University of Washington Reports Findings in Managed Care (Too Sick to be True? Evaluating Potentially Problematic Diagnosis Coding Practices in Medicare’s Patient-Driven Payment Model): Managed Care

2026 FEB 23 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on Managed Care are presented in a new report. According to news reporting originating from Seattle, Washington, by NewsRx correspondents, research stated, “To use a quasi-experimental design to quantify changes in skilled nursing facility (SNF) diagnosis documentation associated with Medicare’s Patient-Driven Payment Model (PDPM). PDPM aims to promote patient-centered care in skilled nursing facilities (SNFs) by matching reimbursement to patient characteristics, including clinical complexity, which is captured in part through documentation of diagnoses.”

Financial supporters for this research include National Institute on Aging, National Center for Advancing Translational Sciences.

Our news editors obtained a quote from the research from the University of Washington, “We used a difference-in-differences design to estimate PDPM’s effects on SNF diagnosis documentation, including the number of diagnoses and clinical complexity scores via the Elixhauser comorbidity index. Hospital claims served as a non-equivalent dependent variable control. Triple interaction terms in fixed effect linear models assessed variation by SNF profit status. Changes in the probability of recording five documentation-sensitive conditions were estimated via marginal effects from generalized linear models. Secondary analysis of 100% Traditional Medicare claims (2018-2021), comprising over 4.8 million hospital-to-SNF episodes. Compared against hospital claims from hospital-SNF episodes, PDPM announcement was associated with 0.83 additional diagnoses on SNF claims, representing a relative increase of 7.1%. Similarly, Elixhauser scores increased by 0.88 points (relative 13.6%). We observed significant variation by profit status; when accounting for anticipatory behavior, profit status was associated with an additional relative 2.8% in diagnoses and 4% in Elixhauser points. PDPM was also associated with increased probability of documenting all five documentation-sensitive conditions: 3.9 percentage points (pp) for chronic pulmonary disease, 5.0 pp for complicated diabetes, 2.8 pp for heart failure, 7.3 pp for obesity, and 9.8 pp for weight loss (all reported p< 0.001). PDPM was associated with increased coding intensity across multiple measures-and more so in for-profit SNFs-highlighting the need to further evaluate whether SNFs are accurately documenting or falsely inflating clinical complexity.”

According to the news editors, the research concluded: “Sustaining Medicare’s payment accuracy will require continued monitoring of diagnosis coding behavior and its alignment with actual clinical complexity.”

This research has been peer-reviewed.

For more information on this research see: Too Sick to be True? Evaluating Potentially Problematic Diagnosis Coding Practices in Medicare’s Patient-Driven Payment Model. Health Services Research, 2026;61(2). Health Services Research can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Health Services Research - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1475-6773)

The news editors report that additional information may be obtained by contacting Rachel A. Prusynski, Dept. of Health Systems and Population Health, University of Washington, Seattle, Washington, United States. Additional authors for this research include Harsha Amaravadi, Paul A. Fishman, Natalie E. Leland and Tracy M. Mroz.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/1475-6773.70084. 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.

Publisher contact information for the journal Health Services Research is: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA.

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