Optimization of Online Patient Scheduling with Urgencies and Preferences

Vermeulen, I. B.; Bohté, Sander M.; Bosman, Peter A. N.; Elkhuizen, Sylvia; Bakker, Piet; Poutré, J.A.

doi:10.1007/978-3-642-02976-9_9

Cited by 7 publications

(5 citation statements)

References 8 publications

(8 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Though limited implications to PAM in healthcare exist primarily due to the challenges in representing a singular objective, such as monetary‐based revenue, other approaches have been proposed, which leverage using multiple access classes to different patient groups. The use of nested capacity has been evaluated using simulation where patients can be scheduled to capacity allocated to equal and lower access classes (Vermeulen et al., 2009). However, this research direction has focused on patient scheduling decisions and little remains understood regarding the design of optimal templates.…”

Section: Literature Reviewmentioning

confidence: 99%

Partially partitioned templating strategies for outpatient specialty practices

Bai

Berg

Sir

et al. 2023

Production and Operations Management

View full text Add to dashboard Cite

Templating strategies specify policies on capacity allocation and appointment booking, which are central to patient access management in outpatient specialty practices (SPs). In the widely implemented partitioned templating strategy, appointment capacity is allocated exclusively to each patient group defined by a combination of patient attributes and medical conditions, which often results in utilization challenges for SPs. Motivated by problems faced by an SP within a large academic medical center, we propose partially partitioned templating strategies that cluster patient groups into access classes and allocate appointment slots to these classes. We formulate a twostage stochastic optimization model to simultaneously optimize decisions on patient group clustering and capacity allocation in the templating strategy design. We develop an efficient solution algorithm for the problem, which otherwise poses a combinatorial challenge, based on Benders' cuts and an anticipatory approximation. Numerical experiments using real-world data show that the partially partitioned strategies outperform benchmark strategies used by SPs through maintaining a balance of high capacity utilization and providing timely access for priority patients. In addition, we study a wide range of SP setups for transferable insights on templating strategies based on practice specifics.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Partially partitioned templating strategies for outpatient specialty practices

Bai

Berg

Sir

et al. 2023

Production and Operations Management

View full text Add to dashboard Cite

show abstract

“…Although not comprehensive, their valuable parameters discussed were also employed and examined in our study [17,18]. The other similar work from Vermeulen et al further investigated the aspects of urgencies and preferences, which are important factors when conducting appointment scheduling [19].…”

Section: Introductionmentioning

confidence: 95%

Stateless Two-Stage Multiple Criteria Scheduling in Nuclear Medicine

Wan

Chang

Lin

2014

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Examination in nuclear medicine exhibits scheduling difficulties due to its intricate clinical issues, such as varied radiopharmaceuticals for different diseases, machine preparation and length of scan, and patients’ and hospital’s criteria and/or limitations. Many scheduling methods exist but are limited for nuclear medicine. In this paper, we present stateless two-stage scheduling to cope with multiple criteria decision making. The first stage mostly deals with patients’ conditions. The second stage concerns more the clinical condition and its correlations with patients’ preference which presents more complicated intertwined configurations. A greedy algorithm is proposed in the second stage to determine the (time slot and patient) pair in linear time. The result shows practical and efficient scheduling for nuclear medicine.

show abstract

“…Patients can change their choices if the preferred time slot or physician is 702 IMDS 115,4 unavailable. Vermeulen et al (2009) combine patient preferences and the urgencies. Dynamic rules are proposed for urgent needs.…”

Section: Patient Preferences and Choicesmentioning

confidence: 99%

Dynamic appointment scheduling with patient preferences and choices

Wang

Fung

2015

Industrial Management &Amp; Data Systems

View full text Add to dashboard Cite

Purpose -The purpose of this paper is to maximize the expected revenue of the outpatient department considering patient preferences and choices. Design/methodology/approach -Patient preference refers to the preferred physician and time slot that patients hold before asking for appointments. Patient choice is the appointment decision the patient made after receiving a set of options from the scheduler. The relationship between patient choices and preferences is explored. A dynamic programming (DP) model is formulated to optimize appointment scheduling with patient preferences and choices. The DP model is transformed to an equivalent linear programming (LP) model. A decomposition method is proposed to eliminate the number of variables. A column generation algorithm is used to resolve computation problem of the resulting LP model. Findings -Numerical studies show the benefit of multiple options provided, and that the proposed algorithm is efficient and accurate. The effects of the booking horizon and arrival rates are studies. A policy about how to make use of the information of patient preferences is compared to other naive polices. Experiments show that more revenue can be expected if patient preferences and choices are considered. Originality/value -This paper proposes a framework for appointment scheduling problem in outpatient departments. It is concluded that more revenue can be achieved if more choices are provided for patients to choose from and patient preferences are considered. Additionally, an appointment decision can be made timely after receiving patient preference information. Therefore, the proposed model and policies are convenient tools applicable to an outpatient department.

show abstract

Optimization of Online Patient Scheduling with Urgencies and Preferences

Cited by 7 publications

References 8 publications

Partially partitioned templating strategies for outpatient specialty practices

Partially partitioned templating strategies for outpatient specialty practices

Stateless Two-Stage Multiple Criteria Scheduling in Nuclear Medicine

Dynamic appointment scheduling with patient preferences and choices

Contact Info

Product

Resources

About