Crowdsourced data for PHC performance improvement (IMPROVE)

Primary health care (PHC) is the first point of contact of people with the health system and forms the foundation of health systems in low- and middle-income countries (LMICs). In order to achieve better population health, a well-functioning PHC is essential. Standardized measurement and reporting of PHC outcomes helps strengthen accountability and ensures progress in improving the quality of PHC.  

Unfortunately, most LMICs lack standardized, good quality data to measure and monitor the performance of PHCs. 

India's public health system caters to 898 million population residing in rural India. PHCs in India faces several challenges that the health system and communities deal with regularly e.g. absenteeism of the workforce, lack of medicine supply, lack of infrastructure and equipment, resulting in poor health outcomes. These challenges have led to poor service delivery and an erosion of trust between the community and health system reflected in low levels of PHC utilisation, poor health outcomes, preference of private healthcare providers and increase out of pocket expenditure. Healthcare at the PHC level is associated with poor services, long waiting times and poor availability of medicines and laboratory tests.

Furthermore, standardised service delivery data are not readily available at the PHC level due to which performance cannot be measured, improved or evaluated. 

Through our solution IMPROVE, we aim to implement crowd-sourced data collection via a proven native app, Tupaia used for data collection across >12 countries. Aggregated data will be presented in an award-winning web-based front-end, for decision makers to harness real-time, analyzed, relevant data across key indicators for evidence-based decision making. The idea is to 

1. collect community-led data (with A-B testing of proven non-financial incentives for crowd-sourced data collection), 
2. combine this with other available data sources and support the integration of this data stream with established government systems, such as DHIS2.
3. present it to PHC workforce and Policy Makers in real-time for action and monitoring PHC performance.  

Our solution involves a human-centered design using IDEO’s 3 I’s model. Our inspiration is based on health workforce and PHC research in LMICs, specifically in India. We believe that trust is an important factor in improving the performance of the health system. Trust between healthcare providers and patients impacts adherence, regular follow up and better health outcomes.  Hence, one way to improve PHC performance is to collect data about the current practices, workforce and service availability and quality through the lens of the population and provide feedback in a respectful manner to improve PHC services.

Due to the lack of standardized data regarding PHC performance in India, we hypothesize that inviting community members who are the key stakeholders of PHC, to provide anonymized feedback about PHC performance will identify areas of improvement, facilitate better communication and trust, consequently, improve health service utilization and ultimately, better health outcomes. In addition, capturing data from the health workforce will provide wholistic understanding of the context, the barriers and facilitators in providing quality healthcare. 

Figure 1: Data lifecycle to improve PHC performance

(PHC Pic credit: https://swarajyamag.com/insta/...)

Effective and timely feedback is an important component for a successful performance management program. Since people respond better to information presented in a positive way, feedback will be expressed to indicate what the health provider did right and then identify the points for improvement which may be beyond their control (e.g. availability of medicines). Crowdsourcing data is more likely to make accurate observations and leveraging social recognition data is a better way to collect, assess and act on performance. By capturing input from many, and presenting the data anonymously, data on performance evaluations would reveal how the PHC team is truly performing. It will also reveal areas for improvement at the upstream level, such as lack of equipment or medicines. 

Figure 2: Data broker tool to collect, collate and present data in real time

Our crowd-sourced data tool will be a pilot source of data and we aim to be able to support data aggregation from multiple sources, presenting it back to government bodies for real-time, evidence-driven decision making. To prevent this being another data silo, we will implement this with a scaled data broker, capable of consuming and routing data between multiple services (including DHIS2) in real time. See figure above summarizing the solution. 

WHO? Our solution, IMPROVE, serves two key stakeholders.

1. Our solution will provide evidence and insights useful to PHC workforce and managers about views, experiences and perceptions of their clients (i.e., consumers) that can inform PHC management.
2. Our solution will create opportunities for communities to contribute to and engage in the process of PHC service improvement. By doing so, the solution provides a mechanism for empowerment, engagement and trust building.

HOW? 

By using unconventional data, IMPROVE will provide real time, fit-for-purpose and contextualized data that would be of meaningful use for PHC performance improvement. It will provide the health workforce and policy makers clear actionable, accountable, and accessible insights that can be used to optimize the performance of the PHC. 

We are a multidisciplinary team of primary care physicians, academics and digital health experts. We have extensive experience working with LMICs to design and deliver solutions to PHC performance challenges. Over the last two decades, our team has worked with PHC policymakers across multiple contexts to address workforce, information exchange, patient management and continuum of care, governance, and leadership challenges. We have extensive professional relationships with PHC stakeholders in India and elsewhere that will be leveraged to support implementation. We have designed several solutions to improve data for health which have been translated into policy and practice.

Our solution builds on the successful implementation of Wiki-based health service delivery monitoring in the Pacific island. We will leverage the lessons learned from these initiatives to guide the implementation of this solution. 

The design of this solution is guided by community need, the need for PHC workforce accountability, especially in the context of critical workforce shortages and the necessity to bring stakeholders together to attain universal health coverage. 

We have been working in the PHC workforce research sector for several years and understand the problem from the lens of the community, workforce and policy makers (through studies in 6 countries). This opportunity has helped us distil our knowledge gained over the years to create a solution which is centered around the consumers. This grant will provided us with the much needed financial backing to pilot, scale up and evaluate this solution. 

Usually, PHC performance is viewed from the lens of attaining targets (immunization, antenatal coverage) and does not include quality of services, trust between healthcare provider and patients, nor does it seek consumer voices. Our solution is creative and innovative as it brings together consumers and the PHC health workforce to collectively improve the quality of PHC services.

Using real time feedback loop between consumers and service providers helps understand the gaps and how the facility is functioning. Our innovation is rooted in research, human centered design thinking (by understanding the perspectives of the stakeholders) and using a systems lens. We will implement and evaluate this solution through co-design with communities and policy makers in India. 

Furthermore, we are experienced with negotiating the complexities of data consumption from disparate sources. Our crowd-sourced data tool will be a pilot source of data but we aim to be able to support data aggregation from multiple sources, presenting it back to government bodies for real-time, evidence-driven decision making.

Other advantages to this solution include seamless integration with DHIS2 whilst supporting multiple data hierarchies (with entities and data points able to be shared across those hierarchies), SSO and highly granular roles-based permission access.

Our impact goal is to improve:

1. service attendance by the health workforce
2. utilization of PHC services by the community
3. quality of services offered
4. supply of medicines
5. equipment and infrastructure for PHC service delivery
6. trust between providers and communities 

In the long term, we aim to improve access to health care and improve health outcomes through quality services at the PHC.

We will measure progress through a mixed-methods approach. Quantitative data will include: 

1. Use of the app by consumers
2. Use of feedback loop by health providers and policy makers

Qualitative data will include interviews with consumers, healthcare providers and policy makers regarding the acceptability and use of the solution. 

IMPROVE aims to address the following SDGs:

1. SDG 1 Decrease poverty: Better PHC services will lead to less out of pocket costs
2. SDG 3 Better health: By increasing utilization of quality health services
3. SDG 8 Decent work: By receiving feedback from the health workforce, policy makers will understand the needs and requirements by the PHC
4. SDG 10 Reduced inequalities: By improving access to PHCs 
5. SDG 17 Partnerships for goals: Improving collaboration between policy makers, health workforce and communities

Our theory of change is:

If we crowdsource data from communities who use PHCs and the PHC workforce 

By collating, analyzing, and presenting data to the workforce and policy makers

And by providing standardized data that is measurable

We can improve service delivery

So that there is improved trust between PHC workforce and the community, and better utilization of services

resulting in the improved health outcomes for our communities

We will implement the project using a native app built on the Tupaia platform, which has been implemented across 12 countries in the region to augment systems such as DHIS2.

Tupaia is a free and open-source, end-to-end data platform that supports the aggregation, analysis and visualization of healthcare system data. It is designed to collect, combine and disseminate information across LMICs. It combines data from multiple sources to create a real-time map highly customized visuals to support programming and evidence-led decision making.

Tupaia’s central platform is built around a Postgres database (with NodeJS) and a React front-end. We use a microservices architecture, harnessing tools such as a data broker, config server, auth server, reports builder and data lake amongst others. Our data collection app is a React Native app, with iOS and Android versions. Our main mapping led front-end is built in React and uses Leaflet and Recharts libraries (along with some bespoke visualizations). Our mapping tiles can be toggled between MapBox and OpenStreetMaps.

Using a powerful data broker, Tupaia pulls and combines live data from various sources in near real-time in areas such as health supply chains, disease surveillance, service provision and quality, HIS, infrastructure, weather, or HR capacity and training to present a rich, live map of a country’s health system. Centralized access to this data helps decision-makers appropriately distribute resources and efficiently respond to disasters.

Importantly, Tupaia integrates with existing tools, such as DHIS2 and mSupply – not replacing but augmenting them to provide a more complete picture of a health system.

We allow users to attach data to entities across multiple data hierarchies - so for example, a regional vaccines team might assess electricity infrastructure at a health clinic in Country X and this would populate the same data field for the national NCD screening program, even though they use an entirely different hierarchy.

Our roles-based permissions model (with SSO and hierarchical permissions) also allows you to be an admin on one project and a junior data analyst on another project. All data collection is offline first and sync-enabled with world-class data security. It is able to handle massive amounts of data and our microservices architecture includes a data broker, data lake and reports builder.

Finally, it is built with context front-of-mind, from the name (Tupaia was a first-nations navigator) to gamification - users earn coconuts and pigs for collecting data, an idea which came from an early project in Solomon Islands.

Data collectors will include: Community members and PHC workforce

Incentives for community members include: 

1. Receive information about their disease or condition 
2. Contribute towards improving the local PHC

Incentives for health workforce and policy makers: 

1. PHC workforce have their voices heard 
2. Contribute towards improving the PHC

Ours is a diverse team comprising men and women working in India and Australia. We believe in working closely with stakeholders, and have based this research on our work with the health workforce, communities and policy makers in India. 

We have used the social business model canvas to develop a for-purpose product with an aim to improve PHC performance. 

In the long term, we envisage service contracts with the government or private healthcare providers interested to improve their health services through real time data collection and monitoring of health services. The money generated would be used to cover the costs of the service and updates to the technology platform. 

• The academic partners (School of Population Health and The George Institute, India) have received multiple peer reviewed and philanthropic funding to design, implement and evaluate interventions to improve health systems. Some examples of our work include:
  • SmartVA for Physicians to improve data for health funded by Bloomberg Philanthropies and Australian Department of Foreign Affairs and Trade
  • SmartHealth funded by the Australian National Health and Medical Research Council
  • INTEGRATE funded by the  Australian National Health and Medical Research Council
  • Understanding the delivery of Primary Health Care through PHC teams.

• BES have been active for 7 years, with ongoing funding support from multiple partners including multilateral agencies, partner countries, bilateral donors, research institutes and the private sector. We have partnerships with DFAT, MFAT, World Bank, UNICEF, UNFPA and others.