FEASIBILITY OF USING BIG DATA TO OVERCOME THE PROBLEM OF MISSED HOSPITAL APPOINTMENTS IN THE SULTANATE OF OMAN

  • Ahmed Alawadhi

Student thesis: Phd

Abstract

The problem of missed hospital appointments is one of the challenges faced by healthcare systems all over the world. According to the available literature, a letter to the editors of The Lancet in 1882 contained the first mention of hospital appointments and the reason why some patients found it difficult to go to the hospital. Missed hospital appointments have countless implications that affect many aspects of life and a diverse range of people, including patients, medical professionals, and the entire healthcare system. Numerous studies have examined the factors linked to missed hospital appointments to identify patients at high risk of skipping their appointment based on their demographics, appointment information, and clinical information. Age, sex, and waiting time were the most often found to have a strong effect on missed hospital appointments rate. A great deal of research has been done to explore reasons for missing hospital appointments. Sleeping, forgetfulness, and transportation problems were the most frequent causes reported by patients and medical staff. Frequently reported interventions to reduce the impact of missed hospital appointments were the use of SMS reminders, phone call reminder, overbooking, and the use of a prediction models. However, the literature is lacking information about the problem of missed hospital appointments in the Sultanate of Oman. No studies have been done to investigate the issue of missed hospital appointments in Oman’s healthcare system. This thesis explored the problem of missed hospital appointments in the Sultanate of Oman. The Royal Hospital, the biggest tertiary hospital in Oman with many specialties and sub-specialties clinics, hosting the National Oncology center and the National Cardiology center was selected as the primary location to conduct our investigations. The aims were to (a) explore the factors associated with missed hospital appointments in the outpatient clinics within the Royal hospital and identify the variance in factors between the clinics, (b) to identify the main reasons for missing hospital appointments from the patients and the medical staff perspective, (c) identify any changes in the predictors of missed hospital appointments caused by the outbreak of the COVID-19 pandemic, and (d) to develop a risk prediction model using the predetermined predictors of missed hospital appointments and to simulate an overbooking approach using individual patients estimated probability of missed appointment and compare the proposed overbooking approach with the current systematic overbooking approach. The findings of the thesis showed that the main factors associated with missed hospital appointments on the Royal Hospital were age, service cost, waiting days for appointment, governorate (distance from hospital) and month of the appointment. There was variation in the predictors of missed hospital appointments and patient or clinical reasoning for a missed hospital appointments between clinics. Recommendations from patients and medical staff to improve attendance included improvement of the SMS reminder system, the additional use of phone call reminders, and the development of a user-friendly appointment rescheduling system. There was a direct impact of COVID-19 on missed face-to-face appointments and virtual appointments in most of the clinics and the case mix analysis of patients who missed their appointments during COVID-19 did not change. Clinic-specific prediction models outperformed the use of single overall model to predict missed appointments. The simulation study showed that overbooking based on individual clinic risk prediction models was more effective than the systematic overbooking approach currently used within The Royal Hospital. In conclusion, this thesis adds to literature and fills the gap caused by the lack of information about missed hospital appointments in the Sultanate of Oman. This thesis also presents an effective proposed overbooking approach t
Date of Award1 Aug 2024
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorCaroline Sanders (Supervisor), Victoria Palin (Supervisor) & Tjeerd Van Staa (Supervisor)

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