OBJECTIVES: Many healthcare systems use prediction models to estimate and manage patient-level probability of hospitalization. Patients identified as high-risk at one point in time may not, however, remain high-risk. We aimed to describe subgroups of patients with distinct longitudinal risk score patterns to inform interventions tailored to patients' needs. STUDY DESIGN: Retrospective national cohort study. METHODS: Using a previously validated prediction algorithm, we identified a cohort of 258,759 patients enrolled in the Veterans Health Administration (VHA) who were in the top 5% of risk for hospitalization within 90 days. During each of the following 24 months, patients were placed in 1 of 6 categories: death, hospitalized, no VHA care, persistently high-risk for hospitalization (≥10% probability), initially high-risk then persistently low-risk (<10% probability), and intermittently high-risk. We used multivariable logistic regression to identify characteristics predictive of being persistently high-risk through the last study month. RESULTS: After 2 years, 17.7% had died, 13.8% had remained persistently high-risk for hospitalization, 41.5% had become persistently low-risk, and 19.9% were intermittently high-risk. Predictors of being persistently high-risk included urban residence, chronic medical comorbidities, auditory and visual impairment, chronic pain, any cancer diagnosis, and social instability. CONCLUSIONS: Few patients who were high-risk for hospitalization at baseline remained so. Nonrandomized evaluations of interventions that identify patients based on a single high-risk score may spuriously appear to have positive effects. Clinical interventions may need to focus on individuals who are persistently high-risk.
OBJECTIVES: Many healthcare systems use prediction models to estimate and manage patient-level probability of hospitalization. Patients identified as high-risk at one point in time may not, however, remain high-risk. We aimed to describe subgroups of patients with distinct longitudinal risk score patterns to inform interventions tailored to patients' needs. STUDY DESIGN: Retrospective national cohort study. METHODS: Using a previously validated prediction algorithm, we identified a cohort of 258,759 patients enrolled in the Veterans Health Administration (VHA) who were in the top 5% of risk for hospitalization within 90 days. During each of the following 24 months, patients were placed in 1 of 6 categories: death, hospitalized, no VHA care, persistently high-risk for hospitalization (≥10% probability), initially high-risk then persistently low-risk (<10% probability), and intermittently high-risk. We used multivariable logistic regression to identify characteristics predictive of being persistently high-risk through the last study month. RESULTS: After 2 years, 17.7% had died, 13.8% had remained persistently high-risk for hospitalization, 41.5% had become persistently low-risk, and 19.9% were intermittently high-risk. Predictors of being persistently high-risk included urban residence, chronic medical comorbidities, auditory and visual impairment, chronic pain, any cancer diagnosis, and social instability. CONCLUSIONS: Few patients who were high-risk for hospitalization at baseline remained so. Nonrandomized evaluations of interventions that identify patients based on a single high-risk score may spuriously appear to have positive effects. Clinical interventions may need to focus on individuals who are persistently high-risk.
Authors: Michelle S Wong; Tana M Luger; Marian L Katz; Susan E Stockdale; Nate L Ewigman; Jeffrey L Jackson; Donna M Zulman; Steven M Asch; Michael K Ong; Evelyn T Chang Journal: J Gen Intern Med Date: 2021-05-13 Impact factor: 5.128
Authors: G Barkai; H Amir; O Dulberg; E Itelman; G Gez; T Carmon; L Merhav; S Zigler; A Atamne; O Pinhasov; E Zimlichman; G Segal Journal: Digit Health Date: 2022-09-15