Genesis Hospital Surgery Simulation Curtis Theel, MBA, CSSBB, PMP 2016 ASQ Columbus Spring Conference March 7 th, 2016
Background information In 2011, Genesis Healthcare System decided to combine 2 separate Hospitals, Good Samaritan and Bethesda The Besthesda Hospital would be renovated and a new 3-story Tower would be added on to it Construction would take place from 2013-2015 The 3-story tour would primary house the Emergency Department, Surgical Services, and a Critical Care Unit (CCU) The Problem: How do we determine how large to build our Surgical Suite?
GS OR Rooms Current Configuration BH OR Rooms 1 2 3 1 2 3 4 5 6 4 5 6 7 8 Total OR suites GS = 8 BH = 6 Combined = 14
Total OR suites GS = 8 BH = 6 Combined = 14 With zero analysis, administration would default to build 14 OR rooms. Was this the correct decision?
GS OR Rooms Current Configuration BH OR Rooms Rm 1: 685 Rm 2: 276 Rm 3: 1089 Rm 1: 309 Rm 2: 513 Rm 3: 481 Rm 4: 1297 Rm 5: 783 Rm 6: 401 Rm 4: 393 Rm 5: 3 Rm 6: 21 Rm 7: 470 Rm 8: 291
GS OR Rooms Current Configuration BH OR Rooms Rm 1: 685 X Rm 2: 276 Rm 3: 1089 Rm 1: 309 Rm 2: 513 Rm 3: 481 Rm 4: 1297 Rm 5: 783 Rm 6: 401 Rm 4: 393 X X Rm 5: Rm 6: 3 21 Rm 7: 470 X Rm 8: 291 2 rooms at BH never used 2 rooms as GS used less than 25% of normal use Rooms currently used = 10 rooms
Basic analysis indicated we only use 10 rooms. Is this the correct amount of rooms to build? 2 key questions: How do we validate this? How do we plan for the future? The answer: SIMULATION
Model Configuration 3 important steps to developing a simulation model Arrival Patterns Process flow Process times The rest is mechanical and data analysis
Model Configuration For arrival patterns and process times: Included complete OR data; separated service lines General Surgery Orthopedics Urology Neurosurgery CVOR Vascular Included complete Cath and EP Lab data; separated by type Cath Lab EP Lab Why differentiate between specialties?
Model Configuration *12 Operating Rooms *3 Cath Rooms *1 EP Room Note: For this model, the Hybrid OR was considered a normal-use OR
Arrival Distributions
Arrival Distributions First Method Arrival distribution by Specialty by Day
Arrival Distributions First Method Arrival distribution by Specialty by Day
Arrival Distributions Second Method Service Line Day Hour 0 1 2 3 4 5 6 7 8 9 Neuro Monday 0 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 1 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 2 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 5 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 6 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 7 65.52% 27.59% 6.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 8 91.38% 8.62% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 9 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 10 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 11 94.83% 5.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 12 89.66% 8.62% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 13 89.66% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 14 94.83% 5.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 15 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 16 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 17 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 18 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 19 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 20 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 21 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 22 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Neuro 23 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% # of arrivals
Arrival Distributions Second Method Service Line Day Hour 0 1 2 3 4 5 6 7 8 9 General Tuesday 0 98.25% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 1 96.49% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 2 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 5 96.49% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 6 98.25% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 7 17.54% 42.11% 22.81% 15.79% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% General 8 12.28% 45.61% 33.33% 5.26% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% General 9 29.82% 45.61% 15.79% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 10 28.07% 42.11% 26.32% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 11 17.54% 45.61% 28.07% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 12 12.28% 35.09% 31.58% 21.05% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 13 15.79% 26.32% 33.33% 21.05% 1.75% 1.75% 0.00% 0.00% 0.00% 0.00% General 14 31.58% 47.37% 15.79% 5.26% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 15 57.89% 33.33% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 16 57.89% 33.33% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 17 70.18% 29.82% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 18 80.70% 19.30% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 19 89.47% 10.53% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 20 89.47% 10.53% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 21 91.23% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 22 98.25% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 23 96.49% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% # of arrivals
Arrival pattern (all service lines) validation: Actual vs Flexsim output Mann-Whitney Test and CI: Actual Arrivals, Flexsim Arrivals Since the p-value is not less than N Median the chosen a level of 0.05, Actual you Arrivals 1716 2.0000 conclude that there is insufficient Flexsim Arrivals 1710 3.0000 evidence to reject H0. Therefore, the data does not support the Point estimate for ETA1-ETA2 is 0.0000 hypothesis that there is a difference 95.0 Percent CI for ETA1-ETA2 is (-0.0001,-0.0001) between the population medians. W = 2903566.5 Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2037 The test is significant at 0.1997 (adjusted for ties)
Arrival pattern (individual service lines) validation: Actual vs Flexsim output Mann-Whitney Test and CI: Ortho Wed Flexsim, Ortho Actual Since the p-value is not less than N Median the chosen a level of 0.05, Ortho you Wed Flexsim 57 4.000 conclude that there is insufficient Ortho Actual 57 4.000 evidence to reject H0. Therefore, the data does not support the Point estimate for ETA1-ETA2 is -0.000 hypothesis that there is a difference 95.0 Percent CI for ETA1-ETA2 is (-1.000,1.000) between the population medians. W = 3209.0 Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7000 The test is significant at 0.6953 (adjusted for ties)
Process Times (individual service lines) validation: Actual vs Flexsim output Mann-Whitney Test and CI: Flexsim Gen 3, Actual Gen 3 Since the p-value is not less than N Median the chosen a level of 0.05, Flexsim you Gen 172 75.34 conclude that there is insufficient Actual Gen 3133 74.00 evidence to reject H0. Therefore, the data does not support the hypothesis that there is a difference Point estimate for ETA1-ETA2 is -0.03 between the population medians. 95.0 Percent CI for ETA1-ETA2 is (-6.47,6.44) W = 284230.0 Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.9944 The test is significant at 0.9944 (adjusted for ties)
*Video clip of simulation*
The Output Replication Number Bed4 Bed5 Bed6 Bed7 Bed8 Bed9 Bed10 Bed11 Bed12 Bed13 Bed14 Bed15 Max Occupied 1 1 1 1 1 1 1 1 0 0 0 0 0 7 2 1 1 1 1 1 1 1 0 0 0 0 0 7 3 1 1 1 1 1 1 0 0 0 0 0 0 6 4 1 1 1 1 1 1 0 0 0 0 0 0 6 5 1 1 1 1 1 1 1 0 0 0 0 0 7 6 1 1 1 1 1 1 0 0 0 0 0 0 6 7 1 1 1 1 1 1 0 0 0 0 0 0 6 8 1 1 1 1 1 0 0 0 0 0 0 0 5 9 1 1 1 0 0 0 0 0 0 0 0 0 3 10 1 1 1 1 0 0 0 0 0 0 0 0 4 11 1 1 1 1 1 1 1 1 1 0 0 0 9 12 1 1 1 1 1 1 1 1 0 0 0 0 8 13 1 1 1 1 1 1 0 0 0 0 0 0 6 14 1 1 1 1 1 1 1 0 0 0 0 0 7 15 1 1 1 1 1 1 0 0 0 0 0 0 6 16 1 1 1 1 1 1 1 0 0 0 0 0 7 17 1 1 1 1 1 1 1 0 0 0 0 0 7 18 1 1 1 1 1 0 0 0 0 0 0 0 5 19 1 1 1 1 1 1 0 0 0 0 0 0 6 20 1 1 1 1 1 1 1 0 0 0 0 0 7 21 1 1 1 1 0 0 0 0 0 0 0 0 4 22 1 1 1 1 1 1 1 0 0 0 0 0 7 23 1 1 1 1 0 0 0 0 0 0 0 0 4 24 1 1 1 1 1 1 1 1 0 0 0 0 8 25 1 1 1 1 1 1 1 1 1 0 0 0 9 Data= Monday 100
OR Monday Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 5% of the day 12.5% = 1 hr 7:30a 3:30p
OR Tuesday Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 12% of the day 12.5% = 1 hr 7:30a 3:30p
OR Wednesday Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 15% of the day 12.5% = 1 hr 7:30a 3:30p
OR Thursday Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 20% of the day 12.5% = 1 hr 7:30a 3:30p
OR Friday Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 7% of the day 12.5% = 1 hr 7:30a 3:30p
OR Average Day (average of mon-fri usage patterns) =22.7 Percent rooms are concurrently occupied Example: 9 beds are used concurrently for 12% of the day 12.5% = 1 hr 7:30a 3:30p Note: Does include turnover time
Simulated OR utilization data by day of week 7:30a 3:30p Note: Does not include turnover time
Utilizing simulation for Scenario Analysis
10 OR s test Thursday 100 replications
OR Average Day (average of mon-fri usage patterns) CONVERTED to projected volumes; rooms removed = 23.7 24.7 Percent rooms are concurrently occupied 93% 69% 43% 23% Add 4.4% volume added to each room Reduce to 9 OR s
OR Utilization by volume growth 10% growth Service Line Day Hr 0 1 2 3 4 5 6 7 8 9 1.1 Service Line Day Hr 0 1 2 3 4 5 6 7 8 9 General Monday 0 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General Monday 0 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 1 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 1 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 2 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 2 98.10% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 5 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 5 98.10% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 6 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 6 98.10% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 7 15.52% 18.97% 41.38% 15.52% 8.62% 0.00% 0.00% 0.00% 0.00% 0.00% General 7 7.07% 20.86% 45.52% 17.07% 9.48% 0.00% 0.00% 0.00% 0.00% 0.00% General 8 34.48% 39.66% 15.52% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 8 27.93% 43.62% 17.07% 11.38% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 9 36.21% 41.38% 22.41% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 9 29.83% 45.52% 24.66% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 10 29.31% 39.66% 20.69% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 10 22.24% 43.62% 22.76% 11.38% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 11 29.31% 46.55% 24.14% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 11 22.24% 51.21% 26.55% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 12 34.48% 50.00% 15.52% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 12 27.93% 55.00% 17.07% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 13 51.72% 37.93% 6.90% 3.45% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 13 46.90% 41.72% 7.59% 3.79% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 14 60.34% 27.59% 10.34% 0.00% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% General 14 56.38% 30.34% 11.38% 0.00% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% General 15 75.86% 22.41% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 15 73.45% 24.66% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 16 82.76% 15.52% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 16 81.03% 17.07% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 17 86.21% 13.79% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 17 84.83% 15.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 18 89.66% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 18 88.62% 11.38% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 19 89.66% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 19 88.62% 11.38% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 20 89.66% 10.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 20 88.62% 11.38% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 21 98.28% 1.72% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 21 98.10% 1.90% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 22 94.83% 5.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 22 94.31% 5.69% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 23 94.83% 5.17% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 23 94.31% 5.69% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General Tuesday 0 98.25% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General Tuesday 0 98.07% 1.93% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 1 96.49% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 1 96.14% 3.86% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 2 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 2 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 3 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 4 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 5 96.49% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 5 96.14% 3.86% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 6 98.25% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 6 98.07% 1.93% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 7 17.54% 42.11% 22.81% 15.79% 1.75% 0.00% 0.00% 0.00% 0.00% 0.00% General 7 9.30% 46.32% 25.09% 17.37% 1.93% 0.00% 0.00% 0.00% 0.00% 0.00% General 8 12.28% 45.61% 33.33% 5.26% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% General 8 3.51% 50.18% 36.67% 5.79% 3.86% 0.00% 0.00% 0.00% 0.00% 0.00% General 9 29.82% 45.61% 15.79% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 9 22.81% 50.18% 17.37% 9.65% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 10 28.07% 42.11% 26.32% 3.51% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 10 20.88% 46.32% 28.95% 3.86% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 11 17.54% 45.61% 28.07% 8.77% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 11 9.30% 50.18% 30.88% 9.65% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 12 12.28% 35.09% 31.58% 21.05% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% General 12 3.51% 38.60% 34.74% 23.16% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
OR Utilization by volume growth Note: Assumes 12 OR rooms available. Does not include Turnover Time Volume growth Subsequent quarter = 4.4% growth
Convincing others
Table top simulation completed on longest/busiest day in year Team utilized 10 OR rooms, 1 hybrid room, 1 minor procedure room Day 1 had 6, 4+ hour cases. 34 OR cases total Day 2 had 3, 4+ hour cases. 34 OR cases total Both days caseload fit running 10 hour day
Future Plan Minor 1 2 3 4 5 6 Shell 12 11 10 9 Hybrid 8 7 10 standard OR Rooms 1 Hybrid Procedure Room 1 Shelled OR Room for future need
OR operational modeling Staff Utilization Determining FTE s for appropriate utilization in Surgery, Cath Lab, EP Lab
Service Line Typical Staffing by Case type Staff needed MD Nurse Tech Anes Total General 1 2 1 1 5 Ortho 1 2 1 1 5 Vascular 1 2 1 1 5 Neuro 1 2 2 1 6 Uro 1 1 2 1 5 Cath Lab 1 2 2 5 EP Lab 1 3 2 1 7 *Did not include assistants to the Surgeons that are not hospital employees
EP MD EP RN OR MD Cath Tech Cath RN Cath MD EP Tech OR Anes OR Tech OR RN Perfusion Model with max needed staff added to availability
Minutes each RN would work per Replication Completed with each job role
Minutes converted to Utilization
Color coded by percentages and grouped in to 3 categories How many OR RN s were more than 50%, 55%, 60% utilized on average during day?
Current vs Simulation Staffing 18 16 Current staffing 14 12 10 8 6 Monday Tuesday Wednesday Thursday Friday Combined Techs 14.7 15.9 16.4 15.7 14.7 Combined RNs 14.9 16.3 16.2 15.3 14.7 18 Simulation staffing 16 14 12 A difference of 27.8 FTE s per week 10 8 6 Monday Tuesday Wednesday Thursday Friday FlexCombined Techs 10.0 11.0 14.0 11.5 9.0 FlexCombined RNs 14.0 15.0 16.0 14.5 12.0
Conclusion: 10 OR s + 1 Hybrid would sufficiently accommodate current and increased volumes (up to +20% validated) Savings: Construction (hard savings): 2 less OR s = $4M Staffing (soft savings): $1.6M (salary + benefits)