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ObjectivesAlthough Medicare has implemented incentives for health plans to reduce fall risk, the best way to identify older people at high risk of falling and to use screening results to target fall prevention services remains unknown. We evaluated 4 different strategies using a combination of administrative data and patient-reported information that health plans could easily obtain.Study designObservational study.MethodsWe used data from 1776 patients 75 years or older in 4 community-based primary care practices who screened positive for a fear of falling and/or a history of falls. For these patients, we predicted fall-related injuries in the 24 months after the date of screening using claims/encounter data. After controlling for age and gender, we predicted the number of fall-related injuries by adding Elixhauser comorbidity count, any claim for a fall-related injury during the 12 months prior to screening, and falls screening question responses in a sequential fashion using negative binomial regression models.ResultsBasic patient characteristics, including age and Elixhauser comorbidity count, were strong predictors of fall-related injury. Among falls screening questions, a positive response to, "Have you fallen 2 or more times in the past year?" was the most predictive of a fall-related injury (incidence rate ratio [IRR], 1.56; 95% CI, 1.25-1.94). Prior claim for a fall-related injury also independently predicted this type of injury (IRR, 1.41; 95% CI, 1.05-1.89). The best model for predicting fall-related injuries combined all of these approaches.ConclusionsThe combination of administrative data and a simple screening item can be used by health plans to target patients at high risk for future fall-related injuries.

Study objective: Hospitalizations that occur shortly after emergency department (ED) discharge may reveal opportunities to improve ED or follow-up care. There currently is limited, population-level information about such events. We identify hospital- and visit-level predictors of bounce-back admissions, defined as 7-day unscheduled hospital admissions after ED discharge. Methods: Using the California Office of Statewide Health Planning and Development files, we conducted a retrospective cohort analysis of adult (aged >18 years) ED visits resulting in discharge in 2007. Candidate predictors included index hospital structural characteristics such as ownership, teaching affiliation, trauma status, and index ED size, along with index visit patient characteristics of demographic information, day of service, against medical advice or eloped disposition, insurance, and ED primary discharge diagnosis. We fit a multivariable, hierarchic logistic regression to account for clustering of ED visits by hospitals. Results: The study cohort contained a total of 5,035,833 visits to 288 facilities in 2007. Bounce-back admission within 7 days occurred in 130,526 (2.6%) visits and was associated with Medicaid (odds ratio [OR] 1.42; 95% confidence interval [CI] 1.40 to 1.45) or Medicare insurance (OR 1.53; 95% CI 1.50 to 1.55) and a disposition of leaving against medical advice or before the evaluation was complete (OR 1.90; 95% CI 1.89 to 2.0). The 3 most common age-adjusted index ED discharge diagnoses associated with a bounce-back admission were chronic renal disease, not end stage (OR 3.3; 95% CI 2.8 to 3.8), end-stage renal disease (OR 2.9; 95% CI 2.4 to 3.6), and congestive heart failure (OR 2.5; 95% CI 2.3 to 2.6). Hospital characteristics associated with a higher bounce-back admission rate were for-profit status (OR 1.2; 95% CI 1.1 to 1.3) and teaching affiliation (OR 1.2; 95% CI 1.0 to 1.3). Conclusion: We found 2.6% of discharged patients from California EDs to have a bounce-back admission within 7 days. We identified vulnerable populations, such as the very old and the use of Medicaid insurance, and chronic or end-stage renal disease as being especially at risk. Our findings suggest that quality improvement efforts focus on high-risk individuals and that the disposition plan of patients consider vulnerable populations. © 2013 American College of Emergency Physicians.