Evidence map›Paper›PMID 40929928›Full record

ArticleJournal of health economics2025

Algorithmic decision-making in health care: Evidence from post-acute care in Medicare Advantage.

Jeffrey Marr

Abstract read
In one paragraph

Article in Journal of health economics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The vendorification of Medicare Advantage.Health affairs scholar · 2026
    Article
  2. Article
  3. Article
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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

1 author.

Jeffrey MarrBrown University School of Public Health, United States of America. Electronic address: jeffrey_marr@brown.edu.

Funding

Health Services and Outcomes Research for Aging PopulationsT32AG066576 · NIA · JOHNS HOPKINS UNIVERSITY · PI CYNTHIA Melinda BOYD, Jennifer L. Wolff · 2020 to 2026
$3.8M
NIA NIH HHS T32 AG066576
6 · The paper itself

Abstract

Health insurers use predictive algorithms to determine the necessary level of care and deny services they deem unnecessary. Using a difference-in-differences design, I study the partnership of a large Medicare Advantage insurer with a firm that uses a predictive algorithm to aid post-acute care coverage decisions. This partnership led to an immediate and sustained 13 percent decline in the length of skilled nursing facility stays. This effect was partially driven by large declines in longer skilled nursing facility stays (over 30 days). Despite reductions in health care use, I do not observe changes in health outcomes following the adoption of the predictive algorithm.

Indexed as

AlgorithmsDecision MakingMedicare Part CSubacute CareAgedAged, 80 and overFemaleHumansLength of StayMaleSkilled Nursing FacilitiesUnited StatesAlgorithmsHealth insuranceMedicareMedicare Advantage

Identifiers

PMID40929928
PMCPMC13479170

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.