Impact of Appointment Waiting Time on Attendance Rates at a Clinical Cancer Genetics Service

Abstract

The increase in demand for clinical cancer genetics services has impacted the ability to provide services timeously. Given limited resources, this often results in extended appointment waiting times. Over the last 3 years, the Cancer Genetics Service at the National Cancer Centre Singapore has continued to experience a steady increase in demand for its service. Nevertheless, significant no-show rates have been reported. This study sought to determine whether an association exists between appointment waiting times and attendance rates. Data was gathered for all participants meeting inclusion criteria. Attendance rates and appointment waiting times were calculated. The relationship between mean waiting times for those who did and did not attend their scheduled appointments was evaluated using Welch's t test and linear regression model. The results showed a significant difference in mean appointment waiting times between patients who did and did not attend (32.66 versus 43.50 days respectively; p < 0.0001). Furthermore, patients who waited for longer than 37 days were significantly less likely to attend. No-show rates increased as the waiting time increased, at a rate of 19.60% per 20 days and 21.40% per 30 days. In conclusion, appointment waiting time is a significant predictor for patient attendance. Strategies to ensure patients receive an appointment within the necessary timeframe at the desired setting are important to ensure that individuals at increased cancer risk attend their appointments in order to manage their cancer risks effectively.

Use of telephone intake for family history taking at a cancer genetics service in Asia

“…Immediate reschedule was offered to patients who were unable to attend their appointments while the telephone intake was performed. With this approach, more than one‐third of patients rescheduled or canceled their appointments, echoing similar findings reported by Mohamed et al (2016) This was crucial as vacant appointment slots could be identified early and replaced with patients from the list of urgent cases who were more likely to attend their appointments as they were recently referred (Shaw et al., 2018). This may lead to a further reduction in clinic no‐show rates, thus maximizing the utilization of available resources.…”

“…This echoed the finding of Hasvold and Wootton (2011) which demonstrated that manual phone call reminder was more effective than an automated reminder. Improving the clinic attendance rate may lead to a major benefit in terms of healthcare costs as it ensures that more patients and families who are at an increased risk of developing cancer can be managed appropriately (Shaw et al., 2018; Wang, Koh, Chow, & Lim, 2012). Also, it helps to decrease the unused clinic appointments and reduce disturbance of planned clinic workflow (Ahmed et al., 2016; Hasvold & Wootton, 2011).…”

The influence of Malay cultural beliefs on breast cancer screening and genetic testing: A focus group study

“…Lastly, community education is imperative for individuals to understand the benefits of a parallel healthcare approach of modern and traditional medicine, especially in cultures in which community/family significantly influence health‐related decisions . There is a general lack of awareness of benefits of genetic testing among the public and physicians, and genetic health education in general is lacking yet essential …”

<p>Evaluating the Impact of Patient No-Shows on Service Quality</p>

“…Further, it was found the noshow rates increased with an increasing lead time, i.e., 19.60% for a lead time of 20 days to 21.40% for a 30 days lead time. 17 In a similar study context, it was found that a lead time exceeding two weeks would remarkably cause a patient's no-show probability to increase. 18 The Association Rule Mining (ARM) is another specific data mining technique used to predict patients' no-show probabilities.…”