Article ID: | iaor20123722 |
Volume: | 15 |
Issue: | 2 |
Start Page Number: | 91 |
End Page Number: | 102 |
Publication Date: | Jun 2012 |
Journal: | Health Care Management Science |
Authors: | Patrick Jonathan |
Keywords: | scheduling, allocation: resources, combinatorial optimization, programming: markov decision, simulation: applications |
Managing an efficient outpatient clinic can often be complicated by significant no‐show rates and escalating appointment lead times. One method that has been proposed for avoiding the wasted capacity due to no‐shows is called open or advanced access. The essence of open access is ‘do today’s demand today’. We develop a Markov Decision Process (MDP) model that demonstrates that a short booking window does significantly better than open access. We analyze a number of scenarios that explore the trade‐off between patient‐related measures (lead times) and physician‐ or system‐related measures (revenue, overtime and idle time). Through simulation, we demonstrate that, over a wide variety of potential scenarios and clinics, the MDP policy does as well or better than open access in terms of minimizing costs (or maximizing profits) as well as providing more consistent throughput.