Reducing Readmissions in the Safety Net Through AI and Automation

This technology-based readmission reduction initiative demonstrated efficacy in reducing readmission rates, closing equity gaps, improving survival, and leading to a positive financial impact in a safety-net health system. This approach could be an effective model of technology-based, value-based care for other resource-limited health systems to meet pay-for-performance metrics and retain at-risk funding while improving clinical and equity outcomes.

Authors

Publication Details

Journal
The American Journal of Managed Care
Published
2025-03-01
DOI
https://doi.org/10.37765/ajmc.2025.89697
Citations
4
Primary Topic
Cognitive Functions and Memory
Type
article
Field-Weighted Citation Impact
8.47
Controls
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article

Reducing Readmissions in the Safety Net Through AI and Automation

Daniel J. Bennett
4 citations
The American Journal of Managed Care
Cognitive Functions and Memory
8.47
article

Reducing Readmissions in the Safety Net Through AI and Automation

Daniel J. Bennett
article en
4 citations

Abstract

This technology-based readmission reduction initiative demonstrated efficacy in reducing readmission rates, closing equity gaps, improving survival, and leading to a positive financial impact in a safety-net health system. This approach could be an effective model of technology-based, value-based care for other resource-limited health systems to meet pay-for-performance metrics and retain at-risk funding while improving clinical and equity outcomes.

The American Journal of Managed CareVol. 31(3)
Openalex Percentile: Top 3%
Cognitive Functions and Memory
8.47
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Reducing Readmissions in the Safety Net Through AI and Automation — Daniel J. Bennett · The American Journal of Managed Care (2025) | TGRS Research Map | TGRS