28 g Number of ampoules 1 g/2 mL: Pritchard = 44 Zuspan = 28 5 g/10 mL: Pritchard = 9 Zuspan = 7 4. The period that the forecast is meant to cover needs to be determined. A two-year forecast that can be broken down into two 12-month periods is recommended. To calculate the quantity required for this period, multiply the number of facility based births expected during that period by 2% (proxy figure: percentage of all pregnancies that develop severe preeclampsia or eclampsia, from step 1) and then multiply by the amount of magnesium sulfate needed for a single case (number of ampoules, from step 2. The supplies required for administration of magnesium sulfate depend on the regimen used and may include in addition to syringes, an IV infusion set and drip. Also, calcium gluconate should be available in facilities where magnesium sulfate is administered. Section 2.2 | Magnesium Sulfate 71 Magnesium sulfate is widely available as it is produced by over 35 manufacturers globally. The figure below illustrates an example of the steps to follow when quantifying for magnesium sulfate for PE/E including the data needed to reach each subsequent step. As mentioned above, the quantification team will need to define the best assumptions to use for forecasting based on the local context. A1 Percentage of population likely to become pregnant or percentage of births A2 Percentage of pregnant women giving birth in facilities A3 Incidence of PE/E. In absence of country level data, proxy data from similar countries or global estimates, e.g., published literature indicates that pre-eclampsia complicates 2–8% of pregnancies (2% is often used as a global average). A4 Percentage of women who give birth in facilities and develop PE/E, and are likely to be treated with magnesium sulfate A5 Average treatment regimen for MgSO4 A6 Rate of expected programmatic change, e.g. scale-up or losses Once the amount of magnesium sulfate required to meet program needs in the forecast period is calculated, this is entered into a supply planning matrix which takes into account Section 2.2 | Magnesium Sulfate 72 current pipelines, losses; price and supplier lead times to determine the amount to be delivered for each specific time period. Please refer to Quantification of Health Commodities for guidance on the supply planning step. Country X recommends the use of magnesium sulfate (MgSO4) for the prevention and treatment of PE/E. Compliance to this recommendation is 50%; however, there are plans to scale-up the use to 90% over 5 years. There are no data on the percentage of pregnant women that develop PE/E. Available data include: x Total population: as of current year: 10,000,000 x Percentage increase in population per year: 2% x Percentage of pregnant women out of total population: 2% x Percentage of facility births: 70% x Recommended dosage: Pritchard regimen x No. of ampoules administered per patient in 24 hours = 9 (5g/10ml) Assumptions: x Each patient requires 9 ampoules for management. x Proxy figure of 2% of all pregnancies that will require treatment for severe PE/E with magnesium sulfate is used as a global average. x All cases of PE/E are treated at the facility level. x All cases of PE/E are treated with magnesium sulfate From the data above, we can calculate the quantity of MgSO4 to be administered over next 2 years Input Current Year Forecast year 1 Forecast year 2 Population Pop. Growth rate 2% 10,000,000 10,200,000 10,404,000 No. of pregnancies % of women pregnant from pop. 2% 200,000 204,000 208,080 No. of facility births % of facility births 70% 140,000 142,800 145,656 No. of pregnant women developing PE/E % of pregnancies that will require treatment for PE/E 2% 2,800 2,856 2,913 Percentage of PE/E cases likely to be treated with MgSO4 % increase from 50%-90% in 5 years 10% increase per year 50% 60% 70% No. of PE/E cases likely to be treated with MgSO4 # of cases of PE/E to be treated at facilities 10% increase per year 1,400 1,714 2,039 Adjusted amount of MgSO4 needed (ampoules) # of ampoules needed per case 9 12,600 15,422 18,353 Section 2.2 | Magnesium Sulfate 73 1 Medicines for Maternal Health. Prepared for the United Nations Commission on Life-Saving Commodities for Women and Children. Working paper. February 2012. Available from: http://www.everywomaneverychild.org/images/Key_Data_and_Findings_Maternal_Health_Medicines_ FINAL_3_26_2012__COMPLETE_reduced.pdf 2 Ibid 3 Ibid 4 World Health Organization (WHO). 2011. WHO Recommendations for prevention and treatment of Pre eclampsia/ Eclampsia. Geneva. WHO 5 WHO Model List of Essential Medicines.19th List.(April 2015).(Amended June 2015). http://www.who.int/medicines/publications/essentialmedicines/en/. 6 USAID, JHPIEGO. Rapid Landscape Analysis of technologies for postpartum hemorrhage. Conducted by JHPIEGO/Accelovate for USAID at the Technologies for Health Consultative Meeting - MNCH Pathways. Unpublished. 2012. 7 United Nations Commission. Every Woman Every Child, Magnesium sulfate Product Profile. 2012. Available from: http://www.everywomaneverychild.org/component/content/article/1-about/304- magnesium-sulfate-mgso4-product-profile 8 World Health Organization (WHO). 2011. WHO Recommendations for prevention and treatment of Pre eclampsia/ Eclampsia. Geneva. WHO 9 Altman D, Carroli G, Duley L et al. Magpie Trial Collaborative Group. Do women with preeclampsia, and their babies benefit from magnesium sulphate? The Magpie Trial: a randomized placebo controlled trial. Lancet. 2002;359(9321):1877–1890. Section 2.2 | Misoprostol 74 Globally, more than half of women give birth at home without a skilled birth attendant. The management of postpartum hemorrhage (PPH) worldwide is particularly challenging in home deliveries. Primary PPH, defined as blood loss equal to or greater than 500 ml within 24 hours after birth, is identified as a major killer of women during childbirth. Therefore, the 24- hour period after birth is the most dangerous for the mother and active management during this period is called for with every birth irrespective of where it happens. WHO recommends that all women giving birth should have access to an uterotonic, preferably oxytocin, but in situations where oxytocin is not available, misoprostol can be used to prevent postpartum hemorrhage. A recent statement issued by the International Confederation of Midwives and the International Federation of Gynecology and Obstetrics also describes the benefits of misoprostol for treatment of PPH in settings where oxytocin is not available.1 PPH has a prevalence rate of approximately 10.5 percent in women who do not receive an uterotonic.2 It is difficult to predict who will have PPH based on risk factors; two-thirds of women who have PPH present no risk factors. Therefore, all women are considered at risk, and hemorrhage prevention must be incorporated into care provided at every birth. The World Health Organization (WHO) affirms that most deaths due to PPH can be avoided with proper diagnosis and use of essential medicines, such as oxytocin in every delivery and misoprostol in settings where oxytocin cannot be administered.3 Misoprostol, a synthetic prostaglandin, is taken orally in a tablet form. Misoprostol is currently in use in many countries for the treatment of gastric ulcers and management of incomplete abortions or miscarriages.4 Introduction and scale up of misoprostol for PPH is underway in a number of countries. There is planned global scale up for the use of misoprostol for the management of PPH. Many countries now have national policies listing misoprostol for the prevention of PPH; and many others are considering its introduction.5Some countries are in the pilot phase of distributing misoprostol to women by Community Health Workers, and a few are expanding distribution to the national level. Scale up of programs tends to roll out much slower than expected and decisions on these factors must be made during forecasting so that neither stock-outs nor surplus is experienced after procurement. National standard treatment guidelines may specify which level of trained health providers are authorized to administer misoprostol and at which facilities. These considerations will also affect the forecast. Providers in some settings may use misoprostol for cervical ripening and induction of labor. The appropriate dosage for this indication is 25 μg and if that presentation is unavailable, providers may either cut pills (not recommended) or dilute them to achieve the proper dosage. In countries with legal indications for safe abortion, misoprostol may be used alone or in combination with mifepristone. Forecasting should take into account these other uses of misoprostol as well as indications unrelated to obstetric conditions. If different presentations Section 2.2 | Misoprostol 75 are used to different purposes, each presentation should be considered a completely different item and a separate forecast should be done. With respect to product considerations, at present, most manufacturers of misoprostol are not producing a 3-tablet blister which may create distribution challenges. If misoprostol is to be used at lower levels of the system, particularly in home deliveries it may be necessary to re-package. While misoprostol does not require cold chain it is sensitive to humidity, so double-aluminium blister packages are best. Since as stated above the use of misoprostol for management of PPH in most countries is new, the quantification team will need to develop and agree on assumptions about the factors and interventions that may affect future changes in demand for misoprostol, such as the population to be treated and scale-up goals. Some assumptions that will need to be defined include: x Percentage of home deliveries that should receive 600 μg of misoprostol. This will most likely be a phased scale-up and quantification should try to include realistic time frames for achieving this target coverage rate x Percentage of facility deliveries that will receive 600 μg misoprostol when oxytocin is unavailable x Percentage of women who will experience PPH after prophylaxis and require treatment x Percentage of women with PPH will require 800 μg misoprostol because oxytocin is unavailable where they present for care x Percentage of pregnancies that may end up in miscarriages (studies indicate between 10 -15% of pregnancies end in miscarriage)5 x Percentage of miscarriages might require 600 μg misoprostol (studies indicate this may be around 28% of miscarriages)6 x Percentage of pregnancies might require misoprostol for post-abortion care (PAC) or unsafe abortion indication (studies indicate this may be around 1.4%) 6 x Rate of unsafe abortion among of reproductive age (studies indicate this may be 14 per 1000)7 Table 8 describes potential sources for the required data. x Target population: Number of pregnant women Number of home births o No. of pregnant women delivering at home (or in settings where oxytocin is not an option) that are likely to be given misoprostol for the prevention of PPH o No. of PAC/unsafe abortion cases o No. of cases of miscarriage o No. of pregnant women that develop PPH that will be given misoprostol where oxytocin is not available x Standard or average treatment regimen (i.e. amount of misoprostol needed for each case for prevention and treatment) x Programmatic issues that can affect consumption (e.g., training and scale up) Section 2.2 | Misoprostol 76 Data Source Limitation Forecasting Total population DHS, National census, US Census Bureau International Programs Database May be outdated; may need to apply estimated annual growth rate to project for forecast years Proportion of pregnant women DHS, HMIS, national maternal morbidity and mortality surveys, special surveys DHS data usually an underestimate Proportion of home deliveries DHS, HMIS, national maternal morbidity and mortality surveys, special surveys, ANC attendance DHS data usually an underestimate Proportion of home deliveries given misoprostol DHS, HMIS, national maternal morbidity and mortality surveys, special surveys May not be included in current surveys; may be difficult to estimate Proportion of cases with PPH requiring third-line treatment with misoprostol DHS, HMIS, national maternal morbidity and mortality surveys, special surveys May not be included in current surveys; may be difficult to estimate Dosage recommended MNCH guidelines May not be listed in current national guidelines Programmatic factors Health services reporting rate MoH This is usually an estimate of how complete health services reports typically are Interventions/factors affecting future changes in demand e.g. scale up plans MoH, MNCH guidelines Planned scale up may be slower than actual implementation or uptake. Records of losses product CMSs, health facilities, LMIS Data on losses are often not systematically recorded at central level, and facilities do not consistently report losses The forecasting formula involves adding the number of pregnant women delivering where oxytocin is not available, that will be given misoprostol for the prevention of PPH multiplied by the average quantity of misoprostol tablets required for each case for prevention to the number of pregnant women likely to develop PPH and be given misoprostol for treatment where oxytocin is not available multiplied by the average quantity of misoprostol required for each episode, and the number of PAC cases given misoprostol multiplied by the average quantity of misoprostol required for each episode. 1. Calculate the population that will need misoprostol for prevention 2. Calculate the population that will need misoprostol for treatment 3. Calculate the population that will need misoprostol for PAC/unsafe abortion 4. Calculate the population that will need misoprostol for miscarriage 5. Calculate the amount of misoprostol needed for each case for prevention of PPH/establish standard or average treatment regimen 6. Calculate the amount of misoprostol needed for each case of treatment of PPH/establish standard or average treatment regimen Section 2.2 | Misoprostol 77 7. Calculate the amount of misoprostol needed for each case of PAC/unsafe abortion/establish standard or average treatment regimen 8. Calculate the amount of misoprostol needed for each case of miscarriage/establish standard or average treatment regimen 9. Calculate the total quantity of misoprostol needed for the forecast period The target population for which misoprostol should be used depends on the national MNCH guidelines. According to WHO, misoprostol should be used in low resource settings where oxytocin or a skilled birth attendant is not available and for all home births for the prevention of PPH. Obtaining data on the proportion of women giving birth at home is challenging. Estimates can be made using DHS data. Many countries are working to promote facility births, which may mean that home births will decrease over time. Once the numbers of births at home are calculated, it is necessary to estimate the proportions of home births with access to misoprostol administration for the prophylaxis of PPH. Assumptions may need to be made to scale up use of misoprostol phase by phase to ensure adequate training of service providers and acceptance by the public otherwise the forecast may result in overestimation and subsequent expiry and wastage of the product. The population for which misoprostol should be used for the treatment of PPH depends on the national MNCH guidelines. In some cases, misoprostol may be recommended for prevention of PPH for home births, but the guidelines may indicate that if PPH develops, women are to be referred to facilities for treatment with oxytocin or other interventions like surgical repair of birth canal damage or removal of retained placenta. In other cases, misoprostol may be provided for both prevention and treatment in home births or in facilities where cold storage of oxytocin is not possible. Approximately 6% of women who received misoprostol for prevention of PPH may still go on to develop PPH. Based on national guidelines and this assumption (or local data if available), calculate: x Number of women who may develop PPH who are likely to be given misoprostol for treatment of PPH Not all the target population will actually be given misoprostol. The proportion likely to be treated with the product will depend on programmatic factors. For example, with misoprostol, many countries have recently introduced misoprostol for PPH and scale-up efforts are underway, including capacity building around administering it for home-based births. For forecasting and budgetary purposes, these programmatic issues will need to be taken into consideration. Again, the target population depends on the content of the national MNCH guidelines. In the absence of local data, proxy data may be used. The rate of unsafe abortions is 14 per 1,000 in women of reproductive age.8 Therefore, 1.4% of pregnancies might require misoprostol for PAC. Section 2.2 | Misoprostol 78 In the absence of local data, proxy data may be used. An estimated 10-15% of pregnancies result in miscarriages. Approximately 28% of these miscarriages might require misoprostol. This also depends on the national MNCH guidelines. Misoprostol may be recommended for all home births, but may also be recommended for facilities where oxytocin is not available. The dosage depends on national MNCH guidelines. WHO recommends 600 μg (3 tablets of 200 μg) orally for the prevention of PPH. WHO recommends 800 μg (4 tablets of 200 μg) of misoprostol sublingually for treatment of PPH, where oxytocin is not available. The dosage depends on national MNCH guidelines. WHO recommends 600 μg (3 tablets of 200 μg) orally. The dosage depends on national MNCH guidelines. WHO recommends 600 μg (3 tablets of 200 μg) orally. The forecast period needs to be determined. A two-year forecast that can be divided into two 12-month periods is recommended. The use of misoprostol does not require any other products, consumables, or equipment. Misoprostol is manufactured by over 50 manufacturers globally, at least 35 of which are in developing countries.9 There is currently one misoprostol product pre-qualified by the World Health Organization.10 Figure 5 is an example of the steps to follow when quantifying for misoprostol for the prevention and treatment of PPH including the data needed to reach each subsequent step. Section 2.2 | Misoprostol 79 A1 Population likely to become pregnant, % A2 Pregnant women likely to deliver at home, % A3 Pregnant women likely to deliver at home that will be given misoprostol for PPH prevention, % A4 Women who received misoprostol for prevention of PPH, who go on to develop PPH and require treatment, % A5 Dosage of misoprostol (e.g., 3 x 200 microgram tablets) A6 Rate of programmatic adjustments (anticipated increase or decrease in coverage), % A7 Miscarriages, % A8 Population that are women of reproductive age, % A9 A8 A7 Section 2.2 | Misoprostol 80 Once the amount of misoprostol required for the program in the forecast period is calculated, this is entered into a supply planning matrix which takes into account current pipelines, losses; price and supplier lead times to determine the amount to be delivered for each specific time period. Please see Quantification of Health Commodities for guidance on the supply planning step. Country X recommends the use of misoprostol as first line for all home births for the prevention of PPH at an average dose of 600 μg. Compliance to this recommendation is currently at 20% however, the target is to increase it by 20% yearly until 100% is reached. This target seemed reasonable to the quantification team given current efforts to intensify training of health workers. Misoprostol is currently not recommended for the treatment of PPH in country X. Misoprostol is recommended for PAC and miscarriages. However, there are no data on these conditions. Below is the data you have been given. Calculate the amount of misoprostol needed for the program in the next two years. Data available x Number of births per annum: 500,000 x Number of facility births per annum: 300,000 x Population growth rate: 5% x Estimated % of pregnancies that end in miscarriage: 10% x Estimated rate of unsafe abortion: 1.4% From the data above, we can calculate: Number of home births per annum = 200,000 Number of pregnancies = 550,000 Input Current year Forecast year 1 Forecast year 2 No. of total pregnancies Pop. Growth Rate 5% 550,000 577,500 606,375 No. of home deliveries Pop. Growth Rate 5% 200,000 210,000 220,500 Uptake, % % annual increase in uptake 20% 20 40 60 No. of pregnant women likely to be given misoprostol for prevention PPH 40,000 84,000 132,300 No. of misoprostol tablets required for PPH prevention # of tablets per case 3 120,000 252,000 396,900 No. of unsafe abortions from total pregnancies % rate of unsafe abortion 1.4% 7,700 8,085 8,489 No. of women requiring hospitlization for PAC % of unsafe abortions requiring hospitalization for complications 23% 1,771 1,860 1,953 (box 10 continued on following page) Section 2.2 | Misoprostol 81 Input Current year Forecast year 1 Forecast year 2 No. of women likely to be given misoprostol for PAC % of women hospitalized for PAC requiring misoprostol 92% 1,629 1,711 1,796 No. of pregnancies ending in miscarriage Estimated rate of miscarriages from total pregnancies 10% 55,000 57,750 60,638 No. of women likely to be given misoprostol for miscarriage % of miscarriages likely to need misoprostol 28% 15,400 16,170 16,979 No. of women likely given misoprostol for PAC and miscarriage Sum of # of women given misoprostol for PAC and miscarriage 17,029 17,881 18,775 No. of misoprostol tablets required for PAC and miscarriages Number of tablets per case 3 51,088 53,642 56,324 Total no. of misoprostol tablets required for all uses Sum of misoprostol tablets needed for prevention + for PAC and miscarriage 171,088 305,642 453,224 Section 2.2 | Misoprostol 82 1 ICM and FIGO Joint Statement. Misoprostol for the treatment of postpartum haemorrhage in low resource settings. March 2014 2 WHO recommendations for the prevention and treatment of postpartum haemorrhage. World Health Organization, 2012. Available from: http://whqlibdoc.who.int/publications/2011/9789241501156_eng.pdf 3 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 4 Medicines for Maternal Health. Prepared for the United Nations Commission on Life-Saving Commodities for Women and Children. Working paper. February 2012. Available from: .http://www.everywomaneverychild.org/images/Key_Data_and_Findings_Maternal_Health_Medicines _FINAL_3_26_2012__COMPLETE_reduced.pdf 5 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 6 Cochrane Database Syst. Review, Expectant care versus surgical treatment for miscarriage. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22419288 7 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 8 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 9 Every Woman Every Child, Product profile. Misoprostol. Available from: http://www.everywomaneverychild.org/component/content/article/1-about/303-misoprostol-product- profile-#sthash.DV42GSo5.dpuf 10 WHO List of Prequalified Medicinal Products. Updated July 15, 2015. http://apps.who.int/prequal/default.htm Section 2.2 | Oxytocin 83 Oxytocin has several obstetric uses: induction and augmentation of labor, and prevention and treatment of postpartum hemorrhage. For calculation, it is assumed that oxytocin is used only by skilled birth attendants in facility-based deliveries.1 Oxytocin is an uterotonic used for the prevention and treatment of postpartum hemorrhage (PPH). It is the first line medicine for all facility-based births.2 If prostaglandins are not available, intravenous oxytocin is also recommended for the induction/augmentation of labor.3 According to WHO, “All women giving birth should be offered uterotonics during the third stage of labor for the prevention of PPH; oxytocin (IM/IV, 10 IU) is recommended as the uterotonic drug of choice.” 4 Oxytocin is currently registered in most countries,5and is included in national protocols for maternal health service provision or standard treatment guidelines, as well as on the Essential Medicines List in the majority of countries.6 Oxytocin is temperature sensitive, and loses effectiveness after three months of being stocked at temperatures greater than 30°C or 90°F; therefore cold chain storage is recommended.7Some manufacturers may indicate that their oxytocin product can be stored at room temperature, but regardless, efforts should be made to ensure that oxytocin is maintained at 30°C (90°F) or below, which is difficult in some countries. Currently, most countries are not collecting routine data necessary for forecasting, so data on the number of women who require oxytocin for treatment may not be available. Similarly, in many countries, oxytocin may also be used for induction or augmentation. The amount of oxytocin used for these purposes based on local data should also be added to the total need for oxytocin. In the absence of local data, the assumptions below can be used until accurate country-specific data are available. All women expected to deliver in health facilities will need oxytocin for PPH prevention. According to scientific literature, 2.85% of hospital deliveries who received oxytocin to prevent PPH will develop PPH and will require oxytocin for treatment. Also, 6% of home deliveries who receive misoprostol for PPH prevention will end up with PPH and need oxytocin.8 While the forecasting guidance provided here is specifically to calculate the need for oxytocin for management of PPH, oxytocin is also used for other purposes. For example, on average, an estimated 9.6% of pregnancies per year are induced and may l require 10 IU of oxytocin. 9 In addition, up to 20% of pregnancies may require 10 IU of oxytocin for augmentation. Countries should take into account these other uses of oxytocin when preparing the forecast. The same logic used in forecasting the need of oxytocin for management of PPH will apply for these other uses. Section 2.3 | Oxytocin 84 Table 9 describes potential sources of the data required for forecasting. Data Sources Limitations Forecasting Total population Census data, DHS -- Proportion of pregnant women DHS, HMIS, national maternal morbidity and mortality surveys, special surveys DHS data usually an underestimate Proportion of pregnant women giving birth at health facilities who will be given oxytocin for the prevention of PPH DHS, HMIS, national maternal morbidity and mortality surveys, special surveys Not all pregnant women will be given oxytocin. Estimate compliance with the STGs. Proportion of pregnant women giving birth at health facilities developing PPH DHS, HMIS, national maternal morbidity and mortality surveys, special surveys Not all pregnant women will be given oxytocin. Estimate compliance with the STGs Proportion of pregnant women giving birth at home developing PPH DHS, HMIS, national maternal morbidity and mortality surveys, special surveys Not all pregnant women will be given oxytocin. Estimate compliance with the STGs. Proportion of pregnant women giving birth at home and receiving misoprostol developing PPH DHS, HMIS, national maternal morbidity and mortality surveys, special surveys Not all pregnant women will be given oxytocin. Estimate compliance with the STGs. Percentage of pregnancies in a year that are induced or augmented and will require oxytocin DHS, HMIS, national maternal morbidity and mortality surveys, special surveys Not all pregnant women will be given oxytocin. Estimate compliance with the STGs. Dosage recommended WHO or national MNCH guidelines Providers may not always follow dosage recommended STGs (actual prescribing practice versus ideal) National essential medicine program, WHO, Ministry of Health, NMCP, surveys Guidelines may propose different medicines for the same condition; parenteral treatment duration varies between patients depending on clinical evolution; STGs not always used by health providers Programmatic changes MNCH Projected changes in consumption due to provider training or other efforts to increase use. x Total population x Number of pregnant women (Population growth rate) x Percentage of births that occur in health facilities o Number of pregnant women likely to be given oxytocin for the prevention of PPH x Incidence of PPH after active management of the third stage of labor with oxytocin as prevention o Number of pregnant women that develop PPH that will be given oxytocin for the treatment of PPH x Standard or average treatment regimen (i.e., the amount of oxytocin needed for each case for prevention, and treatment ) x Programmatic issues that may affect consumption (e.g., efforts to scale-up in use) Section 2.3 | Oxytocin 85 The forecasting formula involves adding the number of pregnant women likely to be given oxytocin X average quantity of oxytocin required for each case for prevention and the nmber of pregnant women likely to develop PPH and be given oxytocin X average quantity of oxytocin required for each episode for treatment (in some cases, women who have received oxytocin to prevent PPH will still develop PPH, so may be administered twice) 1. Estimate population that will need oxytocin for prevention 2. Estimate the target population that will need oxytocin for treatment 3. Calculate the amount of oxytocin needed for each case for prevention of PPH/establish standard or average prevention regimen 4. Calculate the amount of oxytocin needed for each case for the treatment of PPH/establish standard or average treatment regimen 5. Calculate the quantity of oxytocin needed for prevention and treatment for the forecast period The target population for whom oxytocin should be used depends on the national MNCH guidelines. According to WHO, all women giving birth should be offered uterotonics, with oxytocin as the recommended first line for the prevention of PPH.10 Oxytocin is needed at every level of the health care system where deliveries occur, from urban hospitals to rural maternity clinics.11 The data on the population who will receive oxytocin can be obtained from facility records of women giving birth, or calculated from existing demographic data starting with the number of pregnant women. We suggest starting with the number of pregnant women as regardless of the outcome of the birth (live or stillbirth) women will receive oxytocin for prevention of PPH. Several assumptions will then need to be applied as the calculations are continued. For example, if the forecast is meant to cover public sector facilities only, the percentage of births that occur in public sector facilities must be calculated by multiplying the number of births that occur in health facilities by the percentage of births that occur in public sector facilities. If this percentage cannot be found in health services data, data from DHS on care-seeking in public and private facilities can be used as a proxy. Also, as mentioned previously, both oxytocin and misoprostol may be recommended for use for PPH. It may be the case that with introduction of misoprostol, the need for oxytocin at some levels of the system will decrease. These types of programmatic issues need to be considered in the forecast. Oxytocin is also recommended for all deliveries that progress to PPH. This includes all women delivering at facilities that may have been given oxytocin for prevention, but still go on to develop PPH, women who have not received oxytocin for prevention of PPH, as well as women that deliver at home (and may have received misoprostol for prevention) and then present at health facilities for the treatment of PPH. To obtain this number, calculate: x Number of women who did not receive oxytocin but develop PPH and will be treated with oxytocin x Number of women who received oxytocin and go on to develop PPH and require additional treatment with oxytocin Section 2.3 | Oxytocin 86 x Number of women who received misoprostol for home births and who go on develop PPH and will be treated with oxytocin x Number of women who did not receive misoprostol for home births and who develop PPH and are likely to be treated with oxytocin This information is not routinely collected in many health management information systems. When these data are unavailable, the number of PPH cases will need to be estimated based on available information (e.g., special studies, services data from a sample of facilities). Assumptions will then need to be applied; some of these are described below. This step depends on how each country addresses this issue in the national MNCH guidelines. Both oxytocin and misoprostol may be recommended for prevention of PPH at different levels within the health system. The national guidelines should be consulted to determine how to address this in the forecast. The recommended dosage for prevention is 10 IU of PPH intravenously (IV) or intramuscularly (IM). Therefore, 1 vial of 10 IU is needed to prevent each case of PPH, which is caused by uterine atony. Just as with the previous step, calculation of the amount of oxytocin needed for each case of treatment of PPH depends on the content of the national MNCH guidelines. Average actual regimens versus ideal regimens should be considered in the calculation. The recommended dosage for treatment is 20 IU infusion or IM followed by 20 IU/l IV, with a maximum of 3 liters of IV fluids. Therefore, up to 7 vials IU may be needed to treat each case of PPH. In our calculations, we are using an average of 4 vials per case. For this step, the forecast period must be defined. A two-year forecast that can be divided into two 12-month periods is recommended. If the forecast is meant to cover one year, then the amount of oxytocin required for prevention and treatment for one year should be estimated based on the previous steps. Therefore, the number of cases which will be given oxytocin for the prevention of PPH in a year should be multiplied by the amount needed per case. This should then be added to the number of cases which will be given oxytocin for the treatment of PPH in a year, multiplied by the amount needed per case. Oxytocin for prevention of PPH is given IM, while for treatment of PPH it is administered IV, therefore injection supplies are required including: x IV infusion set x Syringe x Alcohol swabs Section 2.3 | Oxytocin 87 Oxytocin is produced by over 100 manufacturers around the globe.12,13 Figure 6 illustrates and example of the steps to follow when quantifying for oxytocin to prevent or treat PPH. Section 2.3 | Oxytocin 88 A1 Percentage of population likely to become pregnant A2 Percentage of pregnant women likely to deliver at home A3 Percentage of pregnant women likely to deliver at health facilities A4 Percentage of pregnant women delivering at health facilities likely to develop PPH and be given oxytocin A5 Percentage of pregnant women delivering at home (with or without misoprostol) likely to develop PPH and be referred to a facility A6 Percentage of women who received oxytocin for prevention and developed PPH A7 Average treatment regimen for PPH treatment (e.g, 4 vials of 10 IU) Once the adjusted amount of oxytocin is calculated, this is entered into a supply planning matrix which takes into account current pipelines, losses, price, and supplier lead times to determine the amount to be procured and delivered for each specific time period. Please see Quantification of Health Commodities for guidance on the supply planning step. Country X recommends the use of oxytocin as first line for all facility births for the prevention of PPH at an average dose of 10 IU. The MNCH program estimates that compliance to this recommendation is 80%. Of all facility births not receiving oxytocin, 20% develop PPH, but only 3% who are given oxytocin develop PPH. Oxytocin is also recommended for the treatment of PPH at an average dose of 40 IU. About 30% of all pregnant women give birth at home and, on average, 20% develop PPH. Of these, about 90% are referred to health facilities and are given oxytocin for treatment. Below are the data you have been given. Calculate the amount of oxytocin required by the program for the two-year forecast period. Available data Number of facility births per annum (from current year): 300,000 Percent increase in birth rate per year: 2% From the data above, we can calculate: Input Current year Forecast year 1 Forecast year 2 No. of facility births Pop. Growth rate 2% 300,000 306,000 312,120 No. of facility births given oxytocin for prevention % compliance 80% 240,000 244,800 249,696 No. of facility births that did not receive oxytocin for prevention % of facility births that did not receive oxytocin (not compliant) 20% 60,000 61,200 62,424 No. of facility births that did not receive oxytocin for prevention that develop PPH and require treatment % of facility births that did not receive oxytocin and develop PPH 20% 12,000 12,240 12,484.80 (box 12 is continued on following page) Section 2.3 | Oxytocin 89 Input Current year Forecast year 1 Forecast year 2 No. of facility births that received oxytocin for prevention, but developed PPH and required treatment % of facility births that received oxytocin and still developed PPH 3% 7,200 7,344 7,490.88 No. of home births Pop. Growth rate 2% 128,571 131,142.42 133,765 No. of home births developing PPH % of home births developing PPH 20% 25,714 26,228 26,753 No. of home births referred and treated for PPH % of home births referred to facility for PPH treatment 90% 23,143 23,606 24,078 No. of patients requiring oxytocin for prevention # of patients at health facility given oxytocin for prevention 240,000 244,800 249,696 No. of patients requiring oxytocin for treatment total sum of facility births that require oxytocin for treatment 42,343 43,190 44,053 Total amount of oxytocin needed (vials) for prevention # of vials needed per case for prevention (10IU) 1 240,000 244,800 249,696 Total amount of oxytocin needed (vials) for treatment # of vials needed per case for treatment (40IU) 4 169,371 172,759 176,214 Total amount of oxytocin needed (vials) total sum of vials needed (treatment + prevention) 409,371 417,559 425,910 Section 2.3 | Oxytocin 90 1 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 2 WHO recommendations for the prevention and treatment of postpartum haemorrhage. World Health Organization, 2012. Available from: http://whqlibdoc.who.int/publications/2011/9789241501156_eng.pdf 3 WHO recommendations for induction of labor. World Health Organization, 2011. Available from: http://whqlibdoc.who.int/publications/2011/9789241501156_eng.pdf. 4 WHO recommendations for the prevention and treatment of postpartum haemorrhage. World Health Organization, 2012. Available from: http://whqlibdoc.who.int/publications/2011/9789241501156_eng.pdf 5 Seligman B, Liu X. Economic Assessment of Interventions for Reducing Postpartum Hemorrhage in Developing countries. Abt Associates Inc.; 2006. Available from: http://www.abtassociates.com/reports/EconReducPPHDevCo.pdf 6 Fujioka A, Smith J. Prevention and Management of Postpartum Hemorrhage and Pre- Eclampsia/Eclampsia: National Programs in Selected USAID Program-Supported Countries. Maternal and Child Health Integrated Program (MCHIP); 2011. Available from: http://www.k4health.org/system/files/PPH_PEE%20Program%20Status%20Report.pdf. Accessed February 2012.) 7 United Nations Commission. Every Woman Every Child, Oxytocin Product Profile. 2012. Available from: http://www.everywomaneverychild.org/component/content/article/1-about/302-oxytocin--product- profile- 8 Maheen Malik, Beth Yeager. 2013. Estimation of Unmet Medical Need for Essential Maternal Health Medicines. Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program. Arlington, VA: Management Sciences for Health. 9 Wei S, Wo BL, Qi HP, Xu H, Luo ZC, Roy C, Fraser WD. Early amniotomy and early oxytocin for prevention of, or therapy for, delay in first stage spontaneous labour compared with routine care. Département d'Obstétrique-Gynécologie, Université de Montréal, Hôpital, Canada. Cochrane Database System. Sept 12, 2012. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22972098 10 WHO recommendations for the prevention and treatment of PPH 11 USAID, JHPIEGO. Rapid Landscape Analysis of technologies for postpartum hemorrhage. Conducted by JHPIEGO/Accelovate for USAID at the Technologies for Health Consultative Meeting - MNCH Pathways. Unpublished. 2012 12 USAID, Jhpiego. Rapid Landscape Analysis of technologies for postpartum hemorrhage. Conducted by JHPIEGO/Accelovate for USAID at the Technologies for Health Consultative Meeting - MNCH Pathways. Unpublished. 2012 13 USAID | DELIVER PROJECT, USAID Procurement Strategy: Oxytocin Market Assessment, unpublished data, 2011 Quantification of Health Commodities RMNCH Supplement 91 Section 2.3 | Antenatal Corticosteroids 92 The administration of certain corticosteroid injections to women at risk of preterm birth causes a considerable reduction in the risk of complications of prematurity such as respiratory distress syndrome, intra-ventricular hemorrhage, and perinatal death.1 The potential lives saved indicate a reduction in neonatal mortality by 31% and moderate to severe respiratory distress syndrome by 45%.2 Research has shown that ACS show greatest effect when used between 31 weeks and 36 weeks gestation; and may be effective as early as 28 weeks.2 Betamethasone and dexamethasone are fluorinated glucocorticoid steroids that are administered as intramuscular injections to prevent these complications; the greatest effect is seen when there is a 24–48 hour time span between the first dose and birth. When birth takes place more than 7 days after treatment, there is no sign of benefit from the intervention.3 The most challenging aspect of administering ACS is identifying pregnant women who are at risk for preterm birth 48 hours prior; timing and appropriate diagnosis are crucial for women who present bleeding, contractions, loss of fluid, or symptoms of pre- eclampsia/eclampsia.4 Both medicines have a long history of use, strong efficacy, and are safe to administer. Both medicines are on the WHO List of Priority Medicines for Mothers and Children. Dexamethasone is currently the preferred antenatal corticosteroid as it is as effective and significantly cheaper and more widely available than betamethasone. It is also on the WHO Essential Medicines List for multiple indications, including fetal maturation.5,6 This depends on the regimen recommended in the national MNCH guidelines. Current global recommendations suggest 24 mg of dexamethasone administered in a 24-hour period, with either 6mg administered every 4 hours or 12mg every 12 hours.7 Looking at levels of care, ACS should be focused on national referral and district hospitals first. Expansion of use of ACS is not recommended beyond regional or district hospitals. The medicines should be administered by a trained health worker/skilled birth attendant, and are not recommended for home-based births.8 Furthermore, recent studies of implementation of ACS in low- and middle-income countries9 indicate that ACS should be used in settings that meet the following four conditions: x Providers are able to accurately assess gestational age and determine risk of imminent preterm birth x Adequate post-delivery care for preterm newborns is available, including thermal protection, adequate feeding support, prevention and management of infection, facilities for Kangaroo Mother Care, and resuscitation equipment x Reliable, timely and appropriate identification and treatment of maternal infection x Patient safety and compliance are monitored, including monitoring of mothers and newborns post discharge for complications and adverse events.10 Dexamethasone is typically available in 1 or 2-ml ampoules of 4mg/ml dexamethasone phosphate. Some producers label dexamethasone for 20°C–25°C storage while others allow a wider temperature storage range of 15°C–30°C. Labelling for dexamethasone sodium phosphate for injection typically also includes “protect from light” and statements on “protect from freezing” and “sensitive to heat.”11 The recommended storage conditions have Section 2.3 | Antenatal Corticosteroids 93 implications for storage and distribution which should also be taken into account by the quantification team during forecasting. Health workers in many settings face the challenge of estimating gestational age, which is an important factor for determining whether a woman is at risk of preterm delivery and hence the administration of dexamethasone. National treatment guidelines or services delivery protocols should indicate how estimation of gestational age should be handled in the local context at different levels of service delivery according to the level of provider available at each level. The target population for dexamethasone is any woman who is considered preterm and has one of the four conditions (preterm labor, preterm pre-labor rupture of membranes, antepartum hemorrhage, severe preeclampsia) that increase her risk of preterm delivery. Service statistics in many settings do not include information on the number of women who have delivered at facilities and have presented with these conditions. An estimated 10% of births globally are preterm; however, this varies by country. For example, in Malawi the preterm birth rate is about 18%.12 Similarly, current coverage of dexamethasone for preterm birth varies widely with 90% coverage of indicated cases in high-income countries, compared with an estimated 10% coverage in middle/low income, high burden countries.13 In the absence of any data, a global average can be used or proxy data from a neighboring country. The quantification team will need to decide on the best estimate to use. Some countries may have both betamethasone and dexamethasone on their treatment guidelines and EML. In that case, program managers will need to decide whether both will continue to be made available or not. If both medicines continue to be made available, then the proportion that will be treated with betamethasone and the proportion that will be treated with dexamethasone will need to be calculated. The proportion likely to be treated with each product will depend on programmatic factors. Finally, dexamethasone may be used for several indications. The quantification team should take into account the other indications listed in national standard treatment guidelines and on the national essential medicines lists during the forecasting exercise. Table 10 shows potential sources for the data needed for forecasting. x Target population o Number of facilities equipped to administer ACS o Number of women giving birth at facilities equipped to administer ACS o Number of pregnant women at risk of preterm birth o Proportion of women that will be given dexamethasone x Standard or average treatment regimen (i.e., amount of dexamethasone needed for each case to prevent risks of preterm birth) x Programmatic issues that may affect consumption (e.g., plans for scale-up, provider training) Section 2.3 | Antenatal Corticosteroids 94 Data Source Limitations and Challenges Forecasting Number of health facilities that meet conditions for use of dexamethasone MoH The information may not be readily available, and will need to be discussed with relevant program managers in MoH. Number of pregnant women giving birth at facilities equipped to administer ACS Service statistics These data maybe not be readily available. Proportion of pregnant women at risk for preterm birth DHS, HMIS, national maternal morbidity and mortality surveys, special surveys DHS data usually an underestimate Dosage recommended WHO or national MNCH guidelines Providers may not always follow dosage recommended STGs (actual prescribing practice versus ideal) National essential medicine program, WHO, Ministry of Health, NMCP, surveys Guidelines may propose both betamethasone and dexamethasone medicines for the same condition; parenteral treatment duration varies between patients depending on clinical evolution; STGs not always used by health providers Programmatic issues MNCH program Scale up plans may not progress as quickly as anticipated The forecasting formula involves multiplying the number of pregnant women at risk of preterm birth likely to be given dexamethasone by the average quantity of dexamethasone required for each case. 1. Calculate the target population (pregnant women at risk of preterm birth giving birth in equipped facilities) who will need dexamethasone 2. Calculate the amount of dexamethasone needed for each case for the prevention of complications of preterm birth/establish standard or average treatment regimen 3. Calculate the quantity of dexamethasone needed for the forecast period The target population for which ACS should be used depends on the national MNCH guidelines, and other documentation that indicates at which facilities ACS can be administered. Any woman giving birth in facilities equipped to administer ACS, who is considered preterm and has one of the four conditions that increase her risk of preterm delivery should be administered an ACS. The data on the number of pregnant women at risk for preterm delivery that will receive an ACS may be obtained from hospital records, national maternal morbidity data and mortality surveys, or non-routine research studies. Where this information is not readily available, estimate target population using the following data: Section 2.3 | Antenatal Corticosteroids 95 x Number of pregnant woman with one of the four conditions (preterm labor, preterm pre-labor rupture of membranes, antepartum hemorrhage, severe preeclampsia) that increase her risk of preterm delivery x Number of pregnant women referred to hospitals x Number of facility-based births x Number of births in facilities that meet conditions for use x Number of pregnant women x Total female population Depending on the scope of the forecast, assumptions will need to be applied as the calculations are made. For example, if the forecast is meant to cover only public sector facilities, the total number of facility-based births will need to be multiplied by the percentage of births that occur in public sector facilities. Also, the level of facility and whether all facilities at that level are equipped to administer ACS, will need to be taken into account as current international guidance recommends use only at facilities that meet the four conditions described above. This depends on the regimen recommended in the national MNCH guidelines. Current global recommendations suggest 24 mg of dexamethasone administered in a 24-hour period, with either 6mg administered every 4 hours or 12mg every 12 hours.14 This is calculated by multiplying the number of cases that will be given dexamethasone with the average amount required per case, to derive the number of ampoules needed. Since the most common formulation of dexamethasone may be 4 mg/ml in 1 ml ampoule, health providers might need to open and draw from two 1-ml ampoules in order to reach the 6mg dose. This would require discarding half of the second 4mg ampoule as the ampoules cannot be resealed.15 If the preferred regimen is 12mg every 12 hours, three ampoules would be fully used for each administration. The use of dexamethasone requires injection supplies, including: x Syringes x Needles x Alcohol swabs x Sharps disposal Section 2.3 | Antenatal Corticosteroids 96 Dexamethasone sodium phosphate is available from many manufacturers globally and from suppliers including UNFPA and Mission Pharma. Figure 7 illustrates an example of the steps to follow when forecasting needs for ACS for pregnant women at risk of preterm delivery including the data needed to reach each subsequent step. A1 Incidence of preterm labor. In absence of country level data, proxy data from similar countries or global estimates, e.g., literature indicates that about 10% of all births are preterm (see assumptions). A2 Percentage of pregnant women likely to be administered dexamethasone. Published literature suggests that only 10% of indicated cases of women in preterm labor in high burden and LMIC receive ACS (see assumptions). A3 Average treatment regimen for dexamethasone Once the amount of dexamethasone to be consumed is calculated, it is entered into a supply planning matrix which takes into account current stock on-hand or on order, losses; price and supplier lead times to determine the amount to be delivered for each specific time period. Please refer to Quantification of Health Commodities for guidance on the supply planning step. Section 2.3 | Antenatal Corticosteroids 97 Country X, which is located in Southern Africa and has a similar epidemiological profile to Malawi, recommends the use of dexamethasone for pregnant women at risk of preterm labor. Compliance to this recommendation is only about 10%; however, there are plans to scale up use down to the regional or district level, to 50% over 4 years through improved diagnosis of risk conditions, intensive training, supervision, and IEC and BCC campaigns. Data available is as follows: x ANC attendances: given below (ANC attendance in this example is a proxy for the # of facility based births down until the regional/district level facilities) x Annual population growth % increase: 2% x Recommended dosage: 4 intramuscular injections spaced 12 hours apart totaling 24 mg of active ingredient. x Average number of ampoules administered per patient = 8 x 1 ml x Dexamethasone is in boxes (packs) of 50 ampoules of 1 ml each Assumptions: x Each patient uses an average of 8 amps for a treatment episode x Country X is similar to Malawi therefore we can use the incidence of preterm labor from Malawi which is 18% of all births x Scale up estimated at 20% coverage of eligible births for forecast year 1; and 30% for forecast year 2 From the data above, we can calculate the quantity of dexamethasone required to meet program needs over the next 2 years. Inputs Current year Forecast year 1 Forecast year 2 Number of ANC attendances Population growth rate 2% 180,000 183,600 187,272 Number of pregnant women at risk of preterm labor Incidence of preterm labor 18% 32,400 33,048 33,709 Percentage of cases likely to be treated with dexamethasone % compliance; plan to scale up to 50% in the next 4 years 10% increase per year 10% 20% 30% Number of cases likely to be treated with dexamethasone 3,240 6,610 10,113 Amount of dexamethasone needed (ampoule) # of ampoules needed per case 8 25,920 52,880 80,904 Section 2.3 | Antenatal Corticosteroids 98 1 Antenatal administration of corticosteroids for women at risk of preterm birth. The WHO Reproductive Health Library. WHO 2013. Available from: http://apps.who.int/rhl/pregnancy_childbirth/complications/preterm_birth/cd004454_hofmeyrgj_com/en/ 2 Case Study: Antenatal Corticosteroids for the reduction of deaths in preterm babies. United Nations commission on Live=saving Commodities for Women and children. March 2012. 3 Administration of Antenatal Corticosteroids. n.d. Available from: http://www.healthynewbornnetwork.org/sites/default/files/resources/ACS%20Advocacy%20Briefer_0.pdf 4 http://www.mchip.net/sites/default/files/ACS%20Technical%20Briefer_0.pdf 5 WHO. WHO Model List of Essential Medicines (April 2013), 18th edition. Available from: http://apps.who.int/iris/bitstream/10665/93142/1/EML_18_eng.pdf (Accessed October 2013) 6 WHO. Priority Medicines for Mothers and Children 2012, 4th edition. http://apps.who.int/iris/bitstream/10665/75154/1/WHO_EMP_MAR_2012.1_eng.pdf (Accessed October 2013). 7 Brownfoot FC, Crowther CA, Middleton P. Different corticosteroids and regimens for accelerating fetal lung maturation for women at risk of preterm birth. Cochrane Database of Systematic Reviews 2008, Issue 4. Art. No.: CD006764. DOI: 10.1002/14651858.CD006764.pub2. 8 Antenatal Corticosteroids (ACS) for Fetal Maturation in Threatened Preterm Birth: Critical Path Discussion Draft. March 2013. http://www.healthynewbornnetwork.org/sites/default/files/resources/ANCS%20Care%20Group%20- %20For%20HNN%20130305.pdf 9 Althabe F, Belizan JM, McClure EM, et al. A population-based, multi-faceted strategy to implement antenatal corticosteriod treatment versus standard care for the reduction of nenonatal mortality due to preterm birth in low-income and middle-income countries: the ACT cluster-randomized trial. Lancet 2014. 10 Adapted from notes developed by the Antenatal Corticosteroids Working Group of the UN Commission on Life-Saving Commodities for Women and Children. October 2014 11 United Nations Commission. Every

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