Allocating operating room capacity to non-elective neurosurgical patients improves access and safety for elective patients at Aarhus University Hospital.

INTRODUCTION: This study addresses surgical scheduling within the Department of Neurosurgery at Aarhus University Hospital (AUH). The department provides neurosurgical care to a population of 1.3 million in central Denmark, and has treatment obligations for specific neurosurgical diseases for the entire country, which has a population of 5.8 million. Efficient utilisation of the department's four operating suites is crucial to ensure that patients have timely access to both non-elective and elective neurosurgical procedures. Historically, the elective operating room (OR) schedule was made without consideration of the possible arrival of non-elective patients; consequently, elective surgeries were often cancelled to accommodate those with more urgent indications. The challenge was thus to introduce a structured way of planning for these non-elective surgical procedures that would minimise the need for cancelling elective surgeries without decreasing overall productivity. METHODS: Using a mathematical model developed in a previous study at Leiden University Medical Center, the effect of allocating OR time during regular working hours for non-elective neurosurgical procedures at AUH was analysed, so that a weighted trade-off could be made between cancellations of elective patients due to an overflow of non-elective patients and unused OR time due to excessive reservation of time for non-elective patients. This allocation was tested in a six-week pilot study during weeks 24 & 25 and weeks 34-37 of 2020 before being implemented in 2021. RESULTS: In the 35 weeks following the implementation, the new allocation strategy resulted in a significant 77% decrease in the cancellation of elective neurosurgical procedures when compared with the same time period in 2019, with a significant 16% increase in surgical productivity. CONCLUSIONS: This study shows that with mathematical modelling complex problems in the distribution of neurosurgical OR capacity can be solved, improving both patient safety and the working environment of neurosurgeons and OR staff.

Increasing cardio-thoracic productivity at Erasmus MC.

The Thoraxcenter of Erasmus MC started an improvement project in 2015 in order to increase the number of open-heart surgeries by 150 for three consecutive years (450 in total, +46%), and to decrease the access time from 12-14 to 2-3 weeks by the end of 2016. This was required to attain economy of scale in a highly competitive market. In this paper we describe the first year of the project, focusing on its structure and interventions taken, resulting in 165 additional open-heart surgeries carried out in 2016 and a significantly shorter access time of 2-3 weeks.

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.

BACKGROUND: The 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. METHODS: An 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. RESULTS: Ten 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. CONCLUSIONS: This 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.

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/.

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 clinic's 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.