The Journal of the American Board of Family Practice, Vol 14, Issue 4 259-265, Copyright © 2001 by American Board of Family Practice

ARTICLES

Open-access appointment scheduling in family practice: comparison of a demand prediction grid with actual appointments

S. N. Forjuoh, W. M. Averitt, D. B. Cauthen, G. R. Couchman, B. Symm and M. Mitchell
Department of Family Practice, Scott & White Memorial Hospital, and Texas A&M University System Health Science Center College of Medicine, Temple 76504, USA.

BACKGROUND: Inadequate access to their primary care physician remains a major reason for patient dissatisfaction in ambulatory care. The concept of open-access appointment scheduling has been found to accommodate patients' urgent health care needs while providing continuous, routine care. We describe the development of a demand prediction grid for future appointments, compare it with one developed by Kaiser Permanente, and compare the predictions with actual appointments made and held in our clinic. METHODS: Using adjusted 1999 appointments based on historical data for the Scott & White Killeen Clinic (> 75,000 annual appointments; 13 family physicians), we computed appointment predictions for calendar year 2000 by day of the week and by month of the year. We then compared our predictions with those of Kaiser and actual appointments for the first half of 2000. RESULTS: Our data and the Kaiser data agreed on the day of week, but they were different for the summer and winter months. Overall, actual appointments made and held at our clinic for January through June 2000 were within 6% of the predictions. Appointments for January and February were 18% and 4% more than the predictions, respectively, while appointments for March were 3% less than the predictions. Appointments for April through June were 3% to 7% more than the predictions. Few daily variations were observed between actual appointments and predictions. CONCLUSIONS: We conclude that the Kaiser data might be tempered by a different climate, underscoring the need for each practice to develop its own demand prediction grid. That our actual appointments were 6% more than predicted overall but fluctuated month by month reemphasizes the need for continuous monitoring of the adjustment factor for prediction.

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