[[alternative]]A Study on the Resident Physicians' Expectation of e-Hospital Medical Information System of National Taiwan University Medical Center

[[abstract]]The concepts and activities of e-commerce, whether in practice or as an area of academic concern, are still at the early stage of development at every hospital in Taiwan. There were many studies about business to business (B2B) model and business to customer (B2C) model of e-commerce, but only a few studies about business to employee (B2E) model. The two purposes of this study were to investigate resident physicians’ satisfaction of using the functions and service content items provided by Intranet, and their expectation of necessity of the e-Hospital medical information B2E model system at National Taiwan University Medical Center (NTUMC). From analysis of the 319 copies (total return rate: 64.97%) of questionnaires, three major results and findings were summarized as follows: 1.Resident physicians at NTUMC were not satisfied with the functions and service content items provided by Intranet. Even by means of the five-category investigation, the degree of their satisfaction was still low. The results indicated that NTUMC had to make great efforts to provide them with better functions and service content items related to medical information. 2.Resident physicians at NTUMC agreed to build the e-Hospital medical information system providing them with support services of medical training, medical treatment and medical study. Through a five-category questionnaire survey of e-Hospital B2E model system, they felt that NTUMC needed to build the best e-Hospital medical information system and answer their requests. 3.The priority of the five categories of which resident physicians felt the degree of importance was: (1) medical out patients department (OPD) and ward admission service, (2) medical information service, (3) medical research and development service, (4) medical continuing education service, and (5) medical administration and management service.

Federated learning for predicting clinical outcomes in patients with COVID-19

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare

36-month clinical outcomes of patients with venous thromboembolism: GARFIELD-VTE

Background: Venous thromboembolism (VTE), encompassing both deep vein thrombosis (DVT) and pulmonary embolism (PE), is a leading cause of morbidity and mortality worldwide.Methods: GARFIELD-VTE is a prospective, non-interventional observational study of real-world treatment practices. We aimed to capture the 36-month clinical outcomes of 10,679 patients with objectively confirmed VTE enrolled between May 2014 and January 2017 from 415 sites in 28 countries.Findings: A total of 6582 (61.6 %) patients had DVT alone, 4097 (38.4 %) had PE +/- DVT. At baseline, 98.1 % of patients received anticoagulation (AC) with or without other modalities of therapy. The proportion of patients on AC therapy decreased over time: 87.6 % at 3 months, 73.0 % at 6 months, 54.2 % at 12 months and 42.0 % at 36 months. At 12-months follow-up, the incidences (95 % confidence interval [CI]) of all-cause mortality, recurrent VTE and major bleeding were 6.5 (7.0-8.1), 5.4 (4.9-5.9) and 2.7 (2.4-3.0) per 100 person-years, respectively. At 36-months, these decreased to 4.4 (4.2-4.7), 3.5 (3.2-2.7) and 1.4 (1.3-1.6) per 100 person-years, respectively. Over 36-months, the rate of all-cause mortality and major bleeds were highest in patients treated with parenteral therapy (PAR) versus oral anti-coagulants (OAC) and no OAC, and the rate of recurrent VTE was highest in patients on no OAC versus those on PAR and OAC. The most frequent cause of death after 36-month follow-up was cancer (n = 565, 48.6 %), followed by cardiac (n = 94, 8.1 %), and VTE (n = 38, 3.2 %). Most recurrent VTE events were DVT alone (n = 564, 63.3 %), with the remainder PE, (n = 236, 27.3 %), or PE in combination with DVT (n = 63, 7.3 %).Interpretation: GARFIELD-VTE provides a global perspective of anticoagulation patterns and highlights the accumulation of events within the first 12 months after diagnosis. These findings may help identify treatment gaps for subsequent interventions to improve patient outcomes in this patient population