scholarly journals A Clinical Decision Support System for Prevention of Venous Thromboembolism

JAMA ◽  
2000 ◽  
Vol 283 (21) ◽  
pp. 2816 ◽  
Author(s):  
Pierre Durieux ◽  
Rémy Nizard ◽  
Philippe Ravaud ◽  
Nicolas Mounier ◽  
Eric Lepage
Keyword(s):  
Decision Support ◽  
Venous Thromboembolism ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision

scholarly journals Validation of a Smartphone Application for Assessment of Risk of Venous Thromboembolism in Obstetrics and Gynecology

2017 ◽  
Vol 24 (2) ◽  
pp. 33-40 ◽  
Author(s):  
Galila F. Zaher ◽  
Soheir S. Adam
Keyword(s):  
Decision Support ◽  
Venous Thromboembolism ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Risk Score ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
University Hospital ◽  
Obstetrics And Gynecology

Venous thromboembolism is a serious but potentially preventable condition. However, morbidity and mortality occur due to lack of thrombo-prophylaxis. Obstetrics and gynecology patients are at risk for developing venous thromboembolism. To improve adherence to thromboprophylaxis in this patient population, we developed a smart phone clinical decision support system designed to assess risk score and recommend thromboprophylaxis. Clinical data were collected by review of electronic medical charts. The risk score and thromboprophylaxis recommendations were calculated for each patient by clinical decision support system and by an expert hematologist and results were compared for correlation. We hypothesize that the system is a valid tool for risk assessment in obstetrics and gynecology patients. A total of 188 female patients admitted at King Abdulaziz University Hospital between December 2015 and March 2016 were included. One hundred and sixteen were gynecology, and 72 were obstetric patients with a mean age of 40.7 (± 12.8). The risk score obtained by the system showed a strong correlation with that of the expert hematologist’s opinion (r = 83%). The clinical decision support system showed a good correlation for thromboprophylaxis decision as well. Accessibility and ease of use of clinical decision support system can improve the clinical outcome of hospitalized patients.

scholarly journals A clinical decision support system for venous thromboembolism prophylaxis at a general hospital in a middle-income country

2013 ◽  
Vol 39 (2) ◽  
pp. 138-146 ◽  
Author(s):  
Fernanda Fuzinatto ◽  
Fernando Starosta de Waldemar ◽  
André Wajner ◽  
Cesar Al Alam Elias ◽  
Juliana Fernándes Fernandez ◽  
...  
Keyword(s):  
Decision Support ◽  
Venous Thromboembolism ◽  
Decision Support System ◽  
General Hospital ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Vte Prophylaxis ◽  
The Impact

OBJECTIVE: To determine the impact that implementing a combination of a computer-based clinical decision support system and a program of training seminars has on the use of appropriate prophylaxis for venous thromboembolism (VTE). METHODS: We conducted a cross-sectional study in two phases (prior to and after the implementation of the new VTE prophylaxis protocol) in order to evaluate the impact that the combined strategy had on the use of appropriate VTE prophylaxis. The study was conducted at Nossa Senhora da Conceição Hospital, a general hospital in the city of Porto Alegre, Brazil. We included clinical and surgical patients over 18 years of age who were hospitalized for ≥ 48 h. The pre-implementation and post-implementation phase samples comprised 262 and 261 patients, respectively. RESULTS: The baseline characteristics of the two samples were similar, including the distribution of patients by risk level. Comparing the pre-implementation and post-implementation periods, we found that the overall use of appropriate VTE prophylaxis increased from 46.2% to 57.9% (p = 0.01). Looking at specific patient populations, we observed that the use of appropriate VTE prophylaxis increased more dramatically among cancer patients (from 18.1% to 44.1%; p = 0.002) and among patients with three or more risk factors (from 25.0% to 42.9%; p = 0.008), two populations that benefit most from prophylaxis. CONCLUSIONS: It is possible to increase the use of appropriate VTE prophylaxis in economically constrained settings through the use of a computerized protocol adhered to by trained professionals. The underutilization of prophylaxis continues to be a major problem, indicative of the need for ongoing improvement in the quality of inpatient care.

1309-P: Utilizing a Clinical Decision Support System for Hypoglycemia Management

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1309-P
Author(s):  
JACQUELYN R. GIBBS ◽  
KIMBERLY BERGER ◽  
MERCEDES FALCIGLIA
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision

A Clinical Decision Support System for Assessing the Risk of Cardiovascular Diseases in Diabetic Hemodialysis Patients

2020 ◽  
Vol 16 (3) ◽  
pp. 262-269
Author(s):  
Tahere Talebi Azad Boni ◽  
Haleh Ayatollahi ◽  
Mostafa Langarizadeh
Keyword(s):  
Decision Support ◽  
Cardiovascular Diseases ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Diabetic Patients ◽  
K Value ◽  
Care Plans

Background: One of the greatest challenges in the field of medicine is the increasing burden of chronic diseases, such as diabetes. Diabetes may cause several complications, such as kidney failure which is followed by hemodialysis and an increasing risk of cardiovascular diseases. Objective: The purpose of this research was to develop a clinical decision support system for assessing the risk of cardiovascular diseases in diabetic patients undergoing hemodialysis by using a fuzzy logic approach. Methods: This study was conducted in 2018. Initially, the views of physicians on the importance of assessment parameters were determined by using a questionnaire. The face and content validity of the questionnaire was approved by the experts in the field of medicine. The reliability of the questionnaire was calculated by using the test-retest method (r = 0.89). This system was designed and implemented by using MATLAB software. Then, it was evaluated by using the medical records of diabetic patients undergoing hemodialysis (n=208). Results: According to the physicians' point of view, the most important parameters for assessing the risk of cardiovascular diseases were glomerular filtration, duration of diabetes, age, blood pressure, type of diabetes, body mass index, smoking, and C reactive protein. The system was designed and the evaluation results showed that the values of sensitivity, accuracy, and validity were 85%, 92% and 90%, respectively. The K-value was 0.62. Conclusion: The results of the system were largely similar to the patients’ records and showed that the designed system can be used to help physicians to assess the risk of cardiovascular diseases and to improve the quality of care services for diabetic patients undergoing hemodialysis. By predicting the risk of the disease and classifying patients in different risk groups, it is possible to provide them with better care plans.

Massive transfusion experience, current practice and decision support: A survey of Australian and New Zealand anaesthetists

2021 ◽  
pp. 0310057X2097403
Author(s):  
Brenton J Sanderson ◽  
Jeremy D Field ◽  
Lise J Estcourt ◽  
Erica M Wood ◽  
Enrico W Coiera
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Response Rate ◽  
Massive Transfusion ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Transfusion Practice

Massive transfusions guided by massive transfusion protocols are commonly used to manage critical bleeding, when the patient is at significant risk of morbidity and mortality, and multiple timely decisions must be made by clinicians. Clinical decision support systems are increasingly used to provide patient-specific recommendations by comparing patient information to a knowledge base, and have been shown to improve patient outcomes. To investigate current massive transfusion practice and the experiences and attitudes of anaesthetists towards massive transfusion and clinical decision support systems, we anonymously surveyed 1000 anaesthetists and anaesthesia trainees across Australia and New Zealand. A total of 228 surveys (23.6%) were successfully completed and 227 were analysed for a 23.3% response rate. Most respondents were involved in massive transfusions infrequently (88.1% managed five or fewer massive transfusion protocols per year) and worked at hospitals which have massive transfusion protocols (89.4%). Massive transfusion management was predominantly limited by timely access to point-of-care coagulation assessment and by competition with other tasks, with trainees reporting more significant limitations compared to specialists. The majority of respondents reported that they were likely, or very likely, both to use (73.1%) and to trust (85%) a clinical decision support system for massive transfusions, with no significant difference between anaesthesia trainees and specialists ( P = 0.375 and P = 0.73, respectively). While the response rate to our survey was poor, there was still a wide range of massive transfusion experience among respondents, with multiple subjective factors identified limiting massive transfusion practice. We identified several potential design features and barriers to implementation to assist with the future development of a clinical decision support system for massive transfusion, and overall wide support for a clinical decision support system for massive transfusion among respondents.

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