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Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management

OBJECTIVE: To characterize challenges and strategies related to algorithmic risk scoring for care management eligibility determinations. MATERIALS AND METHODS: Interviews with 19 administrators from 13 physician organizations representing over 2200 physician offices and 8800 physicians in Michigan....

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Autores principales: Nong, Paige, Adler-Milstein, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433423/
https://www.ncbi.nlm.nih.gov/pubmed/34522847
http://dx.doi.org/10.1093/jamiaopen/ooab076
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author Nong, Paige
Adler-Milstein, Julia
author_facet Nong, Paige
Adler-Milstein, Julia
author_sort Nong, Paige
collection PubMed
description OBJECTIVE: To characterize challenges and strategies related to algorithmic risk scoring for care management eligibility determinations. MATERIALS AND METHODS: Interviews with 19 administrators from 13 physician organizations representing over 2200 physician offices and 8800 physicians in Michigan. Post-implementation interviews were coded using thematic analysis. RESULTS: Utility of algorithmic risk scores was limited due to outdated claims or incomplete information about patients’ socially situated risks (eg, caregiver turnover, social isolation). Resulting challenges included lack of physician engagement and inefficient use of staff time reviewing eligibility determinations. To address these challenges, risk scores were supplemented with physician knowledge and clinical data. DISCUSSION AND CONCLUSION: Current approaches to risk scoring based on claims data for payer-led programs struggle to gain physician acceptance and support because of data limitations. To respond to these limitations, physician input regarding socially situated risk and utilization of more timely data may improve eligibility determinations.
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spelling pubmed-84334232021-09-13 Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management Nong, Paige Adler-Milstein, Julia JAMIA Open Case Report OBJECTIVE: To characterize challenges and strategies related to algorithmic risk scoring for care management eligibility determinations. MATERIALS AND METHODS: Interviews with 19 administrators from 13 physician organizations representing over 2200 physician offices and 8800 physicians in Michigan. Post-implementation interviews were coded using thematic analysis. RESULTS: Utility of algorithmic risk scores was limited due to outdated claims or incomplete information about patients’ socially situated risks (eg, caregiver turnover, social isolation). Resulting challenges included lack of physician engagement and inefficient use of staff time reviewing eligibility determinations. To address these challenges, risk scores were supplemented with physician knowledge and clinical data. DISCUSSION AND CONCLUSION: Current approaches to risk scoring based on claims data for payer-led programs struggle to gain physician acceptance and support because of data limitations. To respond to these limitations, physician input regarding socially situated risk and utilization of more timely data may improve eligibility determinations. Oxford University Press 2021-09-11 /pmc/articles/PMC8433423/ /pubmed/34522847 http://dx.doi.org/10.1093/jamiaopen/ooab076 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Case Report
Nong, Paige
Adler-Milstein, Julia
Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title_full Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title_fullStr Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title_full_unstemmed Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title_short Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
title_sort socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management
topic Case Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433423/
https://www.ncbi.nlm.nih.gov/pubmed/34522847
http://dx.doi.org/10.1093/jamiaopen/ooab076
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