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PDC_2011_Building Smart Without Compromising Efficiency

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PDC_2011_Building Smart Without Compromising Efficiency

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PDC_2011_Building Smart Without Compromising Efficiency

  1. 1. Building Smart Without Compromising Efficiency
  2. 2. Presenters Bill Seed, Staff Vice President, Universal Health Services Angela Lee, AIA, ACHA, LEED AP, Senior Vice President, HKS Debajyoti Pati, PhD, FIIA, LEED AP, Vice President and Director of Research, HKS
  3. 3. Acknowledgments • Summerlin Hospital, Las Vegas, NV • Texoma Medical Center, Denison, TX • Rapid Modeling Corporation
  4. 4. 50 Foot Rule
  5. 5. CAN LARGER INPATIENT BED UNITS AND EFFICIENT USE OF NURSING TIME GO HAND IN HAND? QUESTION
  6. 6. Larger Unit Implications • (+) Staffing efficiency • (-) Large floor plate • (-) Distances between destinations – (-) Longer walking distance – (-) Time spent walking Acute care units have increased in floor area by 118 percent over the past 20 years (KSA)
  7. 7. Implications of Walking • System efficiency – Unnecessary walking = Waste • Care quality – Time away from patients (patient- centric care) – Medication errors • Individual performance – Interactions with workplace stressors – Alertness, stress, fatigue
  8. 8. Private Vs. Semi-Private
  9. 9. Trend Towards Smaller Units
  10. 10. CAN LARGER INPATIENT BED UNITS AND EFFICIENT USE OF NURSING TIME GO HAND IN HAND? QUESTION
  11. 11. The UHS-HKS Projects • Guiding principles: – Proximity of services – Amenities for care – Decentralized nurses’ station – Computer logistics by focusing on the efficiency of flow, one can focus on patient- centric care and supply nurses everything they need without walking long distances
  12. 12. BY OPTIMIZING FLOW AND REDUCING POTENTIAL WASTE, THE LARGE UNIT WOULD NOT RESULT IN WALKING DISTANCES THAT ARE SUBSTANTIALLY HIGHER THAN NATIONAL BENCHMARK HYPOTHESIS
  13. 13. BY OPTIMIZING FLOW AND REDUCING POTENTIAL WASTE, HOW NURSES SPEND THEIR TIME WOULD NOT CONSTITUTE AN OUTLIER HYPOTHESIS
  14. 14. Texoma Medical Center Recognized up front, inpatient strategies can save time, money and promote better patient care.
  15. 15. Texoma Medical Center Use a racetrack configuration, which offers efficiency as well as easy wayfinding. The configuration provides the most efficient perimeter-to- core ratio and enables direct corridor sightlines for caregivers and patients. It also promotes separation of public and service areas.
  16. 16. Design Inpatient Unit as a Racetrack Configuration Provides most efficient perimeter to core ratio.
  17. 17. Design Inpatient Unit as a Racetrack Configuration Enables direct corridor sightlines for caregivers and patients.
  18. 18. Design Inpatient Unit as a Racetrack Configuration Enables direct corridor sightlines for caregivers and patients.
  19. 19. Design Inpatient Unit as a Racetrack Configuration Intermediate passages through the core reduce travel distances.
  20. 20. Design Inpatient Unit as a Racetrack Configuration Lean/efficient double loaded corridors – Easy to Navigate
  21. 21. Summerlin Medical Center
  22. 22. A Patient Centered Expansion Pinwheel design will minimize travel distances, promote patient safety, and maximize views from patient rooms.
  23. 23. A Patient Centered Expansion New tower will blend with the existing hospital in effort to keep the publicly recognized hospital identity.
  24. 24. A Patient Centered Expansion $100 million expansion and renovation in one of southern Nevada’s fastest growing communities in Las Vegas, Nevada All of the changes were made externally, with breaking through the connecting wall as a final step
  25. 25. Summerlin Medical Center
  26. 26. Summerlin Medical Center
  27. 27. DATA COLLECTION POST OCCUPANCY PERFORMANCE
  28. 28. Time-Motion Data • Rapid Modeling Corporation’s programmed Palm PDAs • 1 week on each unit • Summer 2010 • Compared with TCAB Time Study RN national database
  29. 29. Walking Data • Sportline pedometer • 1 week on each unit • Summer 2010 • Compared with 36- hospital time-motion study* *Hendrich, A., M. Chow, B.A. Skierczynski & Z. Lu. (2008). A 36-Hospital Time and Motion Study: How Do Medical- Surgical Nurses Spend Their Time? The Permanente Journal, 12(3), 25-34.
  30. 30. FINDINGS POST OCCUPANCY PERFORMANCE
  31. 31. Time Data by Task Type • Value adding: – Comparison with TCAB data Proportion of time spent in value adding tasks: Minimum, Q1, Mean, Q3, Maximum 34.6% 59.1% 64.2% 68.0% 96.4% 59.8%59.5% TEXOMASUMMERLIN
  32. 32. Time Data by Task Type • Non value adding tasks: – Comparison with TCAB data Proportion of time spent in non value adding tasks: Minimum, Q1, Mean, Q3, Maximum 0% 9.1% 11.5% 13.7% 33.9% 8.2% 10.5% TEXOMA SUMMERLIN
  33. 33. Time Data by Task Type • Necessary tasks: – Comparison with TCAB data Proportion of time spent in necessary tasks: Minimum, Q1, Mean, Q3, Maximum 2.6% 21.6% 24.2% 27.5% 50.0% TEXOMASUMMERLIN 32.0%30.0%
  34. 34. Time Data by Task Category • Direct Care Time: – Comparison with TCAB data Proportion of time spent in direct care: Minimum, Q1, Mean, Q3, Maximum 47.8%43.0% 91.5%15.7% 43.2% 48.3% 51.6% TEXOMASUMMERLIN
  35. 35. Time Data by Task Category • Indirect care time: – Comparison with TCAB data Proportion of time spent in indirect care : Minimum, Q1, Mean, Q3, Maximum 1.7% 13.6% 17.0% 20.1% 37.0% 12.0% 16.5% TEXOMA SUMMERLIN
  36. 36. Time Data by Task Category • Documentation: – Comparison with TCAB data Proportion of time spent in documentation: Minimum, Q1, Mean, Q3, Maximum 1.6% 15.1% 18.0% 21.1% 38.5% 15.8%10.5% TEXOMASUMMERLIN
  37. 37. Time Data by Task Category • Administration: – Comparison with TCAB data 0% 19.2% TEXOMA SUMMERLIN 16.0% 19.4% 3.2%5.2% 6.5% Proportion of time spent in administration: Minimum, Q1, Mean, Q3, Maximum
  38. 38. Time Data by Task Category • Personal: – Comparison with TCAB data Proportion of time spent in personal work: Minimum, Q1, Mean, Q3, Maximum 0% 3.4% 4.5% 5.4% 16.9% 1.0% 2.1% TEXOMA SUMMERLIN
  39. 39. Time Data by Task Category • Waste: – Comparison with TCAB data Proportion of time wasted: Minimum, Q1, Mean, Q3, Maximum 0% 1.9% 2.9% 3.5% 9.8% 3.0%1.7% TEXOMASUMMERLIN
  40. 40. Time Data by Task Level • Nurse station: – Comparison with TCAB data Proportion of time spent in nurse station: Minimum, Q1, Mean, Q3, Maximum 0% 27.8% 36.1% 44.2% 89.9% 54.9%47.3% TEXOMASUMMERLIN
  41. 41. Time Data by Task Level • Patient room: – Comparison with TCAB data Proportion of time spent in patient room: Minimum, Q1, Mean, Q3, Maximum 3.8% 34.6% 40.7% 44.7% 80.7% 37.2%36.3% TEXOMASUMMERLIN
  42. 42. Time Data by Task Level • Medication: – Comparison with TCAB data Proportion of time spent in medication: Minimum, Q1, Mean, Q3, Maximum 0% 13.4% 16.8% 20.6% 45.6% 15.8% 17.3% TEXOMA SUMMERLIN
  43. 43. Time Data by Task Level • Off the unit: – Comparison with TCAB data Proportion of time spent of the unit : Minimum, Q1, Mean, Q3, Maximum 0% 1.8% 3.3% 4.2% 22.0% 0.3% 0.8% TEXOMA SUMMERLIN
  44. 44. Walking Data 0 mile 1 mile 2 miles 3 miles 4 miles 5 miles Day Shift Range 36-Hospital Night Shift Range 36-Hospital 36-Hospital Study Individual Walking Distance Range Day Shift Summerlin Night Shift Summerlin Night Shift Texoma Day Shift Texoma
  45. 45. CONCLUSION
  46. 46. • The unit operations and efficiencies are similar to the middle 50% of TCAB participant hospitals.
  47. 47. • While retaining efficiencies in time distribution across activities and walking distances, the two units successfully incorporated larger number of beds while reducing construction costs.
  48. 48. • A healthcare provider can significantly reduce construction costs but operate with the same efficiencies.
  49. 49. • Integrated decision-making with a primary focus on the efficiencies of flow can be used to address the seemingly difficult task of achieving larger inpatient bed units as well as efficient use of caregiver time.

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