Waiting time at a fast-track diagnostic clinic

Abstract

Purpose - Guidelines stating maximum waiting times fail to take cancer patients' expectations into account. Therefore, the purpose of this paper is to assess patients' expectations and experiences with their waiting time at a fast-track clinic. Design/methodology/approach - Patients were selected using a purposeful sampling strategy and were interviewed four times: before the visit; one day after; two weeks after the visit; and one week after starting treatment. Interviews were audiotaped and independently coded by two researchers. Findings - All patients (n=9) preferred a short waiting time before the first visit; they feared that their disease would spread and believed that cancer warrants priority treatment. Six patients experienced the waiting time as short, one had no expectations and two felt they waited longer than expected; three patients changed this evaluation during the study. Six patients received treatment - four preferred to wait before treatment and two wanted to start treatment immediately. Reasons to wait included putting one's affairs in order, or needing to adjust to the diagnosis. Practical implications - Cancer patients prefer a short waiting time before the first visit but have different expectations and needs regarding waiting time before treatment. Ideally, their expectations are managed by their treating physician to match waiting time reality. Originality/value - This is the first study to assess cancer patients' waiting time experiences and how these experiences change over time. This study paves the way for establishing a framework to better assess patient satisfaction with oncology care waiting time. An important aspect, is managing patients' expectations.

Application of Queuing Theory to Optimize Waiting-Time in Hospital Operations

“…Due to poor hospital service operations, patients tend to spend a lot of time getting the services they need (Dellaert et al, 2015;Lohlun et al, 2015). Long queues are an indication of lack of coordination, poor management, and insufficient resources, which affects the quality of services in hospital operations and reduce patients' satisfaction (Basta et al, 2016;Bringedal, 2016;Bachmann and Barron, 1997). Given the role of waiting time in improving service quality for the higher satisfaction of patients, it is necessary to review it as one of the most common problems in hospital service operations (Benson et al, 2001;Bleustein et al, 2014).…”

Optimizing the Performance of Magnetic Resonance Imaging Department Using Queuing Theory and Simulation

“…Long waiting time indicates poor management, lack of coordination, and insufficient resources (8,9), which impedes the provision of quality services in hospitals, wastes patients' time, and reduces their satisfaction (10). Given that patients' satisfaction with the waiting time plays an important role in improving the quality of services (11), it is necessary to review it as one of the most common problems in the hospitals (7).…”

Smarter imaging management: operations management for radiology

“…Imaging resources appear to be one of the biggest bottlenecks in hospitals, because more and more patients are requiring imaging exams 29 and patients usually have to wait longer than desirable for an appointment [30][31][32][33][34][35] . Many other resources are depending on the operational performance of imaging resources and at the same time imaging resources are very expensive.…”

“…Many other resources are depending on the operational performance of imaging resources and at the same time imaging resources are very expensive. Therefore, they appear to be one of the hospital resources that would greatly benefit from better service and utilization [31][32][33][36][37][38][39] . In many hospitals, imaging resources form a bottleneck for many patient flows.…”

“…Although increasing quality of care was not the objective of the walk-in intervention, literature indicates that reducing access times to diagnostic facilities positively contributes to patients' wellbeing. Severe cases, such as cancer patients, can benefit from quick diagnosis 31,33,34 .…”