Experience-based demand scheduling - A more efficient model for radiation oncology

The supply of radiation therapists has increased, whereas reimbursements ha ve decreased. One hypothesis is that if we choose to employ as permanent st aff sufficient therapists to handle the low-volume periods and scheduled te mporary staff as the demand for radiation therapy services warrants, we wou ld increase efficiency. Using current economic assumptions and the treatmen ts delivered during the past 12 months, we analyzed the labor expense and r evenue consequences of both full staffing and a lower level of staffing wit h per diem supplementation based on the scheduled patient load. We then cor related the scheduled treatments with the actual treatments delivered and f inally, reexamined both the full-staffing model and the per diem supplement ation model based on the predictions of our scheduling model. The reduction in full-time therapists and per diem supplementation did not produce subst antial incremental revenue, However, examining the relationship between pat ients scheduled for treatment on the next day and patients actually treated , revealed an 11% "no show" rate with a 95% confidence interval of 1%. Our new, experienced-based model demonstrated considerable revenues to be reali zed by using the no-show factor to better use therapists by more aggressive scheduling of outpatients, therapists, and more flexible transportation of inpatients. We conclude that the experience-based model predicts the margi nal revenue, but is silent on the quality of the medical care provided.