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Reallocating Resources to Focused Factories: A Case Study in Chemotherapy

Reallocating Resources to Focused Factories: A Case Study in Chemotherapy. Peter Vanberkel, PhD Candidate University of Twente Netherlands Cancer institute – Antoni van Leeuwenhoek Hospital. Outline. About Focused Factories Case Study Decision Support Tool. Focused Factories History.

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Reallocating Resources to Focused Factories: A Case Study in Chemotherapy

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  1. Reallocating Resources to Focused Factories: A Case Study in Chemotherapy Peter Vanberkel, PhD Candidate University of Twente Netherlands Cancer institute – Antoni van Leeuwenhoek Hospital

  2. Outline • About Focused Factories • Case Study • Decision Support Tool

  3. Focused Factories History focus, simplicity and repetition breeds competence. – Skinner 1973 US Factory in the 1960 Focused Factory We produce fewer things! We produce them all Well We produce everything! We produce Nothing Well

  4. Manufacture And Assembly Assembly 2006

  5. Pomegranate Phone: Ultimate Do EVERYTHING phone (www. PomegranatePhone.com) iPhone: Does less but does Everything Well

  6. Health Care Focused Factories Specialized Clinics General Hospitals Specialized Hospitals

  7. Focused Factories within Hospitals Radiology OR Poly Clinics Chemotherapy Radiotherapy

  8. Patient Type Focused Factories? Skin Cancer Colon Cancer Breast Cancer Lung Cancer Prostate Cancer

  9. Focus on Service?Or Patient? Or Mix? Skin Cancer Colon Cancer Breast Cancer Lung Cancer OR Radiology Prostate Cancer

  10. Research Question • General: How can we quantify the impact of decentralizing a centralized service? • Chemotherapy Case Study: Design a decentralized service (Breast Cancer and Non Breast Cancer) that maintains the performance of the existing centralized department

  11. Presentation Focus… Chemotherapy (Existing) Economies of Scale? or Economies of Focus? Breast Cancer Chemotherapy Non Breast Cancer Chemotherapy

  12. About Chemotherapy Dept. New F/U Pnt. in Bed for Treatment Pnt. Arrives Pnt. in Wait Room Pnt. Leaves Appt. Request Access Time: < 5% of patients Should wait more than 1 days • Appointment: • Clinic Runs Smoothly when beds are • Utilized at 90% • Nurses can manage • Waiting Room time is reasonable • Currently 30 beds

  13. About Chemotherapy Dept. Black Box New F/U Pnt. in Bed for Treatment Pnt. Arr Pnt. in Wait Room Pnt. Leaves Appt. Request Arrival Rate: (Patients / day) Poisson(70.2) • ServiceRate: (Patients / day) • Depends on: • Appointment Length • Number of Beds • Output / Performance: • Access Time • Bed Utilization

  14. Service Rate Appt. Length = 90 mins Appt. Length = 60 P1 P2 P3 P4 Capacity Distribution in Patients / day: Int[Poisson(λ)/2] Capacity Distribution in Patients / day: Poisson(λ) Expo (1/λ) Expo (1/λ) Expo (1/λ)

  15. Model Output / Performance • Lqn = (Lqn-1+ Arrivalsn – Servedn)+ • Wait Time Distribution • Utilization = Beds Used / Total Beds

  16. Scenario Model Inputs Service Rate: 2.7 Pnts/day Arrival Rate: 72.1 Pnts/day Model Outputs Bed Utilization: 90% Access time >1 day: <5% Existing Chemotherapy Beds: 30 No Efficiency Improvement Expected Due to Focus Service Rate: 2.5 Pnts/day Bed Utilization: 90% Access time >1 day: <5% BC Chemotherapy Arrival Rate: 42.6 Pnts/day Beds: ? Service Rate: 2.8 Pnts/day Bed Utilization: 90% Access time >1 day: <5% NBC Chemotherapy Arrival Rate: 29.6 Pnts/day Beds: ?

  17. Breast Cancer Chemo Targets Met

  18. Non Breast Cancer Chemo Targets Met

  19. Results Decentralized Service Centralized Service BC Chemotherapy Equal Performance Existing Chemotherapy Beds: 19 NBC Chemotherapy Beds: 30 Beds: 13

  20. Case Study Conclusion • A decentralized Chemotherapy Service requires a total of 32 beds to ensure the same performance as the existing 30 bed centralized Service

  21. General Considerations for FF • Proportional Sizes of the decentralized groups • Variability in Appointment Length • Efficiency Improvement Due to Focus • Different Performance expectations for different patients

  22. Advantages of Methodology • Uses Data that is commonly available from outpatient Scheduling Systems • Applicable in other Focused Factory Decisions • Can determine the min Economies of Focus • Applicable in other outpatient environments • Can be easily adapted to answering a variety of questions related to different treatment plans for a certain segment of the patient population

  23. Other Applications • Impact of Different Drugs with faster infusion times • Impact of Less Frequent Return Appts • Impact of Different Working hours • Impact of Growing Demands • Impact of Dedicated Lab service

  24. Give Drug A Orally

  25. Decision Support Tool

  26. Future Research • Determine the combined advantages of multiple departments decentralized to a Focused Factory.

  27. Discussion & Questions?

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