Organizing timely treatment in multi-disciplinary care

Healthcare providers experience an increased pressure to organize their processes more efficiently and to provide coordinated care over multiple disciplines. Organizing multi-disciplinary care is typically highly constrained, since multiple appointments per patient have to be scheduled with possible restrictions between them. Furthermore, schedules of professionals from various facilities or with different skills must be aligned. Since it is important that patients are treated on time, access time targets are set on the time between referral to the facility and the actual start of the treatment. These targets may vary per patient type: e.g., urgent patients have shorter access time targets than regular patients. In this thesis, we use operations research methods to support multi-disciplinary care settings in providing timely treatments with an excellent quality of care, against affordable costs, while taking patient and employee satisfaction into account. We consider settings in rehabilitation care and radiotherapy, but the underlying planning problems are applicable to many other multi-disciplinary care settings, such as cancer care or specialty clinics. The developed models are applied to case studies in the Sint Maartenskliniek Nijmegen, the AMC Amsterdam and a BCCA cancer clinic in Vancouver, Canada. The results of the thesis demonstrate that adequate admission policies and capacity allocation to different activities and stages in complex treatment processes can improve compliance with access time targets for multi-disciplinary care systems considerably, while using the available resource capacities and taking patient and employee satisfaction into account

Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals

We present a methodology to design appointment systems for outpatient clinics and diagnostic facilities that offer both walk-in and scheduled service. The developed blueprint for the appointment schedule prescribes the number of appointments to plan per day and the moment on the day to schedule the appointments. The method consists of two models that are linked by an algorithm; one for the day process that governs scheduled and unscheduled arrivals on the day and one for the access process of scheduled arrivals. Appointment schedules that balance the waiting time at the facility for unscheduled patients and the access time for scheduled patients, are calculated iteratively using the outcomes of the two models. The method is of general nature and can therefore also be applied to scheduling problems in other sectors than health care

A systematized approach for reduction of medical appointment waiting list

Paper aims: This work aims to develop a systematized approach for the reduction of medical appointment waiting lists, proposing an optimization decision-making model followed by continuous people engagement towards a systematic approach for waiting list problem-solving. Originality: There are several studies related to waiting lists in healthcare contexts, however, the present study presents an innovative approach for waiting list problem-solving by proposing prescriptive decision-making models followed by continuous improvement and people engagement. Research method: A research approach with the following phases was developed: system analysis, problem quantification, and development of an optimization model. After these phases, the model was applied, and the results were analysed, as contributions to a systematized model. Main findings: The model was applied to the screening waiting list for orthopaedics appointments followed by the fundamental involvement of medical doctors, which made it possible to implement the optimal solution generated by the model, resulting in a reduction of 90% by 56 days in waiting time for the screening process. Implications for theory and practice: This model contributes for theory and for practice as a way to deal with different scenarios for waiting list reduction in the upcoming days during and after the pandemic.This work was supported by projects UIDB/00319/2020 and POCI-01-0145-FEDER-030299, from Fundação para a Ciência e Tecnologia (FCT), Portugal

Requirements of time management tools for outpatient physiotherapy practice

The effects of electronic appointment booking systems on the time management activities of health professionals have received little attention to date. We report on time management practices in three outpatient physiotherapy departments with different paper and electronic systems. The study has identified a set of time management activities and associated social behaviours common to physiotherapy departments. The convenience, flexibility and expressive nature of paper diary systems is of significant value to users, whilst the clarity and superior database functionality of electronic systems are valued by staff using this medium. The study highlights several potential barriers to the effective deployment of electronic booking systems in physiotherapy departments, including poor resource and training provision, concerns regarding restrictive diary control measures, the continued reliance on burdensome duplication procedures and the need to coordinate multiple information artefacts, which need to be addressed if such technology is to be successfully designed and deployed. Copyright © 2005 SAGE Publications (London, Thousand Oaks, CA and New Delhi)

Logistics performances of health care system using queue analysis

As there is a very high demand for health service that exceeds the available capacity, the public healthcare centers are overwhelmed with the long queues or they are delivering the service with relatively very low consultation time. In the existing conditions, patients go as early as they can to the healthcare facilities, waiting in queue, even before the opening and had to wait long time for examination, consultation and diagnosis. However, due to high number of patients at the outpatient departments relative to the number of physicians, it results in an increased workload on the physicians and it shortens the patient consultation time, which has an impact on the patients’ health. The main objective of this research was to study the logistic performances of the healthcare system using queuing analysis. This research used three key performance indicators namely, patient queue length, patient waiting time and consultation time length. The performance evaluation was conducted based on data from patients who visited 69 clinical, surgical and diagnosis departments at the outpatient clinics of the hospital. Queue analysis was performed to determine the operational characteristics using a queue scenario with Poisson arrival, exponential service, infinite population, First Comes First Served (FCFS) discipline and multiple server arrangement. The study showed that the patients’ arrival rate highly exceeded the service rate, in each respective clinical department. The outpatient clinics at the SPHMMC achieved an average total waiting time of 92 minutes to get consultation and nearly 70% of the patients waited for more than 95 minutes. The consultation time was as low as 5.71 minute at the Medical clinic and 6.16 minute at the Ophthalmology clinic and around 60% of the patients saw the doctor for a time less than 10 minutes. Therefore, this research recommends addressing the gaps in human resources and logistical supplies, to implement and enforce a staggered patient scheduling and appointment system and to have serious intervention and control on the dual practice, to ensure a smooth clinic process and to reduce waiting times

A Robust Optimization Approach for Advance Scheduling in Health Care Systems with Demand Uncertainty: Policy Insights

Patient wait times have increased significantly over the past few decades. According to the Canadian Institute for Health Information (CIHI), 40% of Canadians have experienced difficulties in receiving diagnostics tests. MRI wait times have increased by 26% from 2012 to 2016. The lengthy wait times for the health care systems are translated to economic losses and risks to the lives of Canadians. These inefficiencies in health care systems are an indication that health care infrastructure investment has not been able to keep pace with the increased demands. While building new health care infrastructure to create capacity may be the first solution that comes to mind, it is often not feasible due to budget limitations. Optimizing the use of the existing capacity is a more feasible and cost-effective solution to healthcare system inefficiencies. This research builds on previous literature and proposes a robust optimization method for a multi-priority multi-period advance scheduling problem with wait time target which is solved using a proposed adversarial-based algorithm. A sensitivity analysis is conducted to calibrate the model parameters. Several numerical examples are used to extract practical policy insights. The advantages of the robust model in comparison with the deterministic model are highlighted. It is shown that the robust modelling leads to policies that are easier to execute and are more suitable for policy planning purposes when compared to deterministic modelling