Abstract
BackgroundData on hospital discharges can be used as a valuable instrument for hospital planning and management. The quantification of deaths can be considered a measure of the effectiveness of hospital intervention, and a high percentage of hospital discharges due to death can be associated with deficiencies in the quality of hospital care.ObjectiveTo determine the overall percentage of hospital discharges due to death in a Mexican tertiary care hospital from its opening, to describe the characteristics of the time series generated from the monthly percentage of hospital discharges due to death and to make and evaluate predictions.MethodsThis was a retrospective study involving the medical records of 81,083 patients who were discharged from a tertiary care hospital from April 2007 to December 2019 (first 153 months of operation). The records of the first 129 months (April 2007 to December 2017) were used for the analysis and construction of the models (training dataset). In addition, the records of the last 24 months (January 2018 to December 2019) were used to evaluate the predictions made (test dataset). Structural change was identified (Chow test), ARIMA models were adjusted, predictions were estimated with and without considering the structural change, and predictions were evaluated using error indices (MAE, RMSE, MAPE, and MASE).ResultsThe total percentage of discharges due to death was 3.41%. A structural change was observed in the time series (March 2009, p>0.001), and ARIMA(0,0,0)(1,1,2)12 with drift models were adjusted with and without consideration of the structural change. The error metrics favored the model that did not consider the structural change (MAE = 0.63, RMSE = 0.81, MAPE = 25.89%, and MASE = 0.65).ConclusionOur study suggests that the ARIMA models are an adequate tool for future monitoring of the monthly percentage of hospital discharges due to death, allowing us to detect observations that depart from the described trend and identify future structural changes.
Highlights
Data on hospital discharges due to death can be used as a valuable instrument for hospital planning and management [1]
Our study suggests that the Autoregressive integrated moving average (ARIMA) models are an adequate tool for future monitoring of the monthly percentage of hospital discharges due to death, allowing us to detect observations that depart from the described trend and identify future structural changes
Through the detection of a structural change in the series of the monthly percentage of hospital discharges due to death, we identified that hospital mortality at the HRAEB can be described by a growing trend from its opening (April 2007) to March 2009 and by a decreasing trend from April 2009 to December 2019, in addition to seasonal behavior
Summary
Data on hospital discharges due to death can be used as a valuable instrument for hospital planning and management [1]. The number of national hospital discharges recorded by Mexican SSA hospitals as primary sources in the SAEH is estimated to be 3 million cases per year, and of these, approximately 2% are deaths [3]. The Bajıo Regional Hospital of High Specialty (Hospital Regional de Alta Especialidad del Bajío—HRAEB) has provided clinical, diagnostic, and tertiary treatment services since April 2007. It has 184 census beds, does not have an emergency department, and discharges patients with complex pathologies. Data on hospital discharges can be used as a valuable instrument for hospital planning and management. The quantification of deaths can be considered a measure of the effectiveness of hospital intervention, and a high percentage of hospital discharges due to death can be associated with deficiencies in the quality of hospital care
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