Social Disadvantage, Access to Care, and Disparities in Physical Functioning Among Children Hospitalized with Respiratory Illness
BACKGROUND AND OBJECTIVES: Understanding disparities in child health-related quality of life (HRQoL) may reveal opportunities for targeted improvement. This study examined associations between social disadvantage, access to care, and child physical functioning before and after hospitalization for acute respiratory illness.
METHODS: From July 1, 2014, to June 30, 2016, children ages 8-16 years and/or caregivers of children 2 weeks to 16 years admitted to five tertiary care children’s hospitals for three common respiratory illnesses completed a survey on admission and within 2 to 8 weeks after discharge. Survey items assessed social disadvantage (minority race/ethnicity, limited English proficiency, low education, and low income), difficulty/delays accessing care, and baseline and follow-up HRQoL physical functioning using the Pediatric Quality of Life Inventory (PedsQL, range 0-100). We examined associations between these three variables at baseline and follow-up using multivariable, mixed-effects linear regression models with multiple imputation sensitivity analyses for missing data.
RESULTS: A total of 1,325 patients and/or their caregivers completed both PedsQL assessments. Adjusted mean baseline PedsQL scores were significantly lower for patients with social disadvantage markers, compared with those of patients with none (78.7 for >3 markers versus 85.5 for no markers, difference −6.1 points (95% CI: −8.7, −3.5). The number of social disadvantage markers was not associated with mean follow-up PedsQL scores. Difficulty/delays accessing care were associated with lower PedsQL scores at both time points, but it was not a significant effect modifier between social disadvantage and PedsQL scores.
CONCLUSIONS: Having social disadvantage markers or difficulty/delays accessing care was associated with lower baseline physical functioning; however, differences were reduced after hospital discharge.
© 2020 Society of Hospital Medicine
All study procedures were approved by the Western Institutional Review Board (IRB) or the participating hospitals’ IRB.
Statistical Analysis
Patients with no missing data for all four social disadvantage markers were categorized based on the number of markers they reported: none, one, two, or three or more markers. We combined patients with three and four social disadvantage markers into one group to maximize power for the analyses. We dichotomized the access to care variable and coded response options as “no difficulty/delays accessing care” if the caregiver chose “Never” and “any difficulty/delays accessing care” if they chose “Sometimes/Usually/Always.”
For each patient–caregiver dyad, PedsQL items were scored using a standard method in which higher scores reflected better functioning.22 A single set of PedsQL scores was used for each patient–caregiver dyad. We used self-reported patient scores if the patient completed the PedsQL instrument; otherwise, we used proxy-reported caregiver scores. Intraclass correlations between child self-report and parent proxy-report demonstrate moderate to good agreement above age 8 years.26 We computed a change in the physical functioning score by subtracting the baseline score from the follow-up score. The minimal clinically important difference (MCID) for the PedsQL instrument is 4.5 points, which we used to identify clinically meaningful differences.13
Analysis of variance models were constructed to test for differences in mean baseline and follow-up PedsQL scores (dependent variable) between the following independent variables: (1) social disadvantage groups and (2) those who reported having any difficulty/delays accessing care compared with those who did not. Only patient–caregiver dyads with both baseline and follow-up assessments were included in these analyses. Mixed-effects linear regression models were constructed to identify clinically meaningful differences in PedsQL scores between groups (MCID =/> 4.5) with adjustment for patient age, gender, respiratory condition, days between surveys, and hospital site as fixed effects. Site-specific random effects were included to account for within-hospital clustering. A similarly adjusted mixed-effects linear regression model was constructed to examine whether having any difficulty/delays accessing care modified the association between social disadvantage and PedsQL change scores (eg, an improvement from baseline to follow-up).
Because 17% of respondents had missing data for at least one social disadvantage marker, sensitivity analyses were conducted using multiple imputation to account for missing social disadvantage markers using chained equations.27 Sensitivity analyses were also conducted to adjust for severity of illness using vital sign data within the first 24 hours, which could only be validly captured on patients with asthma within our dataset. By restricting this latter analysis to patients with asthma, we were able to examine the relationships of interest in a population with chronic disease.
RESULTS
The study sample included 1,860 patients, of which 1,325 had both baseline and follow-up PedsQL data (71%). Descriptive statistics were similar between those who completed the baseline and follow-up surveys (Table 1).
Twenty-two percent of patients had >/=3 social disadvantages and 30% of caregivers reported having any difficulty/delays accessing care. The mean follow-up PedsQL score was higher than the baseline score (90.4 vs 82.5; Table 1).
