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The Association Between Insurance Type and Cost-Related Delay in Care: A Survey
Sora Al Rowas, MD, MSc; Michael B. Rothberg, MD, MPH; Benjamin Johnson, MD; Joel Miller, MD, MPH; Mohanad AlMahmoud, MD; Jennifer Friderici, MS; Sarah L. Goff, MD; and Tara Lagu, MD, MPH
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The Association Between Insurance Type and Cost-Related Delay in Care: A Survey

Sora Al Rowas, MD, MSc; Michael B. Rothberg, MD, MPH; Benjamin Johnson, MD; Joel Miller, MD, MPH; Mohanad AlMahmoud, MD; Jennifer Friderici, MS; Sarah L. Goff, MD; and Tara Lagu, MD, MPH
In a survey of patients and visitors to a large academic medical center, middle-income respondents with private insurance reported more cost-related delays in care than those with public insurance.
Objectives: Massachusetts has insurance rates similar to those projected under the Affordable Care Act, but many of the state's patients are insured through private insurance plans with high out-of-pocket costs. We aimed to explore the relationship between insurance type (private vs public) and delays in care due to cost, stratified by income. 
Study Design: Cross-sectional study.
Methods: We conducted a study of English-speaking adults recruited from the waiting rooms of the emergency department or outpatient clinics of a large healthcare system in western Massachusetts. Our primary outcome was the association between insurance type and cost-related delay in care, stratified by income. 
Results: Of 800 individuals approached, 619 (77%) completed the survey. Participants were 60.6% male and 40.2% white, 37.2% Hispanic, and 12.6% black. The majority (61.4%) of those surveyed had public insurance, 34.1% had private insurance, and 4.5% were uninsured. Overall, 13.3% reported delays in seeking care that were related to cost. The impact of insurance on delay of care differed significantly by income tertile (P = .02): in the middle-income group ($12,500 to <$25,000 per person annually), privately insured respondents were more likely to delay care due to cost compared with publicly insured subjects (15.6% vs 8.1%; odds ratio [OR], 4.4; 95% confidence interval [CI], 1.9-10.2, unadjusted; OR, 2.2; 95% CI, 0.9-5.8, adjusted). 
Conclusions: Cost-related delays in care are prevalent despite the presence of an insurance mandate. Middle-income, privately insured patients report more cost-related delays in care compared with publicly insured patients with similar incomes. 
Takeaway Points
  • We surveyed patients and visitors in a large emergency department and outpatient clinic about type of insurance, out-of-pocket costs, and self-reported cost-related delays in receiving medical treatment. Middle-income respondents with private insurance reported more cost-related delays in care than middle-income respondents with public insurance, although adjustment attenuated these results. 
  • These findings suggest that national healthcare policies that have pushed middle-income patients toward high-deductible healthcare plans with high out-of-pocket costs may have the unintended consequence of increasing cost-related delays in care for this group.
Due to the worse health outcomes of the uninsured, the Affordable Care Act (ACA) aimed to expand health insurance coverage through multiple interventions and mandates: expanding Medicaid coverage; incentivizing employers to provide health insurance; and, for those who do not have employer- or government-provided coverage, implementing an individual mandate for the purchase of private health insurance on a regulated health insurance marketplace.1-3 Decreasing the number of uninsured aimed to improve population health by decreasing financial barriers to healthcare.
 Patients newly insured under the ACA are a heterogeneous group that includes those with employer-sponsored insurance, those with Medicaid, and those who purchased private individual plans from state and federal exchanges.3 Because of this heterogeneity, there is a risk that some types of health insurance will not allow patients to fully access needed care. This concern is all the more relevant however, given that the most rapidly expanding insurance types under the ACA are private plans with high levels of cost sharing.4 ­­­Although these plans offer more affordable monthly premiums,5,6 they are likely to have higher co-pays and deductibles than public insurance,7,8 which may put some patients at risk for reduced access to care due to cost.
Since 2006, Massachusetts has had a mandate requiring individuals to carry health insurance, resulting in less than 5% of the population being uninsured.9 This creates insurance coverage that is similar to the coverage patterns expected nationally after full implementation of the ACA.10,11 We hypothesized that individuals in Massachusetts with private insurance would be more likely to experience cost-related delays in care than participants with public insurance, and that this association would be related to household income and co-pays. To test this hypothesis, we surveyed patients and visitors in a large health system in Massachusetts to explore the relationship between insurance type and delays in healthcare due to cost.
Study Design and Population
We identified a convenience sample of adults recruited from the waiting rooms of an emergency department (ED) and 2 outpatient primary care clinics in western Massachusetts. The ED serves a diverse population, with 110,000 patient visits annually. The outpatient clinics in the study health system serve primarily low-income patients, with 49,000 visits annually. We approached adults who were not visibly in distress in the waiting rooms of the ED and the clinics. After confirming that they were at least 18 years old and English-speaking, we invited patients and those accompanying them to participate in this study. The Baystate Medical Center Institutional Review Board approved the study protocol; informed consent was waived given that no protected health information was collected other than zip code. Data were collected between February 2014 and May 2014.
Survey Design
Using previously validated instruments as a guide,7,12-15 we developed a questionnaire to measure participants’ healthcare utilization and their reported impact of cost on utilization of healthcare (eAppendix A [eAppendices available at]). Demographic data consisted of age, sex, race, education, employment status, annual pre-tax household income, zip code, and household size.16
Our exposure variable, insurance type, was categorized as uninsured, private insurance, or public insurance. Participants were also asked to specify whether they had an individual or a family health insurance plan. We further asked whether private insurance was self-purchased or employer-sponsored, as self-purchased insurance is more likely to have higher out-of-pocket (OOP) costs.17,18 Public insurance included Medicare and Medicaid (referred to as “MassHealth” in Massachusetts), as well as a subsidized public–private insurance partnership called “Commonwealth Care.” We categorized both Medicare and Medicaid as public insurance because both have much lower premiums and less cost sharing than private insurance (although they have different patient populations and payment methods).17,18
Until January 30, 2015, Commonwealth Care was a state-subsidized plan available to individuals whose income was not low enough to qualify for Medicaid, but for whom private insurance at market rates would be a significant financial burden. Under the ACA, there is no clear comparator with Commonwealth Care, but as Commonwealth Care was highly subsidized by the state, with co-pays comparable with Medicaid’s in the lowest-income population, we opted to categorize it under public insurance.19 This decision was supported by the fact that Commonwealth Care respondents’ demographics were more similar to Medicaid/Medicare patient demographics than to the privately insured group.
The questionnaire also included questions about health and access to healthcare. We collected participants’ self-reported number of chronic medical conditions and state of health,20 as well as a variety of previously validated measures of access to care, including number of outpatient visits in the past year,21 usual source of care,21,22 prescription adherence,23 and intentional delays of medical care.16 For those who responded “yes” to delays of medical care, we asked additional questions about type of medical care that was delayed and the reasons for delaying care.
The primary outcome was delay in care due to cost, defined as voluntary delay or refusal of care by the respondent due to the cost of care involved. That is, we defined respondents as such if they affirmatively answered the question, “In the past year, have you ever delayed or avoided getting any kind of medical care?” and then selected the reason, “It cost too much money” when asked, “Why did you delay or avoid medical care?”24
Survey Administration
We first pilot-tested the survey with a sample similar to the target audience using cognitive interviewing techniques.25,26 The goals of pilot testing were to ensure clarity and completeness of the questions and to assess administration and completion time. We then revised the questionnaire based on the feedback we received. No data obtained from the pilot testing were included in the analysis. The survey administration details can be reviewed in eAppendix B.
We generated descriptive statistics as proportions for categorical factors and medians, with interquartile range (IQR) for ordinal variables. We next calculated per-person household income (PPHI) by dividing the median value of self-reported pre-tax household income category by the number of household residents. For respondents with missing PPHI, multiple imputation was used to estimate the value using available education, interview site (ED vs clinic), self-rated health, and self-rated OOP costs as predictors, chosen for their relatively high correlation with income in the complete sample.27 We then divided PPHI into tertiles. We included uninsured respondents in descriptive analyses and in calculations of income tertiles to ensure a representative sample. However, we excluded the uninsured from multivariable models as this group was too small to draw meaningful conclusions.
Because we hypothesized that those with lower incomes would be more sensitive to high co-pays and deductibles than those with higher income, we tested an “income-level by insurance category interaction term” using the Likelihood Ratio (LR) test. If the P value for the LR test of the interaction term was ≤0.2, a stratified approach would be used and separate estimates for the association between delay of care and insurance type would be presented for each income level. Final model fit was examined using the Hosmer-Lemeshow Goodness-of-Fit test. After multivariable adjustment, we wished to quantify the extent to which OOP costs and outstanding bills “explained” differences in delay of care that remained after multivariable adjustment. To do so, we added each variable to the fully adjusted model and noted the change in the insurance variable’s beta coefficient.28 We used Stata version 13.1 (StataCorp; College Station, Texas) for all analyses.
Of 800 individuals approached, 704 responded to the survey (88%). Of these, we excluded 85 (12%) questionnaires that were missing insurance category information or for which there was no response to the question regarding delayed care. Thus, we had 619 surveys completed of the 800 subjects originally approached, giving us a final response rate of 77%. Compared with those included in the study, the 85 excluded participants (who failed to complete the survey) were generally older (median age = 49.5 vs 39.5 years; P = .02), less educated (median years of education 12 vs 14; P = .001), had higher median comorbidity counts (7 vs 2; P <.001), and were more likely to be surveyed in a clinic versus the ED (68.2% vs 23.4%; P <.001).
Of the 619 participant responses analyzed, 474 participants (77%) were recruited from the ED and 145 (23%) from 2 primary care clinics. Participants’ characteristics appear in Table 1.
Household Income
Tertiles of the pre-tax PPHI distribution corresponded to cut points from the 2014 MassHealth Income Standards and Federal Poverty Guidelines29: (tertile 1: <$12,500; tertile 2: $12,500 to <$25,000; tertile 3: ≥$25,000). Household income (HHI) was missing for 111 respondents (17.9%), and we were able to impute HHI for all but 16, who were excluded from the multivariable analysis.
Health Access Issues
The median number of visits to a provider within the past 12 months was 3 (IQR = 2-8). Eight percent reported delays in filling prescriptions, and 32% reported outstanding medical bills. One-third of those analyzed reported OOP costs upwards of $500 annually (32.8%) (Table 1). Overall, 189 of the 619 subjects (30.5%; 95% confidence interval [CI], 27.0%-34.3%) reported any delay in care in the 12 months prior to completing the survey (data not shown). Of the 189 who delayed care for any reason, 82 (43%) did so due to cost. Other nonmutually exclusive reasons for delay are shown in Figure 1.
Health Issues
Forty-three percent had more than 1 chronic medical condition, with 9% reporting upwards of 5 chronic medical conditions for which they receive prescriptions. In terms of self-reported health, 35.4% reported their health to be very good or excellent and 25.7% reported their health to be fair or poor (Table 1).
Uninsured Versus Insured Participants
The uninsured were similar to the publicly insured in terms of race and income level, but were younger overall (Table 1). The uninsured had higher OOP costs than those with public insurance but less than those with private insurance (Figure 2).

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