Bolstering rural healthcare through data science

Rural healthcare providers, in many cases, face significant financial challenges. In 2023, 44% of rural hospitals had negative operating margins, compared to 35% of urban hospitals, according to a Kaiser Family Foundation analysis of RAND Hospital Data.(1) A UNC Sheps Center study shows the median total margins of rural hospitals are razon-thin, at 3.6% in 2022-2023 for those affiliated with health systems and 1.1% for those without such an affiliation(2). The Center for Healthcare Quality & Payment Reform estimates that in 2024, over 30% of all rural hospitals (around 700 facilities) were at risk of closing due to financial problems and over half (364) are at immediate risk of closing due to financial problems.(3)

To bolster their financial viability, rural healthcare providers must make use of all the tools in their toolbox, including pricing data that is now publicly available thanks to the Hospital Price Transparency Rule and the Transparency in Coverage Rule. However, rural healthcare providers often lack the time and resources to make effective use of this data. The challenges providers face when trying to interpret price transparency data are myriad and include:

• Massive data sets. Publicly available price transparency data covers millions of providers and tens of thousands of procedures. Sean Crandel, SVP and GM of Data and Decision Science Solutions, estimates Claritev delivers more than 126 billion enriched price transparency records. To support trending and comparisons, historical records are also needed. This compounds the volume of data needed for analysis.

• Changing file structures and information sources. File repository structures and URLs to access files often change. This makes it challenging and time consuming to retrieve pricing rate files and isolate the relevant information. Simply finding the location of hospital machine-readable files online was one of the technical challenges cited by stakeholders in a 2024 GAO review of the CMS’s implementation of hospital price transparency rules.(4)

• Labor-intensive data interpretation. Published pricing data contains significant variations that require extensive interpretation. In addition, critical information is frequently located in unexpected files or tables. The naming conventions used in the data can also be unclear or misleading. In fact, the same GAO study noted that there was no consistency and standardization for text descriptions of hospital services.

• The need for a variety of data science skills. To effectively interpret price transparency data, extensive data science and actuarial expertise are needed for efficient indexing and search capabilities. Few rural healthcare providers have this expertise in house.

Health technology companies can fill an important gap for rural healthcare providers, allowing them to overcome the above challenges through data science expertise and innovative technology. By working with experts in data science, rural healthcare organizations can:

• Leverage benchmarks to improve pricing strategies and enhance competitiveness by comparing rates across payors and geographies

• Enhance payor negotiations. Key insights derived from public price transparency data help rural healthcare organizations negotiate more effectively with payors

• Identify growth opportunities based on utilization trends and highly utilized services

• Identify key talent gaps. Based on promising market expansion opportunities, rural healthcare organizations can strategically identify and target practitioners for recruitment in high priority areas

• Optimize strategic planning process to plan effectively to meet demands for the future

With the help of new technology, publicly available data, and human expertise, providers can gain a clearer picture not only of their own pricing strategies but of the market landscape. Doing so is imperative, not just for their own financial viability, but for the wellbeing of the communities they serve. 

Sources:

 (1)10 things to know about rural hospitals. (2025, May 13). KFF. https://www.kff.org/health-costs/issue-brief/10-things-to-know-about-rural-hospitals/

(2)Srinivasan SM, Thompson K, Pink G. 2018-23 Profitability of Rural Hospitals by Ownership and System Affiliation. NC Rural Health Research Program, UNC Sheps Center, June 2024.

(3)Center for Healthcare Quality and Payment Reform. (2024). RURAL HOSPITALS AT RISK OF CLOSING. https://ruralhospitals.chqpr.org/downloads/Rural_Hospitals_at_Risk_of_Closing.pdf

(4)Health care transparency: CMS needs more information on hospital pricing data completeness and accuracy. (n.d.). U.S. Government Accountability Office (U.S. GAO). https://www.gao.gov/products/gao-25-106995