Characteristics and related factors of emergency department visits, readmission, and hospital transfers of inpatients under a DRG-based payment system: A nationwide cohort study

Abstract

Objectives Taiwan has implemented the Diagnosis Related Groups (DRGs) since 2010, and the quality of care under the DRG-Based Payment System is concerned. This study aimed to examine the characteristics, related factors, and time distribution of emergency department (ED) visits, readmission, and hospital transfers of inpatients under the DRG-Based Payment System for each Major Diagnostic Category (MDC). Methods We conducted a retrospective cohort study using data from the National Health Insurance Research Database (NHIRD) from 2012 to 2013 in Taiwan. Multilevel logistic regression analysis was used to examine the factors related to ED visits, readmissions, and hospital transfers of patients under the DRG-Based Payment System. Results In this study, 103,779 inpatients were under the DRG-Based Payment System. Among these inpatients, 4.66% visited the ED within 14 days after their discharge. The factors associated with the increased risk of ED visits within 14 days included age, lower monthly salary, urbanization of residence area, comorbidity index, MDCs, and hospital ownership (p < 0.05). In terms of MDCs, Diseases and Disorders of the Kidney and Urinary Tract (MDC11) conferred the highest risk of ED visits within 14 days (OR = 4.95, 95% CI: 2.69–9.10). Of the inpatients, 6.97% were readmitted within 30 days. The factors associated with the increased risk of readmission included gender, age, lower monthly salary, comorbidity index, MDCs, and hospital ownership (p < 0.05). In terms of MDCs, the inpatients with Pregnancy, Childbirth and the Puerperium (MDC14) had the highest risk of readmission within 30 days (OR = 20.43, 95% CI: 13.32–31.34). Among the inpatients readmitted within 30 days, 75.05% of them were readmitted within 14 days. Only 0.16% of the inpatients were transferred to other hospitals. Conclusion The study shows a significant correlation between Major Diagnostic Categories in surgery and ED visits, readmission, and hospital transfers. The results suggested that the main reasons for the high risk may need further investigation for MDCs in ED visits, readmissions, and hospital transfers.

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“…However, the summary metric scores of TCVH, ̅̅̅̅̅̅ , ̅̅̅̅̅̅̅̅ , and ̅̅̅̅̅̅̅̅ suggest that Hospital B performed at a higher level than Hospital A, even though the average cost of Hospital B (10,656) was slightly higher than that of Hospital A (10,572). As an emergency hospital, Hospital A has a different structure to Hospital B that aligns with other studies [39,40].…”

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“…The electronic medical record captured patient status (dead/alive) for all-cause mortality. Although patients may have died at an outside hospital with a separate electronic medical record, we believe the prevalence is low as a previous study of readmissions in Taiwan using the government’s National Health Insurance Research Database found that only 0.16% of readmissions occurred at a different hospital 12 . Moreover, we ensured the censored patients were alive at the last known hospital encounter.…”