Disparities After Discharge: The Association of Limited English Proficiency and Postdischarge Patient-Reported Issues

Abstract

Background: The transition from hospital to home is a vulnerable period for all patients, particularly for those who have limited English proficiency (LEP).

Methods: The research team retrospectively studied adults discharged home from a hospital in 2018-2019 to determine the association of LEP with (1) reach of a care transitions outreach program phone call (automated call within three days after discharge or a subsequent manual phone call) and (2) postdischarge issues reported on the phone calls. All results were adjusted for measured confounders; associations using predicted probabilities and average marginal effects were described.

Results: A total of 13,860 patients were included, and 11.3% had LEP. After adjustment, the program reached most patients regardless of LEP status; automated calls were more likely to reach English proficient patients (81.1% vs. 75.6%, p < 0.01), and when the automated call was unsuccessful, manual calls were more likely to reach LEP patients (47.8% vs. 28.3%, p < 0.001). After adjustment, patients with LEP reported more difficulty with all measured issues: understanding discharge instructions (11.3% vs. 6.5%), obtaining prescriptions (8.3% vs. 5.5%), medication concerns (12.9% vs. 10.6%), follow-up questions (16.1% vs. 13.3%), new or worsening symptoms (15.1% vs. 11.9%), and any other clinical issues (16.6% vs. 13.0%); p < 0.05 for all comparisons.

Conclusion: Although reach was high for the care transitions program, among patients with LEP, important disparities exist in patient-reported postdischarge issues. These results indicate the need for better discharge processes that focus on communication quality and health equity.

Figure 1:

Predicted probabilities from the adjusted model are presented. Separate models are fit at each stage (i.e., reached by automated call, met criteria for manual call, reached by manual call). All models were adjusted for the following confounders: age, race, ethnicity, marital status, insurance, discharging service, Elixhauser score, discharge disposition, length of stay. For all differences, p < 0.01. Unadjusted results can be found in Appendix 3. All patients in the study were eligible for an automated call. If a patient failed to answer the automated call and met any of the following specific criteria—age > 85 years, discharged home with home services, limited English proficiency, or part of the study site’s Medicare accountable care organization—a centralized care transition nurse would review the patient’s chart and call the patient manually if they had not already been contacted by a clinician (physician, nurse practitioner, physician’s assistant) or had another health care encounter.

Figure 2:

Predicted probabilities from the adjusted model are presented. Separate models were fit for each issue and included patients who answered the question: discharge instruction (n = 10,458), getting prescriptions (n = 7,849), medication concerns (n = 10,693), follow-up questions (n = 10,554), new or worsening symptoms (n = 11,224), any other clinical issues (n = 10,170). Models were adjusted for the following confounders: age, race, ethnicity, marital status, insurance, discharging service, Elixhauser score, discharge disposition, length of stay. * The difference between groups is statistically significant with p < 0.05. Discharge instruction difference 4.8% (95% confidence interval [CI], 2.7% to 6.9%), p < 0.001; getting prescriptions difference 2.9% (95% CI, 0.6% to 5.1%), p = 0.012; medications concerns difference 2.3% (95% CI, 0.0% to 4.6%), p = 0.0495; follow-up questions difference 2.8% (95% CI, 0.3% to 5.3%), p = 0.027; new or worsening symptoms difference 3.2% (95% CI, 0.7% to 5.8%), p = 0.012; any other clinical issues difference 3.6% (95% CI, 1.1% to 6.1%), p = 0.004. Unadjusted results can be found in Appendix 3. LEP, limited English proficiency; EP, English proficient.