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Observational Study
. 2017 Oct;32(10):1146-1155.
doi: 10.1007/s11606-017-4072-4. Epub 2017 May 18.

Insurance Transitions and Changes in Physician and Emergency Department Utilization: An Observational Study

Affiliations
Observational Study

Insurance Transitions and Changes in Physician and Emergency Department Utilization: An Observational Study

Michael L Barnett et al. J Gen Intern Med. 2017 Oct.

Abstract

Background: Shopping for health insurance is encouraged as a way to find the most affordable coverage that best meets an enrollee's needs. However, the extent to which individuals switch insurance and subsequent changes in health care utilization that might arise, particularly new physician visits, are not well understood.

Objective: To examine the relationship between insurance switching and new physician and emergency department visits around the time of a switch.

Design: Observational study using a difference-in-differences design to compare those switching insurance carriers with propensity score-matched controls who did not switch, stratified based on whether individuals initially had private or Medicaid insurance coverage. All analyses adjusted for individual and insurance characteristics.

Participants: Continuously insured, non-elderly individuals with private or Medicaid insurance coverage in Massachusetts from 2010 to 2013.

Main measures: Rates of new primary care and specialist physician visits, as well as rates of emergency department visits.

Key results: Before matching, among 1,628,057 continuously insured individuals, 418,231 (26%) switched insurance carriers during a 2-year period. Characteristics of switchers and non-switchers were similar after matching (n = 316,343 in each group). After matching, switching plans was associated with a 203% and 47.5% increase in the rate of new primary care physician visits following switching for those initially with Medicaid or private coverage, respectively (both p < 0.001), with a large short-term increase, diminishing over time. Among those with Medicaid coverage, switching was associated with a 14.9% higher rate of ED visits during the month of switching (p < 0.001), but otherwise decreased modestly after switching.

Conclusions: Insurance switching is common, and is associated with increased new physician visits and temporarily increased ED use among the publicly insured. As insurance markets become more volatile in the current policy environment, understanding changes in utilization after insurance switching may become increasingly important.

Keywords: emergency department utilization; health insurance; insurance exchanges; primary care utilization.

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Conflict of interest statement

AB is a senior advisor at the Center for Medicare and Medicaid Innovation (CMMI), working on the Comprehensive Primary Care Plus (CPC+) initiative. All other authors declare that they do not have a conflict of interest.

Figures

Figure 1
Figure 1
Outcome rates for insurance switchers and non-switchers by type of initial insurance. Trends in outcome rates per 100 persons for new primary care physician (PCP) visits (a), new specialist physician visits (b), and emergency department (ED) visits (c) in 30-day intervals (“months”) relative to insurance switching for switchers and their matched control non-switchers. Each outcome is stratified by whether the individuals started with Medicaid or private insurance. Unadjusted rates for switchers are shown by the solid yellow/light gray line (“Switchers”). The same trend for non-switchers is shown by the solid blue/black line (“Non-switchers”). The solid vertical black line indicates the time point of insurance switching. 95% confidence intervals are shown for all unadjusted estimates, assuming a normal distribution of rates given the large sample size of individuals.
Figure 2
Figure 2
Changes in new PCP visit rates with insurance switching for individuals with initial private insurance coverage. Sensitivity analyses for trends in outcome rates per 100 persons for new primary care physician (PCP) visits in 30-day intervals (“months”) relative to insurance switching for switchers and their matched control non-switchers. a Outcomes for the subgroup of individuals with employer insurance switches or plan cancellations (n = 74,030 including controls). b Outcomes for the subgroup switching insurance on January 1 or July 1 from 2011 to 2013 (n = 273,628 including controls). c Outcomes for the subgroup of individuals living in the same ZIP Code before and after insurance switching (n = 509,038 including controls). These analyses are restricted to individuals with initial private insurance coverage. Unadjusted rates for switchers are shown by the solid yellow/light gray line (“Switchers”). The same trend for non-switchers is shown by the blue/black solid line (“Non-switchers”). The solid veritcal black line indicates the time point of insurance switching. 95% confidence intervals are shown for all unadjusted estimates, assuming a normal distribution of rates given the large sample size of individuals.
Figure 3
Figure 3
Outcome rates for individuals with initial private insurance, by change in cost sharing. Sensitivity analyses for trends in outcome rates per 100 persons for new primary care physician (PCP) visits (a) and new specialist physician visits (b) in 30-day intervals (“months”) relative to insurance switching for switchers and their matched control non-switchers. Both a and b stratify these outcomes by whether individuals switched to insurance plans with a higher, equal, or lower deductible compared to their initial plan. These analyses are restricted to individuals and their matched controls with initial private insurance coverage with deductible information available before and after switching (n = 126,830 including controls). Unadjusted rates for switchers are shown by the solid yellow/light gray line (“Switchers”). The same trend for non-switchers is shown by the blue/black solid line (“Non-switchers”). The solid vertical black line indicates the time point of insurance switching. 95% confidence intervals are shown for all unadjusted estimates, assuming a normal distribution of rates given the large sample size of individuals.

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