ArticleThe Milbank quarterly2010
"Impactibility models": identifying the subgroup of high-risk patients most amenable to hospital-avoidance programs.
Article in The Milbank quarterly, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Risk prediction models to predict emergency hospital admission in community-dwelling adults: a systematic review.Medical care · 2014Pooled it
- Testing the Replicability of a Successful Care Management Program: Results from a Randomized Trial and Likely Explanations for Why Impacts Did Not Replicate.Health services research · 2016Trial
- Development and validation of the Health Segment Classification of Population Encompassed within Singapore (HealthSCOPES) framework.PloS one · 2025Article
- Health care utilization and costs among coordinated care patients in Southeastern Ontario: A difference-in-differences study of a double propensity score-matched cohort.Journal of health services research & policy · 2025Article
- IAPN: a simple framework for evaluating whether a population-based risk stratification tool will be cost-effective before implementation.Cost effectiveness and resource allocation : C/E · 2024Article
- Article
- Social Frailty Index: Development and validation of an index of social attributes predictive of mortality in older adults.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Impactability Modeling for Reducing Medicare Accountable Care Organization Payments and Hospital Events in High-Need High-Cost Patients: Longitudinal Cohort Study.Journal of medical Internet research · 2022Article
- Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: observational study.BMJ (Clinical research ed.) · 2021Observational
- Predicting preventable hospital readmissions with causal machine learning.Health services research · 2020Article
- Preventing Hospital Readmissions: Healthcare Providers' Perspectives on "Impactibility" Beyond EHR 30-Day Readmission Risk Prediction.Journal of general internal medicine · 2020Article
- Effect on secondary care of providing enhanced support to residential and nursing home residents: a subgroup analysis of a retrospective matched cohort study.BMJ quality & safety · 2019Article
- Association of behavioral health factors and social determinants of health with high and persistently high healthcare costs.Preventive medicine reports · 2018Article
- Population-based analysis of patients with COPD in Catalonia: a cohort study with implications for clinical management.BMJ open · 2018Article
- What role for learning health systems in quality improvement within healthcare providers?Learning health systems · 2017Article
- Does the impact of case management vary in different subgroups of multimorbidity? Secondary analysis of a quasi-experiment.BMC health services research · 2017Article
- Patient engagement at the margins: Health care providers' assessments of engagement and the structural determinants of health in the safety-net.Social science & medicine (1982) · 2017Article
- Key aspects related to implementation of risk stratification in health care systems-the ASSEHS study.BMC health services research · 2017Review
- How can we define and analyse drug exposure more precisely to improve the prediction of hospitalizations in longitudinal (claims) data?European journal of clinical pharmacology · 2017Article
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
contextPredictive models can be used to identify people at high risk of unplanned hospitalization, although some of the high-risk patients they identify may not be amenable to preventive care. This study describes the development of "impactibility models," which aim to identify the subset of at-risk patients for whom preventive care is expected to be successful.
methodsThis research used semistructured interviews with representatives of thirty American organizations that build, use, or appraise predictive models for health care.
findingsImpactibility models may refine the output of predictive models by (1) giving priority to patients with diseases that are particularly amenable to preventive care; (2) excluding patients who are least likely to respond to preventive care; or (3) identifying the form of preventive care best matched to each patient's characteristics.
conclusionsImpactibility models could improve the efficiency of hospital-avoidance programs, but they have important implications for equity and access.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.