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Re Engineering Proves Effective For Reducing Courier Costs
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Re Engineering Proves Effective For Reducing Courier Costs

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  • 1. Re-engineering proves effective for reducing courier costs Presented by , Sachin Gujare PGDIE-35 Roll No. 22 Reference: www.emeraldinsight.com http://www.memorialhermann.org/locations/default.html
  • 2. Case Study
    • 1997:Memorial Healthcare System and Hermann Healthcare System Merged into one organization, Memorial Hermann Healthcare System
    • Largest not-for-profit
    • Community owned, healthcare system in southeast Texas.
    • Annual Gross Profit:$3.25 billion.
    • 13300 employees and 3100 inpatient hospital bed.
    • System admits over 113000 patients annually.
    • Eight of the System’s acute care hospitals and 12 of the health clinics are located in the greater Houston area.
    • In annual healthcare expenditure in 1980=$1067 and 2001= $3760
    • Purchaser of healthcare is demanding lower costs.
    • Hospitals service payments because hospital services are estimated to be 35 % of the total healthcare expenditure.
    • Restructured laboratories have proven to save hospital’s millions of dollars
  • 3.  
  • 4. Problem Description
    • Transportation is challenging because of specimens must be handled carefully and according to govt. regulation, routing and staffing needs their attendance costs.
    • The system is seeking a more efficient laboratory courier service to meet needs of the redesigned laboratory system.
    • Basic objective is to reduce courier cost.
  • 5.
    • An overview of research heuristic
  • 6. Determining courier service levels
    • The prior service level used nine full-time equivalent employees and an outsourced courier company.
    • In total,20 courier runs existed, of which 18 where used for specimen delivery and two for errands.
    • The routs were uniform on weekdays, but were sporadic on weekends.
    • Full time employees were responsible for four specific routs that includes 3 hospitals & 8 health clinics (Table I)
  • 7.
    • Note:
    • Routes 2 and 3 are identical. Route 2 is an early morning route including only Memorial Herman Existing laboratory Southeast, while route 3 is midday.
    • Routes 4 and 5 are identical. Route 4 is a midday route while route 5 courier routes for is an evening route including only Memorial Hermann Memorial City
    • *MH- Memorial Harmann
    • Route Day Facility 1 Monday-Friday MH* Northwest & Jane long Clinic 2 and 3 Monday-Friday MH Southwest, Wave Clinic& Power Centre 4 and 5 Monday-Friday MH Memorial City and Wellness Center
    • 6 Monday-Friday LaConcha, Home Health Central, Texas Medical
  • 8.
    • Note:
    • Routes 9 and 10 are identical.
    • Route 9 is a midday route, while route 10 is an evening route including only Memorial Hermann.
    • Routes 11 and 12 are identical.
    • Route 11 is a midday route while route 13 is an evening route including only Memorial Hermann Fort Bend and Memorial Hermann Katy
    • Route Day Facility 9 and 10 Monday-Friday MH Woodlands, Burbank Clinic and Home Health North 11 and 13 Monday-Friday MH Fort Bend, MH Katy, 1 st Colony Mall
    • Clinic, and Sport Center 12 and 14 Saturday/Sunday MH Fort Bend and MH Katy
    • 15 Saturday/Sunday MH Woodlands, MH Memorial City,
    • MH Southeast, and MH Northwest 16-20 Monday-Sunday MH Southwest
  • 9. Service Demand
    • Each hospital required at least five laboratory specimen pickups/deliveries/days during the week.
    • The early morning test results were required to assess patient status and/or revised care plans
    • Critical when specimen were delivered to Hermann at the earliest, the next day.
    • Hospital pickup/delivery demands varied greatly during the weekends.
    • A request was made that specimens arrive at Hermann within 2 hr. of being obtained from the originating hospital
    • Each Health clinic required only one schedule pickup per weekday with no pickup required on the weekend.
  • 10. Determining the optimal routes
    • The traveling salesman model was used because it could readily be made to fit the situation.
    • In this problem the “Salesman” (courier) travels from home to multiple destinations (Hospitals) then returns home.
    • In this model, Hermann was considered the home & each hospital was considered a destination.
    • The health clinics were considered in a separate model because there were no pickup times required on the weekends.
    • Not allowing the salesman to return home until he/she visits all destinations created an infeasible solutions for the courier service because all the specimens had to be delivered to Hermann within 2hr of being obtained by the courier.
    • In Model A, the best direct route was identified, with no consideration of the time limitation just mentioned. In other worlds, the shortest route that went to each hospital and then returned to Hermann was identified.
    • In Model B, forced a stop at Hermann while visiting each of the other hospitals. This model found the shortest route that originated at Hermann, went to at least one hospital, returned to Hermann, and then proceeded to the remaining hospitals before returning to Hermann.
    • In model C, forced two stops at Hermann while visiting each other hospital, then retuned to Hermann. The solution for these three models are shown in TableIII.
  • 11.
    • FB=Memorial Hermann Fort Bend; H=Memorial Hermann;
    • K=Memorial Hermann Kathy; MC=Memorial Hermann Memorial City;
    • NW=Memorial Hermann Northwest; SE=Memorial Hermann Southeast;
    • SW=Memorial Hermann Southwest; W=Memorial Hermann Woodlands
    Model A: Shortest direct route H-SE-NW-MC-K-FB-SW-H 182 miles/259 min Model B: Shortest one-return H-SE-W-NW-MC-K-FB-SW 188 miles/275 min route H-SE-H Model C: Shortest two-return H-NW-MC-K-FB-SW-H 205 miles/297 min route H-SE-H H-W-H
  • 12. Memorial Hermann Parceled routes from Round-trip time/miles Traveling salesman traveling salesman Model solutions Model A W-SE-H 130 min/101miles K-MC-NW-H 98 min/ 72 miles Total: 310 min/219 miles Model B No parceled routes satisfied the time demands Model C W-H 86 min/70 miles SE-H 60 min/72 miles K-MC-NW-H 98 min/72 miles FB-SW-H 82 min/46 miles Total:326 min/226 miles
  • 13. Identifying the Shifts with Gantt charts
    • Gantt chart included employee breaks, were used to show the system’s management a detailed schedule of the runs and to ensure that the selected routes (1A,2A, and 3A) met hospitals pickup/deliveries- one in early morning and one in the late evening.
    • Not more than 2hr could elapse prior to another scheduled visit, with the exception being visits after lunch and dinner.
    • Employee requirements were that each stop required 15 min lunch or dinner break.
    • Separate Gantt charts were used for day and evening services because the routes differed slightly due to the timings of lunch and dinner etc.
    • Total 13 Gantt charts (courier shifts) were necessary. Two of the hospital runs(2 & 4) included pickup/delivery from four health clinics. One run(7) is completely focused on the pickup/ delivery for the remaining seven health clinics.
  • 14.
    • FB: Memorial Hermann Fort Bend; BB: Burbank Clinic; H: Memorial Herman Hermann
    • FBHC: Fort Bend Health Centre; K: Memorial Herman Katy; HHC: Home Health Centre;
    • MC: Memorial Herman City; HHN: Home Health North;
    • NW: Memorial Herman Northwest; JL: Jane Long Clinic;
    • SE: Memorial Hermann Southeast; LC: LaConda (LTAC);
    • SE: Memorial Hermann Southwest; PC: Power Centre;
    • W: Memorial Hermann Woodlands; SC:Sport Centre; MC: Texas Medical Centre ;
    • WV: Wave Clinic; WC: Wellness Centre; W: Memorial Herman Woodlands;
    • SC: Wellness Centre; 1stCM: 1 st colony Mall Clinic
    Number total hours corresponding of runs Days (am/pm) Facility included in run Pickup and route delivery time 1 M-F (am) FB,SW 9 1A 2 M-F (pm) FB, SW,FBHC,JL,WC 8.5 1A 3 M-F (am) K,MC,NW 9 2A 4 M-F (pm) K,MC,NW,SC, 1 st CM 7.5 2A 5 M-F (am) W, SE 10 3A 6 M-F (pm) W,SE 8 3A 7 M-F (am) SE,HHN,BB,LC,MC,WV, 8 CLINICS ONLY 8 Sa-Su (am) FB,SW 8 1A 9 Sa-Su (pm) FB, SW 9 1A 10 Sa-Su (am) K,MC,NW 9 2A 11 Sa-Su (pm) K, MC,NW 5 2A 12 Sa-Su (am) W,SE 6 3A 13 Sa-Su (pm) W,SE 6 3A
  • 15. Developing a staffing schedule with Integer Programming
    • Employee scheduling is critical for service operation, such as courier services.
    • Staffing the system’s 13 courier runs to minimize the number of employees during a two-weeks shift was accomplished using an integer-programming model.
    • The staff resource constraints are given below:
    • 1 Each employee must work <80hr in a two week period. This prevented overtime because are paid on a two week period.
    • 2 Employees cannot work> one shift/day. No employee was required to work greater than one 10hr shift/day.
    • 3 Employees cannot have > four weekend shifts during the two week period. Each employee could not be scheduled to work more weekend days than exist in a two week period.
    • 4 Employees must work> ten shifts in a two week period. Employees have at least four days off every two weeks.
    • 5 Each weekday shift must be performed ten times in a two week period. Weekday routes must be performed Monday to Friday or five times/week.
    • 6 Each weekend shift must be performed four times in a two week period. Weekend routes must be performed Saturday and Sunday, which is twice/week
  • 16. RUNS Total number Employee 1 2 3 4 5 6 7 8 9 10 11 12 13 of shifts 1 7 2 9 2 3 2 4 9 3 6 4 10 4 5 3 8 5 4 2 4 10 6 1 8 1 10 7 7 1 8 8 3 3 1 3 10 9 7 3 10 10 10 Total no. of Runs 10 10 10 10 10 10 10 4 4 4 4 4 4 94 Note: Run 7 was a unique route. Integer programming was not needed to staff this route.
    • Three Integer-programming models were developed, one for each route
    • determined earlier (1A,2A, and 3A).
    • The expectation was that employees (not all were full-time) were required.
    • Also, 94 shifts for each tow-week period were required.
  • 17.
    • A realistic staffing schedule was created using the in formation in table IV. In addition, the following were considered:
    • Avoiding employees working a day shift directly following an evening shift;
    • Maximizing the total hours per employee so that a number of employees would be full-time according to the staffing requirement; and
    • Attempting to give employees the same staffing requirement; and
    • Attempting to give employees the same days off each week.
    • The staffing schedule required
    • 10 employees+1 Dispatcher+ 1 manager=12 Employees
    • 6 employees=full-time (6*79hr every two weeks)
    • 4 employees= 1* 76hr + 3* 73.5hr
    • 2 employees= 2* 68 hr
    • Four vehicle required, one for each route (1A, 2A, 3A)
    • Which comprised 12 runs in total and 1 for clinic run.
  • 18. Cost Savings
    • Laboratory system had a total cost =$829,253 PA
    • Existing service includes two runs devoted solely to errands (Bank, post office and inner system mail)
    • And three additional runs that included errands; these cost were included in the System’s total cost mentioned above.
    • The errand costs ($108,483 PA) were excluded from new courier services
    • Thus the true (existing) laboratory courier service cost (excluding errands) was $720,770 annually.
    • Actual courier service cost is projected to be $603,081 annually, a reduction of $117,689.
    • This is a 19.5% reduction from the existing courier service.
    • The cost data can be expected to increase at predictable rate (Salaries, benefits, and capital depreciation) so the model’s saving may be more that currently expected.
    • The vehicle cost is minimized by efficient route scheduling which allows one
    • Vehicle to be used for two non-overlapping runs.
    • Staff scheduling is optimized, minimized, minimizing the no. of employee involved.
  • 19. Project Summary
    • Prior to re-engineering, the Memorial Hermann laboratory courier service was developed haphazardly on as needed basis.
    • Detailed evolution indicated that the prior system was neither efficient (cost) nor effective (service).
    • Process management methods, fine tuned for reality a lower cost and higher service laboratory courier.
    • Three optimal courier routes were identified using the traveling salesman model.
    • These routes were selected based on the shortest travel time.
    • Each model is manually parceled for multiple routes that were again optimized for shortest travel time.
    • Gantt chart were used to determine the appropriate number of runs to meet specified service levels.
    • Integer Programming was used to minimize the no. of employees needed to staff the 13 runs.
  • 20.
    • Thank You !!

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