Predicting Postoperative Length of Stay for Isolated Coronary Artery Bypass Graft Patients Using Machine Learning.

Purpose: Predictive analytics (PA) is a new trending approach in the field of healthcare that uses machine learning to build a prediction model using supervised learning algorithms. Isolated coronary artery bypass grafting (iCABG), an open-heart surgery, is commonly performed in the treatment of coronary heart disease.

Aim: The aim of this study was to develop and evaluate a model to predict postoperative length of stay (PLoS) for iCABG patients using supervised machine learning techniques, and to identify the features with the highest contribution to the model.

Healthcare predictive analytics: An overview with a focus on Saudi Arabia.

Despite a newfound wealth of data and information, the healthcare sector is lacking in actionable knowledge. This is largely because healthcare data, though plentiful, tends to be inherently complex and fragmented. Health data analytics, with an emphasis on predictive analytics, is emerging as a transformative tool that can enable more proactive and preventative treatment options.

Assessment of health-related quality of life of patients with inflammatory bowel diseases in Eastern Province, Saudi Arabia.

Inflammatory bowel disease patients have impaired quality of life with physical, social and emotional dysfunction. This project aimed to assess the effects of socio-demographic and clinical variables on quality of life and to identify its predictors. In a cross-sectional paper-based study, 50 consecutive non-selected patients attending the teaching hospital completed a disease-specific McMaster quality of life tool.

An Analytic Hierarchy Process-based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System.

Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia.

Accuracy of the Charlson index comorbidities derived from a hospital electronic database in a teaching hospital in Saudi Arabia.

Hospital management and researchers are increasingly using electronic databases to study utilization, effectiveness, and outcomes of healthcare provision. Although several studies have examined the accuracy of electronic databases developed for general administrative purposes, few studies have examined electronic databases created to document the care provided by individual hospitals. In this study, we assessed the accuracy of an electronic database in a major teaching hospital in Eastern Province, Saudi Arabia, in documenting the 17 comorbidities constituting the Charlson index as recorded in paper charts by care providers.

Annual survey on the level and extent of usage of electronic health records in government-related hospitals in Eastern Province, Saudi Arabia.

This study aims to determine the level and extent of usage of electronic health records (EHRs) in government-related hospitals in Eastern Province, Saudi Arabia. Another aim is to develop a Web site to serve as a forum of exchange on the development of EHRs in Saudi Arabia. All government hospitals (n = 19) in the province were included.