title: Experience-based demand scheduling: a more efficient model for radiation oncology.
abstract: The supply of radiation therapists has increased, whereas reimbursements have decreased. One hypothesis is that if we choose to employ as permanent staff sufficient therapists to handle the low-volume periods and scheduled temporary staff as the demand for radiation therapy services warrants, we would increase efficiency. Using current economic assumptions and the treatments delivered during the past 12 months, we analyzed the labor expense and revenue consequences of both full staffing and a lower level of staffing with per diem supplementation based on the scheduled patient load. We then correlated the scheduled treatments with the actual treatments delivered and finally, reexamined both the full-staffing model and the per diem supplementation model based on the predictions of our scheduling model. The reduction in full-time therapists and per diem supplementation did not produce substantial incremental revenue. However, examining the relationship between patients 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 realized 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 marginal revenue, but is silent on the quality of the medical care provided.
authors.affiliation: Department of Radiation Oncology, Montefiore Medical Center, Bronx, New York 10467-2490, USA.
authors.forename: J J
authors.initials: JJ
authors.lastname: Beitler
authors.forename: A
authors.initials: A
authors.lastname: Garcia
authors.forename: B
authors.initials: B
authors.lastname: Vikram
mesh_terms: D001071:Appointments and Schedules; D016001:Confidence Intervals; D003365:Costs and Cost Analysis; D017598:Efficiency, Organizational / Q000191:economics; D005544:Forecasting; D006801:Humans; D018803:Models, Economic; D010045:Outpatients; D010360:Patient Transfer; D010561:Personnel Staffing and Scheduling / Q000191:economics / Q000458:organization & administration; D018787:Radiation Oncology / Q000191:economics / Q000458:organization & administration*; D012051:Reimbursement Mechanisms; D012456:Salaries and Fringe Benefits; D000078329:Workforce