Evidence map›Paper›PMID 35699983›Full record

ArticleJournal of medical Internet research2022

Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study.

Maureen A Smith, Menggang Yu, Jared D Huling, Xinyi Wang, Allie DeLonay, Jonathan Jaffery

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Maureen A SmithDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States.ORCID 0000-0003-4370-000X
Menggang YuDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States.ORCID 0000-0002-7904-3155
Jared D HulingDivision of Biostatistics, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0003-0670-4845
Xinyi WangDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States.ORCID 0000-0002-7316-2209
Allie DeLonayDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI, United States.ORCID 0000-0002-3366-7181
Jonathan JafferyUniversity of Wisconsin Health Office of Population Health, Madison, WI, United States.ORCID 0000-0002-1965-6945
University of Wisconsin–Madison · USUniversity of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImpactability modeling promises to help solve the nationwide crisis in caring for high-need high-cost patients by matching specific case management programs with patients using a "benefit" or "impactability" score, but there are limitations in tailoring each model to a specific program and population.

objectiveWe evaluated the impact on Medicare accountable care organization savings from developing a benefit score for patients enrolled in a historic case management program, prospectively implementing the score, and evaluating the results in a new case management program.

methodsWe conducted a longitudinal cohort study of 76,140 patients in a Medicare accountable care organization with multiple before-and-after measures of the outcome, using linked electronic health records and Medicare claims data from 2012 to 2019. There were 489 patients in the historic case management program, with 1550 matched comparison patients, and 830 patients in the new program, with 2368 matched comparison patients. The historic program targeted high-risk patients and assigned a centrally located registered nurse and social worker to each patient. The new program targeted high- and moderate-risk patients and assigned a nurse physically located in a primary care clinic. Our primary outcomes were any unplanned hospital events (admissions, observation stays, and emergency department visits), count of event-days, and Medicare payments.

resultsIn the historic program, as expected, high-benefit patients enrolled in case management had fewer events, fewer event-days, and an average US $1.15 million reduction in Medicare payments per 100 patients over the subsequent year when compared with the findings in matched comparison patients. For the new program, high-benefit high-risk patients enrolled in case management had fewer events, while high-benefit moderate-risk patients enrolled in case management did not differ from matched comparison patients.

conclusionsAlthough there was evidence that a benefit score could be extended to a new case management program for similar (ie, high-risk) patients, there was no evidence that it could be extended to a moderate-risk population. Extending a score to a new program and population should include evaluation of program outcomes within key subgroups. With increased attention on value-based care, policy makers and measure developers should consider ways to incorporate impactability modeling into program design and evaluation.

Indexed as

Accountable Care OrganizationsAgedCohort StudiesHospitalsHumansLongitudinal StudiesMedicareUnited Statesbenefit scorecase managementhigh-risk patients

Identifiers

PMID35699983
PMCPMC9237769
OpenAlexW4282919714

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.