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

BACKGROUND: Impactability 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 a...

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Autores principales: Smith, Maureen A, Yu, Menggang, Huling, Jared D, Wang, Xinyi, DeLonay, Allie, Jaffery, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237769/
https://www.ncbi.nlm.nih.gov/pubmed/35699983
http://dx.doi.org/10.2196/29420
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author Smith, Maureen A
Yu, Menggang
Huling, Jared D
Wang, Xinyi
DeLonay, Allie
Jaffery, Jonathan
author_facet Smith, Maureen A
Yu, Menggang
Huling, Jared D
Wang, Xinyi
DeLonay, Allie
Jaffery, Jonathan
author_sort Smith, Maureen A
collection PubMed
description BACKGROUND: Impactability 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. OBJECTIVE: We 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. METHODS: We 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. RESULTS: In 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. CONCLUSIONS: Although 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.
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spelling pubmed-92377692022-06-29 Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study Smith, Maureen A Yu, Menggang Huling, Jared D Wang, Xinyi DeLonay, Allie Jaffery, Jonathan J Med Internet Res Original Paper BACKGROUND: Impactability 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. OBJECTIVE: We 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. METHODS: We 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. RESULTS: In 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. CONCLUSIONS: Although 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. JMIR Publications 2022-06-13 /pmc/articles/PMC9237769/ /pubmed/35699983 http://dx.doi.org/10.2196/29420 Text en ©Maureen A Smith, Menggang Yu, Jared D Huling, Xinyi Wang, Allie DeLonay, Jonathan Jaffery. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.06.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Smith, Maureen A
Yu, Menggang
Huling, Jared D
Wang, Xinyi
DeLonay, Allie
Jaffery, Jonathan
Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title_full Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title_fullStr Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title_full_unstemmed Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title_short Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study
title_sort impactability modeling for reducing medicare accountable care organization payments and hospital events in high-need high-cost patients: longitudinal cohort study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237769/
https://www.ncbi.nlm.nih.gov/pubmed/35699983
http://dx.doi.org/10.2196/29420
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