The current climate in the health care industry demands efficiency and patient satisfaction in medical care delivery. These two demands intersect in scheduling of ambulatory care visits. This paper uses patient and doctor-related measures to assess ambulatory care performance and investigates the interactions among appointment system elements and patient panel characteristics. Analysis methodology involves simulation modeling of clinic sessions where empirical data forms the basis of model design and assumptions. Results indicate that patient sequencing has a greater effect on ambulatory care performance than the choice of an appointment rule, and that panel characteristics such as walk-ins, no-shows, punctuality and overall session volume, influence the effectiveness of appointment systems.

T his paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and appointment interval adjustment. In the latter approach, appointment intervals are adjusted to match the consultation time characteristics of different patient classes. Our simulation results indicate that new appointment systems that utilize interval adjustment for patient class are successful in improving doctors' idle time, doctors' overtime and patients' waiting times without any trade-offs. Best performing appointment systems are identified for different clinic environments characterized by walk-ins, no-shows, the percentage of new patients, and the ratio of the mean consultation time of new patients to the mean consultation time of return patients. As a result, practical guidelines are developed for managers who are responsible for designing appointment systems.

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