One-Stop-Shop PHC Performance Clinic

Kano State is situated in North-West Nigeria and has some of the poorest health indices in the country; the maternal mortality ratio is estimated at 1,026 per 100,000 live births, the neonatal mortality ratio is 44 per 100,000 live births, and the under 5 mortality rate of 189 per 100,000 live births (MICS 2017). Furthermore, 58% of children under five in the state are stunted while 40.3% are underweight (NDHS 2018). Although there have been significant improvements in the State’s immunization indices in the past five years, the Penta 3 coverage is 45.9% which is significantly lower than the 80% national target (N-DHS 2018). Despite significant investments by the State Government and its partners, Nigeria’s primary healthcare (PHC) system continues to perform sub-optimally. The institutionalization of the Primary Healthcare Under One Roof (PHCUOR) policy sought to address the challenges by consolidating provision and oversight of PHC under the stewardship of the Kano State Primary Healthcare Management Board (SPHCMB), but huge gaps remain in integrating, coordinating, and managing service delivery at all levels, from the SPHCMB to Local Government Area (LGA), to PHC facility level. Thus, PHC service delivery in Kano state still suffers from the suboptimal quality of care, fragmentation of services, decreased health worker productivity, frequent stock-outs of essential commodities, and low uptake/utilization of services. CHAI postulates, based on its extensive field experience, that many of these issues arise from the inability of managers and leaders at all levels to access, interpret, and utilize data for decision-making and program planning.    

Since 2019 CHAI supported the Kano SPHCMB to develop a Reproductive, Maternal, Newborn and Child Health (RMNCH) scorecard. Furthermore, in 2022, a one-stop-shop dashboard that leverages multiple electronic data sources as a means of measuring PHC performance were developed. This tool has achieved impressive outcomes, such as enabling tracking, posting, and redistribution of health care providers, providing insight into the location of over 1,200 PHC facilities in the state, the scope of services they are providing, the contact information of the facility manager, as well as managing the equipment inventory and fixed assets of the SPHMCB to mention but a few.     

To build upon the successes achieved to date, leverage the strong political buy-in at SPHCMB, and maximize the utility of this tool, the following limitations should be addressed: 

• The scorecard does not collect primary data on clients’ satisfaction from PHC service delivery, or community-level service outcomes, both of which are important measures of a PHC systems performance. The one-stop dashboard provides access to vertical interventions, but no synthesis is made between them to enable the SPHCMB draw insights into the quality of the services provided in PHC facilities. 
• The scorecard only uses service output data from DHIS 2 to measure PHC performance, which only reveals part of the picture and does not shed light into the “why” or “how”. Thus, data related to inputs (e.g., availability of HRH, finance, supplies), outputs (e.g., service uptake), and outcomes (e.g., reduction in mortality rate) are rarely linked. This makes it difficult for policymakers to apply these data for holistic decision making and action planning, to concretely improve PHC service delivery. 
• Data visualization platforms such as the One-stop-shop dashboard are frequently designed with limited concrete, realistic knowledge of what decision-makers need and want, leading to the development of many unsustainable, overly complex dashboards that are not user friendly, particularly for lower levels. Furthermore, integrating and synthesizing multiple data sources to make evidence-based decision making requires iterative multi-stakeholder inputs  
• Data that feeds into the RMNCH scorecard and dashboard include routine government systems data and donor-driven data, which are often of sub-optimal quality, due to limited capacity and high workload of the healthcare workers, insufficient data collection tools and inadequate data collection supervision, partly due to poor understanding of why data is being collected and limited relevance of data collected to their routine tasks 
• The scorecard and dashboard are not interoperable with one another and other existing systems in the state, thus, making it difficult for the management team to holistically correlate PHC performance using multiple parameters.  

CHAI will work with the Kano SPHCMB to consolidate and optimize the integrated PHC Performance Management Dashboard, including the RMNCH scorecard, and build in additional functionalities as follows: 

1. Low-burden patient-centred data generation: include patient- and community-centered data into the PHC performance management system by building a client feedback survey component that collects primary data on patients’ satisfaction after utilizing PHC services. Patients visiting PHC facilities are automatically prompted to share their perspectives on PHC service quality following receipt of services and whilst they are still within  the vicinity of a facility, leveraging mobile geolocation technologies to crowdsource data, increasing the rights-based nature of PHC performance measurement.

2. Holistic visibility of the PHC system’s program cycle & interdependencies: expand and update the PHC performance monitoring website to create holistic visibility of the PHC system’s program cycle & interdependencies: 

• Integrate and triangulate service delivery inputs, outputs and outcomes and generate insights useful for PHC programming at all levels – state, LGA and health facility 
• Integrate community health level PHC data 

3. Human-centred, actionable insights for all decision-makers: stakeholders from facility to state level receive customized, actionable insights and recommendations to improve pillars of the PHC system under their purview, developed through application of Human Centred Design (HCD) to craft formats responsive to their concrete information needs and communication preferences. The systems will generate customized, actionable insights and recommendations targeting stakeholders from facility to state levels to help them interpret the data and use the findings to improve pillars of the PHC system under their purview. 

There are three broad categories of beneficiaries to this innovation. The primary beneficiaries are the community/clients who need continuous access to high-quality PHC services.  

• Community Beneficiaries: Provision and access to quality patient centered PHC services has proven unattainable for service users especially the over 10 million vulnerable population in Kano, who make up >70% of the population. Our proposed solution will ensure the system captures and responds to their needs through deployment of patient satisfaction surveys and generation of data insights to guide improvements in and ensure a more responsive PHC service delivery system.  
• Healthcare Providers: another category of beneficiaries include the facility officers in-charge stationed at health facilities, who will benefit from responsive, data-driven insights on how best to optimize or allocate their available human, financial and medical supply resources to achieved desired PHC outcomes. Facility officers are often burdened with collection of multiple service provision data, with limited capacity to translate and apply these data for decision making and facility level improvements. Our solution will be designed to ensure that data gathered is responsive to the needs of facility officers and generates actionable insights and recommendations that guide facility improvements.  
• State and LGA Government Officials: PHC managers across State (Kano State Primary Health Care Board) and LGA levels constitute the direct users of the solution.  State policy makers require up-to date, relevant, straightforward information on the performance of the primary health care systems and how that translates to improved performance on the State’s key RMNCH and other health indicators. Insights generated from the proposed solution will position State policy makers to be more responsive to the health needs of the population and prioritize allocation of available resources as these needs evolve.  

CHAI is well placed to achieve the stated objectives in Kano state. The resident team to work on this investment is made up of 99% Nigerians, the majority of whom reside in Kano state, where this project will be implemented.  

CHAI has experience supporting the Kano State government in PHC service delivery improvements and management, including the application of data-driven improvements in PHC service delivery. More specifically CHAI supported the Kano State Primary Healthcare Board to pilot implementation of the delivery type approachto operationalize the Kano Minimum Service Package plan, using an iterative people-centered problem-solving approach and thus giving the community a voice in the design and running of their health facilities. Through this process, facility assessments were conducted across PHCs in the State to inform facility improvement plans and track progress towards provision of the minimum service package in select facilities. To generate improved insight and carry critical stakeholders along, CHAI facilitated engagements with community representatives, service users, healthcare providers and local government officials to collectively identify root causes of poor PHC performance, co-create interventions and mobilize domestic resources to solve identified challenges As a result, facilities have begun streamlining utilization of their funds to evidence-based collectively agreed interventions, thereby increasing allocative efficiency of limited resources.

CHAI had worked with the government to design a stand-alone analytical dashboard of progress facility performance towards attainment of the MSP. This investment will convene a community forum session to seek input and ideas of the community and facility in-charges on appropriate methods to relay feedback, what and when to receive the response from the authorities and in what format.  Furthermore, CHAI will leverage our strong relationship with the SPHMCB staff and leadership to review the utility of the existing platforms, seek recommendations on their data needs, format for display and cadence of update to give room for decision making. This will foster ownership and confidence. 

Since 2018, CHAI has worked with the National PHC Development Agency (NPHCDA) and the Kano and Kaduna State Governments to support ongoing PHC strengthening efforts. CHAI’s support has spanned operationalization of the BHCPF at national and state levels, including designing and rolling out the Kano State Contributory Health Management Agency (KSCHMA) Scheme’s Vulnerable Populations Program (VPP) and supporting monitoring of the PHC reform in Kano State. In 2019, CHAI supported a pilot of the VPP program ahead of BHCPF operationalization which generated community buy-in and demand for the program and the validation, enrollment, and tracking of 20,000 women and children under five. The community leadership were engaged to identify and screen the most vulnerable members of the population for enrollment, thus boosting the community’s confidence in the enrollment.  

Currently, CHAI is supporting the state to design an operational model using the ‘Delivery approach’ for the implementation of the Minimum Service Package (MSP) investment plan.

CHAI is a global health organization committed to saving lives and reducing the burden of disease in low- and middle-income countries by working with government to strengthen its capacity to deliver health services to the population. In line with our mandate, CHAI supported the Kano SPHCMB to develop a Reproductive, Maternal, Newborn and Child Health (RMNCH) scorecard as a means of measuring PHC performance and identified four key limitations that impact optimal implementation of the PHC performance tracking dashboard. Addressing these identified limitations will require technical and financial support to grow our PHC performance tracking solution and maximize its potential for impact by deploying enhanced solutions that adequately address identified limitations in PHC performance tracking. The MIT innovation ecosystem has been identified as an optimal platform that can provide the financial and technical support required to drive sustainable and transformational impact in delivering PHC services.

Service delivery data from the District Health Information System (DHIS 2.0) is the predominant source of data used to measure Primary Health Care delivery in Kano state and Nigeria at large. While this reveals important insights regarding service uptake, it does not give a holistic picture of the PHC performance. For example, the current system does not show how essential inputs like human resources, equipment, basic supplies, and financing, affect service provision, and how service availability affects health outcomes. Additionally, the current system only focuses on measuring the number of services delivered without capturing service quality.  

Our solution aims to address the gaps along the continuum of PHC performance monitoring in the current system – data collection, analysis, interpretation and use for decision making.   

Data collection: To ensure comprehensive measurement of PHC performance, our solution will incorporate the collection of data related to the quality of care from the client's perspective, an important, but often neglected goal of universal health coverage. We will leverage QR-code, SMS, and voice recognition technologies to allow a diverse range of patients with different literacy levels and socioeconomic backgrounds to provide feedback on their experiences regarding PHC service quality. The use of a self-reported patient satisfaction measurement system also serves to reduce the burden of data collector on the HCWs, and minimize assessor biases that may affect the quality of the generated data.    

Data analysis and visualization: Data relating to service inputs, outputs, and outcomes, both at the facility and community level are currently generated from existing databases such as the Reproductive Maternal Newborn Child, Adolescent Health and Nutrition (RMNCAH+N scorecard), District Health Information Software (DHIS2), Community Based Health Management Information System (CBHMIS) dashboard, and Family Planning (FP) Dashboard, but these systems operate in silos and independent of each other. Therefore, the second arm of our solution will aim to integrate all the different databases into a single dashboard and analyzing data from several sources together, to create end-to-end visibility of the PHC system. This allows for rapid identification of the cause-and-effect relationships between service inputs, outputs, and outcomes. The integrated data system will have a transformational impact on data management and use at the PHC level. It will streamline and ease access to data within the PHC system. Stakeholders will have all the data needed to make decision within a single dashboard. Thus, stakeholders can use evidence from the pool of data to determine which input or process to prioritize and implement, to provide the desired improvement in health outputs and outcomes.   

Data use for Action: One key limitation to data use for decision-making at the PHC level is the poor understanding and contextualization of generated data. Stakeholders interacting with the data including those who collect it, do not understand how they can concretely use it to improve the aspects of the health system which they are responsible. Thus, the third piece of our solution involves a novel approach to generating insights from generated and analyzed data. We will use the Human Centered Design (HCD) approach to understand what actionable insights facility, district/Local Government, and state decision-makers need and want, why, at what frequencies, and how they want to access it to improve their ability to carry out their responsibilities related to PHC strengthening. For example, while the state team may be keen in knowing the HRH distribution across facilities, a priority for the facility managers may be the availability of the required number of HCWs in a single facility. We will apply findings from the HCD workshops to design a system that will generate actionable insights from the integrated data sources and seamlessly share them with stakeholders at all levels. These insights will be generated using an Artificial Intelligence (AI) modelling technology that will correlate different data points that will be integrated into the unified PHC dashboard. These insights will be auto generated at pre-defined intervals and shared with stakeholders as notifications, through their email addresses and on the interphase of the integrated PHC dashboard. At the state level, the data generated from the dashboard will be used to guide performance reviews at the various technical working groups working groups of the PHC system. It will also provide evidence needed to prioritize and plan for interventions in the annual operational planning process. At the facility level, facility data generated from the dashboard will be used to guide identification of suboptimal performance root cause and develop interventions to improve quality of care.   

These three interventions will ensure that all the data needed to have a comprehensive picture of facility performance is available, integrated, and routinely shared with stakeholders for enhanced decision-making. 

We hope to achieve three outcomes in the medium term through this investment: 

• Improved investments into PHC inputs: The integration of multiple data points for PHC systems and the use of AI to generate customized insights will guide PHC managers at all levels to make evidence-based decisions, thereby leading to efficiency gains in the utilization of available resources. This will in turn free up more resources for additional investments and improvement of the PHC system. It will also provide the evidence base to advocate for increased budgetary allocation to PHCs. 

•  Increased demand for services and client satisfaction: Incorporating the patients’ feedback survey component into the PHC performance monitoring framework will generate useful insights into the quality of experience of PHC services quality, which will guide relevant stakeholders across all levels to take appropriate action, ultimately leading to improved service quality and patient satisfaction. This makes make PHC system more responsive to patients needs and creates a positive feedback loop of increased patients demand for PHC services. 

• Improved supply of high-quality patient-centered PHC services: The holistic visibility and insights into the PHC system’s program cycle provided through our solution will help stakeholders at all levels to diagnose and proffer solutions, both financial, technical, or operational, to service delivery challenges at the input, output, and outcome levels. This ultimately leads to an increase in service access and utilization 

Measurable Indicators under each outcome

Outcome 1: Improved investments into PHC inputs: 

• Proportion of PHC facilities with the full complement of essential service delivery inputs – Human resources, tracer equipment, basic supplies 
• Proportion of PHC facilities delivering a minimum package of essential PHC services  

Outcome 2: Increased demand for services and client satisfaction: 

Proportion of target facilities with active feedback mechanisms 

• Percentage patients reported satisfaction with care  
• ANC 4 Coverage 
• Percentage of Family Planning new acceptors 

Outcome 3: Improved supply of high-quality patient-centered PHC services 

• Percentage of asphyixated babies succesfully resuscitated 
• Percentage of women whose labor is managed with partograph  Percentage of deliveries attended by a Skilled-Birth Attendant 

The current PHC performance monitoring system does not collect primary data on clients’ satisfaction of PHC service delivery, or community level service outcomes, which are both important measures of a PHC system. CHAI will develop a mobile system using QR code and SMS technology for patients to self-report satisfaction with PHC services they received, and the patient satisfaction data collection system will be deployed to crowdsource the information to reduce the burden on data collectors. Then, the patient satisfaction data will be integrated into PHC Performance Monitoring System.  

 Data related to service delivery inputs (e.g., availability of HRH, finance, supplies), outputs (e.g., service uptake), and outcomes (e.g., reduction in mortality rate) are rarely linked to one another. This makes it difficult for decision makers to use the data for holistic decision making. As a result, a human Centered Design will be conducted and solutions identified for information needs and communication method preferences and a PHC performance monitoring website will be improved to bring together multiple data sources to link inputs, outputs, and outcomes, creating visibility into the PHC system’s interdependencies. 

 Data visualization platforms are frequently designed with limited concrete, realistic knowledge of what decision-makers need and want, leading to the development of many unsustainable, overly complex dashboards that are not user friendly, particularly for lower levels. An AI system will be developed to generate specific recommendations for PHC, LGA, and state officials to make data-informed decisions on service delivery input investments or allocations. PHC, LGA, and state officials will be oriented on understanding and utilizing the information that is generated by the AI system.  

 The combined efforts will lead to improved investments into PHC inputs, which will be informed by a holistic view of system bottlenecks thus, making the PHC System more responsive to the needs of the beneficiaries. This will in turn improve the supply of high-quality patient-centered PHC services, increased the demand for PHC services and patient satisfaction. TTwo examples from CHAI’s work in Kano state demonstrate how data can be generated and used to improve timely decision making in the health system. The MSP MT dashboard allows the identification of gaps across different thematic areas in primary health facilities, which is summarized on a google studio dashboard. CHAI and SPHMCB facilitate multi-stakeholders’ (including the community, healthcare providers and PHC managers) discussion to identify bottlenecks and co-design solutions thereby enabling targeted evidence-based community-driven interventions. Similarly, the RMNCH scorecard draws service data from the DHIS through an API, analyzed the data for errors using an already define threshold, thus allowing data errors in DHIS to be identified. LGA specific error messages are sent to the respective local government monitoring and evaluation officer   via emails and prompts them to correct wrong data on the DHIS. The corrected data is used by to automatically plot the RMNCH+N scorecard for the month and shared with all relevant stakeholders per their level of authority. This has led to an improved data quality, and use for tracking service uptake.  

  The long-term impact will improve health status and health outcomes in Kano State.

Our solution will be built using disruptive technology solutions to strengthen data systems for PHC improvement.     

We will use mobile technology to provide an unbiased assessment of patient satisfaction with care provided at the PHC level. This will involve using a mobile SMC and voice technology to assess patient satisfaction with the quality of care provided at the facility. Each of the intervention facilities will be provided with QR and text codes for clients with a mobile phone to provide independent feedback on satisfaction with care. A patient will scan the QR code or send a text code to a toll-free number. Once the message is sent, a patient will receive a recorded call to assess his satisfaction with care, either in English or any of the three predominant local languages in Nigeria. Patients’ responses will be converted to data at the back-end through vocal recognition software and synthesized to generate patient satisfaction results.    

We will also build a website that will be scripted with an algorithm to extract data from the patient satisfaction system back-end and other parallel databases existing in the PHC system, including the RMNCAH+N scorecard, DHIS 2, CBHMIS, and the FP dashboard. The website will therefore integrate all the data points needed to assess PHC performance.     

Beyond aggregating the data and visualizing it on a single platform, we will deploy a third technology based on AI predictive modeling to correlate data points in all the integrated data sources and generate an actionable insight into the cause of suboptimal performance and provide specific broad recommendations to kickstart discussions, decision-making, and next steps utilizing the findings. These insights will be customized to the stakeholders' needs and influence. Thus, only insights that are relevant to a stakeholder will be shared with him by the system as email notifications and will also be made available on the user interface of the dashboard.   

Data on client service satisfaction would be crowdsourced by collecting self-reported feedback from PHC patients leveraging mobile technologies including QR code and SMS. Clients can be encouraged by their health provider to submit feedback, particularly if the facility OIC is eager to improve the faclity's performance and coaches the health center staff to engage patients on this. However, ultimately patients will be incentivized to provide their feedback about services once they see that their requests or complaints have been taken into account by the facility with financial or operational changes. The assumption underlying this is that health facility OICs and LGA supervisors will utilize the data results and will implement changes in their facility accordingly.

All other data being used is already collected through routine pre-existing data collection processes, such as DHIS2.

One of CHAI’s core values is to fostering diversity and inclusions and this is implemented rigorously in the organization. CHAI is made of teams from diverse social, cultural and multi-disciplinary backgrounds working together harmoniously to save lives which we have demonstrated in several implemented programs. The Senior Management Team at CHAI Nigeria is made up of 50% women and the proposed project team of 8 is 40% women. CHAI has zero tolerance for discrimination and harassment in any form and fosters an environment of inclusivity regardless of people’s race, color, religion, gender (including gender identity and gender expression), sexual orientation, ethnicity, national origin, age, disability, HIV status, political or interest group affiliation,  genetic  information, veteran  status,  marital  status,  parental or pregnancy  status or any other characteristic.  

 CHAI has a policy on the prevention of sexual exploitation, abuse and harassment (PSEAH). The purpose of this policy is to create a secure environment for beneficiaries and members of the public and to protect children and vulnerable adults from any harm that may be caused due to their coming into contact with CHAI. It is also to establish procedures for addressing incidents of sexual exploitation, abuse and harassment, and to inform staff of their contractual and moral responsibilities to safeguard children and vulnerable adults in all areas of CHAI’s work. All CHAI staff must undergo a compulsory and comprehensive training on the prevention of sexual exploitation, abuse, and harassment.   In addition, CHAI has put in place some steps to prevent sexual exploitation, abuse and harassment and protect victims when  concerns arise. 

 In the communities where we work, CHAI engages local stakeholders (state, local government and communities) in planning, implementation and evaluation of program interventions. CHAI adopts a Human Centered Design which engages relevant stakeholders across all levels in designing and planning program interventions that takes into consideration the local context and environment and most pressing needs affecting the populace in which we work.     

 By adopting this approach, we strive to target our interventions to all those in need especially the furthest left behind thereby improving access, reducing disparities, and helping governments and communities remove systemic obstacles and barriers to access needed care. A human-centered design which incorporates local stakeholders’ (state, local government, and communities) feedback also ensures acceptability and sustainability while being sensitive to local sensitivities. Another benefit of engaging the lower-level stakeholders such as LGA officials and officers in-charge of health facilities is that it ensures that interventions designed, planned, implemented and evaluated are relevant and appropriate within the context in which these programs are executed.   

The following three beneficiary segments are as follows: Facility Officers-in-Charge; LGA Officers; and SPHCMB Officers.   

1. Facility Officers-In-Charge (OICs) and staff: They oversee the day-to-day running of the primary health care facilities. They engage directly with the patients and provide services such as health information, treatment, and referrals, deploy health technology, and conduct a lot of data collection related to overall primary health care service delivery. CHAI's solution will benefit them in the following ways: 

• The novel patient satisfaction data collection system will allow them to gain up-to-date insights into why demand for services may be lower than expected or understand how to improve their facility operations. With increased demand for services, the facility's service volumes will increase, thereby justifying the need for additional inputs such as commodities, and allowing them to further expand service provision. In addition, the self-reported data collection method provides a model for crowdsourcing PHC data without burdening PHC staff with data reporting.  

• The integration of data sources linking inputs, outputs, and outcomes would allow facility OICs to see how their facility compares to others across various indicators. This provides opportunity for peer-learning and sharing best practices, as well as fostering friendly competition.  

• The AI-powered insights generated from the multi-source analysis provides facility OICs with them a ready source of information for quarterly and annual business planning sessions, as they can use the results to inform prioritization, management decisions, and optimized budget allocations.  

2. LGA Officers: They provide support and oversight functions into the activities at the primary health care facility level, collate aggregate data from the OICs under their purview and are meant to operate as an interface between the state program managers and facility OICs in key aspects including mentoring, and on-the-job-capacity building. CHAI's solution will benefit them in the following ways: 

The integrated dashboard and AI-powered insights will provide them with a comparison of PHC performance across all facilities in their LGA, enabling them to prioritize facilities of focus for upcoming supervision schedules and limited supervision budgets. It also allows them to identify high performing facilities which LGA staff may want to investigate to understand successes, provide acknowledgement and support for continuous progress, and invite to participate in peer-mentoring for other facilities. 

• The information contained in the dashboards and recommendations will be highly valuable to LGA staff as it will be a guide or job aid for them to determine which aspects of service provision to focus on during supervision visits.  
• LGA staff are required to provide reports to state level, and the dashboard can be leveraged for reports, updates, or presentations.  
• LGAs may also want to use the information collected through this solution to advocate for additional funding to support specific program activities such as mentorship or supervision to address system gaps.  

 3. State level SPHCMB officers: They are responsible for developing strategies, policies, plans, and budgets for Kano State PHC system, coordinating and implementing their roll-out, and providing technical and managerial oversight to all pillars of the system.  

• The solution will provide critical information to help these stakeholders prioritize budget allocations, reforecast as needed, and release funds to lower levels in need of specific PHC performance improvements.  
• The data will also inform advocacy for resource mobilization from domestic and external sources by demonstrating concretely how the funds will be used to impact PHC service delivery.   The solution will also provide states with data to document and demonstrate their successes with PHC improvements, and to share data-backed experiences and approaches with other states and national level, for replication elsewhere.

Once CHAI supports the Kano State government to consolidate, optimize and expand the functionality of an integrated PHC performance monitoring dashboard on a website, the financial requirements needed to sustain the website will be limited to server and maintenance costs, which are relatively low. CHAI will support the State Primary Health care Board to identify a department as well as a program officer that will serve as the custodian of the website, and will ensure the management of the Board buys into the idea to developing a budget line in the annual budget of the department for annual subscription for the server that will host the website. The program officer will be charged with the responsibility of developing a memo and applying for the release of the funds for the annual subscription. The existing SPHCMB ICT team will be tasked with basic maintenance, and contacting the server company in case of changes needed such as an upgrade to server size. 

CHAI has supported the government of Nigeria to develop different tools to aid the measurement of PHC performance and has worked to ensure the financial sustainability of these intervention beyond . The RMNCH scorecard system that is currently being used to collect multiple data sources in Kano state and the PHC website that is being developed by the SPHCB to house data on the human resource for health, management information system, infrastructure and inventory for hospital equipment were both designed with CHAI’s close support. To ensure their financial sustainability, CHAI ensured that the fees for the annual server subscriptions are included in the annual budget of the State Primary Health Care Board (SPHCB). The funds have been released in 2022 by the government and used to pay for the two server subscriptions.  

Similarly, CHAI supported the government of Nigeria to develop a family planning dashboard that houses data on all family planning related interventions across the country. Although CHAI has paid for a 5-year server subscription on behalf of the government for the period of 2022 – 2025., the government has committed to creating a budget line for the annual server subscription and use the released funds to pay in subsequent years. A champion for the FP dashboard has also been identified within the FP department of the Federal Ministry of Health.