Sarah Zheng1, Zhong Justin Ren, Janelle Heineke, Kimberley H Geissler. 1. *Department of Operations and Technology Management, Boston University Questrom School of Business, Boston ‡Department of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst †Massachusetts Institute of Technology (MIT) Sloan School of Management, Cambridge, MA.
Abstract
BACKGROUND: Diagnostic imaging utilization grew rapidly over the past 2 decades. It remains unclear whether patient cost-sharing is an effective policy lever to reduce imaging utilization and spending. MATERIALS AND METHODS: Using 2010 commercial insurance claims data of >21 million individuals, we compared diagnostic imaging utilization and standardized payments between High Deductible Health Plan (HDHP) and non-HDHP enrollees. Negative binomial models were used to estimate associations between HDHP enrollment and utilization, and were repeated for standardized payments. A Hurdle model were used to estimate associations between HDHP enrollment and whether an enrollee had diagnostic imaging, and then the magnitude of associations for enrollees with imaging. Models with interaction terms were used to estimate associations between HDHP enrollment and imaging by risk score tercile. All models included controls for patient age, sex, geographic location, and health status. RESULTS: HDHP enrollment was associated with a 7.5% decrease in the number of imaging studies and a 10.2% decrease in standardized imaging payments. HDHP enrollees were 1.8% points less likely to use imaging; once an enrollee had at least 1 imaging study, differences in utilization and associated payments were small. Associations between HDHP and utilization were largest in the lowest (least sick) risk score tercile. CONCLUSIONS: Increased patient cost-sharing may contribute to reductions in diagnostic imaging utilization and spending. However, increased cost-sharing may not encourage patients to differentiate between high-value and low-value diagnostic imaging services; better patient awareness and education may be a crucial part of any reductions in diagnostic imaging utilization.
BACKGROUND: Diagnostic imaging utilization grew rapidly over the past 2 decades. It remains unclear whether patient cost-sharing is an effective policy lever to reduce imaging utilization and spending. MATERIALS AND METHODS: Using 2010 commercial insurance claims data of >21 million individuals, we compared diagnostic imaging utilization and standardized payments between High Deductible Health Plan (HDHP) and non-HDHP enrollees. Negative binomial models were used to estimate associations between HDHP enrollment and utilization, and were repeated for standardized payments. A Hurdle model were used to estimate associations between HDHP enrollment and whether an enrollee had diagnostic imaging, and then the magnitude of associations for enrollees with imaging. Models with interaction terms were used to estimate associations between HDHP enrollment and imaging by risk score tercile. All models included controls for patient age, sex, geographic location, and health status. RESULTS: HDHP enrollment was associated with a 7.5% decrease in the number of imaging studies and a 10.2% decrease in standardized imaging payments. HDHP enrollees were 1.8% points less likely to use imaging; once an enrollee had at least 1 imaging study, differences in utilization and associated payments were small. Associations between HDHP and utilization were largest in the lowest (least sick) risk score tercile. CONCLUSIONS: Increased patient cost-sharing may contribute to reductions in diagnostic imaging utilization and spending. However, increased cost-sharing may not encourage patients to differentiate between high-value and low-value diagnostic imaging services; better patient awareness and education may be a crucial part of any reductions in diagnostic imaging utilization.
Authors: Meredith B Rosenthal; Carrie H Colla; Nancy E Morden; Thomas D Sequist; Alexander J Mainor; Zhonghe Li; Kevin H Nguyen Journal: Am J Manag Care Date: 2018-03 Impact factor: 2.229