Laura R. Wherry, PhD; Sarah Miller, PhD
Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily reflect the views of the Research Data Center, the National Center for Health Statistics, or the Centers for Disease Control and Prevention.
Acknowledgment: The authors thank Patricia Barnes and John Sullivan for their assistance in accessing the restricted-use data used in this project.
Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-2234.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Reproducible Research Statement:Study protocol: Not available. Statistical code: Available from Dr. Wherry (e-mail, firstname.lastname@example.org). Data set: Available from the National Center for Health Statistics (www.cdc.gov/rdc/index.htm).
Requests for Single Reprints: Laura R. Wherry, PhD, Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at UCLA, 911 Broxton Avenue, Room 226, Los Angeles, CA 90024; e-mail, email@example.com.
Current Author Addresses: Dr. Wherry: Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at UCLA, 911 Broxton Avenue, Room 226, Los Angeles, CA 90024.
Dr. Miller: University of Michigan, Stephen M. Ross School of Business R4416, Business Economics and Public Policy, 701 Tappan Avenue, Ann Arbor, MI 48109.
Author Contributions: Conception and design: L.R. Wherry, S. Miller.
Analysis and interpretation of the data: L.R. Wherry, S. Miller.
Drafting of the article: L.R. Wherry, S. Miller.
Critical revision of the article for important intellectual content: L.R. Wherry, S. Miller.
Final approval of the article: L.R. Wherry, S. Miller.
Statistical expertise: L.R. Wherry, S. Miller.
Administrative, technical, or logistic support: S. Miller.
Collection and assembly of data: L.R. Wherry, S. Miller.
In 2014, only 26 states and the District of Columbia chose to implement the Patient Protection and Affordable Care Act (ACA) Medicaid expansions for low-income adults.
To evaluate whether the state Medicaid expansions were associated with changes in insurance coverage, access to and utilization of health care, and self-reported health.
Comparison of outcomes before and after the expansions in states that did and did not expand Medicaid.
Citizens aged 19 to 64 years with family incomes below 138% of the federal poverty level in the 2010 to 2014 National Health Interview Surveys.
Health insurance coverage (private, Medicaid, or none); improvements in coverage over the previous year; visits to physicians in general practice and specialists; hospitalizations and emergency department visits; skipped or delayed medical care; usual source of care; diagnoses of diabetes, high cholesterol, and hypertension; self-reported health; and depression.
In the second half of 2014, adults in expansion states experienced increased health insurance (7.4 percentage points [95% CI, 3.4 to 11.3 percentage points]) and Medicaid (10.5 percentage points [CI, 6.5 to 14.5 percentage points]) coverage and better coverage than 1 year before (7.1 percentage points [CI, 2.7 to 11.5 percentage points]) compared with adults in nonexpansion states. Medicaid expansions were associated with increased visits to physicians in general practice (6.6 percentage points [CI, 1.3 to 12.0 percentage points]), overnight hospital stays (2.4 percentage points [CI, 0.7 to 4.2 percentage points]), and rates of diagnosis of diabetes (5.2 percentage points [CI, 2.4 to 8.1 percentage points]) and high cholesterol (5.7 percentage points [CI, 2.0 to 9.4 percentage points]). Changes in other outcomes were not statistically significant.
Observational study may be susceptible to unmeasured confounders; reliance on self-reported data; limited post-ACA time frame provided information on short-term changes only.
The ACA Medicaid expansions were associated with higher rates of insurance coverage, improved quality of coverage, increased utilization of some types of health care, and higher rates of diagnosis of chronic health conditions for low-income adults.
The effect on health care and patient outcomes of the 2014 state Medicaid expansions for low-income adults is of interest to politicians, policymakers, insurers, and the public.
Data from the National Health Interview Survey for 2010 to 2014 show that states implementing the expansions saw improvements in several outcomes, including insurance coverage and quality, health care utilization, and rates of diagnosis of key conditions. There was no improvement in self-reported health status among enrollees.
State Medicaid expansions seem to be achieving the broad goals of the Patient Protection and Affordable Care Act. Assessing the effects of such expansions over time, including perceptions of health status among participants, will be important.
12-mo look-back for participant response relative to timing of 2014 ACA state Medicaid expansions, by National Health Interview Survey interview month.
ACA = Patient Protection and Affordable Care Act.
Unadjusted trends in coverage outcomes, by ACA Medicaid expansion status.
The figure is based on calculations using data from the National Health Interview Survey for 2010 to 2014 and presents unadjusted weighted means in expansion and nonexpansion states by survey year. The error bars represent 95% CIs. Data from nonexpansion states are shifted slightly to the right to prevent overlap of confidence bounds. Note the differences in scale on the y-axes across outcomes. ACA = Patient Protection and Affordable Care Act.
Unadjusted trends in selected utilization, access, and health outcomes, by ACA Medicaid expansion status.
The figure is based on calculations using data from the National Health Interview Survey for 2010 to 2014 and presents unadjusted weighted means in expansion and nonexpansion states by survey year. The error bars represent 95% CIs. Data from nonexpansion states are shifted slightly to the right to prevent overlap of confidence bounds. Note the differences in scale on the y-axes across outcomes. ACA = Patient Protection and Affordable Care Act; ED = emergency department.
Table 1. Baseline Characteristics of Sample, by State Medicaid Expansion Status*
Table 2. Changes in Health Insurance Coverage and Health Care Utilization in States With Medicaid Expansions*
Table 3. Changes in Access, Health, and Diagnosed Health Conditions in States With Medicaid Expansions*
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Josh Gray, MBA, Anna Zink, BA, Tony Dreyfus, MCP, Katherine Hempstead, PhD
athenaResearch, Robert Wood Johnson foundation
April 28, 2016
The article by Wherry and Miller on Medicaid expansion uses survey data up through 2014 to show that the Affordable Care Act has increased coverage and the diagnosis of chronic disease. We reach similar conclusions, using data from clinical records through the end of 2015. Our work is part of a joint effort between the Robert Wood Johnson Foundation and athenahealth, a company offering network enabled services to health care providers. The sample broadly represents the nation’s physicians, with data from 21,900 providers, including data on 4,900 primary care physicians (PCPs) and 40 million visits by 5 million patients from 2011 to 2015.Our data show that in Medicaid-expansion states PCPs are seeing substantially more Medicaid patients. The share of visits to PCPs made by Medicaid-covered patients in expansion states rose rapidly in early 2014 and reached about one-fifth of all primary care visits, rising from about 15 percent in the first quarter of 2014 to 21 percent by the year’s end and remaining at this higher level in 2015. In the non-expansion states, the share of visits by Medicaid-covered patients remained steady over this period at about 9 percent. Analysis of visit patterns for Medicaid patients who visited a PCP for the first time in the first half of 2014 indicates that many stable relationships are forming. Among these patients, 67 percent returned for a second visit within 18 month, 38 percent visiting more than three times. Moreover, medical attention is being paid to patients who need it most – those with multiple chronic conditions. We found that the return rate for a second visit is much higher for patients diagnosed with more than one chronic disease in the first visit. The data on return visits suggest that expanded Medicaid coverage is helping patients (especially sicker patients) access regular care settings. New Medicaid patients are developing stable provider relationships which should create important continuous care rather than fragmented “one-off” services for acute problems. It remains to be seen whether these relationships will improve outcomes.1 Josh Gray, Anna Zink and Tony Dreyfus, Effects of the Affordable Care Act through 2015, March 1, 2016 (a report from the athenahealth and the Robert Wood Johnson Foundation project, “ACAView: Tracking the Impact of Health Care Reform”) available at http://www.athenahealth.com/~/media/athenaweb/file/pdf/acaview_tracking_the_impact_of_health_care_reform.
Wherry LR, Miller S. Early Coverage, Access, Utilization, and Health Effects Associated With the Affordable Care Act Medicaid Expansions: A Quasi-experimental Study. Ann Intern Med. 2016;164:795-803. doi: 10.7326/M15-2234
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Published: Ann Intern Med. 2016;164(12):795-803.
Published at www.annals.org on 19 April 2016
Cardiology, Coronary Risk Factors, Diabetes, Dyslipidemia, Endocrine and Metabolism.
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