DESIGN AND IMPLEMENTATION OF AN APPOINTMENT SCHEDULING SYSTEM IN HEALTH CARE SERVICE

ABSTRACT

Nowadays, patients in many healthcare facilities face the problem of long waiting times, waiting times in healthcare clinics are categorized into “indirect waiting time” and “direct waiting time”. Indirect waiting time is mostly expressed in days and is defined as the number of days between appointment request day and appointment date, direct waiting time is defined as the time that a patient spends in a clinic to see a doctor more like an emergency, indirect waiting times may bring medical impacts, especially for multiple chronic conditions and higher-priority patient,  indirect waiting times also increase the no-show probability of patients which decreases the utilization of the healthcare facility, prioritization of patients based on their chronic conditions and characteristics thereby deciding which one should get a sooner appointment is not a simple problem, many factors play important roles in determining the level of urgency of a patient. Machine learning methods provide a decision-making tool for grouping patients into different priority classes which is more accurate than a human diagnosis. Considering patients’ backgrounds and environments for clustering patients are important issues that humans may ignore. Therefore, having a tool to find a pattern for patient’s priority, considering patients’ histories and environmental factors helps the healthcare facilities to come up with a more accurate priority diagnosis and a better scheduling process.