Evidence map›Paper›PMID 28345144›Full record

ArticleHealth services research2018

Adapting Evaluations of Alternative Payment Models to a Changing Environment.

Thomas W Grannemann, Randall S Brown

Abstract read
In one paragraph

Article in Health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

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

2 authors.

Thomas W GrannemannMathematica Policy Research, Cambridge, MA.
Randall S BrownMathematica Policy Research, Princeton, NJ.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify the most robust methods for evaluating alternative payment models (APMs) in the emerging health care delivery system environment. STUDY DESIGN (APPROACH): We assess the impact of widespread testing of alternative payment models on the ability to find credible comparison groups. We consider the applicability of factorial research designs for assessing the effects of these models. PRINCIPAL

findingsThe widespread adoption of alternative payment models could effectively eliminate the possibility of comparing APM results with a "pure" control or comparison group unaffected by other interventions. In this new environment, factorial experiments have distinct advantages over the single-model experimental or quasi-experimental designs that have been the mainstay of recent tests of Medicare payment and delivery models.

conclusionsThe best prospects for producing definitive evidence of the effects of payment incentives for APMs include fractional factorial experiments that systematically vary requirements and payment provisions within a payment model.

Indexed as

Centers for Medicare and Medicaid Services, U.S.Cost-Benefit AnalysisData Interpretation, StatisticalFactor Analysis, StatisticalHumansReimbursement, IncentiveReimbursement MechanismsRisk AdjustmentUnited Statesalternative payment modelsfactorial designMedicare

Identifiers

PMID28345144
PMCPMC5867185

What OpenQuestion holds

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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.