Implementation of a Simulation Model for Optimizing the Traffic Flow from Arafat to Muzdalifah

This project simulates the flow of pilgrims when they travel from Arafat to Muzdalifah. The system includes the roads network that connects Arafat to Muzdalifah, which is represented as a queuing system with different queue measurements that simulate reality. The system also includes different types of transportation, such as small and large buses and trains, all of which are represented as objects with different size and colors. All system objects carry specifications as their corresponding source system objects, and these specifications are based on data collected by the Ministry of Hajj. The primary objective of the system is to answer “what if” questions to support decision making to optimize Hajj traffic, which can be achieved by manipulating the system’s variables and then by observing the key performance indicators of the system. The system presents the experimental results as visual feedback alongside written reports with statistics and illustrations

Improving inappropriate radiology referrals: a template for imaging requests in Saudi Arabia

Abstract Background Imaging requests are the first line of communication between the referring physician and the radiology department. The information provided allows the imaging team to choose the optimal examination for the clinical question. There are no imaging referral guidelines in Saudi Arabia. The Radiological Society of Saudi Arabia (RSSA) and Arabsafe have surveyed to develop an imaging referral tool in Saudi Arabia. This study aims to determine the most critical clinical information that should be included in an imaging request form in Saudi Arabia. Methodology A questionnaire was sent to the RSSA members to rank —using the Likert scale— the importance of 8 pieces of clinical information to discern what must be included in the imaging request form. Results The response rate was 80% of the RSSA members, which included 75 respondents, mostly Radiology consultants and residents in training. Radiologists carried different specialties and came from 4 main provinces in the Kingdom. 90.6% of Radiologists ranked the clinical question with relevant details as very important. The contact information of the requesting clinician came next in the ranking, with 82.3% scoring it as very important. The “very important” scores were 64.9% for the past medical history, 67.3% for past surgical history, 49.2% for laboratory, 38.3% for risk factors, and 56.7% for prior radiological studies. The RSSA-Arabsafe imaging request template was proposed because of the respondents’ votes to include all eight points: a clear clinical question relevant to the requested exam, the contact information of the referring physician, relevant surgical history, relevant medical history, past radiological tests if any, patient demographics, and relevant laboratory tests. Conclusions The RSSA-Arabsafe template is the first tool to improving imaging referrals and hence patients’ safety and services in Radiology departments in Saudi Arabia. It is crucial for healthcare institutions to actively implement standardized imaging request forms, such as the proposed RSSA-Arabsafe template, to reduce inappropriate referrals, enhance communications and optimize resource utilization

WMSS: A Web-Based Multitiered Surveillance System for Predicting CLABSI

Central-line-associated bloodstream infection (CLABSI) rates are a key quality metric for comparing hospital quality and safety. Manual surveillance systems for CLABSIs are time-consuming and often limited to intensive care units (ICUs). A computer-automated method of CLABSI detection can improve the validity of surveillance. A new web-based, multitiered surveillance system for predicting and reducing CLABSI is proposed. The system has the capability to collect patient-related data from hospital databases and hence predict the patient infection automatically based on knowledge discovery rules and CLABSI decision standard algorithms. In addition, the system has a built-in simulator for generating patients’ data records, when needed, offering the capability to train nurses and medical staff for enhancing their qualifications. Applying the proposed system, both CLABSI rates and patient treatment costs can be reduced significantly. The system has many benefits, among which there is the following: it is a web-based system that can collect real patients’ data from many IT resources using iPhone, iPad, laptops, Internet, scanners, and hospital databases. These facilities help to collect patients’ actual data quickly and safely in electronic format and hence predict CLABSI efficiently. Automation of the patients’ data diagnosis process helps in reducing CLABSI detection times. The system is multimedia-based; it uses text, colors, and graphics to enhance patient healthcare report generation and charts. It helps healthcare decision makers to review and approve policies and surveillance plans to reduce and prevent CLABSI