Improving CT Scan Throughput Using Process Improvement, Analysis and Simulation Methodologies. Roque Perez-Velez, PE

Transcription

1 Improving CT Scan Throughput Using Process Improvement, Analysis and Simulation Methodologies Roque Perez-Velez, PE

2 Roque Perez-Velez, PE Degrees BS in Industrial Engineering, University of Puerto Rico. MS in Engineering Management, University Of Florida. Experience: Shands Healthcare, Management Engineer Avon-Mirabella, Inc. (Jewelry) Warner-Lambert Pharmaceutics (OTC) Hanes Menswear, Inc. (Clothing) Professional Affiliations: Institute of Industrial Engineers. Florida Board of Professional Engineers. Association of Professional Engineers and Surveyors of PR. Captain, 146th Facilities Engineer Team, Unites States Army Reserves

3 Shands HealthCare Affiliated with the University of Florida. One of the Southeast's premier health systems. 9 hospitals, more than 80 affiliated primary and specialty physician practices. Medical staff of 1,500 UF faculty and community doctors.

4 Management Engineering Consulting Services MECS mission is to function as in-house management consultants who assist Shands HealthCare management in identifying ways to improve processes and enhance the effective deployment of resources (people, equipment, facilities, supplies) in order to: Improve financial performance Improve quality Reduce turnaround time (TAT) Improve customer satisfaction

5 Agenda Session Objectives Project introduction & background Data Analysis Simulation Modeling Recommendations Financial Analysis Conclusions / Q&A References

6 Session Objectives Learning Objectives: Impact of working with referring physicians to reduce Add-on patients. Steps involved in developing a comprehensive simulation involving a diverse team. Impact of adding specialized patients. Learn about recommended process improvements that allow for higher patient throughput. How to perform simulation sensitivity analysis.

7 Project Introduction & Background Radiology s CT Scan Department 24 hours operations Treats Outpatients, Inpatients, and Emergency patients. Hospital will provide Trauma Level I care. Department wants to diversify services to include cardiac patients.

8 Project Background (2) Major limitations for a smooth process: Inaccurate protocols. Incomplete patient s paperwork. Process of getting paperwork complete before patient gets on the scanning table. Add-on patients. No-show patients in relation with add-ons. Patients showing for appointments at earlier times than scheduled. The possibility of adding cardiac and Trauma Level I patients to schedule.

9 Project Objectives Provide process improvement recommendations to increase patient throughput. Analyze impact of reducing number of unscheduled patients. Analyze impact of reducing incomplete paperwork. Shifting of ortho outpatients to external location. Analyze impact of cardiac and trauma patients.

10 Data Analysis Interviews and shadowing. Historical data available. Patient mix (Outpatient - 42%, Inpatient - 36%, Emergency - 22%). Forecasting Rule (14 exams accounts for 90% of workload).

11 JAN 2005 MAR 2005 SEPT 2004 NOV 2004 Data Analysis (2) Shands at UF CT Scan Procedures Actual and Forecasted Volumes JAN 2002 MAR 2002 MAY 2002 JULY 2002 SEPT 2002 NOV 2002 JAN 2003 MAR 2003 MAY 2003 JULY 2003 SEPT 2003 NOV 2003 JAN 2004 MAR 2004 MAY 2004 JULY 2004 Month Forecast Actual Volume

12 Data Analysis (3) Average processing times (in-processing, patient prep time, scanning and out-processing). Patient's date of arrival Clerical processing times Patient s prep time Exam's start and end times Exam type Patient type Arrival Patterns. (Stat::Fit, VIM) Statistical Distributions. (Stat::Fit, VIM)

13 Simulation Model Simulation is the imitation of the operation of a real-world process or system over time. MECS fork-in-the road: Analytic techniques or simulation? Static simulation (mathematical methods) or dynamic simulation? Since there are so many variable, MECS decided to use a dynamic simulation modeling to provide support for management in their decision making process.

14 Simulation Model (2) Steps in a simulation study (1-6): Problem Formulation. Setting of objectives and overall project plan. Model building.* Data collection. Coding. Verification.

15 Simulation Model (3) Steps in a simulation study (7-12): Validation. Experimental design.* Production run and analysis. Additional runs. Document program and report results. Implementation.

16 Simulation Model (4) Production run and analysis. Volume (Day) Time (min) 50% Transfer from AO to OP and Actual 25% reduction of Incomplete Paperwork Name Minimum Average Maximum Minimum Average Maximum scan time ct scan time ct scan time ct Pt wait time IP\ER Prep time Pt waiting PLWBS (month) Outpatient Inpatient Add On Emergency Cardiac Trauma Additional runs. Document program and report results. Implementation.

17 Simulation Model (5) Simulation sensitivity analysis: Identify major measures of performance or variables. Change values and run what-ifs scenarios. Compare against prior results. Use gained information to make recommendations. Use software s optimization tool.

18 Recommendations Reduce the amount of incomplete paperwork by 25%. Convert 50% of Add-on patients to scheduled patients. Shift Ortho outpatients to satellite clinic. Upgrade CT Scanner to a 64-slice equipment.

19 Presentation to Management (Financials) 10% increase in volume results in a revenue enhancement of $1,118, % increase in volume results in a revenue enhancement of $1,677,940. Machine cost is $1.9 MM. Payback is less than 2 years. After incurred costs, revenue is $168,732 (10%) and $727,940 (15%).

20 Conclusion Physician buy-in is key to success. Positive financial impact can be achieved by second year. Improvements in process results in patient satisfaction. Use the knowledge and strengths of frontline staff in order to develop a good simulation model.

21 Questions?

22 References Sunil Chopra, Peter Meindl. Supply Chain Management: Strategy, Planning, and Operations by Prentice-Hall. G. Geoffrey Vinning. Statistical Methods for Engineers by Brooks/Cole Publishing Company. Jerry Banks, John S. Carson II. Discrete - Event System Simulation by Prentice-Hall. Geer Mountain Software Corporation. Stat::Fit Version 2, Stephen Roberts and Lijun Wang. Visual Interactive Modeler, Version 2.0.

23 Legend Outpatients Inpatients Emergency Specials Trauma, Cardiac

24 Experimental Design Scenario of reducing incomplete patient's paperwork by 25% and reduction of 50% add-on patients (conversion to scheduled outpatients). Scenario of forecasted increases in volume of 10%. Scenario of forecasted increases in volume of 15%. Scenarios of transferring a percentage of Ortho outpatients, to an outside clinic, at the 10% and 15% volume increase. Scenario of adding Cardiac patient testing at the same volume increases. Scenario of adding Trauma Patients at same volume increases. Same scenarios as above with 20% volume increase. Scenarios of adding a new machine with 15% and 20% volume increase.