Predicting Risk of Potentially Preventable Hospitalization in Older Adults with Dementia

Reducing potentially preventable hospitalization (PPH) among older adults with dementia is a goal of Healthy People 2020, yet no tools specifically identify patients with dementia at highest risk. The objective was to develop a risk prediction model to identify older adults with dementia at high imminent risk of PPH.

A 30-day risk prediction model was developed using multivariable logistic regression. Patients from fiscal years (FY) 2009 to 2011 were split into development and validation cohorts; FY2012 was used for prediction.

Community-dwelling older adults (≥65 years of age) with dementia who received care through the Veterans Health Administration.

There were 1 793 783 participants.

Characteristics associated with hospitalization risk were (1) age and other demographic factors; (2) outpatient, emergency department, and inpatient utilization; (3) medical and psychiatric diagnoses; and (4) prescribed medication use including changes to psychotropic medications (eg, initiation or dosage increase). Model discrimination was determined by the C statistic for each of the three cohorts. Finally, to determine whether predicted 30-day risk strata were stable over time, the observed PPH rate was calculated out to 1 year.

In the development cohort, .6% of patients experienced PPH within 30 days. The C statistic for the development cohort was .83 (95% confidence interval [CI] = .83-.84) and .83 in the prediction cohort (95% CI = .82-.84). Patients in the top 10% of predicted 30-day PPH risk accounted for more than 50% of 30-day PPH admissions in all three cohorts. In addition, those predicted to be at elevated 30-day risk remained at higher risk throughout a year of follow-up.

It is possible to identify older adults with dementia at high risk of imminent PPH, and their risk remains elevated for an entire year. Given the negative outcomes associated with acute hospitalization for those with dementia, healthcare systems and providers may be able to engage these high-risk patients proactively to avoid unnecessary hospitalization.