title: Coordinating clinic and surgery appointments to meet access service levels for elective surgery.
abstract: Providing timely access to surgery is crucial for patients with high acuity diseases like cancer. We present a methodological framework to make efficient use of scarce resources including surgeons, operating rooms, and clinic appointment slots with a goal of coordinating clinic and surgery appointments so that patients with different acuity levels can see a surgeon in the clinic and schedule their surgery within a maximum wait time target that is clinically safe for them. We propose six heuristic scheduling policies with two underlying ideas behind them: (1) proactively book a tentative surgery day along with the clinic appointment at the time an appointment request is received, and (2) intelligently space out clinic and surgery appointments such that if the patient does not need his/her surgery appointment there is sufficient time to offer it to another patient. A 2-stage stochastic discrete-event simulation approach is employed to evaluate the six scheduling policies. In the first stage of the simulation, the heuristic policies are compared in terms of the average operating room (OR) overtime per day. The second stage involves fine-tuning the most-effective policy. A case study of the division of colorectal surgery (CRS) at the Mayo Clinic confirms that all six policies outperform the current scheduling protocol by a large margin. Numerical results demonstrate that the final policy, which we refer to as Coordinated Appointment Scheduling Policy considering Indication and Resources (CASPIR), performs 52% better than the current scheduling policy in terms of the average OR overtime per day under the same access service level. In conclusion, surgical divisions desiring stratified patient urgency classes should consider using scheduling policies that take the surgical availability of surgeons, patients' demographics and indication of disease into consideration when scheduling a clinic consultation appointment.
authors.affiliation: Medical Practice Evaluation Center, Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States. Electronic address: pooyan.kazemian@mgh.harvard.edu.
authors.forename: Pooyan
authors.initials: P
authors.lastname: Kazemian
authors.affiliation: Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Health Care Policy & Research, Mayo Clinic, Rochester, MN 55905, United States. Electronic address: sir.mustafa@mayo.edu.
authors.forename: Mustafa Y
authors.initials: MY
authors.lastname: Sir
authors.affiliation: Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, United States. Electronic address: vanoyen@umich.edu.
authors.forename: Mark P
authors.initials: MP
authors.lastname: Van Oyen
authors.affiliation: Hospital Pharmacy Services, Mayo Clinic, Rochester, MN 55905, United States. Electronic address: lovely.jenna@mayo.edu.
authors.forename: Jenna K
authors.initials: JK
authors.lastname: Lovely
authors.affiliation: Division of Colon and Rectal Surgery, Department of Surgery, Mayo Clinic, Rochester, MN 55905, United States. Electronic address: larson.david2@mayo.edu.
authors.forename: David W
authors.initials: DW
authors.lastname: Larson
authors.affiliation: Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Health Care Policy & Research, Mayo Clinic, Rochester, MN 55905, United States. Electronic address: pasupathy.kalyan@mayo.edu.
authors.forename: Kalyan S
authors.initials: KS
authors.lastname: Pasupathy
mesh_terms: D001071:Appointments and Schedules; D003198:Computer Simulation; D017558:Elective Surgical Procedures; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009873:Operating Rooms
keywords: Access to care; Clinic appointment scheduling; Coordinated care delivery; Discrete-event simulation; Surgery scheduling; Wait time target