Supplementary appendix This appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors. Supplement to: Pronyk PM, Nemser B, Maliqi B, et al, for the UNCoLSC Technical Resource Teams, UN Agency Leads, and UNCoLSC Monitoring and Evaluation Advisory Group. The UN Commission on Life Saving Commodities 3 years on: global progress update and results of a multicountry assessment. Lancet Glob Health 2016; 4: e276 86.
Web Appendix Detailed Methodology Development of the RMNCH Situation Analysis tool Facilitation of the Situation Analysis was conducted by the Reproductive Maternal Newborn and Child Health (RMNCH) Strategy and Coordination Team (SCT) - an interagency team comprised of WHO, UNICEF and UNFPA. The SCT, in consultation with global consortium of experts from the technical resource teams (TRTs) of the UN Commission on Life Savings Commodities (UNCoLSC), developed the RMNCH Situation Analysis tool to rapidly profile the status of RMNCH programs and key implementation bottlenecks along the RMNCH continuum. The tool utilizes the 13 life-saving commodities highlighted in the UNCoLSC report as tracers to identify bottlenecks across the health system. The RMNCH Situation Analysis process systemically gathers information on RMNCH programs and the state of manufacturing, import, procurement, regulation, quality, access and utilization for the 13 commodities. Most of this information already exists in the form of national strategic plans, essential medicine/medical device lists, training materials, and other related documents. Document reviews were accompanied by semi-structured interviews with key stakeholders in the Ministry of Health, procurement and regulatory agencies, as well as with UN country teams and local experts. Information from established nationally representative health facility surveys contributed data on the status of infrastructure, resources, training and stock availability at the facility level. Lastly, aggregated indicators from health and logistics management information systems (H/LMIS) are reviewed (where available) for commodity availability and service utilization at the facility level. Given the time and resource limitations at country-level, the content and length of the tool was designed to maximize the use of available information in a timely manner. Inquiries requiring detailed and/or time consuming research by MoH staff (e.g. review of each procurement contract within the last 12 months) were deemed inappropriate for this process. All data sources for the RMNCH Situation Analysis, including facility and population-based surveys, are from 2012 onward to capture country progress since the launch of the UNCoLSC report. The specific timing of the various components for countries included in this assessment are specified in Web appendix Table 2. The resulting data are typically qualitative, categorical or continuous in nature, which are given a performance rating (weakest 1 to 5 strongest) based on established criteria (Web-appendix Table 6). The performance rating cutoffs were developed in consultation with the global TRTs to illustrate incremental improvements in systemic or programmatic conditions. Administration of these performance ratings may be subjective; however, it produces an easy to interpret quantification, which is comparable over time and across countries. Conducting the RMNCH Situation Analysis The inputs for the Situation Analysis, including document reviews and expert interviews, were conducted by an independent team of RMNCH experts who worked in partnership with Ministries of Health and UN agencies. These experts underwent a one-week orientation jointly conducted by WHO, UNICEF and UNFPA. A focal point from this team was designated for each country, who generally conducted the Situation Analysis with the support of a local consultant. Data collection was supervised remotely by the Strategy and Coordination Team (SCT). The RMNCH Situation Analysis Tool and Enumeration Manual provided a template and guide to support this process. All Situation Analysis results were reviewed by the SCT for completeness and adherence to processing protocols. The SCT, facilitator and select country team members together reviewed the results and addressed inconsistencies prior to finalizing country reports. These reports were circulated to the wider country teams for additional endorsement. The RMNCH Situation Analysis requires approximately 7-10 working days in-country to review the relevant documents and coordinate the necessary interviews. Approximately 10-15 key informant interviews are conducted, which range from 15-60 minutes. Data processing and cleaning with the SCT typically requires an addition 2-3 working days. Data collection is conducted primarily via Microsoft Excel. Results are entered into a relational
database and processed for upload to a web-based dashboard (see below for more details). Once the data processing is complete, the final Situation Analysis template, a summary report, and access to the SCT Dashboard is shared with in-country MoH, UN agencies and partners participating in the process. Timeline for the RMNCH Situation Analysis The RMNCH Situation Analysis is implemented in countries receiving support from the RMNCH Fund, as well as a sub-set of additional Every Woman Every Child (EWEC) countries. As of the time of writing, the SCT, in partnership with USAID, has conducted the RMNCH Situation Analysis in 12 countries (Democratic Republic of the Congo, Cameroon, Ethiopia, Kenya, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Tanzania, and Uganda, Zambia) including repeat enumeration in five (5) countries (Ethiopia, Malawi, Senegal, Tanzania and Uganda). In countries with two rounds of data collection, only data from the latest round has been utilized to generate bottleneck-related indicators. The SCT plans to repeat the RMNCH Situation Analysis in each country approximately every 12-18 months. Analysis and Visualization Indicator results from all sources, including the RMNCH Situation Analysis, health facility assessments and household surveys, are entered into an internal Microsoft Access relational database (MS Access, Microsoft, 2013) and processed (R version 3.2.0, 2015) for upload to a web-based dissemination and visualization Dashboard. Values presented in the online RMNCH Dashboard are computed with the help of scripts written in R (version 3.2.0), outputted into structured Excel files and uploaded to a remote Dashboard application that utilizes PHP, MySQL and WordPress technology stack to store, process and display the data to the end user. The SCT Dashboard provides a visual representation of bottlenecks along the RMNCH continuum for a single country as well as multi-country maps and aggregations See Web-appendix Figures 1-4 below for examples. The 13 life-saving commodities and UNCoLSC recommendations act as an organizational basis for the visualizations. The SCT Dashboard provides an innovative and comprehensive view of available information on the UNCoLSC recommendations and 13 life-saving commodities.
Web-appendix Table 1: Estimates of population coverage for 13 Life Saving Commodities, 2012 Intervention coverage estimates presented below for maternal, newborn and child were available in the Lives Saved Tool (LiST) for analysis in the UNCoLSC Final Report 2012. Zinc coverage estimates were updated based on available information from the Demographic Health Surveys (DHS, USAID) or Multiple Indicator Cluster Surveys (MICS, UNICEF) for survey rounds occurring in 2005-2012. For reproductive health, coverage estimates from the UN Populations Division, World Contraceptive Use 2012 report, are presented below with Female Condom and Emergency Contraceptives aggregated under Other modern methods. Country Contraceptive prevalence (any modern method) Reproductive (1) Maternal (3) Newborn (3) Child (3) Other modern methods (2) Active Management Third Stage Labor Antenatal Corticosteriods Clean postnatal care Newborn Resuscitation Pre- Injectable Pneumonia Zinc Implants Eclampsia Eclampsia Antibiotics Treatment ORS (4) Afghanistan 16% 0% 0% 1% 18% 18% 0% 18% 23% 7% 68% 45% 5% Bangladesh 52% 1% 0% 1% 6% 6% 0% 6% 32% 2% 22% 77% 29% Benin 6% 1% 0% 3% 58% 58% 0% 58% 27% 35% 36% 23% 10% Burkina Faso 15% 3% 0% 1% 21% 21% 0% 21% 21% 8% 31% 21% 0% Burundi 18% 1% 1% 1% 8% 8% 0% 8% 21% 2% 26% 78% 0% Cambodia 35% 0% 0% 3% 40% 40% 0% 40% 10% 24% 39% 21% 2% Central African Republic 9% 0% 0% 2% 27% 27% 0% 27% 21% 10% 39% 91% 1% Chad 2% 0% 0% 1% 4% 4% 0% 4% 21% 1% 13% 15% 0% Comoros 19% 1% 0% 3% 23% 23% 0% 23% 21% 9% 41% 77% 0% Côte d Ivoire 8% 0% 1% 2% 26% 26% 0% 26% 21% 9% 19% 84% 0% DRC 6% 0% 0% 2% 53% 53% 0% 53% 8% 32% 32% 31% 2% Democratic Rep. of Korea 58% 0% 0% 5% 90% 90% 0% 90% 21% 66% 88% 74% 19% Eritrea 5% 0% 0% 2% 7% 7% 0% 7% 2% 2% 31% 45% 0% Ethiopia 27% 3% 0% 1% 3% 3% 0% 3% 2% 1% 9% 20% 0% Gambia 13% 0% 0% 3% 42% 42% 0% 42% 21% 26% 61% 74% 0% Ghana 17% 1% 0% 4% 43% 43% 0% 43% 12% 26% 24% 45% 0% Guinea 4% 0% 0% 2% 17% 17% 0% 17% 21% 6% 37% 33% 1% Guinea Bissau 0% 0% 0% 3% 21% 21% 0% 21% 21% 8% 42% 26% 0% Haiti 24% 2% 0% 3% 7% 7% 0% 7% 4% 2% 3% 40% 0% India 48% 0% 0% 2% 21% 21% 0% 21% 2% 8% 13% 26% 0% Kenya 39% 2% 0% 2% 23% 23% 0% 23% 7% 9% 50% 39% 0% Kygyz Republic 46% 0% 0% 4% 91% 91% 0% 91% 21% 67% 45% 40% 0% Lao PDR 35% 0% 0% 1% 6% 6% 0% 6% 21% 1% 52% 96% 1% Liberia 10% 0% 0% 3% 20% 20% 0% 20% 12% 8% 49% 53% 0% Madagascar 28% 2% 0% 3% 19% 19% 0% 19% 14% 7% 20% 17% 1% Malawi 42% 1% 0% 2% 55% 55% 0% 55% 3% 33% 24% 69% 0% Mali 6% 0% 0% 2% 25% 25% 0% 25% 22% 9% 30% 14% 0% Mauritania 8% 0% 0% 1% 26% 26% 0% 26% 21% 10% 24% 22% 0% Mozambique 11% 1% 0% 3% 26% 26% 0% 26% 21% 10% 22% 49% 0% Myanmar 46% 0% 0% 4% 20% 20% 0% 20% 21% 7% 34% 61% 0% Nepal 43% 1% 0% 2% 5% 5% 0% 5% 2% 1% 25% 29% 6% Niger 5% 0% 0% 1% 5% 5% 0% 5% 17% 1% 28% 18% 10% Nigeria 9% 0% 0% 2% 19% 19% 0% 19% 3% 7% 23% 26% 1% Pakistan 19% 0% 0% 1% 19% 19% 0% 19% 6% 7% 50% 41% 0% Papua New Guinea 0% 0% 0% 3% 39% 39% 0% 39% 21% 23% 49% 8% 0% Rwanda 44% 6% 0% 2% 8% 8% 0% 8% 5% 2% 13% 21% 0%
Sao Tome & Principe 33% 0% 0% 4% 59% 59% 0% 59% 18% 36% 56% 84% 0% Senegal 12% 1% 0% 2% 40% 40% 0% 40% 21% 24% 29% 7% 0% Sierra Leone 6% 0% 0% 3% 7% 7% 0% 7% 23% 2% 27% 68% 2% Solomon Islands 27% 0% 0% 3% 63% 63% 0% 38% 51% 63% 7% 38% 0% Somalia 1% 0% 0% 0% 3% 3% 0% 3% 21% 1% 32% 30% 0% Tajikistan 32% 0% 0% 4% 46% 46% 0% 46% 21% 28% 41% 96% 0% Tanzania 26% 2% 0% 2% 26% 26% 0% 26% 3% 9% 55% 54% 5% Togo 13% 0% 0% 3% 27% 27% 0% 27% 2% 10% 26% 95% 2% Uganda 26% 3% 0% 2% 23% 23% 0% 23% 3% 8% 47% 40% 2% Uzbekistan 59% 0% 0% 4% 89% 89% 0% 89% 21% 66% 56% 94% 0% Vietnam 60% 0% 0% 2% 48% 48% 0% 48% 21% 29% 55% 94% 1% Yemen 19% 0% 0% 1% 7% 7% 0% 7% 21% 2% 38% 33% 0% Zambia 27% 0% 0% 3% 25% 25% 0% 25% 5% 9% 47% 60% 0% Zimbabwe 57% 3% 0% 4% 51% 51% 0% 51% 4% 31% 16% 78% 0% AVERAGE COVERAGE 23% 1% 0% 2% 29% 29% 0% 29% 15% 16% 35% 48% 2% (1) United Nations, Department of Economic and Social Affairs, Population Division. 2012. World Contraceptive Use 2012 (POP/DB/CP/Rev2012). Available at http://www.un.org/esa/population/publications/wcu2012/mainframe.html (2) Other modern methods' includes emergency contraception, female condom and modern methods not reported separately. [Does not include: male and female sterilization, pills, injectables, implants, IUDs, vaginal barriers (e.g. sponges, diaphragm)] (3) The Lives Saved Tool (LiST), Spectrum software, version 4.5 (4) Updated based on available results from Demographic Health Surveys (USAID) or Multiple Indicator Cluster Surveys (UNICEF) from 2005-2012.
Web appendix Table 2: RMNCH Situation Analysis data sources by type and date (12 countries)* Country Situation Analysis tool Health Facility Data Population-based Data Cameroon 2014 2014 SDP DRC 2015 2012 EMONC 2012 EMONC Ethiopia 2013 2012 SDP 2015 2014 PMA 2014 PMA 2014 SDP Kenya 2015 2013 SARA 2014 PMA 2014 PMA 2014 DHS Malawi 2013 2014 SDP 2010 DHS 2015 2013/14 SPA 2014 MICS Mali 2015 2012/13 DHS Nigeria 2014 2014 SDP 2011 MICS 2013 DHS Senegal 2013 2012/13 SPA 2011 DHS 2012 EMONC 2015 2014 SPA 2014 SDP 2014 DHS 2014 MICS Sierra Leone 2013 2012 SARA 2010 MICS 2013 SDP 2014 DHS Tanzania 2015 2012 SARA 2010 DHS 2015 SDP Uganda 2013 2013 SARA 2011 DHS 2015 2014 PMA 2014 PMA 2014 SDP Zambia 2015 2010 SARA 2013 DHS EMOC: Emergency Obstetric and Neonatal Care, Averting Maternal Death and Disability DHS: Demographic and Health Survey, USAID MICS: Multiple Indicator Cluster Survey, UNICEF PMA2020: Performance Monitoring and Accountability 2020 Survey, Family Planning 2020 SARA: Service Availability and Readiness Assessment, WHO SDP: Service Delivery Point Survey, UNFPA SPA: Service Provision Assessment, USAID In countries with two rounds of data collection, only data from the latest round has been utilized to generate bottleneck-related indicators
Web appendix Table 3: Number of Countries with bottlenecks by indicator, level of healthcare system and RMNC service area (12 countries) Commodity-related indicators: National-level Bottlenecks Facility-level Bottlenecks Population R M N C Commodity by RMNC Service Area Female Condom Implant Emergency contraceptive Oxytocin Misoprostol Magnesium Sulfate Injectable antibiotic Antenatal Steriod Chlorhexidine Neonatal Resuscitation Amoxicillin ORS Zinc Regulatory Efficiency (1) National EML (2) National treatment guidelines (3) Registered in-country (4) Prescription authority Supply & Awareness (5) Tracked in elmis (6) National level stockouts Performance and Accountability (7) Training Curriculum (8) Job aids or checklists Reaching Women & Children (9) Policy against user fees Supply & Awareness (10) Stock out in health facilities Performance and Accountability (11) Recent training at facilities (12) Job aids or checklists at facilities Demand & Utilization (13) Coverage rates (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) 1 / 12 2 / 12 1 / 12 5 / 11 4 / 9 4 / 12 3 / 12 6 / 12 7 / 10 8 / 9 5 / 9 10 / 10 2 / 12 3 / 12 3 / 12 2 / 12 4 / 11 1 / 9 4 / 12 3 / 12 6 / 12 6 / 10 8 / 9 5 / 9 12 / 12 4 / 12 4 / 12 3 / 12 3 / 12 4 / 11 3 / 10 4 / 12 3 / 12 6 / 12 6 / 9 8 / 9 5 / 9 3 / 3 0 / 12 1 / 12 1 / 12 0 / 12 5 / 11 2 / 10 2 / 12 3 / 12 6 / 12 4 / 11 6 / 7 5 / 8 No data 2 / 12 4 / 12 2 / 12 2 / 10 5 / 10 4 / 8 2 / 12 3 / 12 6 / 12 9 / 9 6 / 7 5 / 8 No data 1 / 12 2 / 12 3 / 12 1 / 12 5 / 10 3 / 10 2 / 12 3 / 12 6 / 12 7 / 11 6 / 7 5 / 8 No data 4 / 12 3 / 12 3 / 12 0 / 12 5 / 9 2 / 10 5 / 12 7 / 12 6 / 12 5 / 10 7 / 7 1 / 1 No data 0 / 12 4 / 12 3 / 12 7 / 12 5 / 9 2 / 9 5 / 12 7 / 12 6 / 12 6 / 9 7 / 7 1 / 1 No data 4 / 12 9 / 12 3 / 12 5 / 9 1 / 7 5 / 12 7 / 12 6 / 12 3 / 3 7 / 7 1 / 1 No data 1 / 12 1 / 12 7 / 9 2 / 5 5 / 12 7 / 12 6 / 12 1 / 2 7 / 7 1 / 1 No data 5 / 12 1 / 12 5 / 12 5 / 12 4 / 9 4 / 8 0 / 12 0 / 12 6 / 12 6 / 9 4 / 5 1 / 1 10 / 10 0 / 12 0 / 12 3 / 12 0 / 12 5 / 10 1 / 8 0 / 12 0 / 12 6 / 12 2 / 6 4 / 5 1 / 1 8 / 12 5 / 12 0 / 12 5 / 12 0 / 12 5 / 10 2 / 8 0 / 12 0 / 12 6 / 12 4 / 5 4 / 5 1 / 1 9 / 9 Systems-related indicators: National-level Bottlenecks RMNCH Coordination (14) Coordination mechanism (15) RMNCH plan costed and budgeted (16) Commodi ty s ecuri ty strategy Innovative Financing (17) Results-based financing mechanism Supply & Awareness (18) Forecasting tools (19) Comprehensive national elmis (20) Supply chain training to districts Quality Strengthening (21) Procure GMP-accredited manuf. (22) National medicines control lab (23) Medicine quality (24) Patient safety Demand & Utilization (25) Demand generation (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) 3 / 12 6 / 12 7 / 9 8 / 12 4 / 12 10 / 11 5 / 12 2 / 11 4 / 12 5 / 12 6 / 10 4 / 12 Legend: % of countries with bottlenecks <= 20% 21-40% 41-60% 61-80% 81-100% No data
Web appendix Table 4: Average percent of health facilities with no recently trained staff by service area (12 countries) SERVICE AREA COMMODITY Female Condom Cameroon DRC Ethiopia Kenya Mali Malawi Nigeria Senegal Sierra Leone Tanzania Uganda Zambia Reproductive Implant Emergency contraceptives 51% * 77% 67% 51% * 54% * 51% * 37% * 51% 63% 56% Maternal Oxytocin Misoprostol Magnesium Sulfate 41% 49% 75% 27% 51% * 56% 80% 54% Injectable antibiotics Newborn Antenatal Steroids 60% 70% 62% 41% 80% 56% 80% 64% Chlorhexidine Neonatal Resuscitation Amoxicillin Child ORS Zinc TOTAL AVERAGE 51% 59% 62% 51% 64% 40% 56% 54% 74% 58% AVERAGE * Based on data source, 'Recent training' defined as taking place within last 12 months. If not marked with an '*', then the data source defines 'recent training' as taking place within the last (2) years.
Web appendix Table 5: Average percent of health facilities with no job/aids or checklists present at time of assessment by service area (12 countries) Cameroon SERVICE AREA COMMODITY Average Female Condom Reproductive Implant 64% 58% 71% 29% 62% 30% 58% 8% 40% 47% Emergency contraceptives Oxytocin Maternal Misoprostol 70% 67% 19% 67% 38% 48% 11% 50% 46% Magnesium Sulfate Injectable antibiotics Newborn Antenatal Steroids Chlorhexidine 53% 53% Neonatal Resuscitation Amoxicillin Child ORS 65% 65% Zinc TOTAL AVERAGE 67% 63% 68% 24% 65% 34% 53% 9% 45% 53% DRC Ethiopia Kenya Mali Malawi Nigeria Senegal Sierra Leone Tanzania Uganda Zambia
Web-appendix Table 6: Performance cut-off ratings for UNCoLSC commodity-specific and systems-related indicators
Indicator Definitions Updated: July 28, 2015
Web-appendix Figure 1: RMNCH Dashboard single country visualization
Web-appendix Figure 2: RMNCH Dashboard - Frequency Chart Performance by Commodity
Web-appendix Figure 3: RMNCH Dashboard - Multi-country Grid
Web-appendix Figure 4: RMNCH Dashboard - Multi-country Map