Estimates of Quality-Adjusted Life-Year Loss for Injuries in the United States

William Raich, Jennifer Baxter, Megan Sheahan, Jeremy Goldhaber-Fiebert, Patrick Sullivan and Janel Hanmer
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William Raich: Industrial Economics, Inc., Cambridge, MA, USA
Jennifer Baxter: Industrial Economics, Inc., Cambridge, MA, USA
Megan Sheahan: Industrial Economics, Inc., Cambridge, MA, USA
Jeremy Goldhaber-Fiebert: Stanford University School of Medicine. Stanford, CA, USA
Patrick Sullivan: PRECISIONheor, New York, NY, USA
Janel Hanmer: University of Pittsburgh Medical Center, Pittsburgh, PA, USA

Medical Decision Making, 2023, vol. 43, issue 3, 288-298

Abstract: Purpose The goal of this study is to develop an approach for estimating nationally representative quality-adjusted life-year (QALY) loss from injury and poisoning conditions using data collected in the Medical Expenditure Panel Survey (MEPS) and the National Health Interview Survey (NHIS). Methods This study uses data from the 2002–2015 NHIS and MEPS surveys. Injuries were identified in the MEPS medical events file and through self-reporting of medical conditions. We restricted our model to 163,731 adults, for which we predict a total of 294,977 EQ-5D scores using responses to the self-administered questionnaire. EQ-5D scores were modeled using age, sex, comorbidities, and binary indicators of the presence and duration of injury at the time of the health status questionnaire. These models consider nonlinearity over time during the first 3 y following the injury event. Results Injuries are identified in MEPS using medical events that provide a reasonable proxy for the date of injury occurrence. Health-related quality of life (HRQL) decrements can be estimated using binary indicators of injury during different time periods. When grouped into 29 injury categories, most categories were statistically significant predictors of HRQL scores in the first year after injury. For these groups of injuries, mean first-year QALY loss estimates range from 0.005 (sprains and strains of joints and adjacent muscles, n = 7067) to 0.109 (injury to nerves and spinal cord, n = 71). Fewer estimates are significant in the second and third years after injury, which may reflect a return to baseline HRQL. Conclusion This research presents both a framework for estimating QALY loss for short-lived medical conditions and nationally representative, community-based HRQL scores associated with a wide variety of injury and poisoning conditions. Highlights This research provides a catalog of nationally representative, preference-based EQ-5D score decrements associated with surviving a large set of injuries, based on patient-reported health status. Mean first-year QALY loss estimates range from 0.005 (sprains and strains of joints and adjacent muscles, n = 7067) to 0.109 (injury to nerves and spinal cord, n = 71). This article presents a novel methodology for assessing quality-of-life impacts for acute conditions by calculating the time elapsed between injury and health status elicitation. Researchers may explore adapting these methods to study other short-lived conditions and health states, such as COVID-19 or chemotherapy.

Keywords: EQ-5D; health measurement; injury; HRQoL; MEPS; NHIS; QALY; RQL; SF-6D; SF-12 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:43:y:2023:i:3:p:288-298

DOI: 10.1177/0272989X221141454

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