How Can Community Data Be Leveraged to Advance Primary Health Care? A Scoping Review of Community-Based Health Information Systems

"Community-level data through CBISs [community-based health information systems] are essential for understanding what the health needs of the population are and can directly support the achievement of universal health coverage."



Community-based health information systems (CBISs) can comprise a combination of paper, software, hardware, processes, and people facilitating recording and reporting of services provided at the community level, often by community health workers (CHWs). During the COVID-19 pandemic and Ebola epidemic, CHWs and community health systems played a role in contact tracing, case management, and provision of health services, which were critical in understanding what the health contexts and needs were at the community level. However, there are few examples of CBISs that are well functioning, have good data quality, and are implemented at scale. This scoping review aims to understand how CBISs have been implemented, integrated, and used to support community health outcomes in low- and middle-income countries (LMICs).



Search strategies were conducted on November 15 2021 to identify articles addressing the use of CBISs in LMICs. A total of 11,611 total records were identified from 5 databases and the gray literature. After deduplication, 6,985 peer-reviewed/gray literature were screened, and 95 articles/reports were included, reporting on 105 paper, digital, and mixed CBIS implementations across 38 countries.



The majority of CBIS implementations (55.2%, n=58) reported using both paper and digital components for data collection and reporting, with just 28% of CBISs being fully digitised (for data collection and reporting).



Community-level data were largely collected by CHWs across the included articles; other community leaders, such as the village chief, community mobilisers, religious/faith leaders, traditional birth attendants, and nurses or midwives, were also identified as collectors of community data. Data reporting from the community level to the health system varied, but data were typically collected in the community at the household level, primarily by CHWs. These data were reviewed, aggregated, and submitted to primary health care (PHC) facilities, where they could be further aggregated and submitted to district-level and other subnational-level administrative units before reaching national-level integration. CBISs that were focused on vertical programming, such as malaria or HIV, were more likely to report being integrated into a national health information system (HIS).



Also, digitised CBISs more likely to reach national-level integration. Paper-based reporting could be hampered by challenges such as not having access to the very registers and reporting forms to submit data to health facilities, registers and reporting forms being vulnerable to damage and loss due to weather, and delays in submitting data in a timely manner when data were available. These challenges could have impeded the ability of a paper-based CBIS being able to reach national-level integration. That said, although digitised CBISs offer promise, challenges with electricity and connectivity infrastructure, insufficient training and digital literacy among the health workforce, and transitioning from paper-based to digital systems negatively impacted data collection, data quality, data flow, and reporting.



Thus, data quality challenges were present in both paper-based and digitised CBISs, exacerbated by fragmentation of the community health landscape with often parallel reporting systems. The studies in this review identified a number of strategies that could help improve data quality, primarily around the implementation of robust and largely digitised monitoring and evaluation systems that could identify strengths and gaps in CBIS data flow and facilitate real-time feedback on health system performance; components also included consistently implemented data review meetings with CHWs and CHW supervisors to promote accountability.



In terms of data use, limited availability and lack of trust in the quality of community-level data impeded ability to effectively use CBIS data for decision-making and toward improving community-level health services and health outcomes. The literature emphasised the need for interoperability, improved data quality, increased digital literacy training, improved network and connectivity infrastructure, and human resources to enable effective data use.



The key implication, according to researchers, is that strengthening CBISs requires strengthening community health systems. There needs to be alignment of country-led integration of community health services along with efforts to ensure that the digital environment can enable the collection of community-level data and its integration within the broader health system.



There have been calls to action to further advocate for CBISs. For example, the Community Health Impact Coalition, an advocacy-focused network focused on professionalising and supporting CHWs, has led initiatives to harmonise and connect community-level data across 8 countries represented within the Coalition.



In conclusion: "Despite the increase in digitization of CBISs, it is important to focus on the broader ecosystem to strengthen data collection and reporting systems and address challenges around training, connectivity, and integration of health services to improve the quality and use of community-level data."