• Tuberculosis and Respiratory Diseases
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• v.83 no.2
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• pp.147-156
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• 2020

Background: Limited studies have been performed to assess readmission following hospitalization for community-acquired pneumonia (CAP) in an Asian population. We evaluated the rates, reasons, and risk factors for 30-day readmission following hospitalization for CAP in the general adult population of Korea. Methods: We performed a retrospective observational study of 1,021 patients with CAP hospitalized at Yeungnam University from March 2012 to February 2014. The primary end point was all-cause hospital readmission within 30 days following discharge after the initial hospitalization. Hospital readmission was classified as pneumonia-related or pneumonia-unrelated readmission. Results: During the study period, 862 patients who survived to hospital discharge were eligible for inclusion and among them 72 (8.4%) were rehospitalized within 30 days. In the multivariable analysis, pneumonia-related readmission was associated with para/hemiplegia, malignancy, pneumonia severity index class ≥4 and clinical instability ≥1 at hospital discharge. Comorbidities such as chronic lung disease and chronic kidney disease, treatment failure, and decompensation of comorbidities were associated with the pneumonia-unrelated 30-day readmission rate. Conclusion: Rehospitalizations within 30 days following discharge were frequent among patients with CAP. The risk factors for pneumonia-related and -unrelated readmission were different. Aspiration prevention, discharge at the optimal time, and close monitoring of comorbidities may reduce the frequency of readmission among patients with CAP.

• Quality Improvement in Health Care
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• v.22 no.1
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• pp.29-37
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• 2016

Readmission which reflects capacity to manage patients and general level of medical services has been known for one of the causes of medical expenditure due to inefficient service. Compared to disease-specific readmission, hospital wide readmission (HWR) is relatively easy to understand, and has merit to get over limitation of collateral medical services assessment; therefore, a growing interest in development and usage of readmission indicator as quality of care indicator focusing on all-disease is detected. In this study, we investigate current state of risk standardized readmission rate indicator used in the United States, the United Kingdom, and Canada, and examine the considerations when using readmission rate as quality indicator in Korea. Differences in risk-adjustment methods were showed among countries. The United States do not control race not to hide socio-demographic factors on readmission. Canada shows differentiation compared to other countries about reflecting community factors. All three-countries utilize readmission rate as monitoring quality of care rather than incentives or penalty due to the fact that readmission rate could not represent the whole quality of hospital and has a limitation at controlling socio-economic factors. Therefore, for usage readmission rate as quality indicator in Korea, preparing readmission classification standard for Korean medical environment and additional methods for acquiring information by using discharge summary is need. Moreover, continued discussion with clinical specialists is needed for obtain clinical reliability and validity.

• Health Policy and Management
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• v.25 no.3
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• pp.197-206
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• 2015

Background: The purpose of this study was to propose a method for developing a measure of hospital-wide all-cause risk-standardized readmissions using administrative claims data in Korea and to discuss further considerations in the refinement and implementation of the readmission measure. Methods: By adapting the methodology of the United States Center for Medicare & Medicaid Services for creating a 30-day readmission measure, we developed a 6-step approach for generating a comparable measure using Korean datasets. Using the 2010 Korean National Health Insurance (NHI) claims data as the development dataset, hierarchical regression models were fitted to calculate a hospital-wide all-cause risk-standardized readmission measure. Six regression models were fitted to calculate the readmission rates of six clinical condition groups, respectively and a single, weighted, overall readmission rate was calculated from the readmission rates of these subgroups. Lastly, the case mix differences among hospitals were risk-adjusted using patient-level comorbidity variables. The model was validated using the 2009 NHI claims data as the validation dataset. Results: The unadjusted, hospital-wide all-cause readmission rate was 13.37%, and the adjusted risk-standardized rate was 10.90%, varying by hospital type. The highest risk-standardized readmission rate was in hospitals (11.43%), followed by general hospitals (9.40%) and tertiary hospitals (7.04%). Conclusion: The newly developed, hospital-wide all-cause readmission measure can be used in quality and performance evaluations of hospitals in Korea. Needed are further methodological refinements of the readmission measures and also strategies to implement the measure as a hospital performance indicator.

• Journal of Korean Clinical Nursing Research
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• v.19 no.2
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• pp.265-274
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• 2013

Purpose: The aim of this study was to determine the risk factors contributed to unplanned readmission to intensive care unit (ICU) and to investigate the prediction model of unplanned readmission. Methods: We retrospectively reviewed the electronic medical records which included the data of 3,903 patients who had discharged from ICUs in a university hospital in Seoul from January 2011 to April 2012. Results: The unplanned readmission rate was 4.8% (n=186). The nine variables were significantly different between the unplanned readmission and no readmission groups: age, clinical department, length of stay at 1st ICU, operation, use of ventilator during 24 hours a day, APACHE II score at ICU admission and discharge, direct nursing care hours and Glasgow coma scale total score at 1st ICU discharge. The clinical department, length of stay at 1st ICU, operation and APACHE II score at ICU admission were the significant predictors of unplanned ICU readmission. The predictive model's area under the curve was .802 (p<.001). Conclusion: We identified the risk factors and the prediction model associated with unplanned ICU readmission. Better patient assessment tools and knowledge about risk factors could contribute to reduce unplanned ICU readmission rate and mortality.

• Archives of Plastic Surgery
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• v.41 no.2
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• pp.116-121
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• 2014

Background Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery. Methods The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both "Plastics" as their recorded surgical specialty and inpatient status. Readmission was tracked through the "Unplanned Readmission" variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission. Results A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD) (odds ratio [OR], 2.01; confidence interval [CI], 1.12- 3.60; P=0.020), previous percutaneous coronary intervention (PCI) (OR, 2.69; CI, 1.21-5.97; P=0.015), hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001), bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046), American Society of Anesthesiologists (ASA) class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004), and obesity (body mass index ${\geq}30$) (OR, 1.43; CI, 1.09-1.88, P=0.011) to be significant predictors of readmission. Conclusions Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations.

• Health Policy and Management
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• v.31 no.4
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• pp.451-461
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• 2021

Background: Readmissions related to lack of quality care harm both patients and health insurance finances. If the factors affecting readmission are identified, the readmission can be managed by controlling those factors. This paper aims to identify factors that affect readmissions of convalescent rehabilitation patients. Methods: Health Insurance Review and Assessment Service claims data were used to identify readmissions of convalescent patients who were admitted in hospitals and long-term care hospitals nationwide in 2018. Based on prior research, the socio-demographics, clinical, medical institution, and staffing levels characteristics were included in the research model as independent variables. Readmissions for convalescent rehabilitation treatment within 30 days after discharge were analyzed using logistic regression and generalization estimation equation. Results: The average readmission rate of the study subjects was 24.4%, and the risk of readmission decreases as age, length of stay, and the number of patients per physical therapist increase. In the patient group, the risk of readmission is lower in the spinal cord injury group and the musculoskeletal system group than in the brain injury group. The risk of readmission increases as the severity of patients and the number of patients per rehabilitation medicine specialist increases. Besides, the readmission risk is higher in men than women and long-term care hospitals than hospitals. Conclusion: "Reducing the readmission rate" is consistent with the ultimate goal of the convalescent rehabilitation system. Thus, it is necessary to prepare a mechanism for policy management of readmission.

• Health Policy and Management
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• v.26 no.2
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• pp.148-152
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• 2016

The hospital readmission rate has been widely used as an indicator of the quality of hospital care in many countries. However, the transferrability of this indicator that has been developed in a different health care system can be questioned. We reviewed what should be considered when using the risk-standardized readmission rate (RSRR) as a generic quality indicator in the Korean setting. We addressed the relationship between RSRR and the quality of hospital care, methodological aspects of RSRR, and use of RSRR for external purposes. These issues can influence the validity of the readmission rate as a generic quality indicator. Therefore RSRR should be used with care and further studies are needed to enhance the validity of the readmission rate indicator.

• Tuberculosis and Respiratory Diseases
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• v.83 no.4
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• pp.303-311
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• 2020

Background: If the duration of mechanical ventilation (MV) is related with the intensive care unit (ICU) readmission must be clarified. The purpose of this study was to elucidate if prolonged MV duration increases ICU readmission rate. Methods: The present observational cohort study analyzed national healthcare claims data from 2006 to 2015. Critically ill patients who received MV in the ICU were classified into five groups according to the MV duration: MV for <7 days, 7-13 days, 14-20 days, 21-27 days, and ≥28 days. The rate and risk of the ICU readmission were estimated according to the MV duration using the unadjusted and adjusted analyses. Results: We found that 12,929 patients had at least one episode of MV in the ICU. There was a significant linear relationship between the MV duration and the ICU readmission (R²=0.85, p=0.025). The total readmission rate was significantly higher as the MV duration is prolonged (MV for <7 days, 13.9%; for 7-13 days, 16.7%; for 14-20 days, 19.4%; for 21-27 days, 20.4%; for ≥28 days, 35.7%; p<0.001). The analyses adjusted by covariables and weighted with the multinomial propensity scores showed similar results. In the adjusted regression analysis with a Cox proportional hazards model, the MV duration was significantly related to the ICU readmission (hazard ratio, 1.058 [95% confidence interval, 1.047-1.069], p<0.001). Conclusion: The rate of readmission to the ICU was significantly higher in patients who received longer durations of the MV in the ICU. In the clinical setting, closer observation of patients discharged from the ICU after prolonged periods of MV is required.

• Korean Journal of Clinical Pharmacy
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• v.33 no.1
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• pp.1-7
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• 2023

Background: Along with the increase in the elderly population, concerns about polypharmacy, which can cause medication-related problems, are increasing. This study aimed to find out the association between drug-related factors and readmission in elderly patients within 30 days after discharge. Methods: Data of patients aged ≥65 years who were discharged from the respiratory medicine ward of a tertiary hospital between January and March 2016 were retrospectively obtained. The medication regimen complexity at discharge was calculated using the medication regimen complexity index (MRCI) score, comorbidity status was assessed using the Charlson comorbidity index (CCI), potentially inappropriate medications (PIMs) were evaluated based on the Beer 2019 criteria, and adverse drug events (ADEs) were examined using the ADE reporting system. Multivariable logistic regression analysis was used to evaluate the effect of medication-related problems on hospital readmission after controlling for other variables. Results: Of the 206 patients included, 84 (40.8%) used PIMs, 31 (15%) had ADEs, and 32 (15.5%) were readmitted. The mean age, total medications, MRCI, CCI, and PIMs in the readmission group were significantly higher than those in the non-readmission group. Age significantly decreased the risk of readmission (odds ratio [OR], 0.89; 95% confidence interval [CI], 0.84-0.96) after adjusting for sex, length of hospital stay, and ADEs. The use of PIMs (OR, 2.38; 95% CI, 1.10-5.16) and increased CCI (OR, 1.50; 95% CI, 1.16-1.93) and MRCI (OR, 1.04; 95% CI, 1.01-1.07) were associated with an increased occurrence of readmission. Conclusion: PIMs were associated with a significantly greater risk for readmission than MRCI.

• Journal of Preventive Medicine and Public Health
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• v.32 no.3
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• pp.289-296
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• 1999

Objectives: This study describes the risk factors affecting the unexpected readmission of 261 patients who were discharged from a university hospital in Seoul. Methods: This case-control study reviewed medical records of inpatients who had been discharged from a hospital between 1 August 1995 and 31 October 1995 after the treatment for general diseases. The cases were 68 patients who were readmitted unexpectedly within 28 days of discharge from an index stay, and the controls were 193 Patients who were discharged without readmission during the study period. Results: Logistic regression analysis results were as follows; Patients who had no operation during their hospital stay were more likely to be readmitted unexpectedly than patients who had operation. Patients who had 1 or 2 parts of their body being involved in treatment were more likely to be readmitted unexpectedly than patients who hand more than 3 parts of their body being involved in treatment. Patients who had complications after surgery were more likely to be readmitted unexpectedly than patients who had no complications. Insufficient discharge planning caused unexpected readmissions. Conclusions: Discharge planning education should be extended to health care providers. And the assessment of discharge planning should be evaluated. Readmission is often necessary for the treatment of related problems of originating from initial hospitalization, which causes cost problems. Unexpected readmission is preventable and the models for readmission can serve as a valuable clinical tool for high risk patients.