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.
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.
Authors: Jonathan F Bard; Zhichao Shu; Douglas J Morrice; Dongyang Ester Wang; Ramin Poursani; Luci Leykum Journal: Health Care Manag Sci Date: 2014-08-26