COST ANALYSIS OF EMERGENCY VISITS DUE TO DRUG RELATED PROBLEMS

Objective: To identify patients coming to Emergency Medicine Department (EMD) with drug related problems, classify the DRPs and calculate the direct cost spent for treating them. Methods: This was a prospective observational study conducted in emergency medicine department. The patients coming to EMD with DRPs were classified according to Cipolle’s classification and the direct medical and non-medical costs were calculated. Results: A total of around 107 patients identified with DRPs of which 99 patients were included in the study. In this study, 51% of the cases were due to ADR and 35% due to non-adherence and rest of the cases were due to overdose (10%), drug interaction (3%) and sub therapeutic dose (1%). Major portion for treatment was spent for direct medical cost in which cost for laboratory investigations have contributed the most, INR 10,93,992 (42%) followed by Health care professional cost INR 55,6814 (21%), Pharmacy cost INR 4,00,524.6 (15%), Admission cost INR 3,80,400 (15%). The direct non-medical cost includes cost for diet and travel which was found to be INR 1,68,443 and INR 71,947 respectively. Conclusion: The drug related problems adds a significant economic burden on the patients which can be reduced by imparting knowledge about the proper use of medicines and by improving collaborative efforts of the patients, physicians, pharmacists and caregivers

Development of Machine Learning Algorithms for Prediction of 30-Day Mortality After Surgery for Spinal Metastasis

BACKGROUND: Preoperative prognostication of short-term postoperative mortality in patients with spinal metastatic disease can improve shared decision making around end-of-life care. OBJECTIVE: To (1) develop machine learning algorithms for prediction of short-term mortality and (2) deploy these models in an open access web application. METHODS: The American College of Surgeons, National Surgical Quality Improvement Program was used to identify patients that underwent operative intervention for metastatic disease. Four machine learning algorithms were developed, and the algorithm with the best performance across discrimination, calibration, and overall performance was integrated into an open access web application. RESULTS: The 30-d mortality for the 1790 patients undergoing surgery for spinal metastatic disease was 8.49%. Preoperative factors used for prognostication were albumin, functional status, white blood cell count, hematocrit, alkaline phosphatase, spinal location (cervical, thoracic, lumbosacral), and severity of comorbid systemic disease (American Society of Anesthesiologist Class). In this population, machine learning algorithms developed to predict 30-d mortality performed well on discrimination (c-statistic), calibration (assessed by calibration slope and intercept), Brier score, and decision analysis. An open access web application was developed for the best performing model and this web application can be found here: https://sorg-apps.shinyapps.io/spinemets/. CONCLUSION: Machine learning algorithms are promising for prediction of postoperative outcomes in spinal oncology and these algorithms can be integrated into clinically useful decision tools. As the volume of data in oncology continues to grow, creation of learning systems and deployment of these systems as accessible tools may significantly enhance prognostication and management

Proceedings of National Conference on Relevance of Engineering and Science for Environment and Society

This conference proceedings contains articles on the various research ideas of the academic community and practitioners presented at the National Conference on Relevance of Engineering and Science for Environment and Society (R{ES}2 2021). R{ES}2 2021 was organized by Shri Pandurang Pratishthan’s, Karmayogi Engineering College, Shelve, Pandharpur, India on July 25th, 2021. Conference Title: National Conference on Relevance of Engineering and Science for Environment and SocietyConference Acronym: R{ES}2 2021Conference Date: 25 July 2021Conference Location: Online (Virtual Mode)Conference Organizers: Shri Pandurang Pratishthan’s, Karmayogi Engineering College, Shelve, Pandharpur, India

Proceedings of International Conference on Women Researchers in Electronics and Computing

This proceeding contains articles on the various research ideas of the academic community and practitioners presented at the international conference, “Women Researchers in Electronics and Computing” (WREC’2021). WREC'21 was organized in online mode by Dr. B R Ambedkar National Institute of Technology, Jalandhar (Punjab), INDIA during 22 – 24 April 2021. This conference was conceptualized with an objective to encourage and motivate women engineers and scientists to excel in science and technology and to be the role models for young girls to follow in their footsteps. With a view to inspire women engineers, pioneer and successful women achievers in the domains of VLSI design, wireless sensor networks, communication, image/ signal processing, machine learning, and emerging technologies were identified from across the globe and invited to present their work and address the participants in this women oriented conference. Conference Title: International Conference on Women Researchers in Electronics and ComputingConference Acronym: WREC'21Conference Date: 22–24 April 2021Conference Location: Online (Virtual Mode)Conference Organizers: Department of Electronics and Communication Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, INDI