Patient claims data were matched to the hospitals where each pati

Patient claims data were matched to the hospitals where each patient was admitted.

Hospital-level data included fty720 PP2a characteristics of the hospital, such as hospital type (specialty, tertiary, large, small), number of beds (in 100 bed increments), specialists per 100 beds, nurses per 100 beds, hospital location (metropolitan if located in cities with a population of more than one million), teaching status and bed occupancy rate. According to the Korean Hospital Association, Korean hospitals are categorised into three groupings based on bed size: (1) hospitals with over 1000 beds: tertiary research university hospitals, (2) hospitals with 300–1000 beds: mid-sized general hospitals and (3) hospitals with 100–300 beds: small general hospitals. The specialty hospitals and the small general hospitals in our study both fell within category 3 (small general hospitals).21 The hospital level data were obtained from the Agency for Health Insurance Review and Assessment Services. In order to investigate the post

policy designation effect, we included the interaction term of type of hospital and year, which we named designation effect. We also included data envelopment analysis (DEA) using efficiency as the dummy variable (1=efficient, 0=non-efficient) to determine whether hospitals were operated efficiently using a conventional technical efficiency measuring technique.22 It is derived from microeconomics methodology where input and output combinations are depicted

using a production function to measure the efficiency of multiple decision-making units (in this case hospitals) when the production process presents a structure of multiple inputs and outputs.22 Input variables included number of beds, surgical beds, recovery beds, specialists, residents, nurses, physical therapists and pharmacists; and positron emission tomography, CT and MRI units of each hospital. Output variables included total number of inpatient cases and AV-951 sum of charges in 2011 and 2012 study periods for each hospital. Hospital-level statistics were collected based on their first quarter of 2012 status, which was the only available data set at the time of this study. Analytical approach Mean and SD were analysed for continuous variables; frequency and per cent were analysed for categorical variables. Univariate analysis of inpatient charges, LOS, readmission within 30 days of discharge and mortality within 30 days of admission was performed to investigate the unadjusted effects of hospital types on these measures. Analysis of variance and χ2 tests were performed for identification of group differences.

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