Fast evaluation of appointment schedules for outpatients in health care

We consider the problem of evaluating an appointment schedule for outpatients in a hospital. Given a fixed-length session during which a physician sees K patients, each patient has to be given an appointment time during this session in advance. When a patient arrives on its appointment, the consultations of the previous patients are either already finished or are still going on, which respectively means that the physician has been standing idle or that the patient has to wait, both of which are undesirable. Optimising a schedule according to performance criteria such as patient waiting times, physician idle times, session overtime, etc. usually requires a heuristic search method involving a huge number of repeated schedule evaluations. Hence, the aim of our evaluation approach is to obtain accurate predictions as fast as possible, i.e. at a very low computational cost. This is achieved by (1) using Lindley's recursion to allow for explicit expressions and (2) choosing a discrete-time (slotted) setting to make those expression easy to compute. We assume general, possibly distinct, distributions for the patient's consultation times, which allows us to account for multiple treatment types, as well as patient no-shows. The moments of waiting and idle times are obtained. For each slot, we also calculate the moments of waiting and idle time of an additional patient, should it be appointed to that slot. As we demonstrate, a graphical representation of these quantities can be used to assist a sequential scheduling strategy, as often used in practice

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

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.Scientific Assessment and Innovation in Neurosurgical Treatment Strategie

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

Background\ud Changes in patient length of stay (the duration of one visit) as a result of the introduction of an electronic patient file system forced an anesthesia department to change their outpatient clinic organization. The aim of this study is to demonstrate how the involvement of essential employees combined with mathematical techniques to support the decision making process resulted in a successful intervention. \ud Methods\ud The setting is the preanesthesia evaluation clinic of a university hospital, where patients consult several medical professionals, either on walk-in or appointment basis. 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, 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 if the initial design should be maintained, or an intervention was needed. \ud Results \ud The queuing model predicted that three 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 one year 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.\ud Conclusions\ud Queuing theory provides robust methods to evaluate alternative designs for the organization of preanesthesia evaluation clinics. Combining these mathematical techniques with the essential involvement of employees may lead to a successful intervention that improves clinic performance

Injurious tail biting in pigs: How can it be controlled in existing systems without tail docking?

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Why are most EU pigs tail docked? Economic and ethical analysis of four pig housing and management scenarios in the light of EU legislation and animal welfare outcomes

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