Nigeria: Direct Delivery and Information Capture Activities--March 2012-August 2014
Publication date: 2014
Nigeria: Direct Delivery and Information Capture Activities March 2012–August 2014 OCTOBER 2014 This publication was produced for review by the U.S. Agency for International Development. It was prepared by the USAID | DELIVER PROJECT, Task Order 4 and Task Order 7. Nigeria: Direct Delivery and Information Capture Activities March 2012–August 2014 The authors' views expressed in this publication do not necessarily reflect the views of the U.S. Agency for International Development or the United States Government. USAID | DELIVER PROJECT, Task Order 4 The USAID | DELIVER PROJECT, Task Order 4, is funded by the U.S. Agency for International Development (USAID) under contract number GPO-I-00-06-00007-00, order number AID-OAA-TO-10-00064, beginning September 30, 2010. Task Order 4 is implemented by John Snow, Inc., in collaboration with PATH; Crown Agents Consultancy, Inc.; Eastern and Southern African Management Institute; FHI 360; Futures Institute for Development, LLC; LLamasoft, Inc.; The Manoff Group, Inc.; Pharmaceutical Healthcare Distributers (PHD); PRISMA; and VillageReach. The project improves essential health commodity supply chains by strengthening logistics management information systems, streamlining distribution systems, identifying financial resources for procurement and supply chain operation, and enhancing forecasting and procurement planning. The project encourages policymakers and donors to support logistics as a critical factor in the overall success of their healthcare mandates. USAID | DELIVER PROJECT, Task Order 7 This document was prepared by staff of the USAID | DELIVER PROJECT, Task Order 7, which is funded by the U.S. Agency for International Development (USAID) under contract number GPO-I-00-06-0007-00, order number AID- OAA-TO-11-00012, beginning on March 28, 2011. Task Order 7 is implemented by John Snow, Inc., in collaboration with 3i Infotech, Inc.; Crown Agents USA, Inc.; FHI 360; Foundation for Innovative New Diagnostics; Logenix International, LLC; The Manoff Group, Inc.; MEBS Global Reach, LC; PATH; PHD International (a division of the RTT Group); Population Services International; Social Sectors Development Strategies, Inc.; UPS Supply Chain Solutions, Inc.; and VillageReach. Task Order 7 supports USAID's goal of reducing the malaria burden in sub-Saharan Africa by procuring and delivering safe, effective, and high-quality malaria commodities; by providing technical assistance and on-the-ground logistics expertise to strengthen in-country supply systems and build capacity for managing commodities; and by improving the global supply and long-term availability of malaria commodities. Recommended Citation USAID | DELIVER PROJECT, Task Orders 4 and 7. 2014. Nigeria: Direct Delivery and Information Capture Activities: March 2012–August 2014 Abuja, Nigeria: USAID | DELIVER PROJECT, Task Orders 4 and 7. Abstract In 2013, the USAID | DELIVER PROJECT implemented a vendor-managed inventory system of distributing health commodities to public sector health facilities in two states in Nigeria. This system, the Direct Delivery and Information Capture system (DDIC) was modelled after the Delivery Team Topping Up system (DTTU) implemented in Zimbabwe by the project since 2003. The DDIC was piloted in Bauchi and Ebonyi states, as a last mile delivery option in a resource limited setting, in terms of reduced human and transport capacity, limited or no stock availability and low data visibility for decision making. In the Nigerian context, the DDIC system was used to distribute family planning, maternal, neonatal and child health (MNCH) and malaria commodities. The collection of logistics data from the service delivery points is concurrent with commodity replenishment and is automated, using the Auto DRV soft-ware. After a year, two additional states, Sokoto and Zamfara implemented the DDIC system. After the pilot phase of the DDIC, a cost evaluation study was conducted in 5 states in Nigeria where the DDIC system was compared to review and re-supply, review and direct delivery and information capture and direct delivery models of last mile distribution. Stock out rates, start up and operating costs, scalability and data quality of each last mile delivery option were compared to the DDIC system. The results of the evaluation were disseminated at a conference in August 2014. Cover photo: Direct Delivery and Information Capture Conference, Abuja, Nigeria, August 7, 2014. Photo credit: USAID | DELIVER PROJECT USAID | DELIVER PROJECT John Snow, Inc. 1616 Fort Myer Drive, 16th Floor Arlington, VA 22209 USA Phone: 703-528-7474 Fax: 703-528-7480 Email: firstname.lastname@example.org Internet: deliver.jsi.com Contents Acronyms. v Figures Figure 4. Stockout rates at the service delivery point level for family planning commodities in Bauchi Tables Acknowledgments . vii Executive Summary . ix Transportation component of the DDIC . ix Commodities delivered by the DDIC . ix DDIC Delivery Team. x Implementation of the DDIC . x Evaluating the DDIC . x Background. 1 Accomplishments of the DDIC Activity. 1 Roll Out of DDIC Distribution Runs in Pilot States . 7 DDIC Roll Out Activities in Ebonyi State .7 DDIC Roll Out Activities in Bauchi State . 10 DDIC Roll Out in FY2014 to Two Project–Supported States . 15 DDIC Roll Out in Sokoto State . 15 DDIC Roll Out in Zamfara State . 16 Last Mile Distribution Systems Evaluation in Nigeria.17 Key Findings . 17 Last Mile Distribution Systems Evaluation in Nigeria Dissemination Conference .19 Conclusion. 21 References. 23 Figure 1. Stockout rates for malaria commodities at health facility levels in Ebonyi state .9 Figure 2. Stockout rates for family planning commodities at health facility levels in Ebonyi state .9 Figure 3. Stockout rates at the service delivery point level for malaria commodities in Bauchi State .12 State . 13 Table 1. The sixteen DDIC supported commodities as agreed at the system design in May 2012 .2 Table 2. Starter pack table for first distribution run in Ebonyi state . 4 Table 3. Roll out of DDIC distributions in Ebonyi State. 7 Table 4. DDIC roll out in Bauchi State . 10 iii iv Acronyms AS/AQ artesunate/amodiaquine AMC average monthly consumption BACATMA Bauchi State Agency for the Control of AIDS, Tuberculosis and Malaria CMS Central Medical Store DDIC Direct Delivery and Information Capture DMMA Drug and Medical Consumables Management Agency DRF Drug Revolving Fund DTTU Delivery Team Topping Up FMOH Federal Ministry of Health GFATM Global Fund to Fight AIDS, Tuberculosis and Malaria GHLI-L General and Health Logistics International, Limited HCH Honorable Commissioner for Health HF health facility IC&DD Information Capture then Direct Delivery IT information technology JSI John Snow, Inc. LGA local government area LLIN long-lasting insecticide-treated bed net MAPS Malaria Action Plan for States MNCH maternal, neonatal, and child health MOS months of supply N naira (currency in Nigeria) NMEP National Malaria Elimination Program PHC primary health care PMI President’s Malaria Initiative R&DD Review & Direct Delivery R&R Review and Resupply RRM Review and Resupply Meetings v SCMS Supply Chain Management System SDP service delivery point SMOH State Ministry of Health SOP standard operating procedure UNFPA United Nations Population Fund USAID U.S. Agency for International Development VMI vendor-managed inventory vi Acknowledgments The authors would like to thank and express their sincere appreciation to the staff of the Nigeria and Core USAID | DELIVER PROJECT; of the Nigeria Supply Chain Management System (SCMS) office; of the Ministry of Health in Ebonyi; Bauchi, Zamfara and Sokoto states; of the Federal Ministry of Health in Nigeria; and the management and staff of General and Health Logistics International Limited for the time, expertise, and support they provided for this activity. Special thanks go to Elizabeth Igharo, Ezekiel Akintunde, Innocent Ibegbunam, Miranda Gyang, Kingsley Obasi, Jonah Dienye, Kolawole Falayajo, Oluwole Olalandu, John Durgavich, and Iyeme Efem of the Nigeria USAID | DELIVER PROJECT and SCMS. vii viii Executive Summary The Direct Delivery and Information Capture (DDIC) model of distributing health commodities—a vendor-managed inventory (VMI) system—enables delivery teams to use an automated inventory control process to replenish health facilities with commodities. A similar VMI model, the Delivery Team Topping Up (DTTU) system is managed by the USAID | DELIVER PROJECT in Zimbabwe; it was the inspiration for the DDIC. Initially, the DDIC system was part of a cost survey to investigate alternative distribution models that would address supply chain challenges, such as limited human resource capacity, low reporting rates, frequent expiries, and limited product availability. The USAID | DELIVER PROJECT implemented the DDIC system as a pilot in two states in Nigeria: Ebonyi and Bauchi. This document reports on the DDIC activities from March 2012 to August 2014. In the health facilities selection process, advocacy meetings were held with State Ministry of Health (SMOH) officials and major stakeholders in the DDIC-supported states on selecting health facilities (HFs) for the DDIC roll out. The criteria for selection included accessibility to primary/secondary roads, availability of skilled personnel, availability of storage facilities (security), programs for HFs that implement malaria and reproductive health, and a geographical spread. Based on these criteria, and after a road transportation network analysis, 165 and 213 health facilities were selected for the pilot in Bauchi and Ebonyi states respectively. Transportation component of the DDIC As part of the DDIC model, transport was outsourced, based on the evaluation of the technical proposals. One of the three short-listed vendors submitted the most competitive technical and business proposal and they were selected to provide the rolling warehouses, as well as the personnel to manage the inventory in transit. Commodities delivered by the DDIC Initially, 16 commodities from three health programs—malaria: six; contraceptives: five; and maternal, neonatal, and child health (MNCH): five—were selected for the pilot. This is now expanded to include additional commodities, not all which have been in full supply during any distribution run in any state. Availability of MNCH commodities, in particular, has been erratic. Overall, the total number of commodities available for distribution ranges between 19 and 22. In developing the capacity to manage the DDIC, two technical assistance providers from Zimbabwe, one provider from the project office in Washington, D.C., and the Nigeria office staff provided and supported the training. Twenty-six participants—the transport vendor: two; the project: five; and state pilot coordinators: two—were included. Of the 26 participants, 20 were certified. ix DDIC Delivery Team The strength of the DDIC is the delivery team. They not only deliver the commodities to the health facilities, but they also manage the inventory on the trucks; determine how much replenishment a health facility will receive; and provide on-the-job mentoring to service providers for commodities management, inventory control practices, and good storage procedures. The quantity of replenishment stock is determined by entering logistics data into the Automated Delivery Receipt Voucher (AutoDRV), which then generates the quantity of stock required to replenish that facility for stock that will last for up to four months. At the end of the delivery run, the AutoDRV is synchronized with the Top-Up software, from which reports can be generated. These reports provide information on the stock status, delivery coverage, stockout, and adjustment summary at the facility-, regional-, and state-levels. Stakeholders receive the reports and use them for decisionmaking. Implementation of the DDIC Delivery runs in Ebonyi state began in January 2013, while Bauchi state made its first delivery run in July 2013. Since the DDIC started, stockout rates in the pilot states are lower. For example, in Ebonyi state, stockout rates dropped from above 70 percent (January 2013) to below five percent (March 2014) for all commodities in full supply. In all the supported states, the coverage rate is 100 percent for all HFs and logistics data are readily available for decisionmaking. Although the delivery coverage is 100 percent, replenishment may be limited by seasonal accessibility for some health facilities. By January 2014, with delivery coverage rates above 95 percent, a significant drop in stockout rates for DDIC commodities, and the availability of real-time data in Ebonyi and Bauchi states; in FY2014, the USAID mission in Nigeria agreed to adopt the DDIC distribution model in two new states: Sokoto and Zamfara. Evaluating the DDIC In August 2014, a cost analysis compared three last mile delivery models to the DDIC. These models under study included the Review and Resupply Meetings (RRM), Information Capture and Direct Delivery (IC&DD), and the Review & Direct Delivery (R&DD) options. The costs, data quality, stockout rates, and inventory levels were compared; as well as the considerations for scalability. Evaluating these last mile delivery options showed that when information capture is based on physical counts, such as in the DDIC, the data accuracy is twice as accurate as when it is based on inventory records. For DDIC and R&R, where the information capture is supported by physical counts, the percentage of inventory records that are within 5 percent of the physical inventory is above 60 percent—averaging 76 percent. However, the accuracy for the IC&DD and R&DD systems, where information capture is based more on inventory records, is below 40 percent—averaging 29 percent. So, when physical counts drive information capture, inventory-level records are at least twice as accurate as when they are not counted. The study also showed that the DDIC had comparatively higher implementation costs, but lower operational costs, when compared to the other delivery models evaluated. Average costs tend to decrease with addition of commodities, confirming economies of scale, even for the DDIC (Watson and McCord 2014). x Background At the start of 2013, to address supply chain challenges they faced as a resource-limited country, Nigeria launched a pilot vendor-managed inventory (VMI) system of health commodities distribution . These challenges included a reduced human and transport capacity, limited or no stock availability, and low data visibility for decision-making. The USAID | DELIVER PROJECT began implementing this pilot with initial funding from USAID Washington and USAID Nigeria; it was called the Direct Delivery and Information Capture (DDIC). The DDIC was modeled after a successful mechanism for distributing health commodities that the USAID | DELIVER PROJECT has implemented in Zimbabwe since 2003. In Zimbabwe, the Delivery Team Topping Up (DTTU) system is used to deliver health commodities to 1,650 health facilities (HFs) across the country. The DDIC was piloted in two states in Nigeria: Bauchi and Ebonyi. Accomplishments of the DDIC Activity DDIC System Design (May 2012) The DDIC distribution system was designed during a workshop with key Federal and State Ministry of Health officials and other stakeholders, from May 8–12, 2012. A two-level bimonthly integrated distribution system was designed for 16 commodities from three health programs: family planning, malaria, and essential medicines. The required resources, implementation, and research plans were all prepared during the system design workshop. Participants selected the name for the system—Direct Delivery and Information Capture (DDIC)— after the design workshop. DDIC Study Tour to Zimbabwe The project made a DDIC study tour to Zimbabwe in July 2012. A 10-person delegation participated in the study tour, comprising commissioners for health, directors, program officers, and technical experts from the Federal Ministry of Health (FMOH); selected officials from the State Ministries of Health (SMOH) for the pilot states (Bauchi and Ebonyi); USAID Nigeria; and the USAID | DELIVER PROJECT Nigeria field office. The tour was intended to provide participants with a comprehensive understanding of the structure and operations of the DTTU system, as applied in Zimbabwe. The team learned about the challenges encountered with strategies employed by Zimbabwean counterparts during the development, as well as possible strategies for refinement and subsequent operation of the DTTU system. The tour was informative and offered practical knowledge of the DTTU operations, which would help participating SMOHs and project staff design, promote; and, otherwise, support the pilot project envisioned for Nigeria. The study tour also gave key Government of Nigeria officials and staff a much greater awareness and understanding of the DTTU model as a possible alternative to the existing public sector health commodity supply chains. 1 DDIC Software (AutoDRV and Top Up) To prepare for implementing the pilot in Nigeria, the project team decided to adopt the AutoDRV and Top Up software used for DTTU in Zimbabwe. The source codes for the software were collected from Zimbabwe during the study tour visit. ADS 548 approvals were obtained to adapt the software to the Nigeria context and to acquire hardware components. Two servers (one for each pilot state) were procured; the project’s office in Arlington donated laptops for the DDIC activities. The office information technology (IT) staff routinely addressed all software-related bugs, with occasional support from the project’s IT team in Arlington. Since the pilot started, Nigeria office staff have made various enhancements for the software. In March 2014, the Top Up software was transferred to a cloud-based server where DDIC reports and data are uploaded. To ensure that stakeholders have regular access to DDIC distribution data, a DDIC report portal was also created on the cloud-based server. DDIC Commodities Sixteen commodities from three health programs—malaria: six; contraceptives: five; and maternal, neonatal, and child health (MNCH): five—were selected for the pilot (see table 1). It was assumed that full availability of donor-supported commodities (family planning and malaria) would be ensured. The project participated in advocacy-related activities with the President’s Malaria Initiative (PMI); National Malaria Elimination Program (NMEP), which is the principle recipient for the Global Fund’s (GFATM) malaria program; and the United Nations Population Fund (UNFPA) for procuring commodities for the DDIC pilot states. The USAID | DELIVER PROJECT prepared forecasts for malaria commodities for Ebonyi and Bauchi states; and PMI agreed to support the procurement of malaria commodities for the DDIC pilot roll out. PMI procured malaria commodities for 200 and 165 HFs in Ebonyi and Bauchi states, respectively. Table 1 lists all 16 commodities selected for the DDIC pilot. Table 1. Sixteen DDIC-Supported Commodities as Agreed at the System Design in May 2012 Contraceptives MNCH Malaria Microgynon Oxytocin A/L 1 x 6 Microlut ORS A/L 1 x 12 Noristerat Zinc A/L 1 x 18 Depo-Provera Misoprostol tab A/L 1 x 24 Male condoms Magnesium sulfate Rapid diagnostic tests Sulfadoxine-pyrimethamine In Ebonyi state, UNFPA, through the DDIC model, provided misoprostol tablets and magnesium sulphate injections for distribution to HFs. The GFATM provided malaria commodities in Ebonyi state, while the World Bank provided malaria commodities through the malaria booster project in Bauchi. At the stakeholder meetings, which were held at both the state- and federal-levels, it was 2 agreed that harmonization of all donors’ commodities should take place at the state Central Medical Store (CMS) for distribution to the DDIC-supported facilities. Because of the preliminary success of DDIC, the decision was made that all malaria commodities— except long-lasting insecticide-treated bed nets (LLINs) and all family planning commodities— should be included as DDIC-supported commodities. During the same period, DDIC was also rolled out in Bauchi state, with 24 DDIC-supported commodities. It should be noted that not all 24 commodities have been in full supply during any distribution run, in any state. Availability of MNCH commodities has been very erratic. Overall, the total number of commodities available for distribution varies between 19 and 22. Bauchi SMOH, through the Bauchi State Agency for the Control of AIDS, Tuberculosis and Malaria (BACATMA), decided not to distribute artesunate/amodiaquine (AS/AQ) in the state because of the perceived side effects attributed to the medicine. The refusal to distribute AS/AQ persisted even after a sensitization activity informing the state that AS/AQ supplied by PMI had been reformulated to decrease the side effects attributed to the amodiaquine component. But, AS/AQ has not been distributed through DDIC in Bauchi state. DDIC Commodities Starter Packs for First Distribution Runs in Supported States Prior to DDIC standard operating procedures (SOP) training of team leaders, consumption data was collected for the available commodities from programs supporting the various commodities in the two states. For malaria commodities, consumption data were used from the Malaria Action Program for States (MAPS)–supported HFs in the state. For family planning commodities, consumption data from the state family planning program were used. In states where the project has supported the family planning program, logistics data from the most recent review and resupply (R&R) meeting were loaded into the AutoDRV for the first DDIC distribution runs. This enabled staff to use AutoDRV historical data for the supported HFs, and it supported the data transition from the R&R distribution mechanism to the DDIC. For MNCH commodities, forecasted quantities were used to determine average monthly consumption (AMC), which were rounded up to four months of stock (MOS). This was done for all commodities to determine the starter pack quantities—which were for estimated consumption for four months (see table 2). Another important factor was the quantity of each commodity available at the state CMS, prior to the commencement of the delivery run, to determine if available commodities were sufficient for the distribution run. Stock count was completed for each commodity at the state CMS prior to beginning each distribution run. 3 Table 2. Starter Pack Table for First Distribution Run in Ebonyi State Pilot DDIC Commodities Starter Packs for Each Health Facility in Ebonyi Commodities Units Quantities for each HF Packs Total No. (units) for 63 HFs during first delivery run Available stock at state level A Malaria Commodities (using maximum consumption data from Ebonyi PHCs) 1 Artemether/ lumefantrine 1 x 6 Blister of 6 tabs 300 10 18,900 88,140 2 Artemether/ lumefantrine 2 x 6 Blister of 12 tabs 180 6 11,340 142,770 3 Artemether/ lumefantrine 3 x 6 Blister of 18 tabs 90 3 5,670 72,660 4 Artemether/ lumefantrine 4 x 6 Blister of 24 tabs 510 17 32,130 147,960 6 Malaria rapid diagnostic test Test 575 23 36,225 259,270 B Contraceptives (using adjusted consumption data from Ebonyi state) 1 Microgynon Cycle 15 5 945 1,281 2 Microlut Cycle 12 4 756 1,254 3 Noristerat Amp 25 0 1,575 2,536 4 Depo-Provera Vial 15 0 945 1,111 5 Male condoms Piece 288 2 18,144 30,923 C MNCH Commodities (using forecast figures from Ebonyi state) 1 Misoprostol tablets Tablet 150 50 9,450 10,377 2 Magnesium sulfate injection vial 20 2 1260 2265 DDIC Transport Management A DDIC transport services request for proposal (RFP No 12 - 093) was advertised on September 5, 2012, on the USAID | DELIVER PROJECT website. Eleven vendors submitted both technical and business proposals for evaluation. All technical proposals were evaluated and three were short- listed for business evaluation. The Nigeria field office conducted due diligence site visits to review the fleet and management capacity of the offerors to successfully complete the operational strategies 4 provided in their proposals. Field staff determined that General and Health Logistics International, Limited (GHLI-L) submitted the most competitive technical and business proposals; they were subcontracted to provide transportation service for the DDIC pilot in Bauchi and Ebonyi states. Selection of DDIC-Supported Health Facilities Advocacy meetings were held with SMOH officials and major stakeholders in the DDIC-supported states on the selection of HFs for the DDIC roll out. The criteria for selection included the following; accessibility to primary/secondary roads availability of skilled personnel storage facilities (security) HFs implementing malaria and reproductive health programs geographical spread. Based on this criteria, the 15 GFATM-supported HFs in each local government area (LGA) were included in Ebonyi state. Earlier, because the project decided to roll out the pilot to 200 HFs in the state, additional health facilities were selected from LGAs with a larger number of HFs: Ikwo, Ezza South, and Ivo. An increase in PMI/MAPS–supported HFs, and the inclusion of six government- supported rural HFs, increased the total number of HFs to the current 213. In Bauchi state, the project decided to roll out the DDIC pilot in 250 HFs across the 20 LGAs in the state. A road network analysis informed the HF selection criteria to only include facilities located within 5 kilometers of primary and secondary roads. Based on these criteria, the number of HFs was decreased from 250 to 165, which was accepted for the pilot. DDIC SOP/AutoDRV training The pilot DDIC SOP/AutoDRV training, held during January 8–12, 2013, was facilitated by a team of two technical assistance providers from Zimbabwe; one provider from the project office in Arlington, Virginia; and one Nigeria office staff. An interactive, five-day training on the DDIC SOPs included activities and scenarios on using laptops loaded with AutoDRV software for the DDIC distribution system. The key content areas covered in the course included— quick overview of DDIC system—video clip of DTTU from Zimbabwe introduction to computers and caring for laptops purpose of a DDIC SOP manual introduction to DDIC and commodities role and responsibilities in the DDIC system overview of LMIS forms and how to complete them (letters of request, stock reconciliation form, truck stock card, paper-based DRV) 5 introduction to AutoDRV how to complete the AutoDRV facility worksheet how to complete the post-delivery report and summary delivery report how to manage emergency orders in the DDIC system how to supervise storage practices and handling expired/damaged stock strategy for first delivery run DDIC transport guidelines. Participants were highly motivated to learn the Box 1. Adult Learning Theory Approach DDIC system. Throughout the course, facilitators The training followed the Adult Learning Theory gave participants practical exercises and many approach, which encourages active participation examples to help them understand the DDIC and engagement. Training methods like question system, including software functionality. The final and answer, small and large group discussion, assessment helped the participants understand all exercises (individual and pair), lecturettes, and the activities required in preparing and executing brainstorming were used throughout the training. These helped participants to appreciate the pilot the DDIC delivery runs, including completing DDIC system in Nigeria. A training evaluation reporting in the AutoDRV system. questionnaire was distributed at the conclusion of the course. The training was highly rated and Course participants appreciated by the participants. Twenty-six participants attended: nine from Ebonyi, eight from Bauchi, two from General and Health Logistics International, two pilot coordinators from the state, and five from the project. Of the 26 participants, 20 (77 percent) received certificates of competency; six participants (23 percent) received certificates of completion. To receive a certificate of competency; participants had to score 75 percent or above on the final course assessment; and they were also tested on computer skills and leading a revision exercise in a group. All certified participants were part of the pilot in Ebonyi and Bauchi states. Simulated Distribution Runs for Team Leaders Team leaders did a simulated distribution run before the actual distribution runs in each state. It tested DDIC operations at the CMS and HFs and gave the team leaders firsthand experience at the facilities. To ensure effective deployment of the AutoDRV software, an assessment of team leaders during the simulated distribution runs identified components of the distribution activities that required further mentoring. DDIC Sensitization/Orientation Activities Sensitization and orientation meetings were held for staff from all the supported HFs and LGA program officials in all the LGAs that received pilot first-time DDIC deliveries. The meeting was used to introduce DDIC and its operations to the HFs and LGA personnel. They discussed relevant issues that are likely to occur during the delivery runs, including roles and responsibility of all key players in the pilot DDIC activities. 6 Roll Out of DDIC Distribution Runs in Pilot States DDIC Roll Out Activities in Ebonyi State The first delivery runs in Ebonyi state began in January 2013. Since then, 10 delivery runs have been successfully completed in the state. Table 3. Roll Out of DDIC Distributions in Ebonyi State Ebonyi State Period Duration Delivery Coverage (HFs) Number of Commodities Delivered 2013 1 Jan. 28–Feb. 14 61 12 2 March 11–April 5 107 12 3 May 6–-June 14 198 12 4 July 8–-Aug. 16 204 19 5 Sept. 9–Oct. 18 204 19 6 Nov. 4–Dec. 13 202 20 2014 7 Jan. 13–Feb. 21 213 21 8 March 10–April 22 207 21 9 May 5–-June 13 212 21 10 July 7–Aug. 21 209 21 Because of the frequent staff attrition and inter-facility transfers, the delivery team frequently found that the service providers from some service delivery points (SDPs) were not available. This resulted in fluctuating delivery coverage rates after full scale-up to 213 health facilities in January 2014. DDIC Achievements in Ebonyi State Release of naira (N) 80 million for procuring MNCH commodities to distribute in Ebonyi state The Ebonyi State Honorable Commissioner for Health (HCH) is committed to procuring MNCH commodities for distribution to HFs in the state using the DDIC distribution model. The state released N80 million to procure the MNCH commodities; they were available for distribution through the DDIC during the 2014 MNCH week celebrations in May 2014. 7 Governor of Ebonyi state, Chief Martin Elechi, flag off of DDIC activities In May 2014, DDIC flag off activities took place in Iboko, Izzi local government headquarters, as part of the MNCH week activities. Participants at the flag off ceremony included the state governor and his wife; deputy governor and his wife; commissioners; state house of assembly members; LGAs; development centers chairmen; traditional rulers; partners; and health workers, among others. Various dignitaries with the HCH made speeches; they expressed their appreciation to the USAID | DELIVER PROJECT for selecting Ebonyi state as a pilot state to distribute essential medicines to 213 HFs, across the 13 state LGAs. The DDIC national coordinator, representing the project, spoke on behalf of the project and development partners. The coordinator expressed his appreciation to the state government for supporting DDIC with procuring MNCH commodities for distribution through the DDIC model. DDIC, he stated, has reduced the stockout rates of malaria and family planning commodities to below 3 percent in supported HFs. With the SMOH procuring MNCH commodities, DDIC would ensure their distributions and provide data that could inform future procurements. Gov. Martin Elechi addressing the crowd Improving commodities and data availability in Ebonyi state After 10 bimonthly distribution cycles in Ebonyi state, commodity availability has dramatically improved. Stockout rates have been reduced from above 70 percent (January 2013) to below 5 Samples of MNCH commodities at the flag off ceremony in Ebonyi state Ph ot o Cr ed it: U SA ID | D EL IV ER P RO JE CT 2 00 9 Ph ot o Cr ed it: U SA ID | D EL IV ER P RO JE CT 2 00 9 percent (March 2014) for all commodities in full supply (see figure 1 and figure 2). Coverage rate is 100 percent for all HFs and logistics data are readily available for decisionmaking. 8 Figure 1. Stockout Rates for Malaria Commodities at Health Facility Levels in Ebonyi State Figure 2. Stockout Rates for Family Planning Commodities at Health Facility Levels in Ebonyi State 9 DDIC Roll Out Activities in Bauchi State DDIC roll out in Bauchi state started in July 2013. Since then, seven delivery runs have been successfully completed. Table 4. DDIC Roll Out in Bauchi State Bauchi State Period Duration Delivery Coverage No. of Commodities Delivered 2013 1 July9–23 79 12 2 Sept. 10–Oct. 4 116 12 3 Nov. 4–Dec. 5 165 12 2014 4 Jan. 13–Feb. 17 162 19 5 March 10–April 11 162 19 6 May 5–June 4 159 20 7 July 7–Aug. 10 163 21 The USAID | DELIVER PROJECT conducted a refresher training for team leaders and other operators of the system who were initially trained in January 2013. The project also completed a state-level sensitization for HF staff and key stakeholders at the SMOH, State Ministry of Local Government & Chieftaincy Affairs, state transport company, Yankari Express, and local governments with the goal of informing all relevant and concerned stakeholders about their roles and responsibilities, and to brief them on the schedule of upcoming pilot DDIC activities in the state. DDIC Achievements in Bauchi State Governor of Bauchi State, Mal. Isa Yuguda, flag off of DDIC activities Pilot DDIC activities were flagged off by the Executive Governor of Bauchi State, Mal. Isa Yuguda on Monday, July 1, 2013. Attending were commissioners, permanent secretaries, directors, and executive chairmen of various agencies; and other dignitaries from Bauchi state. The HCH, Dr. Sani Abubakar Malami, the chief host of the ceremony, expressed his appreciation to the project, on behalf of the SMOH, for supporting the state health programs with an innovative distribution mechanism for health commodities. The governor was grateful for all the support Bauchi state received from all USAID-supported Gov. Isa Yuguda and Ministry of Health staff inspecting the delivery vehicles and commodities Ph ot o Cr ed it: U SA ID | D EL IV ER P RO JE CT 2 00 9 projects in the state. He pledged the support of his government to the DDIC delivery model and promised that the relevant agencies will procure MNCH commodities for distribution to HFs through the DDIC model. Following on this commitment, 50,000 doses of misoprostol tablets—out 10 of an expected 125,000 doses—were procured by the state government for distribution to HFs through the DDIC model. After flagging off the DDIC pilot activities, he inspected the DDIC delivery trucks and the warehouse of the Bauchi State’s Drug and Medical Consumables Management Agency (DMMA), where the DDIC commodities, particularly the PMI-procured malaria commodities, were stored. The USAID | DELIVER PROJECT Nigeria deputy chief of party and the DDIC national coordinator represented the project. Renovation of Bauchi CMS warehouse Gov. Isa Yuguda and John Durgavich at the launching of the DDIC pilot To effectively roll out the pilot DDIC in Bauchi state, commodities were stored at the state level and conveyed from there to the HFs. The Bauchi SMOH had twin warehouse structures located in the state library complex. The DMMA renovated one of the structures for storing the commodities managed under the Bauchi State Drug Revolving Fund (DRF). During the DDIC system design, storage space in this renovated facility was allocated for DDIC commodities. Due to insufficient space in the DMMA warehouse, the option of renovating the next warehouse building was proposed at the DDIC system design. The project, therefore, with funds from Task Order 4 field office technical support services, renovated this warehouse structure; it will be used to store DDIC commodities. Improving commodities and data availability in Bauchi state After five bimonthly distribution cycles in Bauchi state, commodity availability has drastically improved and stockout rates are significantly reduced. Coverage rate is 100 percent for all HFs and essential logistics data are readily available for decisionmaking. Figures 3 and 4 show stockout rates for malaria and family planning commodities at the health facilities in Bauchi state. Ph ot o Cr ed it: U SA ID | D EL IV ER P RO JE CT 2 00 9 11 Figure 3. Stockout Rates at the SDP-Level for Malaria Commodities in Bauchi State 12 Figure 4. Stockout Rates at the SDP-Level for Family Planning Commodities in Bauchi State The World Bank Booster project supports the malaria program in Bauchi state. PMI support began when the pilot started. Initial quantification for PMI-supported states did not include Bauchi state; therefore, malaria commodities for the pilot were drawn for other states. Coupled with limited stock at the central level, this led to the rationing of malaria commodities, which meant comparatively high stockout rates for AL-1, AL-2, AL-3, and AL-4. 13 14 DDIC Roll Out in FY2014 to Two Project–Supported States With delivery coverage rates above 95 percent, significant reductions in stockout rates for DDIC commodities, and the availability of real-time data shown in Ebonyi and Bauchi states; the USAID mission in Nigeria, in FY2014, agreed to adopt the DDIC distribution model in two new states: Sokoto and Zamfara. Engagement/sensitization meetings were held at the state level; the state agreed to collaborate with the project on DDIC activities. Key stakeholders, including the SMOH, Ministry of Local Government and Chieftancy Affairs (MOLG&CA), and implementing partners, selected the commodities and HFs. In January 2014, to prepare for the roll out of the DDIC, team leaders and other DDIC personnel were selected and trained. Orientation activities were carried out for supported HFs and LGA personnel prior to the roll out of the model across the states. DDIC Roll Out in Sokoto State DDIC roll out in Sokoto state started in February 2014. Since then, four delivery runs have been successfully completed (see table 5). Table 5. DDIC Roll Out in Sokoto State Sokoto State Period Duration Delivery Coverage No. of Commodities Delivered 2014 1 Feb. 10–March 8 344 12 2 March 31–May 7 344 12 3 May 30–June 25 344 12 4 July 8–Aug. 18 344 19 15 DDIC Roll Out in Zamfara State DDIC roll out in Zamfara state started in February 2014. Since then, four delivery runs have been successfully completed (see table 6). Table 6. DDIC Roll Out in Zamfara State Zamfara State Period Duration Delivery Coverage No. of Commodities Delivered 2014 1 Feb. 10–March 4 210 12 2 March 17–April 17 219 21 3 May 5–June 5 211 12 4 July 7–Aug. 12 211 19 16 Last Mile Distribution Systems Evaluation in Nigeria A cost-effectiveness study was conducted in five states in Nigeria: Bauchi, Ebonyi, Sokoto, Cross River, and Benue. Four last mile delivery systems were evaluated—the R&R system; the DDIC; the cluster review meeting or Review & Direct Delivery (R&DD); and the LGA review meetings, referred to as the Information Capture then Direct Delivery (IC&DD). The goal of the study was to— 1. Cost each of the four last mile distribution systems and investigate cost variations between the systems. 2. Determine the stockout rates and inventory levels achieved by the various last mile system instances. 3. Determine the data quality and lead time for collection of data achieved by the various last mile system instances. 4. Consider the scalability of the last mile distribution systems given the considerations for adding commodities and facilities to the systems. Key Findings Inventory management For inventory performance, all systems were similarly functional with single-digit stockout rates and good general inventory availability, given the supply. Costing A costing exercise using standard costing methodology revealed that, at their respective scales, all last mile systems use significant levels of management, facility labor, and logistics resources; and they have significant funding from both the Government of Nigeria and donors. The costs, whether normalized by cubic meters delivered or dollars’ worth of commodity delivered, showed clear effects of scale with the systems, with larger volumes distributed tending to have lower costs. Normalizing costs by assuming a common scale—number of facilities and volume distributed for all systems— showed the DDIC and IC&DD with the lowest costs, followed by the R&DD and the R&R. Scalability The cost ranking from normalizing costs to account for differences in scale seemed to play out in simulations of increasing scale, whether by adding commodities or facilities to last mile distribution systems. DDIC and IC&DD have similar costs, with a slight preference for DDIC for lower 17 number of commodities; followed by R&DD and then R&R. Average costs tend to decrease with the addition of commodities, confirming economies of scale, even for the DDIC. Data quality For DDIC and R&R, where the information capture is supported by physical counts, the percentage of inventory records within 5 percent of the physical inventory is above 60 percent, with an average of 76 percent. While the accuracy for the IC&DD and R&DD systems, where information capture is based more on inventory records, is below 40 percent, averaging 29 percent. Therefore, when physical counts drive information capture, inventory level records are at least twice as accurate as when they are not physically counted (Watson and McCord 2014). 18 Last Mile Distribution Systems Evaluation in Nigeria Dissemination Conference The last mile distribution systems evaluation dissemination conference took place on August 7, 2014. In attendance were representatives of the following organizations: 1. USAID Nigeria a. Acting Deputy Mission Director b. Two activity managers for the USAID | DELIVER PROJECT and SCMS. 2. Federal Ministry of Health a. Directors b. National Program Managers/Coordinators c. Program staff 3. State Ministries of Health a. Commissioners for Health (Ebonyi, Benue and Nasarawa) b. Representatives of States Commissioners for Health c. Directors of Pharmaceutical Services 4. Donors and implementing partners The keynote address was given by the Acting USAID Mission Director, Kathy Body, with goodwill messages from the United Nations Population Fund (UNFPA), FMOH, MAPS, and Targeted States High Impact Project (T/SHIP). An overview of DDIC processes and other last mile distribution models were presented. This was followed by the dissemination of the last mile distribution models evaluation. Questions and answers; and panel discussions on lessons learned, were followed by a presentation on engaging third-party logistics providers from the supply chain operations department at the USAID | DELIVER PROJECT office. The conference was a success in terms of attendance, dissemination of evaluation findings, and participation and engagement of participants. 19 20 Conclusion The DDIC mechanism for distributing health commodities was successfully implemented in Nigeria. During one year, a significant reduction in stockout rates for commodities in full supply was recorded. Results of the cost evaluation study showed that while separate and simultaneous information capture and delivery can be the foundation for cost-efficient last mile distribution systems, the DDIC benefited from the automatic cost savings with simultaneous information capture and delivery (Watson and McCord 2014). When operating at the same scale, the operating costs for facility labor was 10 times less for the DDIC system compared to the review and resupply models for last mile distributions. Finally, when physical counts are used for information capture, it usually results in more accurate inventory records (Watson and McCord 2014). 21 22 References Watson, Noel, and Joseph McCord. 2014. Evaluating Last Mile Distribution Systems in Nigeria. Arlington, Va.: USAID | DELIVER PROJECT, Task Order 4. 23 24 For more information, please visit deliver.jsi.com. USAID | DELIVER PROJECT John Snow, Inc. 1616 Fort Myer Drive, 16th Floor Arlington, VA 22209 USA Phone: 703-528-7474 Fax: 703-528-7480 Email: email@example.com Internet: deliver.jsi.com
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