![]() ![]() The dataset consisted of 1901 patients' lengths of stay and values for a number of covariates. ![]() The resulting phase-type probability distributions provide a flexible modeling framework for length-of-stay data which are known to be awkward and difficult to fit to other distributions. Admission is via state 1 and discharge from this first state would correspond to a short stay, with transitions to later states corresponding to longer stays. The model has the process of hospital stay organized into Markov phases/states that describe stay in hospital before discharge to an absorbing state. To demonstrate the effect of poorly fitting models on decision-making. To undertake critical comparisons with alternative models based on the gamma and log-normal distributions. ![]() To present a relatively novel method for modeling length-of-stay data and assess the role of covariates, some of which are related to adverse events. From the data processing results obtained a total bed occupancy rate 60.83%, bed turnover rate 6.86 times, turnover interval 2 days and average length of stay 3 days.Conclusions: Statistical data obtained from SPH in 2018 shows the value of BOR, TI is in an efficient, while BTR and LOS are inefficient. This research method is descriptive by direct observation of the medical record file of inpatients since the January to December 2017 period.Results: Statistical data obtained from SPH in 2018 showed the value of service days 30132, and the Number of beds 144 units. This research was conducted at Semen Padang Hospital (SPH), Padang, West Sumatera, Indonesia.Methods: The purpose of this study was to determine the statistical value of hospital and hospital service efficiency levels by using the Barber Johnson graphic. This graph can also be used to compare or view hospital developments at different times, and to increase the likelihood of changes in one variable by changing other variables. The indicators used are bed occupancy rate (BOR), bed turnover rate (BTR), turnover interval (TI), and length of stay (LOS). GBJ is needed to see and measure the level of service efficiency in hospitals. One measurement of service indicators that can be used is the Barber Johnson graph (GBJ). ![]() Background: The efficiency of service delivery is very important for hospitals. ![]()
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