Association of the Affordable Care Act Medicaid Expansion with Dilated Eye Examinations among the United States Population with Diabetes

Journal Pre-proof Association of the Affordable Care Act Medicaid Expansion with Dilated Eye Examinations among the United States Population with Diabetes Evan Chen, BS, Grayson W. Armstrong, MD, Jacob T. Cox, MD, M.Phil, David M. Wu, MD, PhD, Donald R. Hoover, PhD, MPH, Luciano Del Priore, MD, PhD, Ravi Parikh, MD, MPH PII:

S0161-6420(19)32056-1

DOI:

https://doi.org/10.1016/j.ophtha.2019.09.010

Reference:

OPHTHA 10918

To appear in:

Ophthalmology

Received Date: 2 June 2019 Revised Date:

5 September 2019

Accepted Date: 9 September 2019

Please cite this article as: Chen E, Armstrong GW, Cox JT, Wu DM, Hoover DR, Del Priore L, Parikh R, Association of the Affordable Care Act Medicaid Expansion with Dilated Eye Examinations among the United States Population with Diabetes, Ophthalmology (2019), doi: https://doi.org/10.1016/ j.ophtha.2019.09.010. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc. on behalf of the American Academy of Ophthalmology

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Association of the Affordable Care Act Medicaid Expansion with Dilated Eye Examinations among the United States Population with Diabetes Authors: Evan Chen BS,1 Grayson W. Armstrong MD,2 Jacob T. Cox MD, M.Phil,2 David M. Wu MD, PhD,2,3 Donald R. Hoover PhD, MPH,4 Luciano Del Priore, MD, PhD,1 and Ravi Parikh MD, MPH2,3,5 1. Department of Ophthalmology and Visual Science, Yale School of Medicine, 40 Temple St., New Haven, CT, 06510, USA. 2. Department of Ophthalmology, Harvard Medical School, Boston, MA 3. Retina Service, Massachusetts Eye and Ear, Boston, MA 4. Manhattan Retina and Eye Consultants, New York, NY 5. Department of Statistics and Institute for Health Care Policy and Aging Research, Rutgers University, Piscataway, NJ, USA

Meeting Presentation: This data has been submitted and presented at the Nantucket Retina Annual Meeting, 2019 in Nantucket, MA. Financial Support: No financial support was provided for this study Conflicts of Interest(s): The author(s) have no relevant financial disclosures or conflicts Running Head: Medicaid Expansion and Dilated Exams among Diabetics Correspondence: Ravi Parikh, MD, MPH 67 E 78th Street Suite 1C New York, NY E-mail: [email protected]

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ABSTRACT Purpose: To evaluate the association between Medicaid expansion and diabetic dilated eye examinations. Design: A retrospective difference in differences analysis using individual-level survey response data from January 1, 2009 to December 31, 2017. Subjects: A total of 52,392 survey responses from 50 states and the District of Columbia between 2009 and 2017. Responders were adults aged 18-64 reporting a previous diagnosis of diabetes and a household income below 138% of the United States federal poverty line. Methods: The Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System data was used to identify survey responders who were asked about the presence of dilated eye examinations from years before and after Medicaid expansion implementation. Main Outcome Measures: The difference in differences in proportion of dilated eye examinations among diabetics 18-64 years of age with household incomes below 138% of the federal poverty line between states that did and did not implement Medicaid expansion. Results: Implementation of Medicaid expansion policies was associated with a 1.3% (95% CI, -3.8 to 6.4; p=0.61), 6.3% (95% CI, 1.3 to 11.3; p=0.016), 4.1% (95% CI, -0.8 to 9.0; p=0.11) and 2.3% (95% CI, -1.6 to 6.2; p=0.23) increase in the proportion of diabetics aged 18-64 with incomes below 138% of the federal poverty line receiving a dilated eye examination within the past year due to Medicaid expansion 1, 2, 3 and 4 cumulative years after expansion, respectively. Conclusions: Medicaid expansion policies were significantly associated with an increase in dilated eye examination rates within the first 2 years after implementation. However, this increase did not persist beyond this period with non-significant increases 3 and 4 cumulative years after implementation. Healthcare policy makers should be aware that additional measures beyond expanding insurance coverage may be necessary to increase the rate of dilated eye examinations among diabetic populations.

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Introduction

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Few aspects of ophthalmology capture the attention of the medical community as a whole as diabetic

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retinopathy. When assessing quality of care across all of healthcare in the US, the only ophthalmic quality

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benchmark included was annual dilated eye examination.1 Diabetic retinopathy screening has been shown

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to be both clinically and cost effective in preventing vision loss from diabetes.2-4 However, despite

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excellent treatments to prevent and even reverse vision loss from diabetes, such as intravitreal anti-

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vascular endothelial growth factor or pan retinal photocoagulation, diabetes remains the leading cause of

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preventable blindness in the US among adults 20-74 years of age and is the fifth most common cause of

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preventable blindness globally.5-8 Among the 30.3 million adults in the US with diabetes, approximately

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one-third have retinopathy, yet the US Centers for Disease Control and Prevention (CDC) consistently

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reports that less than two-thirds of diabetics are screened annually with a dilated ophthalmic exam.9 These

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rates are even lower amongst children and adolescents with diabetes, with less than half of youth with

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type 2 diabetes receiving an examination within 6 years of diagnosis.10,11 Detection and treatment of

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diabetic retinopathy remains a major public health challenge as the number of adults living with diabetes

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continues to increase.12

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Following the passage of the Patient Protection and Affordable Care Act (ACA), which included

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a provision for expansion of state-based Medicaid programs to provide low income individuals with

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insurance coverage, numerous studies have found improvements in patient access to high quality

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healthcare in states that chose to expand Medicaid.13 One study of Oregon Medicaid patients found, two

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years after Medicaid expansion, an increased utilization of health care services, increased rate of detection

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of diabetes, decreased rates of depression, and reduced financial strain on patients.14 Other research has

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shown that Medicaid expansion is associated with earlier presentation and more timely care for common

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general surgical conditions, and increased access to cancer screenings.15,16 However, to date, no studies

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have assessed the impact of Medicaid expansion on dilated examination rates among diabetics, despite the

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ACA mandate of zero-cost diabetic screenings to eliminate financial barriers to care.17 Therefore, the aim

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of our study was to determine if ophthalmology’s key quality indicator, annual dilated eye exams among

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diabetic patients, was also improved after the ACA’s Medicaid expansion.

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Methods

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Study Design

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This study is a retrospective difference in difference (DiD) analysis to compare rates of dilated eye

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examinations among patients diagnosed with diabetes aged 18-64 with household income below 138% of

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the federal poverty line (FPL) in states that implemented Medicaid expansion versus non-expansion states

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before (2009-2013) and after (2014-2017) Medicaid expansion.

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Data Source

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The primary data source used for this study was the CDC’s Behavioral Risk Factor Surveillance System

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(BRFSS). BRFSS is a nation-wide telephone survey of the adult population (aged 18 years or older) that

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collects over 400,000 surveys annually regarding preventative health practices and behavioral disease risk

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factors for all 50 states, the District of Columbia and three US territories.18 It has been used in multiple

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previous analyses to study diabetes and ophthalmic conditions.19,20 This data is publicly available from the

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CDC, does not contain any protected health information and was deemed exempt from institutional

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review board review by Yale University under the US Department of Health & Human Services rule 45

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CFR 46.21

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This study utilized individual-level survey responses from individuals reporting a previous diagnosis of

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diabetes, aged 18-64 years and income below 138% of the FPL residing in 50 states including the District

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of Columbia from 2009 to 2017 to capture pre- and post-expansion trends in dilated eye examinations.

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These inclusion criteria limit the study cohort to only those who would be affected by Medicaid

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expansion. Additional parameters from these surveys were gathered including responder age, gender,

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race, income, household size and diabetes status.

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Exposure and Outcome

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The definition of exposure in this study is a state-level policy expanding Medicaid coverage between

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January 1, 2014 and July 1, 2016. Of 50 included states, 32 (including DC) were defined as “Expansion

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States” according to this exposure definition. Several states expanded after 2016 or have adopted but not

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yet implemented expansion and were classified as “Non-expansion States” for this study. Included states

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that expanded in 2015 (Pennsylvania, Alaska, and Indiana) or 2016 (Montana and Louisiana) received a

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modifier to align pre- and post-expansion data points with states that expanded in 2014. States that

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expanded Medicaid after the first half of the calendar year had the next year designated as the first post-

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expansion year. Selection criteria for each analysis in this study are depicted in Figure 1 and Table S1

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depicts the list of expansion and non-expansion states included in this study.

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The main outcome of interest was the proportion of adults aged 18-64 with diabetes and income

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below 138% of the FPL reporting a dilated eye examination in the past year after being asked, "When was

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the last time you had an eye exam in which the pupils were dilated?" Previous research has shown

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substantial agreement between self-report of recent dilated eye examination details and information

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obtained from medical records with a Cohen’s kappa (κW) of 0.64.22 State-specific numbers of diagnosed

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diabetics was collected from BRFSS and included all responders responding “yes” to the question. “Has a

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doctor, nurse, or other health professional ever told you that you have diabetes?" Self-report of diabetes

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has also been shown to be highly accurate.23 Of note, because BRFSS surveys continuously throughout

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the calendar year, responses of a dilated examination within the past year may refer to a dilated

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examination in the year prior to the date of that response.

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While the American Academy of Ophthalmology currently recommends annual dilated

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examinations for diabetics, other organizations including the The American Diabetes Association

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recommends annual or biennial screening for those without evidence of retinopathy.24,25 Therefore,

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secondary analysis limiting the cohort to only those individuals responding yes to the question “Has a

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doctor ever told you that diabetes has affected your eyes or that you had retinopathy?” was conducted to

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ensure that all responders were required to receive at least annual examinations. An additional secondary

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analysis was conducted with the outcome revised to individuals receiving a dilated eye examination in the

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last 2 years (rather than 1) to account for individuals that may adhere to biennial screening guidelines.

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Statistical Analysis

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A linear regression difference in differences model was used to evaluate changes in dilated eye

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examinations in expansion vs non-expansion states. This approach compares the change in an outcome

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between a treatment group and a control group before and after a policy change and has been well

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validated to examine the effect of policy implementations provided the assumptions for the model are

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satisfied.26 Use of self-reported measures for difference-in-differences analysis has also been previously

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conducted examining Medicaid expansion’s effects on insurance status and routine cancer screening.16,27

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Linear models were used in this study due to their preferred unbiased estimation properties in fixed effect

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analyses.28 A binary indicator was created for expansion states with data from the post-expansion period.

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Separate categorical variables to control for state and year fixed effects were included as well as

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covariates to control for the number of diabetics in the state and year where each data point was collected

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as well as responder characteristics including age, sex and race. For all analyses, individual responses

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were weighted according to BRFSS calculated weights from demographic characteristics to reduce

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nonresponse bias and more accurately represent a national cross-section.29 Additionally, standard errors

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were clustered at the state level assuming no intra-group correlation between errors and allowing for

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heteroskedasticity across groups using cluster-correlated robust estimate of variance.

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Controlling for state effects allows the analysis to capture relative changes in dilated eye

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examinations in each state, preventing differing baseline rates of dilated eye examinations from impacting

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the analysis. Additionally, controlling for each state controls for time-invariant state characteristics such

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as cultural, political and other differences that are difficult to measure but could otherwise confound the

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analysis. Finally, controlling for year effects allows the capture of temporal changes in trends of dilated

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eye examinations nationally.

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One primary assumption in DiD analysis is that baseline temporal trends of the outcome are

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equivalent in expansion and non-expansion states prior to the implementation of the policy change: both

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groups are expected to continue to have similar trends in the absence of intervention. This assumption

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was tested through graphical evidence by plotting trends in dilated eye examinations in relation to the

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year of Medicaid expansion, an approach which has been used in previous studies.15,26 Further

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confirmation was conducted by regressing dilated eye examination rates on an interaction term between

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the binary indicator for expansion and a continuous year variable whose coefficient identifies if a

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differential trend in expansion and non-expansion states exists.15

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This study’s main analysis was conducted with pre-treatment data from survey responses

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collected between 2009-2013 and combined response data from the post-treatment period of 2014-2017.

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Additional analysis was conducted comparing the same pre-treatment period with varying combined post-

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treatment periods as well as individual post-treatment years to determine if the effect of Medicaid

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expansion changed over post-expansion periods.

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To assess the robustness of this study’s results, three sensitivity analyses were performed on the

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main analysis. First, a separate regression including state-specific linear time trends was included to

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adjust for differential factors that can change throughout the study period (such as cultural changes),

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which has been cited as part of the best practice methods for public health policy research.26 Second, to

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ensure that trends in dilated eye examinations did not predate the implementation of expansion, a binary

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lead indicator that states would implement Medicaid expansion 1 year in the future was included in the

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regression.30 Finally, 6 states (California, Connecticut, District of Columbia, Minnesota, New Jersey and

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Washington) had limited expansions of Medicaid prior to the 2014. These early adopting states were

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included in the main analysis but were excluded for a sensitivity analysis.31

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All statistical analyses were conducted in R 3.6.0 (R foundation for Statistical Computing,

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Vienna, Austria) and SAS 9.4 (SAS Institute). Graphpad Prism 8 (Graphpad Software, San Diego, CA)

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was used for graphical depictions. A 2-sided p-value <0.05 was considered statistically significant. Data

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are presented as means with standard deviations (SD) or 95% confidence intervals (CI) as indicated.

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Results

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In total, this study analyzed data from 52,392 survey responders from 31 expansion states and DC

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(n=28,665) and 19 non-expansion states (n=23,727) between 2009 and 2017. Survey response rates varied

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from 45.2-54.6% over the period of this study with a response rate of 45.9% in 2017.32 The study cohort’s

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unweighted sociodemographic characteristics and distribution by year are seen in Table 1. Age

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distributions were similar between expansion and non-expansion states. Responders in expansion states

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were more likely to be male (37.9% vs 35.7%), Hispanic (13.7% vs 9.4%) and non-Hispanic White

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(57.3% vs 53.9%) and less likely to be Black or African American (16.7% vs 28.2%).

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Prior to Medicaid expansion, dilated eye examination rates were stable among all states within

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this study’s populations (Fig. 2). A slight decline in examination rates was observed for both expansion

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and non-expansion states in the first year after Medicaid expansion. Expansion states then experienced a

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sharp increase in examination rates in the 2nd year after Medicaid expansion followed by a decline in 2016

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and 2017 to rates similar to pre-expansion. Amongst non-expansion states, dilated examination rates

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continued to decline immediately after expansion but increased slightly in 2016 and remained relatively

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stable in 2017. Throughout the study period, expansion states had higher dilated eye examination rates

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compared to non-expansion states for all but 2016 and 2017 (Fig. 2). Graphically, pre-expansion trends

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appear parallel between expansion and non-expansion states and adjusted models comparing pre-

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expansion trends did not reveal a significant difference for any analysis in this study (Table S2). These

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findings support the assumption of parallel trends prior to intervention and in turn, a more robust causal

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interpretation of expansion effects.

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Raw and adjusted changes in dilated examination rates before and after Medicaid expansion are

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depicted in Table 2. The raw difference in differences comparing expansion and non-expansion states

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among adults aged 18-64 diagnosed with diabetes with income <138% of the FPL indicated that Medicaid

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expansion resulted in a 2.9, 7.6, 5.9 and 3.3% increase in dilated examination rates after 1, 2, 3 and 4

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cumulative years respectively in expansion states compared to non-expansion states. In the adjusted

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model Medicaid expansion accounted for a statistically significant increase in annual examination rates

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comparing pre-expansion to the 2014-2015 post-expansion period, (6.3%; 95% CI, 1.3 to 11.3; p=0.016)

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and non-significant increases after 1 (2014 only), 3 (2014-2016) and 4 (2014-2017) cumulative years.

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When comparing pre-treatment periods with individual post-treatment years (Table 2), Medicaid

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expansion resulted in a raw increase of 2.9, 12.2, 1.0 and decrease of 0.7% in dilated examination rates

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when comparing 2009-2013 with 2014, 2015, 2016 and 2017 respectively. In adjusted DiD analysis,

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expansion was associated with a significant increase in dilated examination rates in 2015 (11.9%; 95%

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CI, 6.5 to 17.3; p<0.0001) and non-significant changes with all other individual years as post-treatment

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periods.

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In secondary analysis, limiting the cohort to only those individuals who had reported a previous

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history of diabetic eye disease (5.3%; CI, 95% CI, -0.8 to 11.4; p=0.09) or altering the outcome of interest

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to proportion of diabetics receiving dilated examinations over the past 2 years period (0.8%; 95% CI, -1.0

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to 2.6; p=0.38) resulted in nonsignificant DiD estimates for the combined post-treatment years of 2014-

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2017.

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In sensitivity analysis, inclusion of state-specific linear time trends did not result in a significant

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association between expansion and a greater number of dilated eye examinations for the combined post-

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treatment period of 2014-2017. The estimate of a binary lead indicator covariate was also non-significant

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when added to the main analysis. Finally, exclusion of early adopting states resulted in similar

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significance findings for all post-treatment cumulative and individual years including 2014-2017 (3.5%;

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95% CI, -1.1 to 8.1; p=0.15) and can be seen in Table S3.

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Discussion

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This study’s results demonstrate that while Medicaid expansion was associated with a significant increase

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in dilated eye examinations among diabetics aged 18-64 years old with household income less than 138%

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of the FPL two years after implementation, this effect was reduced and became non-significant in the

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subsequent 3rd and 4th years after implementation. To our knowledge, this is the first study assessing the

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impact of ACA’s Medicaid expansion on an ophthalmic quality of care measure.

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Recent research has shown that states implementing expansion have had measured improvements

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in coverage and reductions in uninsured rates particularly within low-income, at-risk populations when

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compared to non-expansion states, reducing the financial burden of healthcare on many Americans.13

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Amongst diabetics, Medicaid expansion has been associated with a significant increase in the number of

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insured adults with diabetes and adults receiving consistent care for diabetes and its associated chronic

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conditions.17,33,34 Additionally, routine screening for many other conditions including a variety of cancers

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were also found to have significantly improved.16 However, the large majority of these studies have

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examined the impact of expansion only 1 or 2 years after implementation. Few studies have examined

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prolonged expansion effects on health metrics beyond 2015.

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In this study, limiting the post-expansion period to 2014-2015 or 2015 alone would suggest that

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Medicaid expansion significantly improved dilated examination rates for diabetics. This trend is clearly

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observed in Figure 2 where expansion states experience a sharp surge in examinations while non-

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expansion states experienced a slight decline. It is possible that the increase in 2015 rather than in the

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immediate year after implementation is due to the phrasing of the question with responders asked about

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examinations in the past year and additional time needed for newly qualified individuals to enroll in

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Medicaid and establish care. However, examination rates in expansion states returned to baseline with

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cumulative year and individual post-expansion analyses after 2015 despite widely reported continued

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reduction in uninsurance levels for this study’s demographic through 2017.35 Examination rates in

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expansion states even appear to fall below those of non-expansion states in 2016 with this difference

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approaching significance in adjusted individual year analysis (Table 2). These results demonstrate that

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despite the ACA’s immediate success in improving dilated examination rates, increasing insurance access

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alone may not be sufficient and sustained improvement will require further policy and structural changes

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to reach expected benchmarks. The Department of Health and Human Services’ Healthy People 2020

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goals of vision care includes an aim to reduce the number of adults in the US with visual impairment due

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to diabetic retinopathy by 10%.36 This goal has yet to be reached with only 1-year remaining and changes

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beyond expansion of insurance coverage may be necessary.

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Decreased examination rates in expansion states following an initial increase is likely

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multifactorial in nature. First, the increased number of insured patients requiring examinations may

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exceed current eye care provider availability and newly eligible enrollees may not benefit in areas with

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low provider density. A recent study examining 3-year results of Medicaid expansion detected an

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increased rate of difficulty in obtaining specialist appointments in expansion states for low-income adults

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in 2016 compared to both 2014 and 2015.37 Another national study reported significantly longer

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appointment wait times in expansion states further corroborating possible demand-supply mismatch.38

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Limited provider availability among eye specialists is particularly likely given that an estimated 24% of

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US counties have no ophthalmologists or optometrists and 60.7% of counties in the US are in the lowest 2

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quartiles of both ophthalmologist and optometrist availability.39 Many of these counties are rural areas

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where long travel distances have been shown to negatively impact adherence to diabetic eye screening.40

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Furthermore, in regions with eye care specialists, many providers do not accept Medicaid enrollees; a

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recent study reported significantly greater difficulty obtaining eye care appointments with Medicaid

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compared to private insurance.41 While new enrollees requiring eye care may have been accommodated

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by eye care providers in 2014 and 2015, reduced dilated examination rates in 2016 and 2017 may reflect a

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continued increase in enrollee numbers without an equivalent increase in provider capacity.

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Second, limited access to primary care providers that provide referrals to eye care specialists may

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also be a barrier to regular dilated eye examinations. ACA mandated increases in Medicaid primary care

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payments to Medicare levels in 2013 and 2014 were correlated with several reports of improved primary

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care access immediately after expansion.13 However, results beyond the first 2 years of implementation

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are mixed with a recent study reporting that patients in expansion states reported an increase in difficulty

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obtaining primary care appointments in 2016 compared to 2015.37 Notably, in areas of low primary care

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provider supply, expansion did not significantly increase utilization of cancer screening.42 Even with

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improved primary care access, patients may face difficulty receiving referrals for diabetic eye disease due

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to inadequate screening during appointments or lack of provider referral.43 Differing guidelines in

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ophthalmic screening frequency may further compound non-uniform referral patterns for regular eye

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screenings.24,25 Notably, in this current study, a significant increase in dilated examination rates after

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expansion was not observed amongst individuals with a history of eye disease or when the outcome was

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changed to having received an examination in the past 2 years to account for biennial screening

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schedules.

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Third, limited patient awareness of diabetic eye disease and associated symptoms may reduce the

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likelihood of receiving regular dilated examinations after receiving a referral or even following an initial

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examination. In a study of a county clinic providing heavily subsidized diabetic retinopathy screening,

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only one-third of participants adhered to interval recommendations for follow-up eye appointments,

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despite minimized barriers to accessibility and cost.44 It is plausible that newly enrolled diabetics in this

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study population, who reported receiving a dilated examination in 2015, may not have returned for repeat

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screening in 2016 or 2017. A similar trend has also been observed in adherence to glucose checks

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amongst diabetics which significantly increased in expansion states in 2015 but was no longer

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significantly greater than pre-expansion rates by 2016.37 Lack of follow-up after an initial examination

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may be due to limited patient understanding of the disease; in a 2019 report, a majority of patients with

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diabetic retinopathy were unaware of their diagnosis despite receiving an dilated examination in the past

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year.45 Among patients aware of the disease, the need for routine visits may be underestimated as visual

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symptoms or functional visual loss can occur in later stages of disease after irreversible anatomical

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changes. Indeed, regular diabetic retinal screening adherence has been shown to be correlated with greater

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severity of diabetic disease.46 These findings suggest that improved dilated examination rates may require

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incorporation of eye health education initiatives even for individuals with minimal barriers to care. This is

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important for the population specifically targeted by Medicaid expansion where gaps in knowledge about

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diabetic eye complications have been significantly associated with lower dilated eye examination rates.47

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With the advent of telemedicine and artificial intelligence, opportunities for a paradigm shift in

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the approach to screening patients and improving access are numerous. In the United Kingdom, diabetic

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retinopathy is no longer the leading cause of blindness in large part due to the national diabetic

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retinopathy screening program which utilizes telemedicine to enable broader coverage.48 A

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teleophthalmology screening initiative in the United States would expand opportunities for ophthalmic

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screening to areas with fewer eye care specialists. It would also regulate the process of screening at the

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primary care level, reducing the burden on providers to specifically assess for the presence of ophthalmic

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symptoms and improve the likelihood of referral even in areas with poor referral networks. Successful

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small programs have been implemented in underserved communities in United States with the potential

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for scale-up to state-wide programs for at-risk populations.49 Augmentation of teleophthalmology

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screening with deep learning technologies to detect and grade diabetic macular edema and diabetic

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retinopathy would improve the accuracy of initial screening and decrease unnecessary escalation of

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care.50,51 This would in turn reduce difficulty obtaining appointments and wait times among patients who

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definitively require further examination. Recently, the very first Food and Drug Administration-approved

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artificial intelligence (AI) enabled device was approved for screening for referable diabetic retinopathy

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using fundus photographs in primary care offices.52 However, the success of telemedicine screening will

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depend on reimbursement and system level incentives to implement such screenings as well as patient

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adherence to referral suggestion. To address barriers to care at the patient level, education initiatives

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about screening guidelines could be specifically targeted towards those who are most likely to benefit,

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including new enrollees of Medicaid. This process may even be automated within Medicaid to

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immediately inform newly diagnosed diabetics of eye screening guidelines. After initial screening, AI-

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based diagnostic detection systems with electronic health record integration would then create automatic

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alerts for patients who have missed recommended screening checkpoints. While increased insurance

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coverage is important, future screening programs utilizing a combination of telemedicine, artificial

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intelligence algorithms and education efforts may have the potential to significantly increase diabetic eye

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screening prevalence among insured patients who do not receive regular dilated examinations.

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This study has several limitations to be considered. First, all BRFSS data is obtained via self-

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report and thus subject to respondent recall and knowledge of their condition. While self-reporting of

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diabetes care and eye examination status has been shown previously to be accurate, under-reporting of

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diabetes prevalence is possible with this method of data collection. Second, if individuals already enrolled

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in Medicaid pre-expansion comprised a large portion of survey responders, the effect of expansion may

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be underestimated. This effect is partially controlled by the presence of non-expansion states which likely

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had similar cross-sections of survey respondents. Third, the presence of a “woodwork” effect in non-

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expansion states whereby previously eligible individuals enroll in Medicaid due to increased awareness

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may diminish the observed impact of expansion in expansion states. However, this effect has also been

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observed in expansion states independent of expansion effects which may offset an associated increase in

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enrollment in non-expansion states.53,54 Fourth, the response rates of BRFSS throughout this survey range

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from 45 to 52% increasing the likelihood of this study inaccurately capturing estimates of disease and

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preventive behavior prevalence. However, the inclusion of weighting by demographic characteristics

383

reduces non-response bias and BRFSS has been shown to have similar estimates when compared to

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surveys with larger response rates such as the National Health Interview Survey.29,55 Fifth, the utilization

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of questions inquiring about dilated examinations varied by year in the BRFSS survey, with low

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responder numbers observed in 2016. This effect is partly mitigated by combining post-expansion years

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during analysis. Finally, the BRFSS survey has very few questions pertaining to vision-related features

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which may help further stratify the impact of Medicaid expansion by particularly at-risk populations.

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This study provides evidence that while Medicaid expansion was associated with an increase in

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the proportion of adults with diabetes aged 18-64 receiving dilated eye examinations within 2 years after

391

implementation, significantly increased dilated examination rates failed to persist beyond this period

392

despite sustained reductions in uninsured individuals. Increased insurance coverage may be necessary to

393

increase access to regular eye care among diabetics, however, it may not be sufficient. Continued

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improvement in this ophthalmic quality of care metric likely requires further specific measures targeting

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insured, at-risk populations such as new care delivery models and education initiatives.

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398 399 400 401 402 403 404 405 406 407 408 409 410

Legends

411 412

Figure 1. Study inclusion criteria flowchart. Of BRFSS response data available from 50 states and the

413

District of Columbia, 32 adopted and implemented Medicaid expansion between January 2014 and July

414

2016 and were categorized as “Expansion states”. Nineteen states either did not implement Medicaid

415

expansion or implemented it beyond the end of this study’s expansion period and were categorized as

416

“Non-expansion states.”

417

DC = District of Columbia

418 419

Figure 2. Trends in dilated eye examinations among diabetics by state Medicaid expansion status

420

and age group. Shaded area represents the time of Medicaid expansion. States that expanded between

421

January and February 2015 (Alaska, Indiana, Louisiana, Montana and Pennsylvania) were shifted to align

422

pre- and post-expansion data points with states that expanded in 2014.

423 424 425 426 427 428 429 430 431 432 433

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Table 1. Sociodemographic characteristics of responders aged 18 to 64 years with diabetes and income less than 138% of the federal poverty line Total Population

Expansion States

Non-expansion States

Parameter

N (%)

n (%)

n (%)

No. patients

52,392

28,665

23,727

Age group, years 18-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64

477 795 1522 2474 3900 6194 9499 12786 14745

Gender Male Female

(0.9) (1.5) (2.9) (4.7) (7.4) (11.8) (18.1) (24.4) (28.4)

278 404 798 1371 2119 3481 5210 6970 8034

(1.0) (1.4) (2.8) (4.8) (7.4) (12.1) (18.2) (24.3) (28.0)

199 391 724 1103 1781 2713 4289 5816 6711

(0.8) (1.6) (3.1) (4.6) (7.5) (11.4) (18.1) (24.5) (28.3)

19340 (36.9) 33052 (63.1)

10869 (37.9) 17796 (62.1)

8471 (35.7) 15256 (64.3)

Race Asian American Indian or Alaskan Native Black or African American Hispanic or Latino Native Hawaiian or Pacific Islander Non-Hispanic White Other

487 2361 11466 6157 140 29211 2570

(0.9) (4.5) (21.9) (11.8) (0.3) (55.8) (4.9)

396 1421 4786 3932 106 16426 1598

(1.4) (5.0) (16.7) (13.7) (0.4) (57.3) (5.6)

91 940 6680 2225 34 12785 972

(0.4) (4.0) (28.2) (9.4) (0.1) (53.9) (4.1)

Year 2009 2010 2011 2012 2013 2014 2015 2016 2017

6160 5681 7212 7365 8055 4494 4476 1922 7027

(11.8) (10.8) (13.8) (14.1) (15.4) (8.6) (8.5) (3.7) (13.4)

3845 2615 4251 3961 4024 2361 2722 739 4147

(13.4) (9.1) (14.8) (13.8) (14.0) (8.2) (9.5) (2.6) (14.5)

2315 3066 2961 3404 4031 2133 1754 1183 2880

(9.8) (12.9) (12.5) (14.3) (17.0) (9.0) (7.4) (5.0) (12.1)

Table 2. Changes in rates of dilated eye exams among diabetics with household income < 138% FPL before and after Medicaid expansion Expansion States

Post-expansion period

Before Average, %

After Average, %

Non-expansion States

Difference, %

Before Average, %

After Average, %

Difference, %

Raw change in dilated exams after expansion

Adjusted change in dilated exams after expansion

Difference in Differences, % (±SD)

Difference in Differences, % (95% CI) [p-value]

Cumulative years 2014

54.6

54.0

-0.6

54.8

51.3

-3.5

2.9±1.5

1.3 (-3.8 to 6.4) [0.61]

2014-2015

54.6

57.9

3.3

54.8

50.5

-4.3

7.6±1.1

6.3 (1.3 to 11.3) [0.016]

2014-2016

54.6

57.4

2.8

54.8

51.7

-3.1

5.9±1.0

4.1 (-0.8 to 9.0) [0.11]

2014-2017

54.6

55.7

1.1

54.8

52.6

-2.2

3.3±0.8

2.3 (-1.6 to 6.2) [0.23]

2014

54.6

54.0

-0.6

54.8

51.3

-3.5

2.9±1.5

1.3 (-3.8 to 6.4) [0.61]

2015

54.6

61.6

7.0

54.8

49.6

-5.2

12.2±1.6

11.9 (6.5 to 17.3) [<0.0001]

2016

54.6

55.7

1.1

54.8

54.9

0.1

1.0±2.1

-3.8 (-8.1 to 0.5) [0.08]

2017

54.6

53.5

-1.1

54.8

54.4

-0.4

-0.7±1.3

0.6 (-3.3 to 4.5) [0.98]

Individual years

Medicaid expansion was associated with a significant increase in the proportion of US adults with diabetes receiving dilated eye examinations within 2 years after implementation and non-significant increases 3 and 4 years after implementation.