Principles of Data Reorganization for Rural Health

Below are seven principles to consider when navigating the data needs of rural healthcare provision:

1. Data must be organized to allow the linkage of rural health services with population outcomes.
2. Data should support the evaluation of local innovation in health services provision to meet the population need in order for quality improvement.
3. Data must be available within a reasonable time frame, ideally less than three months
4. Data must support patient privacy while privileging system function and improvement.
5. Core data indicators need to be maintained across the system and local innovation needs to be supported.
6. Data need to be used to scale and spread system improvement.
7. Data need to be organized to respect rural generalism and enhanced skills.

Barriers like social, racial, economic, and physical factors can affect people’s access to healthcare and health outcomes.⁷ Understanding these obstacles can help to better match health care providers, centres, and preventive services to the community’s needs. Location intelligence, such as using Geographic Information System (GIS) technology, can help identify gaps in accessibility and opportunities for intervention. Consequently, by fusing demographics and location intelligence, it becomes possible to understand the unique healthcare needs of diverse communities and respond to them more effectively. This approach can make health care provision more population-centric, identifying the areas where healthcare needs are most significant and how best to address them.

In the context of rural healthcare services, Schuurman et al. developed a GIS model based on travel time to healthcare facilities to define true geographical catchments around rural hospitals.⁸ Specifically, they utilized a GIS network analysis based on vectors to create catchment models that accurately depict and map the availability of hospital-based healthcare services in rural and remote regions of BC. This tool allows for modelling where access to various services like rural maternity care or ICU can be assessed. Additionally, this catchment tool estimates the percentage of the population that can be reached within specific travel times and those that cannot. 

Similarly, researchers in Australia utilized GIS to analyze the distribution of maternity services across rural and remote Australia.⁹ Like Schuurman, they conducted a network analysis to define a health facility catchment as the surrounding geographic region that can be reached by road within a one-hour drive time. The study revealed that rural health facilities located 1 to 2 hours away from a C-section facility were more likely to offer birthing services than those closer to C-section facilities.⁹ 

Research and innovation need to be encouraged within a quality improvement framework in order to support the rapid evolution of the healthcare system. Rural has a number of advantages related associated with small population size and the self-defining isolation which provide a remarkable opportunity to evaluate natural experiments and innovation in health service delivery. If a rural community’s health services are not functioning, the opportunity to introduce radical change is present. Interventions like implementing alternative payment models for physicians, developing innovative applications of virtual care, introducing new providers like physician assistants, and bolstering rural team education can all be piloted and evaluated with relative ease and validity. Developing and implementing these kinds of healthcare changes can allow rural communities to build systems of care that may be more responsive and resilient to ecosystem disruptions like COVID-19 and climate change. 

In addition, experts in place are important and health service innovation at the local level in rural communities needs to be guided by local providers and local community representatives working together in partnership. This expertise will also support the identification of vulnerable populations within the catchment and potentially provide strategic support as necessary. Expertise in research methods, management of bias, and feasibility must be included in the partnership so that the potential for optimizing the learning system can be realized.