To succeed under value-based payment, accountable care organizations (ACOs) must be able to link, analyze, and compare clinical and administrative data from across their constituent organizations. ACOs require a precise costing methodology, such as activity-based costing, to be able to manage costs effectively and gain critical insight into which service lines are delivering value from a clinical and financial standpoint. To support informed strategic decision-making, ACOs also require ready access to integrated patient encounter data to be able to perform the sophisticated modeling of predictive analytics.
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Background: Prior research has explored the link between health information technology (HIT) and performance of accountable care organizations (ACOs). However, the challenges of HIT use in ACOs for the management of chronic diseases among Medicare beneficiaries remain less examined.
Purpose: Given the high costs of implementing HIT and the occurrence of multiple chronic conditions (MCC) among elderly individuals, it is important to understand the extent to which HIT capabilities enable chronic disease management among the Medicare population.
Health Aff (Millwood)
January 2025
Michael E. Chernew, Harvard University.
A core problem with the current risk-adjustment system in Medicare Advantage and accountable care organization (ACO) programs-the Hierarchical Condition Categories (HCC) model-is that the inputs (coded diagnoses) can be influenced for gain by risk-bearing plans or providers. Using existing survey data on health status (which provide less manipulable inputs), we found that the use of a hybrid risk score drawing from survey data and a scaled-back set of HCCs would, in addition to mitigating coding incentives, modestly lessen risk-selection incentives, strengthen payment incentives to deliver efficient care, allocate payment across ACOs more efficiently according to markers of population health that are not as affected by practice patterns or coding efforts, and redistribute payment in a manner that supports equity goals. Although sampling error and survey nonresponse present challenges, analyses suggest that these should not be prohibitive.
View Article and Find Full Text PDFAm J Manag Care
December 2024
Institute for Accountable Care, 2001 L St NW, Ste 500, Washington, DC 20036. Email:
Objectives: To describe the prevalence and characteristics of preferred skilled nursing facility (SNF) networks established by Medicare accountable care organizations (ACOs).
Study Design: Cross-sectional analysis of a 2019 Medicare ACO survey.
Methods: We analyzed surveys from 138 Medicare ACOs to assess preferred SNF network prevalence, characteristics, and challenges.
BMC Health Serv Res
December 2024
Larner College of Medicine, University of Vermont, Burlington, VT, USA.
Background: Most approaches to healthcare reform envision an enhanced role for primary care providers, supported by innovative payment methodology and improved resources. However, there are currently no instruments to measure providers' ability and willingness to work with existing tools provided by payers, such as Accountable Care Organizations (ACO). In this study, we develop and psychometrically test a new instrument to measure provider engagement with ACOs.
View Article and Find Full Text PDFJ Public Health Manag Pract
December 2024
Author's Affiliation: Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin.
Potential changes in health care quality resulting from variation in pandemic severity since 2020 have received less attention. This study aims to assess the relationship between the pandemic and health care quality in Medicare Shared Savings Program (MSSP) accountable care organizations and identify possible heterogeneity in the relationship. The year-by-year difference-in-difference event study of MSSPs between 2016 and 2022 (N = 3390) indicated that 1 standard deviation increase in standardized cumulative COVID-19 incidence in 2020 was associated with a decrease in total quality score of 0.
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