Predictive analytics methods for investigating inpatient volume in rural hospitals

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2 Scopus citations

Abstract

Rural hospitals continue to face significant challenges, including declining inpatient admissions, which may have a deteriorating impact on rural hospitals’ financial viability and the health care of rural residents. We use descriptive and predictive analytics to analyze trends in the average daily census (ADC), a measure of inpatient volume, and identify factors that may be associated with the ADC in Pennsylvania's rural hospitals. We use retrospective longitudinal data on Pennsylvania's rural acute care hospitals from 2000 to 2019. Overall, Pennsylvania's rural hospitals experienced a decline in ADC. Readmission index, registered nurse (RN) staffing, population over 65 years of age, and population per square mile were statistically significant and positively associated with ADC. The mortality index was statistically significant and negatively associated with ADC, and the payer mix did not seem to impact ADC. In addition, critical access hospitals (CAHs) had a statistically significant and negative association with ADC. The continuing decline in ADC may deteriorate rural hospitals’ financial stability and overall health in rural communities. Hospital administrators should consider increasing nurse staffing to improve the quality of care and patient communication to build trust. Policymakers should encourage more hospitals, especially the CAHs and smaller hospitals, to participate in the Pennsylvania Rural Health Model to ensure their financial stability.

Original languageEnglish (US)
Article number100113
JournalHealthcare Analytics
Volume2
DOIs
StatePublished - Nov 2022

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Health Informatics

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