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Use Cases

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Predictive Modelling
Evidence

"Impactibility Models”: Identifying the Subgroup of High-Risk Patients Most Amenable to Hospital-Avoidance Programs.

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Lewis, G. H.

Abstract

Context: Predictive 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.

Methods: This research used semistructured interviews with representatives of thirty American organizations that build, use, or appraise predictive models for health care.

Findings: Impactibility 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.

Conclusions: Impactibility models could improve the efficiency of hospital-avoidance programs, but they have important implications for equity and access.


Lewis, G. H. (2010). "“Impactibility Models”: Identifying the Subgroup of High-Risk Patients Most Amenable to Hospital-Avoidance Programs." Milbank Q 88(2): 240-255.



Website: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2980345/


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