Evidence map›Paper›PMID 36360987›Full record

ArticleInternational journal of environmental research and public health2022

Measuring the State Dependence Effect in Hospital Payment Adjustment.

Lu Liu, Wei Nai, Zan Yang

Abstract read
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Article in International journal of environmental research and public health, 2022. 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

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Lu LiuSchool of Business, St. Bonaventure University, St. Bonaventure, NY 14778, USA.
Wei NaiSchool of Electronic Information, Huzhou College, Huzhou 313000, China.ORCID 0000-0002-4656-7040
Zan YangPublic Teaching and Research Department, Huzhou College, Huzhou 313000, China.ORCID 0000-0002-1813-1768

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since FY 2013, as a part of the Affordable Care Act (ACA) program, the Hospital Value-Based Purchasing (HVBP) program has adjusted Medicare's payments to hospitals based on the total performance score of the hospital. First, the program reduces a portion of the hospital's Medicare payments in a specific fiscal year, and then, by the end of the same fiscal year, the amount of the payment reductions will be awarded to the hospitals based on the total performance score; thus, the hospitals that do not receive the reward will lose the portion of money reduced by Medicare. In this research, we apply the theory of state dependence and use the dynamic random effect probit model to estimate this effect. The results show that the hospital payment adjustment dynamics have a very significant state dependence effect (0.341); this means that hospitals that received a reward in the previous year are 34.1% more likely to receive a reward this year than the ones that received a penalty in the previous year. Meanwhile, we also find that the state dependence effect varies significantly across hospitals with different ownership (proprietary/government owned/voluntary nonprofit), and the results show that voluntary nonprofit hospitals exhibit the largest effect of state dependence (0.370), while government-owned hospitals exhibit the lowest effect of state dependence (0.293), and proprietary hospitals are in the middle. Among the factors that influence the likelihood that a hospital receives a reward, we find that teaching hospitals with a large number of beds (>400) are less likely be rewarded; in terms of ownership, we find that voluntary nonprofit hospitals are more likely be rewarded; in terms of demographic factors, hospitals where the average household income are higher within the region are more likely be rewarded.

Indexed as

Prospective Payment SystemHospitals, TeachingMedicarePatient Protection and Affordable Care ActUnited Stateseconometricshealth economicshospital payment adjustmentpublic policystate dependence effect

Identifiers

PMID36360987
PMCPMC9655927

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LicenceCC BY
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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.