Health Literacy and Hospital Length of Stay: An Inpatient Cohort Study
BACKGROUND: Associations between low health literacy (HL) and adverse health outcomes have been well documented in the outpatient setting; however, few studies have examined associations between low HL and in-hospital outcomes.
OBJECTIVE: To compare hospital length of stay (LOS) among patients with low HL and those with adequate HL.
DESIGN: Hospital-based cohort study.
SETTING: Academic urban tertiary-care hospital.
PATIENTS: Hospitalized general medicine patients.
MEASUREMENTS: We measured HL using the Brief Health Literacy Screen. Severity of illness and LOS were obtained from administrative data. Multivariable linear regression controlling for illness severity and sociodemographic variables was employed to measure the association between HL and LOS.
RESULTS: Among 5540 participants, 20% (1104/5540) had low HL. Participants with low HL had a longer average LOS (6.0 vs 5.4 days, P < 0.001). Low HL was associated with an 11.1% longer LOS (95% confidence interval [CI], 6.1%-16.1%; P < 0.001) in multivariate analysis. This effect was significantly modified by gender (P = 0.02). Low HL was associated with a 17.8% longer LOS among men (95% CI, 10.0%-25.7%; P < 0.001), but only a 7.7% longer LOS among women (95% CI, 1.9%-13.5%; P = 0.009).
CONCLUSIONS: In this single-center cohort study, low HL was associated with a longer hospital LOS. The findings suggest that the adverse effects of low HL may extend into the inpatient setting, indicating that targeted interventions may be needed for patients with low HL. Further work is needed to explore these negative consequences and potential mitigating factors.
© 2017 Society of Hospital Medicine
DISCUSSION
To our knowledge, this study is the first to evaluate the association between low HL and an important in-hospital outcome measure, hospital LOS. We found that low HL was associated with a longer hospital LOS, a result which remained significant when controlling for severity of illness and sociodemographic variables and when testing the model for sensitivity to the highest values of LOS and illness severity. Additionally, the association of HL with LOS appeared concentrated among participants with shorter LOS. Relative to other predictors, the contribution of HL to the overall LOS model was small, as evidenced by the change in adjusted R2 values with HL excluded.
Among the covariates, only gender modified the association between HL and LOS; the findings suggested that men were more susceptible to the effect of low HL on increased LOS. Illness severity and other sociodemographics, including age ≥65, did not appear to modify the association. We also found that being African American and having Medicaid or no insurance were associated with a significantly shorter LOS in multivariate analysis.
Previous work suggested that the adverse health effects of low HL may be mediated through several pathways, including health knowledge, self-efficacy, health skills, and illness stigma.25-27 The finding of a small but significant relationship between HL and LOS was not surprising given these known associations; nevertheless, there may be an additional patient-dependent effect of low HL on LOS not discovered here. For instance, patients with poor health knowledge and self-efficacy might stay in the hospital longer if they or their providers do not feel comfortable with their self-care ability.
This finding may be useful in developing hospital-based interventions. HL-specific interventions, several of which have been tested in the inpatient setting,14,28,29 have shown promise toward improving health knowledge,30 disease severity,31 and health resource utilization.32
Those with low HL may lack the self-efficacy to participate in discharge planning; in fact, previous work has related low HL to posthospital readmissions.8,9 Conversely, patients with low HL might struggle to engage in the inpatient milieu, advocating for shorter LOS if they feel alienated by the inpatient experience.
These possibilities show that LOS is a complex measure shown to depend on patient-level characteristics and on provider-based, geographical, and sociocultural factors.16,33 With these forces at play, additional effects of lower levels of HL may be lost without phenotyping patients by both level of HL and related characteristics, such as self-efficacy, health skills, and stigma. By gathering these additional data, future work should explore whether subpopulations of patients with low HL may be at risk for too-short vs too-long hospital admissions.
For instance, in this study, both race and Medicaid insurance were associated with shorter LOS. Being African American was associated with shorter LOS in our study but has been found to be associated with longer LOS in another study specifically focused on diabetes.34 Prior findings found uninsured patients have shorter LOS.35 Therefore, these findings in our study are difficult to explain without further work to understand whether there are health disparities in the way patients are cared for during hospitalization that may shorten or lengthen their LOS because of factors outside of their clinical need.
The finding that gender modified the effect of low HL on LOS was unexpected. There were similar proportions of men and women with low HL. There is evidence to support that women make the majority of health decisions for themselves and their familes36; therefore, there may be unmeasured aspects of HL that provide an advantage for female vs male inpatients. Furthermore, omitted confounders, such as social support, may not fully capture potential gender-related differences. Future work is needed to understand the role of gender in relationship to HL and LOS.
Limitations of this study include its observational, single-centered design with information derived from administrative data; positive and negative confounding cannot be ruled out. For instance, we did not control for complex aspects affecting LOS, such as discharge disposition and goals of care (eg, aggressive care after discharge vs hospice). To address this limitation, multivariate analyses were performed, which were adjusted for illness severity scores and took into account both comorbidity and severity of the current illness. Additionally, although it is important to study such populations, our largely urban, minority sample is not representative of the U.S. population, and within our large sample, there were participants with missing data who had lower HL on average, although this group represented only 5% of the sample. Finally, different HL tools have noncomplete concordance, which has been seen when comparing the BHLS with more objective tools.20,37 Furthermore, certain in-hospital clinical scenarios (eg, recent stroke or prolonged intensive care unit stay) may present unique challenges in establishing a baseline HL level. However, the BHLS was used in this study because of its greater feasibility.
In conclusion, this study is the first to evaluate the relationship between low HL and LOS. The findings suggest that HL may play a role in shaping outcomes in the inpatient setting and that targeting interventions toward screened patients may be a pathway toward mitigating adverse effects. Our findings need to be replicated in larger, more representative samples, and further work understanding subpopulations within the low HL population is needed. Future work should measure this association in diverse inpatient settings (eg, psychiatric, surgical, and specialty), in addition to assessing associations between HL and other important in-hospital outcome measures, including mortality and discharge disposition.