Wearable devices are used in the new design of the maternal health care system to detect electrocardiogram and oxygen saturation signal while smart terminals are used to achieve assessments and input maternal clinical information. All the results combined with biochemical analysis from hospital are uploaded to cloud server by mobile Internet. Machine learning algorithms are used for data mining of all information of subjects. This system can achieve the assessment and care of maternal physical health as well as mental health. Moreover, the system can send the results and health guidance to smart terminals.
ObjectiveTo verify the reliability of Anticlot Assistant, a patient self-management system for warfarin therapy assisted by artificial intelligence.MethodsIt was a single-center, prospective cohort study. The eligible 34 participants were recruited consecutively between November 29, 2017 to September 27, 2018 and managed by warfarin therapy via Anticlot Assistant. The recommendations of Anticlot Assistant were examined and verified by the doctors to ensure the security. Medical records were exported from the the background management system. An univariate analysis compared the outcomes between accepted and overridden records and a logistic regression model was built to determine independent predictors of the outcomes. The research team analyzed 153 medical records, which were from 18 participants and were input by 19 doctors. There were 97 records with doctor accepting the suggestion and 56 records with doctor rejecting the suggestion .ResultsWhen the doctors accepted the recommendations, the percentage of the next-test international normalized ratio (INR) in the therapeutic range was higher (64.95% vs. 44.64%, RR=2.298, 95%CI 1.173 to 4.499, P=0.014). The logistic regression analysis revealed that accepting the recommendations was an independent predictor for the next-test INR being in the therapeutic range after controlling potentially confounding factors (OR=2.446, 95%CI 1.103 to 5.423, P=0.028).ConclusionThe algorithm of Anticlot Assistant is reasonable and reliable.
The Day Surgery Center of West China Tianfu Hospital of Sichuan University began operation in 2022, with a focus on same-day surgery. To ensure the quality of medical care for patients undergoing same-day surgery, the Day Surgery Center of West China Tianfu Hospital of Sichuan University utilizes information technology support and adopts an innovative patient health education model. This article mainly introduces the whole process management of health education for patients undergoing same-day surgery mentioned above, which involves many links before admission, during hospitalization, and after discharge. The aim is to provide reference for further optimization of same-day surgery and improve the quality and effectiveness of health education for patients undergoing same-day surgery.