Exploring the Association of the Relative Factors of Unplanned Readmission for Patients with Ischemic Stroke in a Medical Center

碩士 === 國立臺灣大學 === 健康政策與管理研究所 === 105 === Background: In 2015, the "Hospital Quality Performance Measurement Index System and Implementation Quality Improvement Program" was developed and implemented by the "Center for Quality Management of Healthcare Indicators", which is part of...

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Bibliographic Details
Main Authors: Fei-Tzu Wang, 王斐慈
Other Authors: 鍾國彪
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/e598e7
Description
Summary:碩士 === 國立臺灣大學 === 健康政策與管理研究所 === 105 === Background: In 2015, the "Hospital Quality Performance Measurement Index System and Implementation Quality Improvement Program" was developed and implemented by the "Center for Quality Management of Healthcare Indicators", which is part of the Joint Commission of Taiwan. Findings from the second stage of this program were used to increase the effectiveness of patient level indicators of stroke. Furthermore, "unplanned readmission" was found to be an important indicator of medical institution quality. Therefore, determining how unplanned readmission rates can be reduced has become an important area of health management research. Objectives: In this study, we sought to elucidate the characteristics of patients who experienced unplanned readmission for ischemic stroke. We also explored associations between composite process scores (which are used to determine the effectiveness of patient-level indicators) and unplanned 30- and 90-day hospital readmissions in ischemic stroke patients. Methods: This study investigated a retrospective cohort of ischemic stroke patients who were discharged from the hospital between 2015 and 2016. For this analysis, we used data from the Medicine Integrated Database maintained by the National Taiwan University Hospital Healthcare System, pay-for-performance documents, and case management files of stroke patients. Specifically, we applied multiple logistic regression modeling to investigate how various hospital- and patient-level factors affect unplanned readmission rates for ischemic stroke. Results: In this study, 59% of the patients were male, and the mean age of all patients was 68.78 years. We identified significant correlations between the two composite scores (Row Sum Score & 70% Standard) describing patient-level process indicators and unplanned readmissions within 30 days (p = 0.0195 ; p = 0.0298). Considering patient risk factors, smoking and heart-related disease were significantly correlated with unplanned readmission within 30 days and 90 days (p = 0.0497 ; p = 0.0299), respectively. Conclusions: For ischemic stroke patients, composite scores and smoking were found to be predictors of unplanned readmission within 30 days; heart-related disease was found to be a predictor of unplanned readmission within 90 days. We suggest that future research on ischemic stroke patients investigate different hospital levels, degrees of stroke severity, and patient age groups in order to further elucidate the adverse effects of unplanned readmission within 30 and 90 days. We also suggest that future researchers include data from the National Health Insurance database in their analysis order to obtain results that are as robust and generalizable as possible.