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Yonsei Medical Journal ; : 243-251, 2018.
Article in English | WPRIM | ID: wpr-713097

ABSTRACT

PURPOSE: Readmission and mortality rates of patients with heart failure are good indicators of care quality. To determine whether hospital resources are associated with care quality for cardiac patients, we analyzed the effect of number of physicians and the combined effects of number of physicians and beds on 30-day readmission and 1-year mortality. MATERIALS AND METHODS: We used national cohort sample data of the National Health Insurance Service (NHIS) claims in 2002–2013. Subjects comprised 2345 inpatients (age: >65 years) admitted to acute-care hospitals for heart failure. A multivariate Cox regression was used. RESULTS: Of the 2345 patients hospitalized with heart failure, 812 inpatients (34.6%) were readmitted within 30 days and 190 (8.1%) had died within a year. Heart-failure patients treated at hospitals with low physician volumes had higher readmission and mortality rates than high physician volumes [30-day readmission: hazard ratio (HR)=1.291, 95% confidence interval (CI)=1.020–1.633; 1-year mortality: HR=2.168, 95% CI=1.415–3.321]. Patients admitted to hospitals with low or middle bed and physician volume had higher 30-day readmission and 1-year mortality rates than those admitted to hospitals with high volume (30-day readmission: HR=2.812, 95% CI=1.561–5.066 for middle-volume beds & low-volume physicians, 1-year mortality: HR=8.638, 95% CI=2.072–36.02 for middle-volume beds & low-volume physicians). CONCLUSION: Physician volume is related to lower readmission and mortality for heart failure. Of interest, 30-day readmission and 1-year mortality were significantly associated with the combined effects of physician and institution bed volume.


Subject(s)
Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Cohort Studies , Heart Failure/diagnosis , Hospitalization , Hospitals, High-Volume/statistics & numerical data , Hospitals, Low-Volume/statistics & numerical data , Patient Readmission/statistics & numerical data , Physicians/economics , Proportional Hazards Models , Quality Improvement , Quality Indicators, Health Care/statistics & numerical data , Time Factors , Treatment Outcome
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