ArticleJAMIA open2021
Socially situated risk: challenges and strategies for implementing algorithmic risk scoring for care management.
Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Psychometric Evaluation of the Bilingual Russian-Kazakh Problem Gambling Severity Index: Item-Level Response Patterns and Behavioral Factors Associated with Gambling-Related Harm.Behavioral sciences (Basel, Switzerland) · 2026Article
- A qualitative interview study investigating patient, health professional, and developer perspectives on real-world implementation of patient-centered AI systems.NPJ digital medicine · 2026Article
- A qualitative Interview Study Investigating Patient, Health Professional, and Developer Perspectives on Real-World Implementation of Patient-Centered AI Systems.Research square · 2025Article
- Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.JMIR mental health · 2024Article
- Integrating the Polysocial Risk Score: Enhancing Comprehensive Healthcare Delivery.Methodist DeBakey cardiovascular journal · 2024Review
- Non-response Bias in Social Risk Factor Screening Among Adult Emergency Department Patients.Journal of medical systems · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo characterize challenges and strategies related to algorithmic risk scoring for care management eligibility determinations. MATERIALS AND
methodsInterviews 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.
resultsUtility of algorithmic risk scores was limited due to outdated claims or incomplete information about patients' socially situated risks (eg, caregiver turnover, social isolation).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
conclusionCurrent 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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Registered trials
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