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The American Journal of Managed Care May 2018
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Pankaj B. Patel, MD; David R. Vinson, MD; Marla N. Gardner, BA; David A. Wulf, BS; Patricia Kipnis, PhD; Vincent Liu, MD, MS; and Gabriel J. Escobar, MD
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Impact of Formulary Restrictions on Medication Intensification in Diabetes Treatment
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Characteristics and Medication Use of Veterans in Medicare Advantage Plans
Talar W. Markossian, PhD, MPH; Katie J. Suda, PharmD, MS; Lauren Abderhalden, MS; Zhiping Huo, MS; Bridget M. Smith, PhD; and Kevin T. Stroupe, PhD
Rural Hospital Transitional Care Program Reduces Medicare Spending
Keith Kranker, PhD; Linda M. Barterian, MPP; Rumin Sarwar, MS; G. Greg Peterson, PhD; Boyd Gilman, PhD; Laura Blue, PhD; Kate Allison Stewart, PhD; Sheila D. Hoag, MA; Timothy J. Day, MSHP; and Lorenzo Moreno, PhD
Understanding Factors Associated With Readmission Disparities Among Delta Region, Delta State, and Other Hospitals
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Changes in Specialty Care Use and Leakage in Medicare Accountable Care Organizations
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Currently Reading
Nevada's Medicaid Expansion and Admissions for Ambulatory Care–Sensitive Conditions
Olena Mazurenko, MD, PhD; Jay Shen, PhD; Guogen Shan, PhD; and Joseph Greenway, MPH

Nevada's Medicaid Expansion and Admissions for Ambulatory Care–Sensitive Conditions

Olena Mazurenko, MD, PhD; Jay Shen, PhD; Guogen Shan, PhD; and Joseph Greenway, MPH
Hispanic patients with Medicaid were more likely to be admitted for ambulatory care–sensitive conditions after Nevada’s Medicaid expansion.

Objectives: In January 2014, Nevada became 1 of the 32 states that have expanded Medicaid under the Affordable Care Act. As a result of the expansion, 276,400 additional Nevada residents received Medicaid insurance. The objectives of this paper were to examine the impact of Nevada’s Medicaid expansion on changes in rates of hospital admissions for ambulatory care–sensitive conditions (ACSCs), which are potentially preventable with good access to outpatient medical care, and to examine the racial/ethnic disparities in such rates.

Study Design: We used complete inpatient discharge data (for the years 2012, 2013, and 2014, and the first 3 quarters of 2015) from all nonfederal acute care community hospitals in Nevada.

Methods: We employed pooled cross-sectional design with a difference-in-differences approach to identify overall and race/ethnicity-specific changes in admissions for ACSCs, adjusted for secular trends unrelated to expansion. We examined admissions for ACSCs among adults aged 18 to 64 years (those most likely to have been affected by the reform) admitted for overall, acute, and chronic ACSC composites in the 24 months before and 21 months after the date on which expansion was implemented.

Results: After adjusting for confounders, we found that Hispanic patients with Medicaid were more likely to be admitted for ACSCs after Nevada’s Medicaid expansion (overall quality composite: odds ratio [OR], 1.20; P = .05; chronic quality composite: OR, 1.34; P = .02).

Conclusions: This analysis provides evidence that Medicaid expansion may have limited potential to reduce the disparities in rates of hospital admissions for ACSCs. In Nevada, additional efforts might be needed to improve access to outpatient care and reduce preventable admissions.

Am J Manag Care. 2018;24(5):e157-e163
Takeaway Points
  • Hispanic patients with Medicaid were more likely to be admitted for ambulatory care–sensitive conditions after Nevada’s Medicaid expansion.
  • Nevada’s Medicaid expansion program might need to be optimized to realize improvements in access to outpatient care for minority patients.
  • This study adds to the literature on the impact of Medicaid expansions on patient outcomes and healthcare disparities.
  • For other states still considering expanding Medicaid under the Affordable Care Act, our study results suggest that a thorough assessment of available healthcare resources (eg, adequacy of healthcare provider workforce with anticipated demand for care) needs to take place prior to making a final decision.
In January 2014, Nevada became 1 of the 32 states that have expanded Medicaid eligibility under the provisions of the Affordable Care Act (ACA) to adults with annual incomes up to 138% of the federal poverty level.1 Since its expansion (January 1, 2014-June 30, 2016), 276,400 additional Nevada residents have become covered by this program.2 Total net enrollment in Nevada’s Medicaid program increased by 83% (as of July 2016), and the state is second in total enrollment only to Kentucky among all 50 states.2 Furthermore, the uninsured rate in Nevada dropped from 20% in 2013 to 15.7% in 2014.3 Unfortunately, the rapid increase in the number of Medicaid beneficiaries in Nevada has not yet seen a corresponding increase in the number of providers available to treat new Medicaid enrollees.4 Nevada ranks 48th in number of physicians and 50th in primary care physicians providing care per 100,000 residents in the United States, falling far below the national rate.5,6

An important policy concern that arises is whether the improvement in insurance coverage through Medicaid expansion can achieve positive effects on access to care in states like Nevada where healthcare resources are historically lacking, relatively more people are uninsured, and population health status and economic levels are below the national average. Previous expansions of Medicaid eligibility in individual states (eg, Massachusetts, Oregon) showed improved access to care, increased healthcare utilization, better chronic care management, and reduced out-of-pocket (OOP) expenditures among newly enrolled individuals.7-10 Similarly, individuals who received health insurance through the Medicaid expansion under the ACA reported improvements in access to outpatient care, specialty care, better preventive care coverage, improved quality of care, and better overall health.11-17

Using Nevada’s 2014 Medicaid expansion as an example, this study sheds light on how an expansion in coverage may affect access to care for Medicaid beneficiaries. We used hospital admissions for ambulatory care–sensitive conditions (ACSCs) as a validated indicator to measure the effect of Medicaid expansion on access to outpatient care.18 ACSCs are conditions that might not have occurred if the patient had received appropriate and timely outpatient care.19,20 Economic theory indicates that reduced OOP price of care (eg, through Medicaid expansion) increases demand for outpatient care.21 The increased use of outpatient care should decrease hospital admissions or emergency department (ED) visits for ACSCs among Medicaid enrollees. However, if there is a shortage in provider supply for outpatient care, the increased demand for care will most likely be diverted to the hospital or ED as an alternative for regular care.21 Given the constant number of providers in Nevada before and after ACA implementation, we hypothesized an increase in hospitalizations for ACSCs among Medicaid patients. We used a difference-in-differences (DID) design to compare longitudinal changes (from before to after ACA implementation) in hospital admissions for ACSCs. Using Nevada as a focal point, we can illustrate how residents in other expansion states with limited provider supply may experience difficulties accessing outpatient care. Furthermore, our findings could be useful for policy makers in nonexpansion states that are considering expanding Medicaid despite limited resources available to adequately cover potential new Medicaid beneficiaries.



We used the State Inpatient Data of Nevada (SIDN) for 2012, 2013, 2014, and the first 3 quarters of 2015. We did not have access to data from the fourth quarter of 2015 when the analyses were performed. The SIDN contain complete information on discharged hospital admissions from all nonfederal acute care community hospitals in Nevada. We included 213,956 hospital admissions in our analysis.


Our dependent variables were admissions for conditions that make up the Preventive Quality Indicators (PQIs), developed by the Agency for Healthcare Research and Quality (AHRQ) and endorsed by the National Quality Forum as evidence-based tools to assess access to care.22 Specifically, we used AHRQ PQI software to examine chances of being admitted for 3 composite measures for ACSCs: acute composite ACSCs (dehydration, urinary tract infection, and bacterial pneumonia), chronic composite ACSCs (short-term and long-term complications of diabetes, chronic obstructive lung disease, hypertension, heart failure, and angina), and overall composite ACSCs (acute and chronic measures combined). Three dummy variables were created for each of the 3 composite PQIs for each patient, with the value of 1 indicating the patient was admitted for a PQI and the value of 0 indicating the patient was not admitted for a PQI.

Our primary independent variables were time (whether the admission occurred before or after Medicaid expansion) and health insurance status (Medicaid vs uninsured). Among the 2 insurance groups, 1 dummy variable was created, with Medicaid coverage being coded as 1; the uninsured status served as the reference group and was coded as 0. Nevada expanded Medicaid on January 1, 2014. Thus, we considered admissions from 2012 and 2013 as prior to Medicaid expansion (coded as 0) and 2014 and 2015 as after Medicaid expansion (coded as 1).

Data Analysis

Data analysis was performed in SAS version 9.3 (SAS Institute Inc; Cary, North Carolina) and included descriptive, bivariate, and regression analyses. We used a pooled cross-sectional design, given that we were unable to track individual patients. The unit of analysis was the hospital admission, and admissions from the same patients were assumed independent. To confirm our ability to use the DID approach for multivariable data analysis, we first tested for the presence of a constant parallel trend between the Medicaid and uninsured groups before Medicaid expansion using multiple linear regression models, with insurance group and time as predictors.23-24

Because the differences between the 2 trend slopes were small and P values for time for all composites were greater or equal to .10 (the estimated marginal differences between the 2 slopes from the fitted models were 0.02 [P = .33], 0.06 [P = .10], and 0.001 [P = .95]), we concluded that there was no significant difference between Medicaid and the uninsured groups during the pre-expansion period, thus allowing us to use the DID approach for our analysis. The first difference was the odds of having a PQI hospitalization between Medicaid patients and uninsured patients. The second difference was odds of experiencing a change in the first difference before and after the Medicaid expansion. Percentages of overall, acute, and chronic composite measures among all hospital discharges were 11.2%, 3.2%, and 8.0%, respectively, indicating that the use of odds ratios (ORs) to approximate relative risk was appropriate.23 We treated hospital as the random effect, to account for the within-hospital variations. Our analytical model is presented below:
γist = β0 + β1Insurances + β2MEt + β3Insurances × MEt + θχi + εist,
where γist is a binary outcome for the i-th subject given s-type insurance and t-type Medicaid expansion, the variable Insurance is binary with Insurances = 1 when this subject belongs to the Medicaid group, and the ME (Medicaid expansion) variable is also binary with MEt = 1 when the subject is from post–Medicaid expansion. The interaction term Insurances × MEt is used to estimate the effect of Medicaid expansion in the DID approach. χi represents the independent variables from the i-th subject (eg, age, race, etc).

Our multivariate model was adjusted for the patient’s age, sex, race/ethnicity, and comorbidity index25 and for hospital-level characteristics, such as bed size, ownership type, teaching affiliation, and rural or urban location. The Institutional Review Board of the University of Nevada deemed this study exempt from human subjects research.

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