Identification of Fall-related Injuries in Nursing Home Residents using Administrative Claims Data

Abstract

Abstract Background Fall-related injuries (FRIs) are a leading cause of morbidity, mortality, and costs among nursing home (NH) residents. Carefully defining FRIs in administrative data is essential for improving injury-reduction efforts. We developed a series of novel claims-based algorithms for identifying FRIs in long-stay NH residents. Methods This is a retrospective cohort of residents of NH residing there for ≥100 days who were continuously enrolled in Medicare Parts A and B in 2016. FRIs were identified using four claims-based case-qualifying (CQ) definitions [Inpatient (CQ1), Outpatient and Provider with Procedure (CQ2), Outpatient and Provider with Fall (CQ3), or Inpatient or Outpatient and Provider with Fall (CQ4)]. Correlation was calculated using phi correlation coefficients. Results Of 153,220 residents (mean [SD] age 81.2 [12.1], 68.0% female), we identified 10,104 with at least one FRI according to one or more CQ definition. Among 2,950 residents with hip fractures, 1,852 (62.8%) were identified by all algorithms. Algorithm CQ4 (n=326 to 2,775) identified more FRIs across all injuries while CQ1 identified less (n=21 to 2,320). CQ2 identified more intracranial bleeds (1,028 v. 448) than CQ1. For non-fracture categories, few FRIs were identified using CQ1 (n= 20 to 488). Of the 2,320 residents with hip fractures identified by CQ1, 2,145 (92.5%) had external cause of injury codes. All algorithms were strongly correlated, with phi coefficients ranging from 0.82-0.99. Conclusions Claims-based algorithms applied to outpatient and provider claims identify more non-fracture FRIs. When identifying risk factors, stakeholders should select the algorithm(s) suitable for the FRI and study purpose.