Maartje Elisabeth Zonderland

Planning and scheduling of semi-urgent surgeries

This paper investigates the trade-off between cancellations of elective surgeries due to semi-urgent surgeries, and unused operating room (OR) time due to excessive reservation of OR time for semi-urgent surgeries.Semi-urgent surgeries, to be performed soon but not necessarily today, pose an uncertain demand on available hospital resources, and interfere with the planning of elective patients. For a highly utilized OR, reservation of OR time for semi-urgent surgeries avoids excessive cancellations of elective surgeries, but may also result in unused OR time, since arrivals of semi-urgent patients are unpredictable. First, using a queuing theory framework, we evaluate the OR capacity needed to accommodate every incoming semi-urgent surgery. Second, we introduce another queuing model that enables a trade-off between the cancelation rate of elective surgeries and unused OR time. Third, based on Markov decision theory, we develop a decision support tool that assists the scheduling process of elective and semi-urgent surgeries. We demonstrate our results with actual data obtained from a department of neurosurgery.

Redesign of a university hospital preanesthesia evaluation clinic using a queuing theory approach

BACKGROUND: Changes in patient length of stay (the duration of 1 clinic visit) as a result of the introduction of an electronic patient file system forced an anesthesia department to change its outpatient clinic organization. In this study, we sought to demonstrate how the involvement of essential employees combined with mathematical techniques to support the decision-making process resulted in a successful intervention. METHODS: The setting is the preanesthesia evaluation clinic (PAC) of a university hospital, where patients consult several medical professionals, either by walk-in or appointment. Queuing theory was used to model the initial set-up of the clinic, and later to model possible alternative designs. With the queuing model, possible improvements in efficiency could be investigated. Inputs to the model were patient arrival rates and expected service times with clinic employees, collected from the clinics logging system and by observation. The performance measures calculated with the model were patient length of stay and employee utilization rate. Supported by the model outcomes, a working group consisting of representatives of all clinic employees decided whether the initial design should be maintained or an intervention was needed. RESULTS: The queuing model predicted that 3 of the proposed alternatives would result in better performance. Key points in the intervention were the rescheduling of appointments and the reallocation of tasks. The intervention resulted in a shortening of the time the anesthesiologist needed to decide upon approving the patient for surgery. Patient arrivals increased sharply over 1 yr by more than 16%; however, patient length of stay at the clinic remained essentially unchanged. If the initial set-up of the clinic would have been maintained, the patient length of stay would have increased dramatically. CONCLUSIONS: Queuing theory provides robust methods to evaluate alternative designs for the organization of PACs. In this article, we show that queuing modeling is an adequate approach for redesigning processes in PACs.

ORchestra: an online reference database of OR/MS literature in health care

We introduce the categorized reference database ORchestra, which is available online at http://www.utwente.nl/choir/orchestra/.

Development of an observational instrument to determine variations in the patient care process and patient flow among emergency physicians and internists at the emergency department

BackgroundThe increasing demand for acute care and restructuring of hospitals resulting in emergency department (ED) closures and fewer inpatient beds are reasons to improve ED efficiency. The approach towards the patient care process varies among doctors. The objective of this study was to determine variations in the patient care process and patient flow among emergency physicians (EP’s) and internists at the ED of Leiden University Medical Centre (LUMC), the Netherlands.MethodsAn observational instrument was developed during a pilot study at the LUMC ED, following observations of activities performed by EP’s and internists. The instrument divides all different types of activities a clinician can perform on the ED into eight categories. Using the observational instrument, their activities were observed and registered for 10 separate days. Primary outcomes were defined as the time spend on the eight separate activity categories, the total length of stay (LOS) and the number of patients seen during an interval. Secondary outcomes were general observations of working routine features that determine patient flow at the ED. The obtained data were analyzed into SPSS.ResultsTen doctors were observed during a total of ± 36 hours in which 42 patients were seen. Although EP’s were observed for a shorter period of time than internists (13:48 vs. 22:10 hrs, -38%), they saw more patients (26 vs. 16, +62%). EP’s tended to spend a higher proportion of their time on patient contact than internists (27.2% vs. 17.3%, p = 0.06). Both groups dedicated the highest proportion of their time to documentation (31.5% and 33.4%, p = 0.75) and had little communication with ED nurses (3.7% and 2.4% p = 0.57). The average LOS of internal patients was higher than that of EP’s patients (5.25 ± sd 1:33 and 2.26 ± sd 1:32 hours). Internists occupied more treatment rooms at the same time (2.41 vs. 2.08, p < 0.00) and followed a more sequential working routine.ConclusionsThis paper describes the determination of variations in the ED care process and patient flow among EP’s and internists by an observational instrument. A pilot study with the instrument showed variations in the patient care process and patient flow among the two groups at the LUMC ED.

Optimal allocation of MRI scan capacity among competing hospital departments

We consider an MRI scanning facility run by a Radiology department. Several hospital departments compete for capacity and have private information regarding their demand for scans. The fairness of the capacity allocation by the Radiology department depends on the quality of the information provided by the hospital departments. We employ a generic Bayesian game approach that stimulates the disclosure of true demand (truth-telling), so that capacity can be allocated fairly. We derive conditions under which truth-telling is a Bayesian Nash equilibrium. The usefulness of the approach is illustrated with a numerical example.

Appointments in care pathways: the Geo^x/D/1 queue with slot reservations

Motivated by the increasing popularity of care pathways in outpatient clinics, where some patients complete a significant part of the path in one day, hospitals aim to optimize the flow of these patients by prioritizing them in the appointment planning process. This paper considers the

Operations research for occupancy modeling at hospital wards and its integration into practice

Geo^x/D/1

Allocating Emergency Beds Improves the Emergency Admission Flow

Geox/D/1 queue with slot reservations that serves regular patients and priority patients. Priority patients reserve a time slot in a reservation window and are blocked when all slots in the reservation window are occupied by other priority patients. The reservation window models the advance reservation of service slots by patients on a care pathway. We model the