Evidence map›Paper›PMID 39626136›Full record

ArticleHealth affairs (Project Hope)2024

Lack Of Persistent Coding In Traditional Medicare May Widen The Risk-Score Gap With Medicare Advantage.

Niru Ghoshal-Datta, Michael E Chernew, J Michael McWilliams

Abstract read
In one paragraph

Article in Health affairs (Project Hope), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Capacity Planning (Capital, Staff and Costs) of Inpatient Maternity Services: Pitfalls for the Unwary.International journal of environmental research and public health · 2025
    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

3 authors.

Niru Ghoshal-DattaNiru Ghoshal-Datta, Harvard University, Boston, Massachusetts.
Michael E ChernewMichael E. Chernew (Chernew@hcp.med.harvard.edu), Harvard University.
J Michael McWilliamsJ. Michael McWilliams, Harvard University and Brigham and Women's Hospital, Boston, Massachusetts.

Funding

Tradeoffs in the Design of Public Long-Term Care BenefitsP01AG032952 · NIA · HARVARD MEDICAL SCHOOL · PI John Michael McWilliams · 2009 to 2026
$39.0M
NIA NIH HHS P01 AG032952
6 · The paper itself

Abstract

Payments to Medicare Advantage (MA) plans are adjusted by a risk-score model that is calibrated on diagnostic and demographic data from traditional Medicare beneficiaries and then applied to MA beneficiaries. If MA plans capture more diagnostic codes than traditional Medicare, they receive payment that is higher than the amount that would be spent in traditional Medicare. Although most previous research has focused on the coding practices of MA plans, less attention has been paid to the completeness of coding in traditional Medicare. We analyzed 2017-19 traditional Medicare claims data and MA encounter data to compare the persistence of diagnostic coding for sixteen chronic conditions. Our primary analysis found that the lack of persistent coding of these conditions in traditional Medicare accounted for 2.85 percentage points, or 22.3 percent, of the 2020 traditional Medicare/MA risk-score gap, translating to $8.1 billion in Medicare spending. In our most conservative sensitivity analysis, this discrepancy accounted for 9.8 percent of the total gap, although this was likely an underestimate, as it excluded acute conditions and incident chronic conditions. To resolve this discrepancy, a comprehensive approach addressing coding practices in both MA and traditional Medicare may be required.

Indexed as

Clinical CodingMedicareMedicare Part CAgedAged, 80 and overChronic DiseaseFemaleHealth ExpendituresHumansMaleUnited States

Identifiers

PMID39626136
PMCPMC12091224

What OpenQuestion holds

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Registered trials

None linked

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.