The Journal of Texas Medicine: August 2013

Barriers to Health Care Among Bell County Residents With Health Insurance Medical Aid 

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Tex Med. 2013;109(8):e1.

By Theresa Castilla, MA; Jinmyoung Cho, PhD; Matthew L. Smith, PhD, MPH, CHES; Angela K. Hochhalter, PhD; and Marcia G. Ory, PhD, MPH

Scott & White Healthcare, Temple, Texas (Ms Castilla and Drs Hochhalter and Cho); Texas A&M Health Science Center School of Rural Public Health, College Station, Texas (Drs Cho, Ory, and Smith); and The University of Georgia College of Public Health, Athens, Georgia (Dr Smith). Send correspondence to Theresa Castilla, Scott & White Healthcare, 2401 S 31st St, MS-14-A137A, Temple, TX 76508; email: tcastilla@sw.org.

Abstract

Barriers to high-quality health care are associated with negative consequences, not only for the uninsured but also for persons with adequate health insurance or medical aid. Understanding barriers encountered by community residents can improve the outcomes of community interventions designed to address unmet health care needs. The Bell County Needs Assessment was conducted to understand the needs of residents in Bell County, Texas. The current study examined residents' (n = 1422) self-reported barriers to health care and factors associated with reporting one or more such barriers. The most common barriers reported were issues related to health care access and socioeconomic barriers. Residents reporting use of urgent care, emergency room, and walk-in clinics as a regular source of care were significantly more likely to experience two or more barriers to health care (OR = 2.543). Community health interventions may be improved by focusing on reducing barriers among patients who rely on urgent or emergency services as their usual source of care.

Introduction

Provision of high-quality care that meets patients' needs without unnecessarily using limited health care resources is a national goal that affects local payers, providers, and health care consumers. While having adequate health insurance coverage reduces financial barriers to care, persons with adequate health insurance coverage or medical aid still experience barriers to receiving needed high-quality health care. Barriers to care can have severe consequences including increased morbidity and use of high-cost and high-intensity services for reasons that are potentially avoidable.1,2 For example, patients may seek care at an emergency department if they are unable to access primary care services when they have a perceived need.3 Other examples of health care barriers include transportation limitations, lack of child care, not knowing where to go for care, delayed appointments due to lack of providers or suboptimal processes in care settings, and ineffective communication between patients and providers.4-8

The Chronic Care Model9,10 and Patient Centered Medical Home (PCMH) Model emphasize the need for community-wide or system-level approaches to addressing barriers to high-quality health care.11 Evidence suggests the care delivered under these models can improve care quality and reduce the use of high-cost, high-intensity services. For example, Group Health Cooperative found a greater reduction in both emergency department visits and hospitalizations for patients in clinics implementing PCMH compared with those of other group health clinics.12 Efforts to tailor these and other system-based or community-based approaches to meet local patient needs may benefit from information about specific barriers encountered by community groups with the capacity to receive services.

This study documents barriers to health care reported by residents of Bell County, Texas, using any type of health insurance or medical aid. The uninsured population was excluded from this study because that group -- a substantial part of the population in Texas -- faces unique barriers to care that require separate consideration. The objectives of the study are to describe self-reported health care barriers and to examine factors associated with reporting one or more barriers to health care in the study sample.

Methods

Bell County Community Needs Assessment

Survey data were collected as part of the Bell County Community Needs Assessment, which was conducted by the Bell County Community Needs Coalition between April and June 2010. The survey was one aspect of a multimethod assessment conducted by the coalition to identify health and human services needs in the county. The coalition comprised 14 agencies representing state and local governments, health care systems, universities, and human service agencies. Representatives worked with consultants from Texas Health Institute to develop survey items, plan survey administration, and advertise the assessment across the county.13  

The United Way of Central Texas website hosted links to the 35-item questionnaire in Survey Monkey. In addition, a 2-page paper-based version of the questionnaire was distributed in all areas of the county. A paper-based version of the questionnaire was available also at various locations, including local government buildings and human service agencies. Both versions of the survey were available in English, Spanish, and Korean. Emails and letters containing the uniform resource locator (URL) and an invitation to participate in the assessment were sent to potential participants using lists provided by United Way of Central Texas. In addition, 150 chief executive officers were asked to encourage their employees to complete the online questionnaire, press releases were distributed to the media, and efforts were made to target specific groups including low-income populations and the Korean-American population. A total of 2893 questionnaires were completed.

Measures

Health Care Barriers. Health care barriers were defined by responses to a single multipart question on the survey: "Within the last year, if you or someone in your household have needed the following health services, but did not get them, please identify the reason(s) why (Select all that apply)." Participants selected from 11 reasons why someone in their household did not get needed care (eg, "don't know where to go," "lack of childcare"). Reasons were selected for 7 types of services: health care, vision care, dental care, mental health care, prenatal care, medicine, and durable medical equipment. Only reasons associated with "health care" were included in this study. One option for a reason that needed care was not obtained was described on the survey as "no insurance, unable to pay." This response option was excluded from the study because the study topic was limited to barriers among those with some level of health insurance or medical aid.

Independent Variables. Responses to 10 items about individual characteristics (ie, sociodemographics, health status, and primary health care source) were also included in the analysis.

Age. Respondents reported their age in categories that included "16 to 21 years old" (excluded from this analysis), "22 to 29 years old," "30 to 35 years old," "36 to 50 years old," "51 to 59 years old," "60 to 64 years old," "65 to 75 years old," and "76 years old and over." Age categories were collapsed into the following groups for analyses: 22-35 years, 36-50 years, 51-64 years, and 65+ years.

Gender. Respondents endorsed "female" or "male" when asked "What is your gender?"

Education. Respondents answered "What is the highest level of education you have completed? (Select one answer)" with the following options: "8th grade or less," "some high school, but did not graduate," "high school or GED," "vocational certification," "some college," "postgraduate education," or "other" (excluded from this analysis). Education categories were then collapsed into the following groups for analyses: less than high school, high school or GED, some college/vocational certificate, and college graduation/postgraduate.

Race and Ethnicity. Respondents answered "Which of the following would you say is your race?" with one of the following options: "white," "black or African American," "Asian," "Hispanic or Latino," "Native Hawaiian or other Pacific Islander," "American Indian or Alaska Native," or "other." The following categories were used for analyses: Non-Hispanic White, Black/African American, Hispanic/Latino, and Other.

Marital Status. Marital status was documented with responses to the question "What is your marital status? (Select one answer)" indicated as "single/never-married," "domestic partnership," "married," "divorced," or "widow/widower." For the analysis, marital status was organized into the following: single/never-married, married/domestic partner, divorced/widow/widower.

Employment Status. Respondents answered the question "What is your employment status? (Select all that apply)" by endorsing one or more of the following: "employed full-time," "employed part-time," "active military," "self-employed," "unemployed," "student," "retired," and "other" (excluded from this analysis). Responses were categorized for the analysis as follows: full-time/self-employed/on-military, employed/part-time/student, retired, and unemployed.

Military Status. Bell County, Texas, is home to Fort Hood, a large Army base. Needs of the military community were particularly important for the coalition to assess. Military status of the respondent or spouse was identified through the following question: "Have you or your spouse ever served on active duty in the U.S. Armed Forces, Military Reserves or National Guard?" For the purposes of this study, active duty did not include training for the Reserves or National Guard but did include activation (eg, for the Persian Gulf War). Response options included "yes, now on active duty," "yes, on active duty in the past, but not now," "no, never served in the military," and "no, training for Reserves or National Guard only." Military status categories were collapsed for analyses into the following groups: active duty; active duty in the past, not now; and never served/training only.

Household Income. Respondents indicated their household income answering "What is your annual household income (Select one answer)?" by using the following categories: "Less than $10,000," "$10,000 to $14,999," "$15,000 to 24,999," "$25,000 to 34,999," "$35,000 to 49,999," "$50,000 to 74,999," $75,000 to $99,999," "$100,000 and above," and "I do not know" (excluded from this analysis). Income categories were collapsed for analyses to the following: less than $25,000, $25,000-$49,999, $50,000-$74,999, $75,000-$99,999, and more than $100,000.

Self-rated Health. Self-rated health was assessed with the question "Generally, would you say your health is: (Select one answer)." Response options were "excellent," "very good," "fair," and "poor."

Usual Source of Care. Respondents were asked "Which one of the following choices best describes where you go most regularly for health care? (Select one answer)." Response options were "doctor's office," "emergency room," "public/community clinic," "free clinic," "Fort Hood clinics," "urgent care/walk-in clinic," "none," "other, please explain:_____," and "have not needed health care in the past 12 months." For analysis, responses were grouped into the following categories: doctor's office/Fort Hood clinics, free clinic/public/community clinic, and urgent care/walk-in clinic/emergency room. All other responses (eg, "other") were not considered.

Data Analysis

Three analyses were conducted. First, frequencies were calculated to identify the percent of participants who endorsed each of the 11 health care barriers. Second, using Pearson's chi-squared tests, we compared the frequency distribution of participant characteristics (ie, independent variables) with the number of health care barriers reported (ie, 0, 1, 2+). Third, multinomial logistic regression was conducted to explain the contribution of the independent variables on the number of health care barriers reported. The category of reporting no health care barriers served as the referent group. Odds ratios (ORs) and 95% confidence intervals (95% CIs) are presented. All statistical analyses were conducted with SPSS statistical software (version 20.0).

Participants

Participants completed the confidential survey distributed by the Bell County Community Needs Assessment (n = 2893). Participants who were younger than 22 years and those without insurance (n = 608) were omitted from analyses. Young respondents were excluded because age was reported in categories beginning with age 16 to 21. This entire category was excluded to avoid reports from minors whose access to care was likely to be partly determined by parents. Persons who reported having no source of insurance were excluded because having no insurance is a well-known barrier to health care. Exclusion of this group allowed analysis of barriers for those who do have at least some sort of insurance coverage. Additional individual respondents were excluded from the study because data for some of the variables of interest were missing on their surveys (n = 863). The final analytic sample consisted of 1422 participants.

Results

Sample Characteristics by Number of Health Care Barriers

Participants' endorsement for each of the 11 health care barriers is displayed in Table 1. The 5 barriers endorsed by most participants were "long office wait times," "unable to pay copays," "doctor not accepting new patients," "unable to leave work," and "waiting list."

The characteristics of study participants by number of reported health care barriers are presented in Table 2. Of the 1422 respondents, 79.9% reported having no health care barriers in the past year, 11.4% reported having 1 health care barrier, and 8.7% reported having 2 or more health care barriers. Most participants were female, non-Hispanic white, married or in a domestic partnership, and had at least graduated college. More than two-thirds (78.0%) of participants were employed, and 65.8% had never served in the military or received military training. Approximately one-quarter of participants (24.3%) reported their annual income to be between $50,000 and $74,999, and more than half (52.9%) rated their health as very good. The largest proportion of participants reported going regularly to their doctor's office or to a Fort Hood clinic for health care (95.1%).

When comparing participant characteristics by the number of health care barriers reported in the past year, a significantly larger proportion of those aged 36 to 50 (χ2 = 28.46, P < 0.001), females (χ2 = 11.67, P = 0.003), and those who self-identified as African American or Hispanic (χ2 = 21.35, P = 0.002) reported more barriers than comparison groups. Conversely, a significantly smaller proportion of those with a college education than those in other educational categories reported health care barriers (χ2 = 20.48, P = 0.002). A larger proportion of participants who had full-time jobs, were self-employed, or were on active military duty reported more health care barriers, whereas a significantly larger proportion of those who were retired reported no health care barriers than other military categories (χ2 = 22.03, P = 0.001). A larger proportion of participants reporting annual incomes of $50,000 or more reported significantly fewer health care barriers, whereas a significantly larger proportion of those making between $25,000 and $49,999 reported having more health care barriers than those in other income categories (χ2 = 77.50, P < 0.001). A larger proportion of participants reporting fair or poor health reported having more health care barriers than those in very good or excellent health (χ2 = 66.94, P < 0.001). Lastly, a significantly larger proportion of participants who received regular health care from a doctor's office or a Fort Hood clinic reported fewer barriers, whereas those reporting receiving their regular health care from free clinics/public community clinics and from urgent care/walk-in clinics/ER reported significantly more health care barriers than groups with other usual sources of care (χ2 = 42.22, P < 0.001).

Factors Associated With Reporting Health Care Barriers

Multinomial logistic regression examining factors associated with reporting one and two or more health care barriers in the previous year are presented in Table 3 (reporting no health care barriers served as the reference group). Compared with those reporting no health care barriers, participants between the ages of 51 through 64 years (OR = 0.595, CI = 0.355-0.998) and those aged 65 years and older (OR = 0.372, CI = 0.151-0.916) were significantly less likely to report having one health care barrier in the past year. Participants who reported serving in the military in the past (OR = 0.617, CI = 0.394-0.968) or being on active military duty (OR = 0.093, CI = 0.012-0.706) were significantly less likely to report having one health care barrier in the past year. Participants who reported having an annual income of $100,000 or more (OR = 0.223, CI = 0.089-0.561) and those reporting excellent health (OR = 0.331, CI = 0.122-0.901) were significantly less likely to report having one health care barrier in the past year. Conversely, those reporting they received regular health care from urgent care/walk-in clinics/ER were significantly more likely to report one health care barrier (OR = 2.543, CI = 1.136-5.695).

Compared with those reporting no health care barriers, participants aged 65 years and older (OR = 0.191, CI = 0.048-0.771) and those who were unemployed (OR = 0.265, CI = 0.089-0.783) were significantly less likely to report having two or more health care barriers in the past year. Participants who reported very good health (OR = 0.284, CI = 0.114-0.705) or excellent health (OR = 0.123, CI = 0.038-0.394) were significantly less likely to report two or more health care barriers. Conversely, those reporting they received regular health care from urgent care/walk-in clinics/ER were significantly more likely to report two or more health care barriers than those with other sources of usual care (OR = 4.258, CI = 1.847-9.814).

Discussion

Approximately 20% of Bell County residents reported experiencing barriers to needed care in the past year. The most commonly endorsed barriers were health care access issues (eg, wait times and doctors not taking patients) and socioeconomic barriers (eg, unable to pay copayments and unable to leave work). Health care systems or health care-public health partnerships may deem these barrier-related findings useful for tailoring models of care to best meet needs in this community. In particular, the analyses point to higher needs among the small group that reported relying on urgent care, walk-in clinics, or the emergency room as their usual source of care. In Bell County, sites advertised as "walk-in clinics" all deliver urgent care with the exception of one clinic that specializes in testing for and treating sexually transmitted illness. Urgent care, walk-in clinics, and emergency rooms are designed to address minor acute illness or emergent conditions and are unlikely to offer the comprehensive primary care services thought to be important for prevention and long-term management of illness.

Results from our study confirm findings from other reports that document the impact of usual sources of care on barriers to care. For example, DeVoe and colleagues14 found that adults who reported a usual source of care on the Medical Expenditure Panel Survey-Household Component were less likely than those without a usual source of care to experience barriers to care. DeVoe and colleagues did not differentiate the location of the usual source of care; however, Hoilette and colleagues15 found that children who use a clinic/health center as a usual source of care were less likely to have unmet health care needs than children who used an emergency room as a usual source of care. Additionally, Starfield and Shi reported that having a usual source of primary care is associated with having fewer unmet needs and delays in obtaining needed health services.16

Limitations     

This study collected data for the purpose of characterizing the health and human service needs of a county. Our ability to draw conclusions about individual persons is limited in part by the way questions were constructed by community stakeholders for the purpose of documenting community needs. For example, respondents reported barriers that had been experienced when they or their family members could not get care that they felt was needed (ie, household barriers). Respondents reported their own usual source of care (ie, "Which one of the following choices best describes where you go most regularly for health care? [Select one answer]"). Reporting for oneself on some questions and one's household on others limits the ability to draw conclusions about individuals. At the same time, household characteristics such as household income can influence the health care access of individual members of the household.17,18  

Generalizability of the results is also limited in part by the relatively homogeneous group that responded to the coalition's survey. Although the survey was widely distributed, the sampling methodology captured a convenience sample. The sample included overrepresentation (relative to estimates of county demographic characteristics) of adults who were white, non-Hispanic, and affluent. For example, nearly 40% of respondents reported household incomes of $75,000 or more a year. Therefore, barriers of other groups may be relatively underrepresented in the findings.

Results of the study do not address whether respondents who rely on urgent care, walk-in clinics, or emergency rooms for usual care do so because of the barriers they experience at other sites or if their barriers emerge because they are seeking care at sites designed for types of care they are not seeking. Because only persons who reported having a source of insurance were included in the study sample, we can assume that having no coverage was not the reason persons selected these sites as their usual sources of care.

Implications

If stakeholders choose to address barriers to health care services for residents in Bell County, their efforts may be most efficient if directed toward groups reporting more barriers. Residents who rely on urgent or emergency care sites as their usual source of care were most likely to experience barriers in this study. Tailoring system and community intervention efforts to this group may be one way to reduce barriers to care in ways that improve overall health of the community.  

References

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