Impact team last mile distribution of contraceptives in nigeria (2019-2020)

December 2020
Project Implementation Report:
Last-Mile Distribution of
Contraceptives in Nigeria
through the IMPACT Team Model
(January 2019 – October 2020)

Contributors:
Joachim Chijide
Amaka Anene
Stephanie Joyce
Miranda Buba Gyanggyang
Aigbe Eromon
Project Implementation Report: Last-Mile Distribution of Contraceptives in Nigeria through the IMPACT Team Model (January 2019 – October 2020)
iii

Table of Contents
iv
EXECUTIVE SUMMARY 1
ListofFigures v
ACRONYMS viii
4.0. LESSONS LEARNEDAND GENERALRECOMMENDATIONS 90
3.4. BenueState 19
3.15. KatsinaState 72
3.11. YobeState 49
3.14. Cross RiverState 60
3.9. Ondo State 39
3.16. KanoState 77
3.14. Kaduna State 68
2.0. THEIMPACTTEAMSTRATEGY 4
3.1. Abia State 9
3.8. Ogun State 34
3.13. BornoState 55
1.0 BACKGROUND 2
3.6. GombeState 24
3.10. Lagos State 44
3.17. TarabaState 81
5.0. CONCLUSION 91
3.7. Imo State 29
3.0. IMPLEMENTATION 8
3.2. Adamawa State 14
3.15. JigawaState 63
3.12. SCALE-UPOFIMPACTTEAMMEETINGS 54
3.18. ZamfaraState 86
6.0. ANNEX 92

List of Figures
v
Figure5b: DataPlacematforAbiaState:January-February2019
Figure7a: Aggregate Stockout Rate and Reporting Performance for Adamawa State: January
2019 toOctober2020
Figure7b: DataPlacematforAdamawaState:January-February2019
Figure7c: DataPlacematforAdamawaState:September-October2020
Figure11: SupportiveSupervisionandLast-mileDistributiontoHealthFacilitiesinBenueState
Figure5c: DataPlacematforAbiaState:September-October2020
Figure2: Data Placemat Used to Inform IMPACT Team Performance Review Meeting inAbia
State(May/June2020)
Figure5a: AggregateStockoutandReportingRates:January2019 toOctober2020
Figure1: Flow of Information and Commodities through the Contraceptives Logistics
ManagementSysteminNigeria
Figure14: Supportive Supervision and Last-mile Distribution to Health Facilities in Gombe
State
Figure3: Data Placemat (LGA) Used to Inform IMPACT Team Performance Review Meeting
inYobeState(May/June2020)
Figure4: Focus StatesforImplementationofIMPACTTeamModel:January–December2020
Figure6: SupportiveSupervisionandLast-MileDistributiontoHealthFacilitiesinAbiaState
Figure8: Supportive Supervision and Last-Mile Distribution to Health Facilities in Adamawa
State
Figure9: Adamawa State IMPACT team and LMD review meeting at the State Hospitals
ManagementBoard
Figure10a: Aggregate Stockout and Reporting Rate for Benue state: January 2019 to October
2020
Figure10b: DataPlacematforBenueState:January-February2019
Figure10c: DataPlacematforBenueState:September-October2020
Figure13a: Aggregate Stockout and Reporting Performance for Gombe State: January 2019 to
October2020
Figure13b: DataPlacematforGombeState:January-February2019
Figure12: Consultant from NPSCMP providing guidance to MCH Coordinators on how to ﬁll
out proof of delivery forms during distribution and supportive supervision visits in
BenueState
Figure13c: DataPlacematforGombeState:September–October2020
Figure 15: Loading consumable kits procured by UNFPA for distribution to health facilities in
NafadaLGA, GombeState

vi
Figure16b: DataPlacematforImoState:January-February2019
Figure16a: Aggregate Stockout and Reporting Performance for Imo State: January 2019 to
October2020
Figure18b: DataPlacematforOgun State:January-February2019
Figure21a: ReportingPerformancefor Ondo State:January2019 toDecember2019
Figure16c: DataPlacematforImoState:September–October2020
Figure21b: DataPlacematforOndo State:January-February2019
Figure19: SupportiveSupervisionandLast-mileDistributiontoHealthFacilitiesinOgun State
Figure21c: DataPlacematforOndo State:November-December2019
Figure18c: DataPlacematforOgun State:November-December2019
Figure17: SupportiveSupervisionandLast-MileDistributiontoHealthFacilitiesinImoState
Figure18a: Aggregate Stockout and Reporting Performance for Ogun State: January 2019 to
December2019
Figure20: Ogun State IMPACT team meeting with Director, Reproductive Health Division,
FMOH atSMOH Ogun State
Figure922: Ondo StateIMPACTTeamMeetingatSPHCDA,Akure
Figure23: SupportiveSupervisionandLast-MileDistributiontoHealthFacilitiesinOndo State
Figure24a: Aggregate Stockout and Reporting Performance for Lagos State: January 2019 to
December2019
Figure28a: Aggregate Stockout and Reporting Performance for Borno State: January to October
2020
Figure24b: DataPlacematforLagosState:January-February2019
Figure31: Supportive Supervision and Last-Mile Distribution to Health Facilities in Jigawa
State
Figure26b: DataPlacematforYobeState:January-February2019
Figure27: SupportiveSupervisionandLast-MileDistributiontoHealthFacilitiesinYobeState
Figure30c: DataPlacematforJigawaState:September-October2020
Figure29: Supportive supervision and Replenishment Visit at Facility in Maiduguri Municipal
Council
Figure30b: DataPlacematforJigawaState:January-February2020
Figure25: SupportiveSupervisionandLast-MileDistributiontoHealthFacilitiesinLagosState
Figure26a: Aggregate Stockout and Reporting Performance for Yobe State: January 2019 to
October2020
Figure28c: DataPlacematforBornoState:September-October2020
Figure28b: DataPlacematforBornoState:January-February2020
Figure24c: DataPlacematforLagosState:November-December2019
Figure30a: Aggregate Stockout and Reporting Performance for Jigawa State: January to October
2020
Figure26c: DataPlacematforYobeState:September-October2020

vii
Figure34: DeliveryofFPCommoditiesTo LGABYTHEStateTeam
Figure33c: DataPlacematforKatsinaState:September-October2020
Figure35a: Aggregate Stockout and Reporting Performance for Kano State: January to October
2020
Figure32a: Aggregate Stockout and Reporting Performance for Kaduna State: January to
October2020
Figure35b: DataPlacematforKanoState:January-February2020
Figure36a: ReportingPerformanceforTarabaState:JanuarytoOctober2020
Figure36c: DataPlacematforTarabaState:September-October2020
Figure38b: DataPlacematforZamfaraState:January-February2020
Figure35c: DataPlacematforKanoState:September-October2020
Figure38c: DataPlacematforZamfaraState:July-August 2020
Figure33a: Aggregate Stockout and Reporting Performance for Katsina State: January to October
2020
Figure33b: DataPlacematforKatsinaState:January-February2020
Figure37: MCH Coordinator for Ibi LGA travelling by canoe to pick up FP commodities from
theTarabaStatecontraceptivestore
Figure32c: DataPlacematforKadunaState:September-October2020
Figure36b: DataPlacematforTarabaState:January-February2020
Figure38a: ReportingPerformancefor ZamfaraState:JanuarytoAugust 2020
Figure32b: DataPlacematforKadunaState:January-February2020

ACRONYMS
viii
FCDO UnitedKingdom's Foreign,CommonwealthandDevelopmentOﬃce
FMOH FederalMinistryofHealth
HLMIS healthlogisticsmanagementinformationsystem
LARC long-actingreversiblecontraceptives
LGA LocalGovernmentArea
CLMS ContraceptiveLogisticsManagementSystem
FP familyplanning
LMCU LogisticsManagementCoordinatingUnit
RIRF RequisitionIssue andReportForm
SDP servicedeliverypoint
UNFPA UnitedNationsPopulationFund
USAID U.S.AgencyforInternationalDevelopment
NPSCMP NationalProductSupplyChainManagementProgram
LMD last-miledistribution
OJT on-the-jobtraining
MCH maternalandchildhealth
NHLMIS NigeriaHealthLogisticsManagementInformationSystem
JSI John Snow,Inc.

In Nigeria, the United Nations Population Fund (UNFPA) and the United Kingdom's Foreign,
Commonwealth and Development Office (FCDO) provided funding for last mile distribution of
FPcommodities and performance improvement in seventeen (17) states between 2019 and 2020,
usinganadaptationofJSI's IMPACTteammodel.
Following the implementation of the IMPACT Team model, the list of health facilities on the
NHLMIS has been updated to remove duplications, displacements and reflect addition of active
sites offering FP services. As a result, the number of health facilities on the NHLMIS increased
from 5187 to 6073 in fourteen states, reflecting a realistic representation of health facilities
offering FP services in the supported states. Average reporting rates in the supported states
improved from 77% to 88%, with reporting rates in ten states exceeding ninety percent in the last
quarter of 2020. Stock availability in the health facilities also improved from 71% to 74%, with
last mile distributions contributing to an increase in Couple Years of Protection (CYP) from
1,397,967 to 2,031,826 in the supported states. Improved commodities at the health facilities led
to an estimated 3,414 maternal deaths averted and a total cost savings of US$ 68,007,736.11
withintheimplementationperiod.
A critical challenge to program implementation was the limited number of MCH Coordinators
who have been trained on CLMS as majority of the FP workforce at the LGA and facility level
have an insufficient understanding of logistics data for making informed decisions. This training
would improve data quality and inventory management across all levels of the supply chain in the
state. In addition, routine supportive supervision by the state FP and LMCU units would
strengthen the capacity of MCH Coordinators to perform their oversight functions and to transfer
theirknowledgetoimprovecommoditysecurityathealthfacilities.
Bi-monthly supply chain performance review meetings were conducted at the state level, using
data placemats derived from the Nigeria Health Logistics Management Information System
(NHLMIS). These meetings were also used to plan for last mile distribution of FP commodities
which are delivered to the health facilities by the MCH Coordinators during supportive
supervision visits. Due to restrictions on travel and public gatherings imposed as a consequence
of the COVID-19 pandemic, virtual meetings using Zoom and WhatsApp groups were set up for
each state where relevant stakeholders could meet to review the stock situation at multiple levels
andplanfordistributions,whichwereconductedduringsupportivesupervisionvisits.
EXECUTIVE SUMMARY
1

The NHLMIS allows key supply chain performance indicators to be tracked across five health
programs, include the Family Planning program. These indicators include reporting rates,
stockout rates and data quality. In addition to the logistics data entered into the NHLMIS, there is
a function for indicating the quantity of each commodity required to top up health facilities to
The Federal Ministry of Health (FMOH) in Nigeria and global development partners like the
United Nations Population Fund (UNFPA), the United States Agency for International
Development (USAID), the Global Fund to Fight AIDS, Tuberculosis and Malaria, and the
United Kingdom's Foreign, Commonwealth and Development Office (FCDO) have made
significant investments towards building the country's health logistics management information
systems (HLMIS) to improve supply chain data visibility and use across priority health programs.
For the Contraceptives Logistics Management System (CLMS), essential logistics data were
generated at health facilities and transmitted to higher levels at regular intervals. These reports
were used to inform decisions on re-supply, quantification, and procurement of contraceptive
commodities. The CLMS in Nigeria has operated through a predominantly paper-based logistics
management information system. According to this system, service providers are required to fill
out Requisition, Issue and Report Forms (RIRFs), which they submitted to the Maternal and
Child Health Coordinator (MCH) at their Local GovernmentArea (LGA) every 2 months. In turn,
MCH Coordinators filled out quarterly (every 3 months) RIRFs for the LGAlevel and submitted
them to the state's Family Planning Coordinator. Thrice a year (every 4 months), state RIRFs are
submitted to the FMOH, where the data were used to determine quantities to be delivered to states
storesduringnationaldistribution(Figure1).
Figure 1: Flow of Information and Commodities through the Contraceptives Logistics
ManagementSysteminNigeria
1.0 BACKGROUND
Federal Ministry of Health
State Ministry of Health/State Primary
Healthcare Development Board
Local Government Healthcare
Development Board
LGA RIRFs
State RIRFs State RIRFs
Commodities
Commodities
Regional warehouse
(used by GHSC-PSM project
funded byUSAID
Commodities
Central Contraceptive Warehouse
Facility RIRFs
Health Facilities
2

Last-MileDistribution ofFPCommodities
maximum inventory order levels. These quantities can be exported to inform distribution
planning.Table1shows theperformancebenchmarksmarkedforeachperformanceindicator
Table1: BenchmarkLevelsforPerformanceIndicators
Supply chain performance for each state can be viewed on a dashboard, which is accessible
globally. However, data availability alone is not enough for supply chains to perform and get
critical reproductive health (RH) commodities into clients' hands. In addition to building robust
information systems, ensuring commodity security, and improving supply chain performance
requires creation of a “data culture” by training and empowering staff to analyze and use data for
decision-making. For the reporting cycle in July 2018, only 56% of health facilities offering FP
services had successfully submitted their reports on the NHLMIS, and even then, the reporting
rate for eleven states was below 35%. Supply chain managers continued to have limited access to
timely and quality logistics data from health facilities, which impeded effective supply chain
decision-making.
In the past, FP commodities were delivered to health facilities by service providers following
review and re-supply meetings, and in few states, through the direct data and information capture
models of last-mile delivery (LMD). Recently, FMOH through the NPSCMP recommended an
integrated last-mile distribution of commodities across health programs; but this is only being
implemented in few states. Funding constraints continue to challenge models for last-mile
distribution, and states are not able to distribute products on a routine basis, which results in
periodic stockout situations at health facilities even though, sufficient stock may exist at higher
levels. Ad-hoc or non-existent distribution mechanisms in these states have contributed to high
stockout rates of FP commodities at service delivery points (SDPs) (30%, stockout, according to
the 2018 UNFPAsupplies survey, and 48% according to the routine data NHLMIS from the July
2018 reporting cycle). The disconnect between the reporting and resupply systems has de-
motivated health facility service providers to submit their RIRFs. For example, in Borno state, at
least five LGAs have failed to submit reports to the NHLMIS platform since June 2019; and in
Kogi State the reporting rate dropped from 94% in May-June 2018 to 49% in September-October
2020. While the FMOH and stakeholders work to implement a more sustainable system for
integrated last-mile distribution of all public health commodities, an interim solution was needed
toensureclientshaveuninterruptedaccesstothecontraceptivemethodstheyneed.
Performance Benchmark Critical Alert Good
Aggregate Stock Reporting Rate < 70% 70% - 90% >90%
Flagged Reports >50% 20% - 50% 0 – 20%
Stockout Rates >10% 5% - 10% 0-5%
3

At the end of each reporting period, the data entered into the NHLMIS for that period are analyzed
and exported to generate data placemats (Figure 2, Figure 3). These data placemats contain
simple, easy-to-understand information on the reporting rate, stockout rate, and stock status of FP
commoditiesatthestate,LGA, andhealthfacilitylevels.
The key members of the IMPACT team include representatives from the Family Health
Department of FMOH, state Family Planning Coordinators, state LMCU Coordinators, and
MCH Coordinators overseeing FP activities in each LGA in the states implementing the
approach. Other members may include monitoring and evaluation (M&E) oﬃcers, logistics
oﬃcers, and other stakeholders from State Ministry of Health (SMOH) or State Primary Health
CareDevelopmentBoard.
b. DataAnalysis and DevelopmentofData PlacematsforPerformanceReview
The Information Mobilized for Performance Analysis and Continuous Transformation
(IMPACT) team strategy is a people-centered approach to holistically strengthening the supply
chain. The model is based on continuous performance review by a team of stakeholders from
national, state, and LGA levels, with the shared goal of improving product availability and a
collectiveresponsibilitytoidentifyandimplementsolutionstosupplychainproblems.
2.0. THEIMPACTTEAMSTRATEGY
The IMPACT teams support service providers to meet reporting timelines every two months. At
the LGAlevel, MCH Coordinators review the reports before they are entered into the NHLMIS or
sent to the state LMCU.At the state LMCU, the reports undergo another review before entry into
the NHLMIS. This provides a good opportunity to identify service providers who need capacity
buildingso thattheycangeneratereportsthatcontaingoodquality,reliabledata.
a. ReportCollection,Review,andTransmission
TheIMPACTTeam
IMPACTTeamActivities
4

Figure3: Data Placemat (LGA) Used to Inform IMPACT Team Performance Review Meeting in
YobeState(May-June 2020)
Figure 2: Data Placemat Used to Inform IMPACT Team Performance Review Meeting inAbia
State(May-June2020)
ABIA
FAMILY PLANNING SUPPLY CHAIN PERFORMANCE
MAY-JUNE 2020
POTISKUM
FAMILY PLANNING SUPPLY CHAIN PERFORMANCE
MAY-JUNE 2020
5

During IMPACT team meetings,
participants compare order quantities
from health facilities with the quantity
of usable stock available at the state
store. Where commodities can fill out
orders in full, team members decide to
re-supply based on request; but where
there are shortages at the state store, the
team decides to ration commodities or
place emergency orders. The IMPACT
team also agrees on how to deliver
commodities to health facilities during
the IMPACT team meetings (see Box 1
ondistributionmodels).
e. Distribution Planning
c. Stock StatusAssessments
FP coordinators conduct a physical count of the FP commodities at the state stores. These counts
are used to generate the most up-to-date stock status information to be used at the supply chain
performancereviewmeetings.
d. Supply Chain PerformanceReviewMeetings
IMPACTteams meet at the end of the reporting period and use a quality improvement approach to
interpret data, prioritize problems, agree on solutions, and take actions to improve performance.
The state teams make invaluable contributions based on their knowledge of local context,
functional health facilities, and the capacity of the health workforce at lower levels. For instance,
MCH Coordinators know which service providers are trained on long-acting reversible
contraceptive methods (LARCs) and therefore, would be able to identify if a stockout of such
products was due to possible increase in consumption at the health facility or reported in error. In
other instances, MCH Coordinators are able to identify errors on the health facility list reflected
on the NHLMIS. These errors affect reporting rates; so the IMPACT team collaborates with
NPSCMPtoensuresuchdiscrepanciesarerectifiedpromptly.
In 2019, face-to-face meetings—including capacity building as necessary—were conducted at
bi-monthly intervals. These meetings provided opportunities to strengthen capacity for
mentoring and supportive supervision, calculate stock status, and make decisions to improve
commodityavailabilityandminimizewastageandexpiriesathealthfacilityandLGAlevels.
In 2020, following the onset of the COVID -19 pandemic, restrictions were placed on travel and
public gatherings, hindering in-person meetings. Instead, IMPACT team and LMD review
meetings were held virtually, using the Zoom meetings where participants shared data placemats.
Key resolutions and observations were communicated to lower levels using LMD coordination
groups on WhatsApp. These virtual meetings expanded representation from key stakeholders,
especially those from higher levels who frequently could not travel to the meetings because of
conflictingschedules.
Box 1.
Several models have been used to deliver contraceptive
commodities to health facilities in Nigeria.
Review and re-supply meetings are routine meetings between
service providers, MCH Coordinators, and State FP Coordinator.
Participants review stock-keeping records and daily consumption
records at these meetings and provide is provided for delivery to
health facilities.
The Direct Delivery and Information Capture model was piloted
as an automated, vendor-managed inventory model in which a
delivery team made routine visits to health facilities. The team
checked physical inventory, stock keeping, and consumption
records, provided replenishment, or retrieved excess quantities
during the time of the visits.
Integrated distribution of commodities is an example of the
review and direct delivery model, in last-mile distributions are
provided to health facilities based on LMD orders, following
review of records.
6
Last-Mile Distribution of Contraceptive Commodities
in Nigeria

In 2019, the MagPi digital application was installed on the personal mobile smartphones of MCH
Coordinators. The forms contained information on physical stock available at health facilities,
storage conditions and availability of stock-keeping records. This application enabled the
supervisors to log in their findings, which were visible at higher levels in real time, and to record
the facility's GPS location support Service providers or authorities higher up the supply chain
filledoutfeedbackforms,whichservedasthebasisforreimbursementforthevisits.
In 2020, IMPACT amended the feedback forms to contain more information on the quantities of
commodities delivered or retrieved from the health facilities, their batch numbers, and expiry
dates.
f. Supportive Supervision and Last-MileDistribution
Supportive supervision visits are made to each health facility following each supply chain
performance review meeting. Adding on a distribution, mentoring, and supportive supervision
component to the IMPACT team's performance review enables supervisors to address challenges
due to inconsistent distribution mechanisms and human resource capacity to manage health
supplies at the last mile. The MCH Coordinators receive the necessary tools to document their
findings duringthesupportivesupervisionvisits.
7

With funding from UNFPA, John Snow, Inc. (JSI) implemented the IMPACT team approach in
nine states in 2019: Abia, Adamawa, Benue, Gombe, Imo, Lagos, Ogun, Ondo, and Yobe. In
2020, UNFPA continued to provide funding for implementation of the IMPACT team model in
six states: Abia, Adamawa, Benue, Gombe, Imo, and Yobe; and included Cross River State in
August 2020. With LAFYIAproject, FCDO provided funding through UNFPAand expanded the
IMPACT team model to include seven states (Borno, Jigawa, Kaduna, Kano, Katsina, Taraba,
and Zamfara) (Figure 4). The sections that follow describe IMPACT implementation in 2019 and
2020,includingtheadditionalsevenstates.
Figure4:Focus StatesforImplementationofIMPACTTeamModel:January–December2020
3.0. IMPLEMENTATION
8

ReportingPerformance
Maternaldeath averted(2019-2020):80
Findings from each supportive supervision visit were documented using the Magpi digital
application, which contained a checklist of the questions on storage conditions, observations on
stock-keeping tools and practices, and commodity availability. Upon completion of the visit to
each facility, the data were uploaded to a web-based server. This improved data visibility for
stakeholders at higher levels and facilitated insight to track the progress of the supportive
supervision visits. Where mobile smartphones were not available or there was no internet access,
apaper-basedversionofthechecklistwas usedtodocumentfindings fromthevisit.
CommodityAvailability
In 2019, MCH Coordinators picked up commodities for delivery to health facilities at the end of
each IMPACTteam meeting. Quantities were pre-determined based on requisitions on the RIRFs
and available quantities at the state store. The MCH Coordinators took the commodities to each
LGAanddeliveredthemtohealthfacilitiesduringsupportivesupervisionvisits.
CYP(2019)distributed –21,711
Last-MileDistribution and Supportive Supervision
In January/February 2019, the NHLMIS reflected that there were five hundred and fifty-seven
(557) health facilities offering Family Planning services in Abia state. During this period, only
slightly more than half of the health facilities submitted reports (51%). After two IMPACT team
and LMD review meetings, reporting rates surged to 100%. This reporting rate has remained
consistenttillthetimeofthispublication.
Location:SouthEast,Nigeria
1
Population:3,727,347(2016)
3.1.Abia State
Totalcostsavings -US$ 1,717,991.36
NumberofLocalGovernmentAreas:Seventeen(17)
PeriodofImplementation:January2019todate
In 2019, the aggregate stockout rate reported by health facilities in Abia state was 51%.
Consumables kit and cycle beads accounted for the highest proportion of stockout within this
period. By May/June 2019, however, last-mile distributions had commenced and stockout rates
reduced to 3%. Stockout rates have continued to fall within 10% for subsequent periods,
indicating availability of contraceptive commodities in at least 90% of health facilities over the
courseofimplementation(seeFigures5a,5b,5c).
1
NigeriaData PortalAvailableat:https://nigeria.opendataforafrica.org/ifpbxbd/state-population-2006
9

In 2020, the global COVID-19 pandemic disrupted supply chain activities. Restrictions on public
gatheratings made in-person IMPACTteam meetings impossible, and travel restrictions hindered
intra-state travels, making supportive supervision visits diﬃcult. From March to April 2020,
IMPACT teams held meetings using the Zoom virtual platform. Stakeholders from the national
and state levels met after each reporting period to review supply chain performance and plan for
last-mile distribution, and used WhatsApp groups to share data placemats for the LGA level and
key resolutions from the meetings with MCH Coordinators. Following COVID prevention
guidelines from the government and the World Health Organization (WHO), the MCH
Coordinators travelled to the state store on appointed dates to pick up commodities for
distribution to health facilities, and used the occasion of supportive supervision visits to deliver
commodities to each health facility. Quantities delivered to each health facility were documented
on proof of delivery forms, which were also used to track batch numbers and expiry dates, and to
accountforcommoditiesretrieved(Figure6).
Figure5a:AggregateStockout and ReportingRates: January 2019toOctober2020
10

Figure5c:Data PlacematforAbia State:September-October2020
Figure5b: Data PlacematforAbia State:January-February2019
11

The data placemats were used to identify health facilities that did not submit reports. In remote
areas, MCH Coordinators were advised to employ the WhatsApp platform to receive reports, as
had been done in Katsina State to improve their reporting rates. During supportive supervision
visits to remote facilities, re-supply quantities were adjusted to include buffer stock, and service
Figure6: Supportive Supervision and Last-Mile Distribution to Health Facilities in
Abia State
Due to the COVID-19 pandemic, in-person supply chain review meetings could not take place as
planned in April 2020. This was a concern, as these meetings facilitate engagement with
stakeholders at the state and LGA levels, especially for the MCH Coordinators, who are well-
positioned to provide feedback on the reasons for low reporting rates or lack of commodities at
health facilities. Additionally, MCH Coordinators conduct last-mile distribution during
supportivesupervisionvisitsandthesemeetingsprovideagoodavenuefortheirfeedback.
Challenges
StrategiesImplementedtoAddress Challenges
During seasonal rains, there is limited access to health facilities in some areas of the state, such as
Arochukwu LGA. This lack of accessibility usually affects report submission and replenishment
visits,leadingtopoorreportingandperiodsofstockout.
Capacity-building sessions were introduced into the IMPACT team and LMD review meetings,
resulting in a gradual improvement in data quality. From March 2020, however, data quality
issues began to increase again. Since this period coincides with the emergence and control of
COVID-19 in Nigeria, the decline in data quality may be attributed to reports prepared in a hurry,
and to the interruption of the face-to-face meetings with MCH Coordinators, who could have
reinforced good reporting practices. The in-person meetings resumed in November, after the
September-October review period, providing an opportunity for dialogue and capacity building
withMCH Coordinatorsandotherstakeholderspresentatthemeeting.
Lack of capacity to fill out bimonthly reports is reflected in the proportion of reports flagged on
the NHLMIS in each period. In 2019, the percentage of flagged reports fromAbia state fluctuated
between 10% (Jan-Feb), which is considered to be good, to 24% (July-August). This indicated
capacity gaps both in filling out the reports and in reviewing them before transmission to the
nationallevel.
12

providers were advised on procedures for placing emergency orders. To sustain high reporting
rates during the COVID-19 pandemic, members of the LGAFPTask Force inAbia state collected
reports from health facilities and submitted them to the MCH Coordinators for transmission to the
NHLMIS.
Recommendations
The IMPACT team held virtual, rather than in-person, meetings with national and state
stakeholders, and conducted data-driven supply chain review, prioritizing reporting rates, stock
status, and commodity availability.The meetings were also used to review stock status at the state
store and distribution planning. On a broader level, these discussions were facilitated on a
WhatsApp group created for the state, and data placemats were shared for the LGA level
following each reporting period. In addition to reviewing performance, the group provided
updatesonlast-miledistributionandsupportivesupervision.
Abia State has improved commodity availability through routine supportive supervision visits,
which were used to deliver commodities and provide mentorship and on-the-job training. These
routine visits resulted in improvements in data quality and reporting rates, which in turn
supported commodity availability. However, sustaining these improvements will require regular
performance review meetings and capacity-building, especially at the LGA level. Sustaining
these meetings will enable MCH Coordinators to advance their oversight functions and transfer
knowledgetoimprovecommoditysecurityathealthfacilities.
13

NumberofLocalGovernmentAreas:Twenty-one(21)
In Adamawa state, the NHLMIS reported
that 329 health facilities offered FP services
in January/February 2019. During this
period, 63% of facility reports were
transmitted to the NHLMIS.At the IMPACT
team meeting, MCH Coordinators identified
some mistakes on the health facility list—for
example, duplicate facility names on the list,
facilities listed under the wrong LGA, and
facilities missing from the list (Box 2). By
the following period, the IMPACT team
reviewed an updated list of 381 functional
health facilities, 76% of which had
transmitted reports to the NHLMIS. In July-August 2019, further review of the health facility list
ledtoanupdateontheNHLMIS toreflect521functionalhealthfacilities.
Location:NorthEast,Nigeria
Between January and August 2019, the aggregate stockout rate reported by health facilities in
Adamawastateaveraged46%.An analysisof thereports indicatesthatSayanaPress, cyclebeads,
and IUCDs accounted for the highest proportion of stockout within these periods. By May 2019,
last-mile distributions had commenced, but the high stockout rates for these commodities
3.2. Adamawa State
Totalcostsavings -US$7,807,672.33
PeriodofImplementation:January2019todate.
CYP(2019)distributed–101,431
Maternaldeath averted(2019-2020):393
2
Population:4,248,436(2016)
The updated health facility lists are usually compiled by the IMPACT team (MCH Coordinators
and LMCU Coordinators), and then the list is sent to NPSCMP to effect the changes. With time,
the reporting rates and other indicators reflected on the NHLMIS began to reflect a more accurate
pictureofthesituationatthestatelevel.
2
NigeriaDataPortalAvailableat:https://nigeria.opendataforafrica.org/ifpbxbd/state-population-2006
Box 2.
IMPACT team meetings conducted continuous review of
the health facility list to:
· Identify duplicated, displaced, and non-functional health
facilities for removal from the list, as well as new or
omitted functional health facilities to add to the list
· Guide report collection and tracking of reporting rates
· Inform distribution planning and guide last-mile
distribution
Box 2. Facility List Review
14

InAdamawa,proceduresforsupportivesupervisionandLMD weresimilartootherstates:
· In 2019, commodity quantities were determined based on requisitions on the RIRFs and
available quantities at the state store. MCH Coordinators picked up the commodities at the
end of each IMPACT team meeting, transported them to each LGA, and delivered them to
their assigned health facilities during supportive supervision visits. They used the Magpi
digital application to document findings, including observations on storage conditions,
stock-keeping tools and practices, and commodity availability (Figure 8). Where mobile
smartphones were not available or there was no internet access, the MCH Coordinators
used a paper-based version of the checklist. Upon completion of the visit to each facility,
the data were uploaded to a web-based server, which enabled visibility on facility
performanceathigherlevels.
persisted. Feedback from the supportive supervision and last-mile distribution visits showed that
the stockout rates reflected on the NHLMIS stemmed from data quality issues—specifically,
errors in entering commodities that facilities did not classify as being stocked out. By September-
October 2019, after on-the-job mentoring during supportive supervision visits, stockout rates
diminished to 17%. From then on, stockout rates continued to remain below 20%, indicating
availabilityofcontraceptivecommoditiesinatleast80%ofhealthfacilities(Figures7a,7b,7c).
· In 2020, the global COVID-19 pandemic disrupted supply chain activities made in-person
IMPACT team meetings impossible, and hindered intra-state travel and by extension
made supportive supervision visits difficult. From March-April 2020, IMPACT team
meetings were held via Zoom. Stakeholders from the national and state levels met after
each reporting period to review supply chain performance and plan for last-mile
distribution; and shared data placemats for the LGA level and key resolutions from the
meetings with MCH Coordinators using WhatsApp groups. The MCH Coordinators
travelled to the state store on appointed dates to pick up commodities for distribution to
health facilities. Transportation of FPcommodities and supportive supervision visits took
placealongsidethepublichealthresponsetoCOVID-19 atthecommunitylevel.
Supportive Supervision and Last-MileDistribution
Figure7a: Aggregate Stockout Rate and Reporting Performance for Adamawa State:
January 2019toOctober2020
15

Figure7b: Data PlacematforAdamawa State:January-February2019
Figure7c:Data PlacematforAdamawa State:September-October2020
16

· Holding virtual meetings usingWhatsApp with state and national stakeholders, beginning
in May 2020, to review supply chain data, reporting rates, and commodity availability;
Some facilities in Mubi North and Mubi South LGAS are poorly accessible due to security
challenges. In some other LGAs, access to health facilities is restricted by flooding due to
seasonal rains. This lack of accessibility usually affects report submission and replenishment
visits,leadingtopoorreportingandperiodsofstockout.
Adamawa State
Challenges
In general, the reports transmitted to the NHLMIS from Adamawa State have been of good
quality. This is a reflection of the competencies at the state level, from where the reports are
reviewed and entered. For the November-December review period in 2019, however, entries
were made at the LGA level, of which 26% were flagged for data quality issues. This was an
indication of gaps in the ability of MCH Coordinators to adequately review reports submitted by
healthfacilitiesatthislevel.
As in other states, IMPACT teams implemented these measures to improve data quality,
strengthenLMD, andaddressrestrictionsensuingfromtheCOVID-19 pandemic:
· Introducing capacity building into the IMPACT team and LMD review meetings to
improve MCH Coordinators' review of the reports before submission to the state level for
entryintotheNHLMIS.
As inAbia State, in-person supply chain review meetings could not take place inApril 2020, due
to the COVIC-19 virus, which impeded stakeholder engagement and affected LMD by MCH
Coordinators. Also, in October 2020, the FP store was vandalized alongside other offices and
structures at the State Primary Healthcare Development Board.This resulted in significant loss of
FPcommodities,whichwerestoredinthepremises.
· Using data placemats to identify facilities that did not submit reports, and advising MCH
CoordinatorstouseWhatsApptoreceivereports.
17

Recommendations
Figure9: Adamawa State IMPACT team and LMD review meeting at the State
HospitalsManagementBoard
assess stock status and distribution planning at the state store; and provide updates on
LMD andsupportivesupervision.
Adamawa State has improved commodity availability through routine supportive supervision
visits, providing opportunities for mentorship and on-the-job training. These routine visits
resulted in improvements in data quality and reporting rates, which in turn supported commodity
availability. However, sustaining these improvements will require regular performance review
meetings and capacity-building, especially at the LGA level. Sustaining these meetings will
enable MCH Coordinators to advance their oversight functions and transfer knowledge to
improvecommoditysecurityathealthfacilities.
18
Photo submitted by Aigbe Eromon, John Snow Inc.

3.4. BenueState
Location:NorthCentral,Nigeria
3
Population:5,741,815(2016)
Maternaldeaths averted(2019-2020)–306
According to the NHLMIS, 375 health facilities oﬀered FP services in Benue State in
January/February 2019. At this time, the reporting rate was 67%. In the following reporting
periods, there was only a slight improvement in reporting rates, which averaged 69%. The poor
reporting rate was attributed to errors on the health facility list, security challenges, and late
reporting in some LGAs. By May-June 2020, the IMPACT team had reviewed the health facility
list to include 419 functional health facilities, and had implemented more rigorous report
collectionmechanisms,so thatthereportingrateincreasedto97%.
PeriodofImplementation–January2019todate
CYP(2019)distributed–93,738
Totalcostsavings- US$ 6,087,122.66
NumberofLocalGovernmentAreas:Twenty-three(23)
The aggregate stockout rate was 47% for the FP program in Benue State in January-February
2019. Feedback from the supportive supervision and last-mile distribution visits showed that the
stockout rates reﬂected data quality issues, including data entry errors when facilities did not
classify commodities as being stocked out. The IMPACT team incorporated capacity building
during meetings to address capacity gaps at the LGAlevel, and addressed other data quality issues
though on-the-job (OTJ) training during supportive supervision visits. This resulted in a steady
decline in stockout rates in health facilities across the state. Between January and April 2020,
there was a delay in national distribution, exacerbated by the COVID-19 pandemic, leading to
low stock levels at the state store. By May 2020, stock replenishment had begun, but stock
availabilityathealthfacilitiesremainedbelow70%(Figures10a,10b,10c).
3
19

Figure10a: Aggregate Stockout and Reporting Rate for Benue state: January 2019 to
October2020
Supportive Supervision and Last-mileDistribution
InBenueState,proceduresforsupportivesupervisionandLMD weresimilartootherstates:
20

Figure10b: Data PlacematforBenueState:January-February2019
Figure10c:Data PlacematforBenueState:September-October2020
21

Challenges
Some are poorly accessible due to security challenges in some parts of Benue state, such asAgatu
LGA. In some other LGAs, access to health facilities is restricted by flooding due to seasonal
rains. This lack of accessibility usually affects report submission and replenishment visits,
leadingtopoorreportingandperiodsofstockout.
· Introducing capaicity building into the IMPACT team and LMD review meetings to
entry into the NHLMIS. However, data quality problems persisted in Benue, suggesting a
need for more focused capacity building sessions with providers. The state consultant
from FMOH's National Product Supply Chain Program also provided guidance on using
Proof ofDeliveryformstoaccountforcommoditiesissued(Figure18).
In January/February 2019, the flagged reports (18%) for submitted RIRFs in Benue State was
considered good, when compared to the national performance benchmarks. In subsequent
periodshowever,dataqualityissues inthereportstranslatedtoanincreaseinflaggedreports.
Figure11: Supportive Supervision and Last-mile Distribution to Health Facilities in
BenueState
· Using data placemats to identify facilities that did not submit reports, which would
provide an accurate facility list to the FMOH, from which the NHLMS list could be
updated.
As in other states, in-person supply chain review meetings could not take place inApril 2020, due
to the COVID-19 virus, which impeded stakeholder engagement and affected LMD by MCH
Coordinators.
22

Recommendations
LMD andsupportivesupervision
Figure12: Consultant from NPSCMP providing guidance to MCH Coordinators on
how to ﬁll out proof of delivery forms during distribution and supportive
supervision visitsinBenueState
In addition to the capacity-building provided during IMPACT Team meetings, MCH
Coordinators and service providers would beneﬁt from training on CLMS. This training will
improve data quality and reporting performance, and will improve inventory management across
all levels of the supply chain in the state. In addition, routine supportive supervision to the LGA
level by the state LMCU would strengthen the capacity of MCH Coordinators to perform their
oversight functions and to transfer their knowledge to improve commodity security at health
facilities.
· Advising MCH Coordinators to use WhatsApp to receive reports. During supportive
supervision visits to remote areas, MCH Coordinators adjusted re-supply quantities and
advisedprovidersonproceduresforemergencyorders.
23
Photo submitted by Shaibu Adams Itopa, Benue State Consultant, NPSCMP via Benue State FP Coordination Group
on WhatsApp

3.6. GombeState
4
Population:3,256,962(2016)
CYPdistributed (2019)–33,721
NumberofLocalGovernmentAreas:Eleven(11)
There were 353 health facilities reported to be offering FPservices in Gombe State as of January-
February 2019. The reporting rate for the period was 68%, a poor rate attributed to late reporting
in some LGAs.With continuous review of supply chain performance and active report collection,
reportingratesimprovedoversubsequentperiods.
InGombeState,proceduresforsupportivesupervisionandLMD weresimilartootherstates:
Maternaldeath averted(2019-2020)–131
Totalcostsavings –US$2,602,886.73
In January-February 2019, over half of health facilities offering reproductive health services in
Gombe State were stocked out of FP commodities. Following two cycles of supportive
supervision and distribution visits, there was an improvement in commodity availability such that
by November-December 2019, aggregate stockout rates had declined to less than 15%. The
following year, stockout rate was 6% in January-February, but due to disruptions in supply chain
activities over the following months, stockout rates increased significantly. Noristerat, Implanon
and consumable kits contributed the highest proportion of stockouts in health facilities. With
funding from UNFPA, the state procured consumable kits which were distributed to health
facilitiesleveragingonsupportivesupervisionvisits(Figures13a,13b,13c).
4
24

Figure13a: Aggregate Stockout and Reporting Performance for Gombe State: January
2019toOctober2020
25

Figure13c:Data PlacematforGombeState:September–October2020
Figure13b: Data PlacematforGombeState:January-February2019
26

GombeState
Challenges
There were signiﬁcant issues with data quality in Gombe state. In March/April 2019, 24% of the
submitted RIRFs were ﬂagged for errors. These errors included mistakes in entering opening
balances, mathematical errors, and entering data for commodities not managed at health
facilities.According to reporting protocol, where a commodity is not in stock, a zero is entered for
that product. If the commodity is not being managed at that health facility—as may be the case for
long-term methods requiring administration by skilled workers—the entry for such a commodity
is supposed to be left blank. These data quality issues translated to exaggerated stockout data that
neededtobeaddressedduringIMPACTteammeetings.
As in other states, in-person supply chain review meetings could not take place inApril 2020 due
Coordinators.
entryintotheNHLMIS.
· Mentoring MCH Coordinators on how to input entries for commodities not managed at
health facilities; and advising them to provide seed-stock to health facilities that had not
been managing condoms and cycle beads. The MCH Coordinators provided guidance to
service providers to enable them to report on these commodities properly, resulting in a
decreaseintheaggregatestockoutrateforthestate(Figure15).
27

LMD andsupportivesupervision.
Recommendations
all levels of the supply chain in the state. In addition, routine supportive supervision to the LGA
level by the state LMCU would strengthen the capacity of MCH Coordinators to perform their
oversight functions and to transfer their knowledge to improve commodity security at health
facilities.
Figure15: Loading consumable kits procured by UNFPA for distribution to health
facilitiesinNafada LGA,GombeState
28
Photo submitted by Nwese Apu, Maternal and Child Health Coordinator, Nafada LGA in Gombe State,
via Gombe IMPACT Team on WhatsApp

Location:SouthEast,Nigeria
3.7. Imo State
NumberofLocalGovernmentAreas:Twenty–Seven(27)
Totalcostsavings -US$7,505,538.89
There were 129 health facilities reported to be offering FP services in Imo state as of January-
February 2019. The reporting rate for this period was 88%. The health facility list was revised to
remove duplications and errors and then omitted facilities were added to the list. By July-August
2019, a total of 123 health facilities were submitting reports through the NHLMIS. Since then,
reportingratesfortheFamilyPlanningprograminthestatehaveremainedabove95%.
Maternaldeath averted(2019-2020)-377
5
Population:5,408,756(2016)
In January-February 2019, 30% of health facilities offering reproductive health services in Imo
state were stocked out of FP commodities. With the implementaiton of supportive supervision
and distribuiton visits, commodity avaliablity improved significantly. By June, stockout rates had
declined to 16%, and in following review periods, commodity availability averaged 92% in
facilitiesreportingthroughtheNHLMIS (Figures16a,16b,16c).
InImoState,proceduresforsupportivesupervisionandLMD weresimilartootherstates:
5
29

Figure16a: Aggregate Stockout and Reporting Performance forImo State: January 2019
toOctober2020
30

Figure16b: Data PlacematforImo State:January-February2019
Figure16c:Data PlacematforImo State:September–October2020
31

Figure17: Supportive Supervision and Last-MileDistribution toHealthFacilitiesinImo State
Challenges
Some of the MCH Coordinators had not been trained on CLMS and had insufficient capacity to
understandlogisticsdatatomakeinformeddecisions.
As in other states, in-person supply chain review meetings could not take place inApril 2020, due to
the COVID-19 virus, which impeded stakeholder engagement and affected LMD by MCH
Coordinators.
· Introducing capacity building into the IMPACT team and LMD review meetings to improve
MCH Coordinators' review of the reports before submission to the state level for entry into the
NHLMIS.
In addition to the capacity-building provided during IMPACT Team meetings, MCH Coordinators
and service providers would benefit from training on CLMS. This training will improve data quality
and reporting performance, and will improve inventory management across all levels of the supply
· Holding virtual meetings using WhatsApp with state and national stakeholders, beginning in
May 2020, to review supply chain data, reporting rates, and commodity availability; assess
stock status and distribution planning at the state store; and provide updates on LMD and
supportivesupervision.
· Using data placemats to identify facilities that did not submit reports, and advising MCH
CoordinatorstouseWhatsApptoreceivereports.
Recommendations
As in other states, IMPACT teams implemented these measures to improve data quality, strengthen
LMD, andaddress restrictionsensuingfromtheCOVID-19 pandemic:
32

chain in the state. In addition, routine supportive supervision to the LGA level by the state LMCU
would strengthen the capacity of MCH Coordinators to perform their oversight functions and to
transfertheirknowledgetoimprovecommoditysecurityathealthfacilities.
33

3.8. Ogun State
Location:SouthWest,Nigeria
NumberofLocalGovernmentAreas:Twenty(20)
6
Population:5,217,716(2016)
Maternaldeath averted(2019)-152
Totalcostsavings –US$3,026,350
In 2019, there were 429 health facilities transmitting reports to the NHLMIS. The reporting rate
for this period was 88%. During IMPACT team meetings, assessments of supply chain
performance informed the revision of the health facility list. Duplications and errors were
corrected, and omitted health facilities were included on the list. By July 2019, 474 health
facilities were reﬂected on the NHLMIS. Reporting rates also improved and remained above
90%.
PeriodofImplementation–JanuarytoDecember2019
In January-February 2019, the stockout rates reported by 429 facilities was 23%. In the following
periods, the number of health facilities that submitted reports increased to 441(March-April
2019) and 468 (May-June 2019). Stockout rates for these periods was also 23%. In September-
October 2019, stockout rates increased to 30% as a result of additions to the health facility list on
the NHLMIS. By December 2019, the stockout rate reported by 474 health facilities had declined
to25%(Figures18a,18b,18c).
6
34

Figure18a: Aggregate Stockout and Reporting Performance for Ogun State: January
2019toDecember2019
35

Figure18c:Data PlacematforOgun State:November-December2019
Figure18b: Data PlacematforOgun State:January-February2019
36

In the states, commodity quantities were determined based on requisitions on the RIRFs and
available quantities at the state store. MCH Coordinators picked up the commodities at the end of
each IMPACTteam meeting, transported them to each LGA, and delivered them to their assigned
health facilities during supportive supervision visits. They used the Magpi digital application to
document findings, including observations on storage conditions, stock-keeping tools and
practices, and commodity availability (Figure 19).Where mobile smartphones were not available
or there was no internet access, the MCH Coordinators used a paper-based version of the
checklist. Upon completion of the visit to each facility, the data were uploaded to a web-based
server,whichenabledvisibilityonfacilityperformanceathigherlevels.
Ogun State
Challenges
In some LGAs, access to health facilities is restricted by flooding due to seasonal rains. This lack
of accessibility usually affects report submission and replenishment visits, leading to poor
reportingandperiodsofstockout.
There was consistent representation from FMOH and UNFPA at the IMPACT Team meetings in
The LMCU spearheaded capacity-building sessions which were incorporated into the IMPACT
team meetings to build skills on inventory management, calculating stock status and determining
how much to re-supply/retrieve from health facilities. With MCH Coordinators, the LMCU
reviewed mistakes on the submitted reports and provided guidance to prevent future mistakes.
Thisadditionhelpedtoimprovecommoditysupplyandpreventexpiriesandwastageatfacilities.
Some MCH Coordinators had not received CLMS training and did not understand logistics data
sufficientlytomakeinformedre-supplydecisionsorreviewreportsfromhealthfacilities.
37

Ogun state, which increased stakeholders' commitment to coordinate and conduct last-mile
distribution. The activity also increased overall improved understanding of the challenges
aﬀecting commodity availability at health facilities that need to be addressed at national level
(Figure20).
Recommendations
Since December 2019, Ogun state has adopted an alternative mechanism for last-mile
distribution for FP commodities. Nevertheless, MCH Coordinators and service providers would
beneﬁt from training on CLMS to improve data quality and reporting performance. Routine
supportive supervision by the State LMCU to the LGA levels would also improve oversight and
promotecommoditysecurityathealthfacilities.
Figure20: Ogun State IMPACT team meeting with Director, Reproductive Health
Division,FMOHatSMOHOgun State
38
Photo submitted by Miranda Buba Gyanggyang, JSI

NumberofLocalGovernmentAreas:Eighteen(18)
Maternaldeath averted–50
Totalcostsavings –US$ 996,726
3.9. Ondo State
7
Population:4,671,695(2016)
In January 2019, the NHLMIS reflected that there were 547 health facilities offering FP services
in Ondo state. The reporting rate for this period was 93%. Following an assessment of supply
chain performance, the health facility list was reviewed to 531 health facilities. With the deletion
of inactive health facilities, duplications, and displacements, reporting rates improved to over
97%inthefollowingreviewperiods.
In January-February 2019, five hundred and forty-seven (547) health facilities were reflected on
the NHLMIS, with a stockout rate of 38%.The stockout rates reflected on the NHLMIS increased
but this was not a true representation of stock availability at health facilities. A review of stock
status at health facilities identified data quality issues that resulted in misleading information. On-
the-job mentoring during supportive supervision visit enabled service providers to minimize
errors in data entry and improve inventory management. This improved skill translated to
transmission of more accurate data and improved commodity availability (Figures 21a, 21b,
21c).
7
39

Figure21a:ReportingPerformanceforOndo State:January 2019toDecember2019
Commodity quantities were determined based on requisitions on the RIRFs and available
quantities at the state store. MCH Coordinators picked up the commodities at the end of each
IMPACT team meeting, transported them to each LGA, and delivered them to their assigned
health facilities during supportive supervision visits (Figure 22). They used the Magpi digital
application to document ﬁndings, including observations on storage conditions, stock-keeping
tools and practices, and commodity availability.Where mobile smartphones were not available or
there was no internet access, the MCH Coordinators used a paper-based version of the checklist.
Upon completion of the visit to each facility, the data were uploaded to a web-based server, which
enabledvisibilityonfacilityperformanceathigherlevels.
40

Figure21b: Data PlacematforOndo State:January-February2019
Figure21c:Data PlacematforOndo State:November-December2019
41

The State FP Unit and LMCU were very hands-on during the IMPACT team meetings, which
promoted commitment from MCH Coordinators. After a few sessions, the MCH Coordinators
led the supply chain performance review for their LGAs, which built their capacity to use data for
decision-making. LMCU participated actively in the capacity-building sessions, which were
incorporated into the IMPACT team meetings to build skills on inventory management,
calculating stock status, and determining how much to re-supply/retrieve from health facilities.
With MCH Coordinators, the LMCU reviewed mistakes on the submitted reports and provided
guidancetopreventfuturemistakes.
There was consistent representation from FMOH and UNFPA at the IMPACT Team meetings in
Ogun state, which increased stakeholders' commitment to coordinate and conduct last-mile
distribution. The activity also increased overall improved understanding of the challenges
affecting commodity availability at health facilities that need to be addressed at the national level.
MCH Coordinators used supportive supervision visits to provide guidance on reporting
commodities that were not managed at health facilities, and on correcting and preventing errors
that had been observed in submitted reports. They also advised service providers to procure
plastic containers for storing commodities safely—which would prevent exposure to rodents,
dampenvironments,anddust,andthusmaintainthecommodities'shelflife.
Challenges
Ondo State
In some health facilities, service providers lacked sufficient capacity to fill out RIRFs correctly.
For instance, stockouts were reported for LARCs in health facilities that did not manage these
commodities. Some MCH Coordinators reported observing poor storage conditions and lack of
sufficient space to store FP commodities during supportive supervision visits in certain health
facilities.
42

Recommendations
Figure 23:Ondo StateIMPACTteammeetingatSPHCDA,Akure
Since December 2019, Ondo State has adopted an alternative mechanism for last-mile
distribution of FP commodities. Nevertheless, MCH Coordinators and service providers would
beneﬁt from training on CLMS, which would improve data quality and reporting performance.
Routine supportive supervision by the State LMCU to the LGA levels would also support
oversightandpromotecommoditysecurityathealthfacilities.
43
Photo submitted by Miranda Buba Gyanggyang, JSI

3.10. Lagos State
8
Population:12,550,598(2016)
NumberofLocalGovernmentAreas:Twenty(20)
The first round of distributions conducted using the IMPACT team model commenced following
the March/April review period. Following regular supervision visits, commodity availability
started to improve. In addition to more regular re-supply, service providers received guidance to
correct data entry errors on RIRFs. Subsequently, the reports transmitted to the NHLMIS became
increasinglyreflectiveofthestocksituationathealthfacilities(Figures24a,24b,24c).
Totalcostsavings - US$1,827,795.90
In January 2019, the NHLMIS reported 314 health facilities offering FP services in Lagos State.
The reporting rate for this period was 91%. Following an assessment of supply chain
performance, the health facility list was reviewed to exclude duplications and displacement,
resulting in a revised list of 308 facilities. Reporting rates remained over 93% for every review
periodin2019.
8
44

Figure24a: Aggregate Stockout and Reporting Performance for Lagos State: January
2019toDecember2019
45

Figure24c:Data PlacematforLagos State:November-December2019
Figure24b: Data PlacematforLagos State:January-February2019
46

Recommendations
Lagos State
Some MCH Coordinators had not been trained on CLMS and had insufficient understanding of
logistics data for making informed decisions. At some facilities, service providers lacked
sufficient capacity to fill out RIRFs correctly. For instance, stockouts were reported for LARCs in
healthfacilitiesthatwerenotmanagingthesecommodities.
The LMCU spearheaded capacity-building sessions, which were incorporated into the IMPACT
team meetings to build skills on inventory management, calculating stock status and determining
how much to re-supply/retrieve from health facilities. With MCH Coordinators, the LMCU
reviewedmistakesonthesubmittedreportsandprovidedguidancetopreventfutureoccurrence.
MCH Coordinators used supportive supervision visits to provide guidance on reporting
commodities that were not managed at health facilities, and on correcting and preventing errors
thathadbeenobservedinsubmittedreports.
Commodity quantities were determined based on requisitions on the RIRFs and available
quantities at the state store. MCH Coordinators picked up the commodities at the end of each
IMPACT team meeting, transported them to each LGA, and delivered them to their assigned
health facilities during supportive supervision visits. They used the Magpi digital application to
document findings, including observations on storage conditions, stock-keeping tools and
practices, and commodity availability (Figure 25).Where mobile smartphones were not available
or there was no internet access, the MCH Coordinators used a paper-based version of the
checklist. Upon completion of the visit to each facility, the data were uploaded to a web-based
server,whichenabledvisibilityonfacilityperformanceathigherlevels.
Since December 2019, Lagos state has adopted an alternative mechanism for last-mile
47

distribution for FP commodities. Nevertheless, MCH Coordinators and service providers would
beneﬁt from training on CLMS, which would improve data quality and reporting performance.
Routine supportive supervision by the State LMCU to the LGA levels would also support
oversightfunctionstopromotecommoditysecurityathealthfacilities.
48

PeriodofImplementation–January2019toDecember2020
InYobeState,proceduresforsupportivesupervisionandLMD weresimilartootherstates:
Despite regular supervision and last-mile distribution visits, there has been marginal
improvement in stockout rates in Yobe State. Some of the stockout may have been reported in
error, as some service providers are not trained on CLMS and cannot fill out RIRFs correctly
(Figures26a,26b,26c).
Maternaldeath averted(2019-2020)–164
3.11. YobeState
NumberofLocalGovernmentAreas:Seventeen(17)
9
Population:3,294,137(2016)
Totalcostsavings –US$3,254,697.59
In January 2019, the NHLMIS reflected that there were 188 health facilities offering FP services
in Yobe State. The reporting rate for this period was 100%. In July-August, the health facility list
was reviewed and updated to 211 service delivery points on the NHLMIS. In this period,
reporting rates dropped; but frequent review of supply chain performance review facilitated
identification and solving problems with report submission, leading to a gradual improvement in
reportingratesfromhealthfacilities.
9
49

Figure26a: Aggregate Stockout and Reporting Performance for Yobe State: January
2019toOctober2020
50

Figure26c:Data PlacematforYobeState:September-October2020
Figure26b: Data PlacematforYobeState:January-February2019
51

YobeState
Challenges
Some MCH Coordinators had not been trained on CLMS and had insufficient understanding of
logistics data for making informed decisions.. The IMPACT team meetings have been used to
build skills on inventory management, calculating stock status, and determining how much to re-
supply/retrieve from health facilites, but this targeted MCH Coordinators only. Although MCH
Coordinators are expected to step the training down to service providers, this would require a
morefocusedcapacitybuildinginterventionatthislevel.
At some facilities, service providers lacked sufficient capacity to fill out RIRFs correctly. For
instance, stockouts were reported for LARCs in health facilities that were not managing these
commodities. Some facilities in Yobe State are poorly accessible due to security challenges, and
in some other LGAs, access to health facilities is restricted by flooding due to seasonal rains. This
lack of accessibility usually affects report submission and replenishment visits, leading to poor
reportingandperiodsofstockout.
As in other states, in-person supply chain review meetings could not take place inApril 2020, due
Coordinators.
improve MCH Coordinators' capacity in inventory management. This improved
commodityavailablityandhelpedtopreventexpiriesandwastagesathealthfacilities.
52

· Holding virtual meetings, attended by state and national stakeholders, using WhatsApp
with state and national stakeholders, beginning in May 2020. Participants reviewed
supply chain data, reporting rates, and commodity availability; assessed stock status and
at the state store and distribution planning; and provided updates on LMD and supportive
supervision.
Recommendations
· SharingdataplacematsfortheLGAlevelfollowingeachreportingperiod.
all levels of the supply chain in the state. Use of WhatsApp can increase access to health facility
reports from hard-to-reach areas, as in Katsina State. In addition, routine supportive supervision
to the LGA level by the state LMCU would strengthen the capacity of MCH Coordinators to
perform their oversight functions and to transfer their knowledge to improve commodity security
athealthfacilities.
53

3.12. SCALE-UPOFIMPACTTEAMMEETINGS
With funding from FCDO, the implementation of the IMPACT team model was expanded to
include seven states in 2020: Borno, Jigawa, Kaduna, Kano, Katsina, Taraba, and Zamfara.
Lagos, Ogun and Ondo states discontinued the use of the IMPACTTeam model and implemented
alternativedistributionmechanisms.
In the first quarter of 2020, plans were made to conduct the first IMPACT team meeting in these
states. However, during this period, the government responded to the detection of the first few
cases of COVID-19 across the country, imposing public health restrictions and limiting travel and
public gatherings. Since women's reproductive health needs remained a priority in the state, the
IMPACT team used virtual platforms, rather than in-person meetings, to review supply chain
performance.
· Stakeholders from the national and state levels reviewed reporting rates, stockout rates,
and stock status during Zoom meetings, using information developed ahead of the
meetings and shared using data placemats. Facility orders derived from the NHLMIS
were used to develop a distribution plan, which was compared with stock status at the state
store. Using these data, the meeting participants agreed on a schedule for distribution to
eachLGA.
· A WhatsApp group was created for coordination of last-mile distribution. After each
meeting at the state level, data placemats were shared to the WhatsApp group, enabling
discussion of key issues in commodity availability at health facilities. The WhatsApp
group was also used to provide guidance to MCH Coordinators, and to facilitate updates
bythecoordinatorsontheprogress ofdistribution.
54

NumberofLocalGovernmentAreas:Twenty-Seven(27)
Totalcostsavings -US$ 219,887.70
The IMPACT team meetings were held using the Zoom virtual platform and follow- on
discussions on supply chain issues were conducted with MCH Coordinators in a WhatsApp
group.
According to the NHLMIS, only 34 health in Borno State oﬀered FPservices in January 2020. In
this period, only 41% of facility reports were transmitted to the NHLMIS. The state IMPACT
team (FP, LMCU, and MCH Coordinators) reviewed the list of health facilities to remove
duplications, correct displacements, and include omitted service delivery points. The revised list
was sent to NPSMCP to update the site list on NHLMIS, but as of October 2020, the list had not
been updated on the site. Thus, even though reports were submitted to the state, they are not
availablefordecision-makingathigherlevels.
10
Population:5,860,183(2016)
In January-February 2019, there was no stockout reported by any of the 34 facilities on the
NHLMIS; but after that period, reports of stockouts increased. As the health facility list is not
comprehensive, the stockout rates depicted below are not representatives of the actual stock
situationforeachperiod(Figures28a,28b,28c)
3.13. BornoState
Prior to the implementation of the IMPACT team model, FP commodities were picked up from
the state store by MCH Coordinators when their facilities ran out of stock. These pick-ups were
not regular due to funding constraints and therefore, there were frequent episodes in which
facilitieswerestockedoutofcommodities.
10
55

Figure28a: Aggregate Stockout and Reporting Performance for Borno State: January to
October2020
For the ﬁrst distribution, MCH Coordinators travelled from the LGAs to the state store to pick up
commodities, which were pre-packed according to facility orders and in line with stock levels at
the state store. The commodities were then delivered to 93 health facilities during supportive
supervision visits (Figure 29). In subsequent distribution rounds, MCH Coordinators from 20
LGAs travelled from their LGAs to the state store to pick up commodities, while the state
distribution team delivered commodities to seven LGAs. The delivery visits were also used as an
opportunity to inspect storage conditions and provide MCH Coordinators with guidance on
inventorymanagementpriortohealthfacilityvisits.
56

Figure28c:Data PlacematforBornoState:September-October2020
Figure28b: Data PlacematforBornoState:January-February2020
57

Even after validation and updates were made to the Borno State health facility list on the
NHLMIS platform, currently, only 51 out of 225 health facilities offering FPservices are reflected
for the state. There are LGAs for which reports have not been uploaded on the NHLMIS for
several consecutive periods, which impedes assessment of commodity availability and needs for
health facilities in these locations. Furthermore, some facilities in Borno State are poorly
accessible due to security challenges. This lack of accessiblity usually affects report submission
andreplenishmentvisits,leadingtopoorreportingandperiodsofstockout.
· Holding virtual meetings with state and national stakeholders, using WhatsApp,
beginning in May 2020, to review supply chain data, reporting rates, and commodity
availability; assess stock status at the state store and plan distribution; and provide updates
onLMD andsupportivesupervision.
· Using WhatsApp to share placemats at the share data at the LGA level following each
reporting period, review performance, and provide updates on last-mile distribution and
State FP and LMCU teams reviewed the health facility list to ensure that all facilities were
represented on the NHLMIS platform and improve visibility into the stock situation at the last
mile.Additionalmeasuresincluded:
Challenges
Starting in April 2020, the COVID-19 pandemic made it impossible to hold in-person supply
chain review meetings—a major concern, since facilitate engagement with stakeholders at the
state level, especially the MCH Coordinators. Additionally, MCH Coordinators were unable to
provide supportive supervision and last-mile distribution, which created a missed opportunity to
discuss challenges, best practices, or service updates at their assigned facilities. In Borno State,
the virtual meetings that the IMPACT team conducted as a substitute for the in-person meetings
were effective at the state level only. Data placemats were shared for discussion with MCH
Coordinators in aWhatsApp group created for this purpose, but this was not an effective means of
engagementattheLGAlevel.
Lessons learned from other states show that input from the LGAlevel is critical to addressing the
challenges that hinder timely reporting and affect data quality and commodity availability at
health facilities. In Katsina and Jigawa states, the virtual platfroms were effective for working
with LGA level input to develop solutions. However, in Borno State, in-person supply chain
performance and LMD review meetings would provide better opportunities for in-depth
engagementwithstakeholdersattheLGAlevels.
Based on feedback from the state LMCU, and verified by poor reporting performance, there is a
need for training on CLMS across all levels of the FP supply chain in the state. This will improve
data quality and reporting performance, and will support effective inventory management across
theselevels.
Recommendations
The facility list reflected on the NHLMIS need to be complete for the data to be able to inform re-
supplyforallthehealthfacilitiesofferingFPservicesinthestate.
58

Figure29: Supportive Supervision and Replenishment visit at a Health facility in
MaiduguriMunicipalCouncil
59
Photo submitted by Yammama Bukar via Borno Child Birth Spacing Group on WhatsApp

Totalcostsavings -US$ 3,360,955.96
11
Population:3,866,269(2016)
NumberofLocalGovernmentAreas:Eighteen(18)
PeriodofImplementation–SeptembertoDecember2020
Prior to the implementation of the IMPACT team model, FP commodities were delivered to
health facilities from regional warehouses. This distribution was funded by USAID and
conducted by GHSC-PSM project. When funding support ceased, there was a need to provide a
distribution mechanism to prevent commodity stockouts at facilities. IMPACT team meetings
were held using the Zoom virtual platform; and follow-on discussions on supply chain issues
wereconductedwithMCH CoordinatorsinaWhatsAppgroup.
Location:South-South,Nigeria
Maternaldeaths averted(2020)-169
According to the NHLMIS, five hundred and ninety-three health facilities offered FP services in
Cross River state as of September/October 2020. The reporting performance for this period was
97%, which is considered to be good according to the national performance benchmark. Even
with the good performance however, there were health facilities that were not reflected on the
NHLMIS during the reporting period. The national program, NPSCMP, provided authorization
to enable the state team to update the facility list, which would allow reports to be captured from
allthehealthfacilitiesofferingfamilyplanningservicesinthestate.
3.14. Cross RiverState
In September – October 2020, the aggregate stock out rate of FPcommodities in Cross River state
was 25%, with the highest stock out rates attributed to cycle beads, consumable kits, and male
condoms. The stock out rates were attributed to low stock status of majority of the commodities
due to a delay in national distribution the COVID-19 pandemic (Figure 30). By December,
however, the state had received commodities from the central contraceptive warehouse and could
commencedistributiontohealthfacilities.
11
60

The ﬁrst round of supervision and distribution visits to health facilities was scheduled to follow
the IMPACT team meetings for the September-November review period. Following the receipt
of commodities from the central contraceptive warehouse, the state team delivered commodities
to each LGA, from where commodities were delivered to health facilities by MCH Coordinators
duringsupportivesupervisionvisits.
Challenges
State FP and LMCU teams reviewed the health facility list to ensure that all facilities were
represented on the NHLMIS platform and improve visibility of stocks at last-mile facilities.
Othermeasuresincluded:
Figure30:Data PlacematforCross RiverState:September-November2020
As in other states, in-person supply chain review meetings could not take place in November
2020, due to the COVID-19 virus, which impeded stakeholder engagements and travels. In
addition, there was low stock at the state store, due to protests that resulted in loss of commodities
and logistics tools. As such, the state had to wait for replenishment during national distributions
beforecommencingdeliverytohealthfacilities.
· Holding virtual meetings with state and national stakeholders, using WhatsApp,
beginning in September 2020, to review supply chain data, reporting rates, and
61

commodity availability; assess stock status at the state store and plan distribution; and
provideupdatesonLMD andsupportivesupervision.
· Using WhatsApp to share placemats at the share data at the LGA level following each
reporting period, review performance, and provide updates on last-mile distribution and
all levels of the supply chain in the state. We also recommend using the WhatsApp platform to
improve access to facility reports from hard-to-reach areas. In addition, routine supportive
supervision at the LGA level by the state LMCU would strengthen the capacity of MCH
Coordinators to perform their oversight functions and to transfer their knowledge to improve
commoditysecurityathealthfacilities.
Recommendations
62

Impact team last mile distribution of contraceptives in nigeria (2019-2020)

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