Development of an algorithm to identify fall-related injuries and costs in Medicare data.

BACKGROUND: Identifying fall-related injuries and costs using healthcare claims data is cost-effective and easier to implement than using medical records or patient self-report to track falls. We developed a comprehensive four-step algorithm for identifying episodes of care for fall-related injuries and associated costs, using fee-for-service Medicare and Medicare Advantage health plan claims data for 2,011 patients from 5 medical groups between 2005 and 2009. METHODS: First, as a preparatory step, we identified care received in acute inpatient and skilled nursing facility settings, in addition to emergency department visits. Second, based on diagnosis and procedure codes, we identified all fall-related claim records. Third, with these records, we identified six types of encounters for fall-related injuries, with different levels of injury and care. In the final step, we used these encounters to identify episodes of care for fall-related injuries. RESULTS: To illustrate the algorithm, we present a representative example of a fall episode and examine descriptive statistics of injuries and costs for such episodes. Altogether, we found that the results support the use of our algorithm for identifying episodes of care for fall-related injuries. When we decomposed an episode, we found that the details present a realistic and coherent story of fall-related injuries and healthcare services. Variation of episode characteristics across medical groups supported the use of a complex algorithm approach, and descriptive statistics on the proportion, duration, and cost of episodes by healthcare services and injuries verified that our results are consistent with other studies. CONCLUSIONS: This algorithm can be used to identify and analyze various types of fall-related outcomes including episodes of care, injuries, and associated costs. Furthermore, the algorithm can be applied and adopted in other fall-related studies with relative ease.

Targeting a high-risk group for fall prevention: strategies for health plans.

OBJECTIVES: Although 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 DESIGN: Observational study. METHODS: We 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. RESULTS: Basic 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. CONCLUSIONS: The 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.

Effect of a falls quality improvement program on serious fall-related injuries.

OBJECTIVES: To determine whether a program that improves the quality of care for falls reduces the number of episodes of care for serious fall-related injuries. DESIGN: Nonrandomized controlled trial. SETTING: Four community-based primary care practices. PARTICIPANTS: Individuals aged 75 and older who screened positive for fall risk. INTERVENTION: A multicomponent quality improvement program (Assessing Care of Vulnerable Elders Practice Redesign for Improved Medical Care for Elders) involving face-to-face clinician education about falls and decision support to prompt primary care providers to implement appropriate care, including referral to appropriate community resources, in response to individuals screening positive for fall risk. MEASUREMENTS: Episodes of care for selected fall-related injuries, based on healthcare claims. RESULTS: Of 1,791 individuals with data available for analysis, 1,187 were in the intervention group, and 604 were in the control group. Mean age was 83, and more than two-thirds of the sample were women. After adjusting for potential confounders, there were no statistically significant differences between intervention and control groups in episodes of care for fall-related injuries during the 12-month (incidence rate ratio (IRR) 1.27, 95% confidence interval (CI) = 0.93-1.73) or 24-month (IRR 1.18, 95% CI = 0.93-1.49) period after initiation of the intervention. CONCLUSION: Despite improving the care of falls, this quality improvement initiative did not result in a change in the number of episodes of care for serious fall-related injuries. Future work in community-based settings should test higher-intensity interventions to reduce fall-related injuries.