ObjectiveTo present the application of mini-health technology assessment (Mini-HTA) method in configuration management of anti-magnetic anesthesia machine.MethodsFrom February to March 2019, the specialist operation assistant used Mini-HTA method to analyze and evaluate the anti-magnetic anesthesia machine applied by the department from basic situation and four dimensions, including technical dimension, patient dimension, hospital dimension, and economic dimension.ResultsA hospital health technology assessment report was prepared based on the evaluation of the specialist operation assistant, the suggestion of which was adopted by the hospital. As a result, an anti-magnetic anesthesia machine was arranged in the MRI room.ConclusionMini-HTA method can provide decision support for hospital equipment configuration and is conducive to the scientific and rational allocation of resources in hospitals.
Objective To accurately predict the outpatient and emergency visits of a district-level public hospital based on autoregressive integrated moving average (ARIMA) model, providing important basis for hospital budget planning and operational decisions. Methods The monthly outpatient and emergency visits of a public hospital in Shuangliu District, Chengdu City from January 2012 to November 2023 were collected, and R 4.3.1 software was used to establish an ARIMA model based on the data from January 2012 to December 2022. The outpatient and emergency visits from January to November 2023 were predicted and validated. Results Except for January and March 2023, every monthly number of predicted outpatient and emergency visits for 2023 matched the actual one relatively well. The average absolute percentage error for January to November 2023 was 8.504%. The actual total number of outpatient and emergency visits from January to November 2023 was 1441960, and the predicted value was 1417130 with a relative error of –1.722%. Conclusions ARIMA model can predict the outpatient and emergency visits of district-level hospitals relatively well. However, factors such as the high incidence of COVID-19 may affect the accuracy of short-term prediction.