Evidence map›Paper›PMID 41661050›Full record

ArticleHealth services research2026

Too Sick to be True? Evaluating Potentially Problematic Diagnosis Coding Practices in Medicare's Patient-Driven Payment Model.

Harsha Amaravadi, Rachel A Prusynski, Paul A Fishman, Natalie E Leland, Tracy M Mroz

Abstract read
In one paragraph

Article in Health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Harsha AmaravadiDepartment of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0001-6486-9504
Rachel A PrusynskiDepartment of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.
Paul A FishmanDepartment of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.
Natalie E LelandDepartment of Occupational Therapy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-0329-3772
Tracy M MrozDepartment of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.

Funding

NRSA Training CoreTL1TR002318 · NCATS · UNIVERSITY OF WASHINGTON · PI Megan Moore · 2017 to 2026
$8.4M
The impact of post acute care payment changes on access and outcomesR01AG065371 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LELAND, NATALIE ELIZABETH, MROZ, TRACY MITCHELL · 2021 to 2024
$2.7M
NCATS NIH HHS TL1 TR002318NCATS NIH HHS TL1TR002318NIA NIH HHS AG065371NIA NIH HHS R01 AG065371
6 · The paper itself

Abstract

objectiveTo 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. STUDY SETTING AND

designWe 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. DATA SOURCES AND ANALYTIC SAMPLE: Secondary analysis of 100% Traditional Medicare claims (2018-2021), comprising over 4.8 million hospital-to-SNF episodes. PRINCIPAL

findingsCompared 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).

conclusionsPDPM 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. Sustaining Medicare's payment accuracy will require continued monitoring of diagnosis coding behavior and its alignment with actual clinical complexity.

Indexed as

Clinical CodingMedicareReimbursement MechanismsSkilled Nursing FacilitiesAgedAged, 80 and overFemaleHumansMalePatient-Centered CareUnited Statescase mix adjustmentcoding intensityfor‐profithealthcare deliverymultimorbidityreimbursement mechanismsskilled nursing facilities

Identifiers

PMID41661050
PMCPMC12884731

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.