Many outpatient clinics are experimenting with open access scheduling. Under open access, patients see their physicians within a day or two of making their appointment request, and long-term patient booking is very limited. The hope is that these short appointment lead times will improve patient access and reduce uncertainty in clinic operations by reducing patient no-shows. Practice shows that successful implementation can be strongly influenced by clinic characteristics, indicating that open access policies must be designed to account for local clinical conditions. The effects of four variables on clinic performance are examined: (1) the fraction of patients being served on open access, (2) the scheduling horizon for patients on longer-term appointment scheduling, (3) provider care groups, and (4) overbooking. Discrete event simulation, designed experimentation, and data drawn from an intercity clinic in central Indiana are used to study the effects of these variables on clinic throughput and patient continuity of care. Results show that, if correctly configured, open access can lead to significant improvements in clinic throughput with little sacrifice in continuity of care.

Long-term care networks may soon buckle under the weight of overwhelming demand. We present two dynamic, large-scale mixed-integer programs for long-term care network design that execute jointly strategic and tactical facility location, modular capacity acquisition, and patient-assignment decisions. The first model is an adaptive network-design model whose focus is more strategic in nature, whereas the second model focuses exclusively on the expansion of an existing long-term care network and incorporates additional tactical decisions such as patient backlogs. Working directly with the president of the Order of Québec Nurses-the provincial organization representing over 75,000 nurses-we incorporate facets such as assignment permanence, as well as develop and measure patient-centric quality-of-life proxies such as geographic mis-assignment and un-assigned patients, the latter of which is quantified via parametric optimization. Various network-design and patient-assignment policies are explored. We conclude that the use of home care as an alternative to long-term care facilities is cost prohibitive under specific conditions. Employing a bisection algorithm, we identify the implicit cost placed on keeping medically stable elderly patients in a hospital ward, concluding no cost savings are generated from such a policy. The model is analyzed and validated using empirical data from the long-term care network in Montréal, Canada.

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