Rural Public Health Data Challenges During the COVID-19 Pandemic: The Case for Building Better Systems Ahead of a Public Health Crisis

Abstract

Context: Rural public health personnel serve communities that have been particularly susceptible to COVID-19 and yet faced the pandemic with far less well-resourced capacity than their urban counterparts. A critical aspect of addressing local health inequities is access to high-quality population data and the capacity to effectively use data to support decision making. However, much of the data required to investigate inequities are not readily available to rural local health departments and the tools and training to analyze data are often lacking. Program: The purpose of our effort was to explore rural data challenges related to COVID-19 and provide recommendations for improving rural data access and capacity ahead of future crises. Implementation: We gathered qualitative data in 2 phases, more than 8 months apart, from rural public health practice personnel. Initial data were gathered in October-November 2020 regarding rural public health data needs during the COVID-19 pandemic and then to later identify whether the same findings held true in July 2021 or whether access to and capacity to use data to address the pandemic and related inequities improved as the pandemic progressed. Evaluation: In our 4-state exploration focused on access and use of data among rural public health systems to promote health equity in the Northwest United States, we found tremendous and ongoing unmet data needs, challenges with communicating data, and a lack of capacity to meet this public health crisis. Discussion: Recommendations for addressing these challenges include increasing dedicated resources specifically to rural public health systems, improving data access and infrastructure, and providing dedicated data-related workforce development.

The Solutions in Health Analytics for Rural Equity Across the Northwest (SHARE-NW) Dashboard for Health Equity in Rural Public Health: Usability Evaluation

“…Issues related to obtaining quality public health data are well documented in the literature and include the critical problems of a lack of investment in public health data systems and infrastructure [ 36 - 39 ], issues with data quality [ 40 - 42 ] and data fragmentation [ 43 , 44 ], and the sparse data available about rural communities [ 8 , 45 ]. While every effort was made to include as much timely and comprehensive data as possible in SHAREdash, these larger data problems clearly impacted the usability of this tool.…”

Opportunities to Support Secondary Data Access Needs Among Local Health Departments

“…Limited capacity LHDs access data to quickly disseminate analyses externally, and data platforms help fill the gaps that exist due to their lack of access to staffing and expertise. This aligns with research that found limited capacity LHDs “need data that are easy to manage, understand, and communicate with.”3 (p6) Therefore, data should be analyzed and predigested into stories—ready for immediate use. Support in accessing data should center strategies for immediate application, including how to simply describe data limitations—a finding similar to that of other studies 3,7.…”

“…This aligns with research that found limited capacity LHDs “need data that are easy to manage, understand, and communicate with.”3 (p6) Therefore, data should be analyzed and predigested into stories—ready for immediate use. Support in accessing data should center strategies for immediate application, including how to simply describe data limitations—a finding similar to that of other studies 3,7. Moderate capacity LHDs use data to serve intermediate-term goals via benchmarking and resource deployment.…”

“…Support in accessing data should center strategies for immediate application, including how to simply describe data limitations-a finding similar to that of other studies. 3,7 Moderate capacity LHDs use data to serve intermediate-term goals via benchmarking and resource deployment. As a result, data are most useful when shared alongside state, regional, and national averages and support should focus on interpreting data in the context of these comparisons.…”

“…One study identified barriers of capability (eg, limited skills in research translation), opportunity (eg, limited staff capacity), and motivation (eg, perspectives of limited value to applying certain data) 1. Similarly, another study found that rural LHDs faced limited “time and training that undermined their ability to effectively use COVID-19–related data.”3 (p6) However, another study found that LHDs' desires for functionality of a dashboard are different depending upon their data skills 4. Therefore, the extent to which LHDs can access and readily use secondary data likely depends upon their level of data capacity—specifically, demand and use capacity (ie, “how and what [secondary] data are used to inform work and improve outcomes.”5 (p37) )…”