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BACKGROUND: The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences. OBJECTIVE: The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes. METHODS: From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People's Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures. RESULTS: We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased. CONCLUSIONS: In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China.

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OBJECTIVE: To establish the exponential smoothing prediction model and SARIMA model to predict the number of inpatients in a third-class hospital in Zhejiang Province, and evaluate the prediction effect of the two models, and select the best number prediction model. METHODS: The data of hospital admissions from January 2019 to September 2022 were selected to establish the exponential smoothing prediction model and the SARIMA model respectively. Then compare the fitting parameters of different models: R2_adjusted, R2, Root Mean Square Error (RMSE)、Mean Absolute Percentage Error (MAPE)、Mean Absolute Error(MAE) and standardized BIC to select the best model. Finally, the established model was used to predict the number of hospital admissions from October to December 2022, and the prediction effect of the average relative error judgment model was compared. RESULTS: The best fitting exponential smoothing prediction model was Winters Addition model, whose R2_adjusted was 0.533, R2 was 0.817, MAPE was 6.133, MAE was 447.341. The best SARIMA model is SARIMA(2,2,2)(0,1,1)12 model, whose R2_adjusted is 0.449, R2 is 0.199, MAPE is 8.240, MAE is 718.965. The Winters addition model and SARIMA(2,2,2)(0,1,1)12 model were used to predict the number of hospital admissions in October-December 2022, respectively. The results showed that the average relative error was 0.038 and 0.015, respectively. The SARIMA(2,2,2)(0,1,1)12 model had a good prediction effect. CONCLUSION: Both models can better fit the number of admissions, and SARIMA model has better prediction effect.

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To study the application of PBL combined with CBL teaching mode in the teaching of international classification of diseases (ICD) encoding, so as to improve students' grasp of ICD encoding knowledge. From March 2020 to June 2020, 50 students majoring in health information management who were interns in a Grade A general hospital were selected as the research participants and randomly divided into experimental group and control group, 25 in each group. The experimental group and the control group adopted the PBL combined CBL teaching mode and the traditional teaching mode respectively to carry out the classification and coding teaching. The academic achievement of the two groups of students was evaluated by means of achievement assessment and questionnaire survey based on information processing theory. The scores of theoretical knowledge in the experimental group and the control group were 79.78 ± 8.55 and 70.92 ± 10.81, respectively, and the scores of skill operation in the two groups were 79.76 ± 8.28 and 70.00 ± 10.41, respectively. The test scores of the experimental group were higher than those of the control group, and the difference was statistically significant (P < 0.05). The scores of knowledge acquisition ability of experimental group and control group were 16.72 ± 1.79 and 16.60 ± 2.36, the scores of knowledge sharing ability were 24.20 ± 2.61 and 21.00 ± 2.65, the scores of knowledge storage ability were 20.80 ± 2.47 and 17.24 ± 4.90, respectively. The scores of knowledge application ability were 14.00 ± 1.80 and 11.00 ± 2.69, the scores of knowledge innovation ability were 20.16 ± 2.34 and 18.08 ± 3.70, and the total scores were 95.88 ± 6.08 and 83.92 ± 11.30, respectively. The scores of all questionnaires in the experimental group were higher than those in the control group. The scores of knowledge sharing ability, knowledge storage ability, knowledge application ability, knowledge innovation ability and total score between the two groups were higher than those of the control group, and the differences were statistically significant (P < 0.05). PBL combined with CBL teaching model has good academic achievement in ICD encoding teaching, which can significantly improve academic performance and learning ability, and is worthy of promotion.

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