Studies from University of Florida Provide New Data on Medical Informatics and Decision Making (Expenditure variations analysis using residuals for identifying high health care utilizers in a state Medicaid program)

Health Policy and Law Daily

2019 JUL 29 (NewsRx) -- By a News Reporter-Staff News Editor at Health Policy and Law Daily -- Investigators discuss new findings in Health and Medicine - Medical Informatics and Decision Making. According to news originating from Gainesville, United States, by NewsRx correspondents, research stated, “High utilizers receive great attention in health care research because they have a largely disproportionate spending. Existing analyses usually identify high utilizers with an empirical threshold on the number of health care visits or associated expenditures.”

Financial support for this research came from Patient-Centered Outcomes Research Institute.

Our news journalists obtained a quote from the research from the University of Florida, “However, such count-and-cost based criteria might not be best for identifying impactable high utilizers. We propose an approach to identify impactable high utilizers using residuals from regression-based health care utilization risk adjustment models to analyze the variations in health care expenditures. We develop linear and tree-based models to best adjust per-member per-month health care cost by clinical and socioeconomic risk factors using a large administrative claims dataset from a state public insurance program. The risk adjustment models identify a group of patients with high residuals whose demographics and categorization of comorbidities are similar to other patients but who have a significant amount of unexplained health care utilization. Deeper analysis of the essential hypertension cohort and chronic kidney disease cohort shows these variations in expenditures could be within individual ICD-9-CM codes and from different mixtures of ICD-9-CM codes. Additionally, correlation analysis with 3M? Potentially Preventable Events (PPE) software shows that a portion of this utilization may be preventable. In addition, the high utilizers persist from year to year. After risk adjustment, patients with higher than expected expenditures (high residuals) are associated with more potentially preventable events.”

According to the news editors, the research concluded: “These residuals are temporally consistent and hence may be useful in identifying and intervening impactable high utilizers.”

For more information on this research see: Expenditure variations analysis using residuals for identifying high health care utilizers in a state Medicaid program. Bmc Medical Informatics and Decision Making, 2019;19(1):131. (BioMed Central - http://www.biomedcentral.com/; Bmc Medical Informatics and Decision Making - http://www.biomedcentral.com/bmcmedinformdecismak/)

The news correspondents report that additional information may be obtained from C. Yang, Dept. of Computer & Information Science & Engineering, University of Florida, Gainesville, FL, United States. Additional authors for this research include C. Delcher, E. Shenkman and S. Ranka.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1186/s12911-019-0870-4. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.