• No results found

Barriers to Care and Primary Care for Vulnerable Children With Asthma

N/A
N/A
Protected

Academic year: 2020

Share "Barriers to Care and Primary Care for Vulnerable Children With Asthma"

Copied!
11
0
0

Loading.... (view fulltext now)

Full text

(1)

ARTICLE

Barriers to Care and Primary Care for Vulnerable

Children With Asthma

Michael Seid, PhD

Divisions of Pulmonary Medicine and Health Policy and Clinical Effectiveness, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio

The author has indicated he has no financial relationships relevant to this article to disclose.

What’s Known on This Subject

Primary care is important for children with asthma. We know which groups of children are likely to experience poorer primary care but not why and how this occurs. Such knowledge is necessary for reducing disparities.

What This Study Adds

This study measures barriers to care and shows that they predict primary care experi-ences, beyond sociodemographic and access variables, in a highly vulnerable sample. Because barriers are modifiable, there are implications for intervention.

ABSTRACT

OBJECTIVE.I tested the hypothesis that, for vulnerable children with asthma, barriers to care (pragmatics, skills, knowledge and beliefs, expectations of care, and marginal-ization) affect primary care experiences, after accounting for financial, potential, and realized access to care, demographic features, and asthma severity.

METHODS.Patients, recruited primarily from urban, federally qualified health centers, were between 3 and 12 years of age and had been diagnosed as having asthma. Bilingual, bicultural interviewers administered surveys in participants’ homes. Val-idated instruments were used to measure barriers to care (Barriers to Care Ques-tionnaire) and primary care experiences (Parent’s Perceptions of Primary Care mea-sure).

RESULTS.Of 252 families recruited, 56.6% of parents were monolingual Spanish speak-ers, 73.6% of mothers had not graduated from high school, and 24.5% of children were uninsured. Asthma severity was 27% mild persistent, 40.5% moderate persis-tent, and 32.5% severe persistent. In bivariate analyses, better access to care (being insured and having a regular provider) was related to better primary care experi-ences. Consistent with the hypothesis, multivariate regression analyses showed that fewer barriers (Barriers to Care Questionnaire scores) predicted better primary care (Parent’s Perceptions of Primary Care total and subscale scores), after controlling for access to care, demographic features, and asthma severity (a 1-point change in Barriers to Care Questionnaire scores was associated with a 0.59-point change in Parent’s Perceptions of Primary Care total scale scores). Having a regular doctor and not having experienced foregone care were also significant predictors of Parent’s Perceptions of Primary Care scores in the multivariate analysis.

CONCLUSION.For vulnerable children with asthma, barriers to care explain variance in primary care characteristics beyond that explained by access, demographic factors, and disease severity.Pediatrics2008;122:994–1002

P

RIMARY CARE IS an important determinant of health for children with asthma. Expert guidelines from the National Asthma Education and Prevention Program of the National Heart, Lung, and Blood Institute1and the

American Academy of Allergy, Asthma, and Immunology2stress the importance of longitudinal asthma care with a

primary care provider, and most children with asthma do receive the majority of their care from primary care providers.3Access to primary care is associated with better outcomes for children with asthma,4–6 in all likelihood

because the hallmarks of high-quality primary care, namely, continuity, comprehensiveness, communication, contextual knowledge, coordination, and accessibility, are key to good asthma care. However, it is well known that certain groups of children with asthma, those defined by sociodemographic and access indicators such as minority race/ethnicity, low parental education, poverty, limited English language ability, lack of insurance, no usual source of care, and unmet health care needs, are less likely to receive high-quality primary care and are more vulnerable to poor health outcomes.7–20

Although knowledge of which groups may be at greater risk for poor primary care is important, understanding why and how this may occur21is necessary for developing and implementing practice and policy interventions to

reduce such disparities. Seid et al22,23and Sobo et al21posited that “barriers to care” are key to understanding the

processes behind these indicators. Barriers to care are thought of as the sociobehavioral processes that interfere with

www.pediatrics.org/cgi/doi/10.1542/ peds.2007-3114

doi:10.1542/peds.2007-3114

This trial has been registered at www.clinicaltrials.gov (identifier NCT00250588).

Key Words

asthma, chronic disease, health services accessibility, primary health care

Abbreviations

FQHC—federally qualified health center BCQ—Barriers to Care Questionnaire P3C—Parent’s Perceptions of Primary Care measure

Accepted for publication Jan 31, 2008

Address correspondence to Michael Seid, PhD, Divisions of Pulmonary Medicine and Health Policy and Clinical Effectiveness, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH 45229-3039. E-mail: michael.seid@cchmc.org

(2)

a family’s positive interaction with the health care sys-tem and reduce the likelihood of timely access, produc-tive interactions with the health system, and posiproduc-tive outcomes.22,23

Examples of barriers to care can be found in previous research. The roles of barriers such as pragmatic factors (eg, transportation, the ability to take time off work, and convenient office hours), health knowledge and be-liefs,24skills to negotiate the health system,21,25negative

expectations of care,26,27and feelings of marginalization21

in affecting families’ experiences of primary care quality have been examined. For example, a study of parent-reported barriers to quality asthma care for inner-city children with asthma28 showed that problems such as

long waits, lack of transportation, rude staff members, and lack of language-concordant staff members led to problems in accessing high-quality care. In terms of ad-herence to treatment, Mansour et al29cited the inability

to pay for medications and beliefs about the use, safety, and long-term complications of asthma medication use as barriers to implementation of optimal asthma care. Wade et al30documented a link between parental

expec-tations and problem-solving skills on one hand and asthma functional status and symptoms on the other. Valerio et al31 documented barriers such as caregiver

emotions, knowledge, environmental issues, support from the school or day care center, and health care system and provider issues in their study of parents of children with asthma who were insured through Med-icaid. In part on the basis of evidence such as this, Seid et al23 developed and validated a multidimensional

mea-sure of barriers to care for children with chronic health conditions, the Barriers to Care Questionnaire (BCQ), as a tool for quantifying these processes.

Given the existence of a quantitative measure of mul-tiple barriers to care, I sought to determine the extent to which barriers to care explain variance in primary care experiences for vulnerable children with asthma, within the context of sociodemographic and access indicators of vulnerability. By studying a sample of vulnerable chil-dren with asthma who were recruited from federally qualified health centers (FQHCs) and by using previ-ously validated measures of barriers to care and primary care, I examined the extent to which barriers to care explain variance in primary care experiences beyond that explained by financial, potential, and realized access to care. On the basis of previous research describing various barriers,21,28–31I hypothesized that barriers to care

would explain significant additional variance in primary care experiences.

METHODS

Data Source

The data for this study were collected as part of a ran-domized trial of problem-solving skills training to reduce barriers to care for families of vulnerable children with asthma. For this analysis, I used baseline data from the trial. This study was approved by the institutional review boards at Rady Children’s Hospital, the Rand Corp, and Cincinnati Children’s Hospital Medical Center.

Sample

The sample in this study was identical to that recruited for the randomized trial. Patients and their parents were recruited primarily from FQHCs in San Diego County, California. Additional recruitment occurred through self-referral, from private pediatricians’ offices, local school districts, and local asthma initiatives. Eligible pa-tients were between the ages of 3 and 14 years, with a physician diagnosis of persistent asthma (mild, moder-ate, or severe) and parents who spoke English or Span-ish. Patients with comorbid conditions that might affect care or outcomes (eg, Down syndrome or another pul-monary disease) were not eligible.

Procedures

Potential subjects were referred to the study by their treating physician. Once a referral and consent to con-tact were received, study staff members called potential subjects to verify eligibility status. Eligible subjects were invited to participate. Informed consent was obtained, and the baseline survey (the source of the data for this study) was completed during a visit to the subject’s home. Bilingual, bicultural, research staff members ad-ministered the survey interview in English or Spanish.

Measures

Asthma Severity

Asthma severity was determined with a standardized interview based on National Heart, Lung, and Blood Institute guidelines.32

Financial, Potential, and Realized Access

Financial access was measured through parents’ reports of whether their child had health insurance (“Health insurance is insurance your child has to help pay the cost of medical care. Does your child now have health insur-ance?” Response options were yes or no). Potential ac-cess was assessed through parents’ reports of whether their child had a regular source of care33(“Do you have

one person you think of as your child’s personal doctor or nurse?” Response options were yes or no). Realized access was measured through parents’ reports of fore-gone care34(“In the past 12 months, has there been any

time when you thought your child should get medical care but did not?” Response options were yes or no).

Barriers to Care: BCQ

The BCQ, which was designed to measure parents’ re-ports of experiences or circumstances that might inter-fere with access to or use of care, with making the most of the clinical encounter, or with adhering to medical instructions, has been shown to be feasible, reliable, and valid for use with children with special health care needs.23Parents are in a unique position to report on the

care their children receive.28,35–37 Indeed, some parent

(3)

The 39-item BCQ yields scores of 0 to 100 (higher scores are better, denoting fewer barriers) for the total scale (an overall index) and for the subscales. BCQ sub-scales include the following. Pragmatics refer to logistic and cost issues that might prevent or delay appropriate utilization. Skills are a set of acquired or learned strate-gies to navigate through, manipulate, or function com-petently within the health care system. These skills are key to functional biomedical acculturation,25a construct

that likens the biomedical system to a cultural system; patients of all backgrounds must learn to navigate through or function competently within the system. Ex-pectations refer to parent exEx-pectations of receiving poor-quality care.26,27Marginalization refers to the

internal-ization and personalinternal-ization of negative experiences within the health care system.38Knowledge and beliefs24

include lay or popular ideas about the nature and treat-ment of illness, which may differ from those of main-stream allopathic medicine. BCQ items are listed in the Appendix.

The BCQ has the following instructions: “Parents of-ten face barriers when trying to get health care for their children. We are interested in the kinds of things that interfere with getting health care for your child(ren). Please rate how much of a problem each of the following is for you.” Response scores and choices were 100 for “no problem,” 75 for “small problem,” 50 for “problem,” 25 for “big problem,” and 0 for “very big problem”; therefore, higher scores indicate fewer barriers.

The BCQ was developed and tested simultaneously in English and Spanish. The reading level of the BCQ items is at the 5.7 grade level, as assessed with the Flesch-Kincaid39 readability scale. The Flesch-Kincaid method

rates text on a US school grade level. For example, a score of 8.0 means that an eighth-grader can understand the document. The formula for the Flesch-Kincaid grade level score is as follows: (0.39⫻ASL)⫹(11.8⫻ASW)⫺ 15.59, where ASL is the average sentence length (the number of words divided by the number of sentences) and ASW is the average number of syllables per word (the number of syllables divided by the number of words).

Primary Care Experiences: Parent’s Perceptions of Primary Care

Parents’ perceptions of primary care experiences were measured with the Parent’s Perceptions of Primary Care measure (P3C), a brief, practical, parent report of the parents’ experiences with their children’s primary care. The P3C has been shown to have adequate reliability (all total scale and subscale␣values of⬎.70) and validity.40

The P3C measures parents’ experiences with primary care processes, rather than technical or clinical quality of care or adherence to evidence-based medicine. The P3C is based on the Institute of Medicine definition of pri-mary care,41which is similar to the American Academy

of Pediatrics concept of a medical home.42With the use

of this definition as a criterion, the P3C was designed to measure 6 components of care that, when present, con-stitute high-quality primary care experiences. High scores reflect care conforming to this a priori definition.

Therefore, the P3C measures perceptions of quality based on parents’ reports of their experiences, rather than ratings of satisfaction with those experiences. The P3C was designed to measure parents’ perceptions of experiences in receiving primary care, rather than the quality of a particular provider of primary care. This was done so that the care received by children without a regular provider also could be described in relation to the Institute of Medicine definition of quality primary care. This is important, given the large proportions of unin-sured children43and children without a regular source of

care44,45who receive primary health care at emergency

departments or community clinics, where they might not see a consistent provider.

The components of primary care included in the P3C are those on which parents are considered able to report. The 6 components of primary care measured by the P3C are defined as follows. Longitudinal continuity is defined as the parent’s report of the length of time they have been bringing their children to a regular place or physi-cian.46,47Access is defined as the parent’s report of timely

and convenient access to care for their children.47

Com-munication is defined as the parent’s report of how well the physician listens and explains during their interac-tions.48Contextual knowledge is defined as the parent’s

report that the physician knows his or her values and preferences about medical care issues, clearly under-stands his or her child’s health needs, and knows the child’s medical history.46Comprehensiveness is defined

as the parent’s report of the extent to which a regular place and/or doctor provides care for acute and chronic problems and preventive services.47,48 Coordination of

care is defined as the parent’s report of the physician’s knowledge of other visits and visits to specialists, as well as follow-up monitoring of problems through subse-quent visits or telephone calls.46

The 23-item P3C yields scores of 0 to 100 (higher scores indicate better primary care) for the total scale (an overall index score) and for subscales measuring conti-nuity, access, contextual knowledge, communication, comprehensiveness, and coordination. All items are at or below an eighth-grade reading level.39

The P3C was developed in English and translated to Spanish. Translation was accomplished by using for-ward-backward translation, striving for conceptual, as opposed to syntactical, equivalence and consistent lan-guage level.49–53 The final English-language and

trans-lated version of the P3C were reconciled by bilingual lay people familiar with the purpose of the survey.

Analysis

Independent-samplettests and 1-way analyses of vari-ance were used to assess the bivariate relationships of demographic variables, measures of access, and BCQ scores with P3C. Descriptive statistics and internal con-sistency (␣) values were calculated for the BCQ and subscales. Pearson correlation coefficients for correla-tions between the BCQ scales and the P3C scales were calculated to examine the bivariate relationships be-tween the 2 measures.

(4)

estima-tion were used to assess the effects of financial access (insurance coverage), potential access (regular source of care), realized access (forgone care), and barriers to care (BCQ total scale) on parent perceptions of primary care (P3C), after controlling for sociodemographic character-istics. Eight regression models were constructed, reflect-ing the total P3C score (with and without the continuity domain) and each domain of primary care (accessibility, continuity, communication, contextual knowledge, com-prehensiveness, and coordination). It is important to note that the second total P3C score accounts for the analyt-ical overlap between one of the covariates, namely, po-tential access or having a regular source of care, and the dependent measure of continuity by dropping this do-main from the total score. For each model, unstandard-ized regression coefficients (B), with SEs andP values, and standardized regression coefficients for each variable are presented. Unstandardized regression coefficients in-dicate the effect of a 1-point change in the predictor variable on the dependent variable, with all other vari-ables held constant. Standardized regression coefficients denote the effect of a 1-point change (in the case of a dichotomous variable, eg, changing from no insurance to insurance) or the effect of a 1-SD change (in the case of a continuous variable, eg, BCQ total scale scores) in the predictor variable on the dependent variable, ex-pressed in SDs of the dependent variable.

By using SPSS (SPSS, Chicago, IL), colinearity be-tween the independent measures was assessed by run-ning each independent variable, in turn, as a dependent variable predicted by the other independent variables. The output for these diagnostic tests included the toler-ance (ranging from 0 to 1; scores closer to 0 indicate more colinearity) and the variance inflation factor (a variance inflation factor of⬎10 is considered indicative of colinearity).54 Intercorrelations among the

indepen-dent variables were also examined.

RESULTS

The study received 610 referrals. Of those, 144 subjects (23.6%) could not be located, 122 (20%) did not meet inclusion criteria, and 344 (56.4%) were eligible. Of the eligible participants, 252 (73.3%) were enrolled and 92 (26.7%) refused. There were no differences between eligible enrolled and eligible refused subjects with re-spect to child age or gender, source of referral, or asthma severity. Participants (77%) were more likely than those who refused (50%) to prefer Spanish as the interview language. Most participants were referred from FQHCs (n ⫽ 212), with the remainder being referred from a commercial health maintenance organization (n⫽15), school or day care center (n ⫽ 11), or local asthma initiative (n ⫽ 3) or through self-referral (n ⫽ 11). Participants received care from FQHCs (n ⫽ 223) or private practice physicians (n ⫽ 25) or had no listed source of care (n⫽4).

As can be seen in Table 1, the majority of participants were of Hispanic ethnicity (83%), with 56.6% being monolingual Spanish speakers, and 73.6% of mothers had less than a high school education. In terms of access to care, 75.5% of children had health insurance (of

those, 77.4% had Medicaid/State Children’s Health In-surance Program coverage, 10.3% had private insur-ance, and 12.3% had limited coverage for asthma med-ications), 91.7% reported a regular doctor, and 20.2% reported foregone care in the past 12 months.

Table 1 also shows the bivariate relationships be-tween the demographic and access variables and P3C total scale scores. There were no significant relationships between demographic variables and primary care expe-riences. Children with health insurance (t250⫽2.77;P⬍ .01) and with a regular doctor (t250⫽5.14; P⬍ .001) had higher P3C scores.

As shown in Table 2, mean responses for the BCQ total scale and subscales generally fell between the re-sponses of no problem and small problem, and internal consistency was generally strong, with all except the pragmatics subscale having ␣ values of ⬎.70. Table 3 displays the Pearson coefficients for correlations be-tween BCQ scales and P3C scales. As can be seen, the BCQ total scale and all subscales were moderately cor-related with the P3C total scale and subscales, with the exception of the continuity subscale, in the expected direction.

Table 4 shows the multivariate regression analysis TABLE 1 Sample Demographic Features, Access to Care, and P3C

Scores

Variable n(%) P3C Total Scale Score, Mean⫾SD

Race

Hispanic 210 (83.0) 71.80⫾19.32

Black 20 (8.3) 81.17⫾15.77

White 11 (4.3) 74.64⫾13.61

Other 11 (4.3) 77.78⫾9.44

Language

Bilingual, prefers English 20 (8.0) 71.88⫾19.69 Bilingual, prefers Spanish 52 (20.3) 75.43⫾17.06 Monolingual English 38 (15.1) 75.44⫾17.35 Monolingual Spanish 142 (56.6) 71.49⫾19.42 Mother’s education

ⱕ6th grade 65 (26.4) 72.78⫾19.59

7th to 9th grade 58 (23.2) 72.06⫾19.43 10th to 12th grade 60 (24.0) 71.46⫾20.24 High school graduate 20 (8.4) 76.79⫾11.89

Some college 33 (12.8) 73.79⫾19.93

College graduate 12 (4.8) 74.17⫾9.62

Graduate/professional degree 1 (0.4) 76.75 Severity

Mild 68 (27.0) 77.09⫾15.53

Moderate 103 (40.5) 71.36⫾18.53

Severe 81 (32.5) 71.43⫾20.81

Insureda

Yes 190 (75.5) 74.76⫾17.73

No 62 (24.5) 67.31⫾20.41

Regular doctorb

Yes 231 (91.7) 74.67⫾17.21

No 21 (8.3) 53.82⫾23.43

Foregone care

Yes 51 (20.2) 70.05⫾19.99

No 200 (79.4) 73.62⫾18.33

(5)

predicting P3C scores by using access to care and barriers to care, controlling for demographic characteristics and asthma severity. In every regression model except for that predicting the P3C continuity subscale, the regres-sion coefficients showed that the BCQ total scale con-tributed significantly to the variance explained. In terms of unstandardized regression coefficients, for the P3C total scale with and without the continuity subscale, a 1-point increase in the BCQ score was associated with 0.59-point and 0.66-point increases, respectively, in P3C scores (it should be noted that higher scores on the BCQ denote fewer barriers). The pattern was similar for the P3C subscales; with the exception of the P3C continuity subscale, a 1-point increase in the BCQ scale was asso-ciated with increases of 0.55 to 1.02 points in the P3C subscales.

Examining the standardized regression coefficients al-lows comparison of the relative effects of the predictors on the dependent variables, with all other predictors held constant. As can be seen, the largest standardized regression coefficient for all equations was that for the BCQ. For example, in predictions of the P3C total scale score, going from having a usual source of care to not having a usual source of care, with all other predictors

held constant, would decrease the P3C total scale score by 0.266 SD, whereas changing the BCQ scores by 1 SD, with all other predictors held constant, would increase the P3C total scale score by 0.444 SD. Therefore, in this case, barriers to care (BCQ total scale) have a larger effect than regular source of care (0.266 vs 0.444) on primary care (P3C total scale), in terms of magnitude (absolute value).

In none of the multivariate regression analyses was insurance status a predictor of primary care experiences, and foregone care was a predictor of primary care expe-riences only for the P3C total scale and the accessibility and communication subscales. In this sample, having a regular doctor was significantly associated with better primary care experiences for all except the P3C coordi-nation subscale. In additional analyses (not shown), all BCQ subscales contributed significant independent vari-ance to the prediction of the P3C total scale score.

Potential statistical threats to this analysis were con-sidered by testing for colinearity among the independent variables. A model predicting the P3C total score by using all independent variables was created. The range of tolerances was 0.63 to 0.95 and the variance inflation factors were small, ranging from 1.06 to 1.58, indicating no colinearity. The largest correlation between any 2 independent variables was 0.53, which is large. I con-cluded that there was no significant colinearity among the independent variables.

DISCUSSION

Consistent with the hypothesis, these data demonstrated that, with accounting for the effects of demographic factors, disease severity, and financial, potential, and realized access to care, barriers to care were significantly associated with primary care experiences for vulnerable children with asthma. A multivariate regression analysis measured the effect of each variable, taking into account

TABLE 3 Pearson Coefficients for Correlations Between BCQ Scales and P3C Scales

BCQ P3C Total Continuity Access Coordination Comprehensiveness Communication Accumulated Knowledge

Total

Correlation coefficient 0.459a 0.017 0.333a 0.444a 0.302a 0.441a 0.350a

N 252 252 249 114 251 252 248

Pragmatics

Correlation coefficient 0.317a ⫺0.050 0.418a 0.335a 0.168a 0.220a 0.228a

N 252 252 249 114 251 252 248

Skills

Correlation coefficient 0.372a 0.147b 0.215a 0.311a 0.285a 0.345a 0.261a

N 252 252 249 114 251 252 248

Expectations

Correlation coefficient 0.406a ⫺0.002 0.272a 0.340a 0.289a 0.426a 0.302a

N 252 252 249 114 251 252 248

Marginalization

Correlation coefficient 0.414a ⫺0.031 0.221a 0.446a 0.274a 0.464a 0.320a

N 252 252 249 114 251 252 248

Knowledge and beliefs

Correlation coefficient 0.344a 0.063 0.173a 0.373a 0.205a 0.307a 0.341a

N 252 252 249 114 251 252 248

aCorrelation is significant at the .01 level (2-tailed). bCorrelation is significant at the .05 level (2-tailed).

TABLE 2 BCQ Descriptive Statistics and Internal Consistency (N252)

Score ␣

Minimum Maximum Mean SD

Total 12 100 86.31 14.08 .93

Pragmatics 22 100 78.34 18.34 .69

Skills 0 100 87.75 16.99 .80

Expectations 0 100 87.93 17.45 .79

Marginalization 14 100 88.98 16.91 .89

(6)

the simultaneous effects of all other variables. These data showed that, even for children with health insurance, a regular source of care, and access to care when needed, barriers to care such as logistics, skills, health beliefs and knowledge, expectations about care, and marginaliza-tion interfere with families’ abilities to make the most of the clinical encounter and primary care relationship. Examination of the standardized regression coefficients showed that differences in barriers to care had a greater impact on primary care experiences than did differences in either sociodemographic variables or indicators of ac-cess. In this highly vulnerable sample of children with persistent asthma, primary care experiences are likely to be key to asthma outcomes.55

Other researchers have described barriers to care. For example, culturally mediated beliefs about health, pathogenesis, and treatment have been described. Rob-ledo et al56used structured qualitative interviews to

ex-plore knowledge and care of respiratory illnesses in a small group of mothers of Mexican origin living in the United States. The authors reported that the mothers

relied on folk beliefs regarding the causes and treatment of respiratory illnesses. Similarly, Bearison et al57

inter-viewed mothers of Dominican children with moderate/ severe asthma. They found that, whereas most moth-ers’ understanding of the causes of asthma were consistent with standard knowledge about asthma, this understanding was supplemented by culturally derived folk beliefs about illness and treatment. As a result, mothers treated their children’s asthma differ-ently depending on whether the treatment was for prevention or for controlling an asthma attack. Moth-ers were likely to treat an acute asthma attack by using medically prescribed treatments but were likely to rely on folk beliefs, such as preventing an imbalance of body humors or temperature, to prevent attacks. There was a general mistrust of medically prescribed preventive medications, with mothers citing the over-use of medicines in this country, fear of dependency on the medications, and suspicion of physicians’ fail-ure to disclose possible adverse effects.

In addition to health beliefs that differ from those of TABLE 4 Multivariate Regression Analyses of Access to Care, Barriers to Care, and P3C Scores, Controlling for Sociodemographic Features and

Severity

P3C Total P3C Total Without

Continuity

Accessibility Continuity Communication Contextual Knowledge

Comprehensive Coordination

Sociodemographic features Race/ethnicity

White/non-Hispanic

B(SE) 2.2 (5.58) 1.9 (5.8) 3.3 (8.2) 2.2 (8.7) 8.0 (6.2) 10.2 (9.2) ⫺9.8 (9.0) 3.4 (10.4)

␤ 0.023 0.019 0.026 0.017 0.078 0.069 ⫺0.068 0.033

Black/non-Hispanic

B(SE) 4.2 (4.2) 4.0 (4.4) 4.1 (6.3) 5.4 (6.7) 0.7 (4.8) 4.9 (7.0) 8.0 (6.9) ⫺2.1 (9.4)

␤ 0.062 0.055 0.044 0.056 0.009 0.046 0.077 ⫺0.024

Mother’s education

B(SE) ⫺0.1 (0.8) ⫺0.03 (0.9) ⫺0.03 (1.3) ⫺0.7 (1.3) 0.2 (0.9) ⫺1.1 (1.4) 0.3 (1.4) 0.7 (2.1)

␤ ⫺0.008 ⫺0.002 ⫺0.002 ⫺0.041 0.018 ⫺0.055 0.018 0.043

Monolingual Spanish

B(SE) ⫺4.6 (2.5) ⫺4.5 (2.7) ⫺7.1 (3.8) ⫺4.6 (3.9) ⫺0.1 (2.9) ⫺3.1 (4.2) ⫺6.5 (4.2) ⫺4.6 (6.2)

␤ ⫺0.12 ⫺0.114 ⫺0.139 ⫺0.087 ⫺0.003 ⫺0.053 ⫺0.114 ⫺0.082

Asthma severity

B(SE) ⫺1.4 (1.3) ⫺1.5 (1.4) ⫺0.3 (2.0) ⫺0.8 (2.1) ⫺0.9 (1.5) ⫺3.4 (2.3) ⫺2.0 (2.2) 2.1 (3.5)

␤ ⫺0.057 ⫺0.056 ⫺0.01 ⫺0.022 ⫺0.034 ⫺0.090 ⫺0.055 0.056

Access No insurance

B(SE) ⫺2.0 (2.5) ⫺1.8 (2.6) 3.1 (3.7) ⫺4.3 (3.9) ⫺3.3 (2.8) ⫺2.0 (4.2) ⫺5.5 (4.1) 3.0 (6.0)

␤ ⫺0.046 ⫺0.039 0.052 ⫺0.07 ⫺0.068 ⫺0.029 ⫺0.082 0.045

No regular doctor

B(SE) ⫺17.9 (3.8)a 16.6 (4.0)a 12.9 (5.6)a 30.7 (6.0)a 11.2 (4.3)b 26.8 (6.3)a 21.0 (6.2)a 0.03 (9.3)

␤ ⫺0.266 ⫺0.234 ⫺0.142 ⫺0.326 ⫺0.153 ⫺0.257 ⫺0.207 0.00

Forgone care

B(SE) ⫺5.6 (2.7)c 5.9 (2.8)c 8.5 (4.1)c 3.1 (4.3) 6.7 (3.1)c 6.0 (4.6) 3.7 (4.5) 4.9 (6.7)

␤ ⫺0.12 ⫺0.121 ⫺0.133 ⫺0.048 ⫺0.133 ⫺0.083 ⫺0.053 ⫺0.075

Barriers to care

B(SE) 0.59 (0.08)a 0.66 (0.08)a 0.67 (0.12)a 0.08 (0.12) 0.64 (0.09)a 0.65 (0.13)a 0.55 (0.13)a 1.02 (0.21)a

␤ 0.444 0.471 0.373 ⫺0.043 0.444 0.317 0.273 0.211

AdjustedR2 0.28 0.28 0.16 0.08 0.21 0.17 0.15 0.15

Results represent the unstandardized regression coefficient (B), the SE of the unstandardized regression coefficient, and the standardized regression coefficient (␤). aP.001.

(7)

allopathic medicine, researchers have documented other barriers faced by such families. Mosnaim et al58

con-ducted focus groups with Spanish-speaking Hispanic subjects and documented barriers to care, including lo-gistic factors such as lack of transportation, the sense of isolation and inadequate social support for caregivers, the impact of poor living conditions, the lack of knowl-edge about asthma causes, triggers, and treatments, and the need for better education from health professionals in a manner that is understandable. Conn et al59found

that 34% of surveyed parents had strong concerns about medication adverse effects and this was significantly re-lated to nonadherence. Yu et al60,61showed, by analyzing

data from the National Survey of America’s Families, that immigrant families were less likely to be aware of health and community resources and children from im-migrant families were likely to have both poorer health and less access to health care. The current research ad-vances the literature in that it demonstrates that the barriers to care described previously in qualitative terms have a measurable, statistically significant effect, beyond access, in primary care for vulnerable children with asthma.

Unlike much of the research on access to care, insur-ance status was not significantly related to primary care experiences in the current study. The lack of association between insurance status and primary care experiences may be explained by the fact that the vast majority of the subjects were recruited from FQHCs, which have sliding fees and accept and treat patients regardless of insurance status. Therefore, the effect of insurance status within this sample might have been blunted.

This study has several limitations. First, both barri-ers to care and perceptions of primary care were as-sessed from the parents’ perspective, introducing the possibility that the relationship between the 2 might be attributable, in part, to respondent bias. Relying on the parents’ perspective also raises the issue of whether parents are adequate reporters of these vari-ables. However, because many aspects of barriers to care and of primary care experiences are defined by patient or parent experience, self-report is thought to be a valid method for assessing these constructs. An-other limitation is the cross-sectional nature of this study. Future research will need to establish the di-rection of causality and the role of potential unmea-sured variables. Generalizability is an issue, because participants were referred by their health care provid-ers and therefore are likely to be systematically differ-ent from individuals with similar sociodemographic characteristics who have not been able to access the health care system. The greater proportion of Hispanic subjects in the study reflects, to some degree, county demographic characteristics, as well as the fact that subjects were recruited predominantly from FQHCs. I did not have information on subjects who were re-ferred but not located; therefore, I could not deter-mine whether those subjects were systematically dif-ferent from eligible subjects. Although data on insurance status, the presence of a regular source of care, and unmet needs were captured, more-detailed

questions regarding recent periods of uninsurance, the type of provider, or the type of forgone care were not asked. I did not consider interactions between differ-ent barriers to care and sociodemographic or access variables; introducing an interaction term in the re-gression equation resulted in unacceptably high mul-ticolinearity.

Nevertheless, this study adds to the literature by documenting and quantifying the effect of barriers to care, over and above traditional measures of access to care, in a highly vulnerable sample. Given the impor-tance of primary care, especially for vulnerable chil-dren and chilchil-dren with special health care needs, the research has implications for both practitioners and policymakers. Barriers are clearly important predictors of primary care, but they are modifiable. Cabana et al62

suggested several useful strategies for eliminating dis-parities in asthma care that are also applicable to modifying barriers to care. At the structural level, the authors suggested creating programs to increase work-force diversity, creating standards for culturally and linguistically appropriate services, requiring health care systems to collect and to analyze data according to race/ethnicity, ensuring that health care financing does not lead to fragmentation of care, and supporting community health centers. To change processes of care at the health care system level, the authors sug-gested improved adherence to standards of care, qual-ity improvement interventions, and ensuring the availability of professional interpreter services. At the interpersonal level, they suggested efforts to reduce stereotyping and to improve patient education and patient empowerment. Practitioners should anticipate and be prepared to address the fact that barriers to optimal care exist even within the examination room. Policymakers seeking to improve primary care should develop and evaluate programs and policies that ad-dress multiple types of barriers to care, beyond a nar-row focus on insurance status. Additional research is clearly necessary, to establish temporal order and cau-sality and to determine better ways to reduce barriers to care and to help families overcome these barriers to care.

ACKNOWLEDGMENT

This research was supported by a grant from the Mater-nal and Child Health Bureau of the Health Resources and Services Administration (grant R4001214).

REFERENCES

1. National Asthma Education and Prevention Program.Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma. Bethesda, MD: National Institutes of Health; 2007 2. American Academy of Allergy, Asthma, and Immunology,

Pe-diatric Asthma Committee.Pediatric Asthma: Promoting Best Prac-tice Guide for Management of Asthma in Children. Milwaukee, WI: American Academy of Allergy, Asthma, and Immunology; 1999

(8)

4. Perrin JM, Homer CJ, Berwick DM, Woolf AD, Freeman JL, Wennberg JE. Variations in rates of hospitalization of children in three urban communities. N Engl J Med. 1989;320(18): 1183–1187

5. Christakis DA, Mell L, Koepsell TD, Zimmerman FJ, Connell FA. Association of lower continuity of care with greater risk of emergency department use and hospitalization in children.

Pediatrics.2001;107(3):524 –529

6. Cree M, Bell NR, Johnson D, Carriere KC. Increased continuity of care associated with decreased hospital care and emergency department visits for patients with asthma. Dis Manag.2006; 9(1):63–71

7. Huang ZJ, Kogan MD, Yu SM, Strickland B. Delayed or forgone care among children with special health care needs: an analysis of the 2001 National Survey of Children with Special Health Care Needs.Ambul Pediatr.2005;5(1):60 – 67

8. Javier JR, Wise PH, Mendoza FS. The relationship of immigrant status with access, utilization, and health status for children with asthma.Ambul Pediatr.2007;7(6):421– 430

9. Halfon N, Inkelas M, Wood D. Nonfinancial barriers to care for children and youth.Annu Rev Public Health.1995;16:447– 472 10. Yoon EY, Davis MM, Van Cleave J, Maheshwari S, Cabana MD. Factors associated with non-attendance at pediatric subspe-cialty asthma clinics.J Asthma.2005;42(7):555–559

11. Dougherty D, Meikle SF, Owens P, Kelley E, Moy E. Children’s health care in the First National Healthcare Quality Report and National Healthcare Disparities Report. Med Care.2005;43(3 suppl):I58 –I63

12. Canino G, Koinis-Mitchell D, Ortega AN, McQuaid EL, Fritz GK, Alegria M. Asthma disparities in the prevalence, morbid-ity, and treatment of Latino children.Soc Sci Med.2006;63(11): 2926 –2937

13. Flores G, Bauchner H, Feinstein AR, Nguyen US. The impact of ethnicity, family income, and parental education on children’s health and use of health services.Am J Public Health. 1999; 89(7):1066 –1071

14. Flores G, Abreu M, Olivar MA, Kastner B. Access barriers to health care for Latino children.Arch Pediatr Adolesc Med.1998; 152(11):1119 –1125

15. Flores G, Fuentes-Afflick E, Barbot O, et al. The health of Latino children: urgent priorities, unanswered questions, and a research agenda.JAMA.2002;288(1):82–90

16. Brotanek JM, Halterman J, Auinger P, Weitzman M. Inade-quate access to care among children with asthma from Span-ish-speaking families. J Health Care Poor Underserved. 2005; 16(1):63–73

17. Akinbami LJ, Schoendorf KC. Trends in childhood asthma: prevalence, health care utilization, and mortality. Pediatrics.

2002;110(2):315–322

18. McDaniel M, Paxson C, Waldfogel J. Racial disparities in child-hood asthma in the United States: evidence from the National Health Interview Survey, 1997 to 2003.Pediatrics.2006;117(5). Available at: www.pediatrics.org/cgi/content/full/117/5/e868 19. Seid M, Stevens GD. Access to care and children’s primary care

experiences: results from a prospective cohort study. Health Serv Res.2005;40(6):1758 –1780

20. Seid M, Stevens GD, Varni JW. Parents’ perceptions of pediat-ric primary care quality: effects of race/ethnicity, language, and access.Health Serv Res.2003;38(4):1009 –1031

21. Sobo EJ, Seid M, Reyes Gelhard L. Parent-identified barriers to pediatric health care: a process-oriented model.Health Serv Res.

2006;41(1):148 –172

22. Seid M, Sobo EJ, Zivkovic M, Nelson M, Davodi-Far M. Con-ceptual models of quality of care and health-related quality of life for vulnerable children. In: Sobo EJ, Kurtin PS, eds.Child Health Services Research: Applications, Innovation and Insights.San Francisco, CA: Jossey-Bass; 2003:243–274

23. Seid M, Sobo EJ, Gelhard LR, Varni JW. Parents’ reports of barriers to care for children with special health care needs: development and validation of the Barriers to Care Question-naire.Ambul Pediatr.2004;4(4):323–331

24. Good BJ.Medicine, Rationality, and Experience: An Anthropological Perspective. Cambridge, England: Cambridge University Press; 1994

25. Sobo E, Seid M. Cultural issues in health services delivery: what kind of “competence” is needed, and from whom?Ann Behav Sci Med Educ.2003;9(2):97–100

26. Fiscella K, Franks P, Clancy CM. Skepticism toward medical care and health care utilization.Med Care.1998;36(2):180 –189 27. Doescher MP, Saver BG, Franks P, Fiscella K. Racial and ethnic disparities in perceptions of physician style and trust.Arch Fam Med.2000;9(10):1156 –1163

28. Crain EF, Kercsmar C, Weiss KB, Mitchell H, Lynn H. Reported difficulties in access to quality care for children with asthma in the inner city.Arch Pediatr Adolesc Med.1998;152(4):333–339 29. Mansour ME, Lanphear BP, DeWitt TG. Barriers to asthma care

in urban children: parent perspectives.Pediatrics.2000;106(3): 512–519

30. Wade SL, Holden G, Lynn H, Mitchell H, Ewart C. Cognitive-behavioral predictors of asthma morbidity in inner-city chil-dren.J Dev Behav Pediatr.2000;21(5):340 –346

31. Valerio M, Cabana MD, White DF, Heidmann DM, Brown RW, Bratton SL. Understanding of asthma management: Medicaid parents’ perspectives.Chest.2006;129(3):594 – 601

32. National Asthma Education and Prevention Program.Expert Panel Report II: Guidelines for the Diagnosis and Management of Asthma. Bethesda, MD: National Institutes of Health; 1997 33. Agency for Healthcare Research and Quality. CAHPS 2.0

questionnaires. Available at: www.cahps.ahrq.gov/cahpskit/ cahpskit_main.asp?p⫽10238&s⫽23. Accessed September 2, 2008

34. Ford CA, Bearman PS, Moody J. Foregone health care among adolescents.JAMA.1999;282(23):2227–2234

35. Homer CJ, Marino B, Cleary PD, et al. Quality of care at a children’s hospital: the parent’s perspective.Arch Pediatr Adolesc Med.1999;153(11):1123–1129

36. Dinkevich EI, Cunningham SJ, Crain EF. Parental perceptions of access to care and quality of care for inner-city children with asthma.J Asthma.1998;35(1):63–71

37. Garwick AW, Kohrman C, Wolman C, Blum RW. Families’ recommendations for improving services for children with chronic conditions. Arch Pediatr Adolesc Med. 1998;152(5): 440 – 448

38. Kreps GL. Communicating to promote justice in the modern health care system.J Health Commun.1996;1(1):99 –109 39. Kincaid J, Fishburne R, Rogers R, Chissom B.Derivation of New

Readability Formulas (Automated Reading Index, Fog Count, and Flesch Reading Ease Formula) for Navy Enlisted Personnel. Mem-phis, TN: Naval Air Station; 1975. Research Branch report 8 –75

40. Seid M, Varni J, Olson-Bermudez L, et al. Parent’s Perceptions of Primary Care measure (P3C): measuring parents’ experi-ences of pediatric primary care quality.Pediatrics.2001;108(2): 264 –270

41. Institute of Medicine.Primary Care: America’s Health in a New Era. Washington, DC: National Academy Press; 1996 42. American Academy of Pediatrics, Medical Home Initiatives for

Children With Special Needs Project Advisory Committee. The medical home.Pediatrics.2002;110(1):184 –186

43. US Bureau of the Census.Census Brief: Children Without Health Insurance. Washington, DC: US Bureau of the Census; 1998. Publication CENBR/98-1

(9)

Access to medical care for children and adolescents in the United States.Pediatrics.1990;86(5):666 – 673

45. Halfon N, Newacheck PW, Wood DL, St Peter RF. Routine emergency department use for sick care by children in the United States.Pediatrics.1996;98(1):28 –34

46. Starfield B.Primary Care: Balancing Health Needs, Services, and Technology. New York, NY: Oxford University Press; 1998 47. Bindman AB, Grumbach K, Osmond D, Vranizan K, Stewart

AL. Primary care and receipt of preventive services.J Gen Intern Med.1996;11(5):269 –276

48. Flocke SA. Measuring attributes of primary care: development of a new instrument.J Fam Pract.1997;45(1):64 –74

49. Canales S, Ganz PA, Coscarelli CA. Translation and validation of a quality of life instrument for Hispanic American cancer patients: methodological considerations. Qual Life Res.1995; 4(1):3–11

50. Hendricson WD, Russell IJ, Prihoda TJ, Jacobson JM, Rogan A, Bishop GD. An approach to developing a valid Spanish lan-guage translation of a health-status questionnaire.Med Care.

1989;27(10):959 –966

51. Herdman M, Fox-Rushby J, Badia X. “Equivalence” and the translation and adaptation of health-related quality of life questionnaires.Qual Life Res.1997;6(3):237–247

52. Keller SD, Ware JE Jr, Gandek B, et al. Testing the equivalence of translations of widely used response choice labels: results from the IQOLA Project: International Quality of Life Assess-ment.J Clin Epidemiol.1998;51(11):933–944

53. Ware JE Jr, Keller SD, Gandek B, Brazier JE, Sullivan M. Evaluating translations of health status questionnaires: meth-ods from the IQOLA Project.Int J Technol Assess Health Care.

1995;11(3):525–551

54. University of California, Los Angeles, Academic Technology Services Statistical Consulting Group. Regression with SAS: regression diagnostics. Available at: www.ats.ucla.edu/stat/sas/ webbooks/reg/chapter2/sasreg2.htm. Accessed January 11, 2008

55. Halterman JS, Fisher S, Conn KM, et al. Improved preventive care for asthma: a randomized trial of clinician prompting in pediatric offices. Arch Pediatr Adolesc Med. 2006;160(10): 1018 –1025

56. Robledo L, Wilson AH, Gray P. Hispanic mothers’ knowledge and care of their children with respiratory illnesses: a pilot study.J Pediatr Nurs.1999;14(4):239 –247

57. Bearison D, Minian N, Granowetter L. Medical management of asthma and folk medicine in a Hispanic community.J Pediatr Psychol.2002;27(4):385–392

58. Mosnaim G, Kohrman C, Sharp LK, et al. Coping with asthma in immigrant Hispanic families: a focus group study.Ann Al-lergy Asthma Immunol.2006;97(4):477– 483

59. Conn KM, Halterman JS, Fisher SG, Yoos HL, Chin NP, Szilagyi PG. Parental beliefs about medications and medication adher-ence among urban children with asthma.Ambul Pediatr.2005; 5(5):306 –310

60. Yu SM, Huang ZJ, Schwalberg RH, Kogan MD. Parental aware-ness of health and community resources among immigrant families.Matern Child Health J.2005;9(1):27–34

61. Huang ZJ, Yu SM, Ledsky R. Health status and health service

access and use among children in US immigrant families.Am J Public Health.2006;96(4):634 – 640

62. Cabana MD, Lara M, Shannon J. Racial and ethnic disparities in the quality of asthma care. Chest. 2007;132(5 suppl): 810S– 817S

APPENDIX BCQ ITEMS

Skills

1. Knowing how to make the health care system work for you. 2. Doctors or nurses not fluent in your language.

3. Doctors or nurses who speak in a way that is too technical or medical. 4. Getting referrals to specialists.

5. Understanding doctor’s orders.

6. Having enough information about how the health care system works. 7. Needing to be more “savvy” or knowledgeable about getting health care. 8. Getting enough help with paperwork or forms.

Marginalization

1. Feeling like doctors are trying to give as little service as possible.

2. Feeling like the health care system is trying to give as little service as possible. 3. Impatient doctors.

4. Intimidating doctors. 5. Rude office staff. 6. Uncaring office staff.

7. Getting the doctor to listen to you. 8. Getting your questions answered.

9. Not knowing what to expect from one visit to the next. 10. Being judged on your appearance, your ancestry, or your accent. 11. Doctors rushing you and your child through the visit.

Expectations

1. Offices and staff that are not child-friendly. 2. Mistakes made by doctors or nurses.

3. Worrying that doctors and nurses will not do what is right for your child. 4. Doctors treating the symptom without finding out the cause of the illness. 5. Getting a thorough examination.

6. Lack of communication between my child’s doctor and others in the health care system.

7. Lack of communication between different parts of the health care system.

Knowledge and Beliefs

1. Disagreeing with the doctor’s orders.

2. Doctors not believing in home or traditional remedies. 3. Doctors giving you instructions that seem wrong.

4. Doctors or nurses that have different ideas about health than you do.

Pragmatics

1. Getting to the doctor’s office.

2. Getting hold of the doctor’s office or clinic by telephone. 3. Having to wait too many days for an appointment. 4. Getting care after hours or on the weekends. 5. Having to take care of household responsibilities. 6. Having to take time off work.

(10)

DOI: 10.1542/peds.2007-3114

2008;122;994

Pediatrics

Michael Seid

Barriers to Care and Primary Care for Vulnerable Children With Asthma

Services

Updated Information &

http://pediatrics.aappublications.org/content/122/5/994 including high resolution figures, can be found at:

References

http://pediatrics.aappublications.org/content/122/5/994#BIBL This article cites 50 articles, 8 of which you can access for free at:

Subspecialty Collections

http://www.aappublications.org/cgi/collection/asthma_sub Asthma

ub

http://www.aappublications.org/cgi/collection/allergy:immunology_s Allergy/Immunology

following collection(s):

This article, along with others on similar topics, appears in the

Permissions & Licensing

http://www.aappublications.org/site/misc/Permissions.xhtml in its entirety can be found online at:

Information about reproducing this article in parts (figures, tables) or

Reprints

(11)

DOI: 10.1542/peds.2007-3114

2008;122;994

Pediatrics

Michael Seid

Barriers to Care and Primary Care for Vulnerable Children With Asthma

http://pediatrics.aappublications.org/content/122/5/994

located on the World Wide Web at:

The online version of this article, along with updated information and services, is

by the American Academy of Pediatrics. All rights reserved. Print ISSN: 1073-0397.

Figure

TABLE 1Sample Demographic Features, Access to Care, and P3CScores
TABLE 2BCQ Descriptive Statistics and Internal Consistency(N � 252)
TABLE 4Multivariate Regression Analyses of Access to Care, Barriers to Care, and P3C Scores, Controlling for Sociodemographic Features andSeverity

References

Related documents

On February 26, 2003, the Board of Directors, in application of the proxy assigned by the Shareholders’ Meeting on April 6, 2001, resolved a capital increase pursuant to article

and social inclusion, it is felt that guided imagery - if used to enhance social self- esteem - could help to reduce social exclusion in children after all..

In addition, various factors (e.g., water chemistry; types and concentrations of flocculants, biocides, phosphonates, and deposit control polymers used as components of

Conversely, application of 2.5 mMol clodronate bisphospho- nate concentration showed a greater effect on tooth move- ment in the 3-day interval group (E2) compared to 7-day inter-

Portal Solution Reporting Harmonize -Purchasing masters -User Authorization -System Landscape -Global functionalities (P2P cycle). -Cross system data access via one

We then use the Michigan Model of World Production and Trade to simulate the economic effects on the major trading countries/regions of the reductions in tariffs, subsidies

Head Coach Vance Joseph said earlier in the offseason this would "probably" be the case, and it would get Leary back to the position at which he displayed overpowering form

So this study was intended to identify and assess the role of various socio demographic and obstetric factors associated with anaemia among pregnant women in a