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Emergency Department Directors Academy Phase I Spring 2020 Staffing and Scheduling Methodologies I DESCRIPTION One of the most important aspects of being a director is creating the right mix of physicians and mid-level providers to ensure efficient care, satisfied patients, and proper revenue. Proper scheduling and awareness of practitioner wellness is essential for practitioner satisfaction. The presenter will review several methods for making an ED schedule that maximizes staff satisfaction yet effectively provides necessary ED coverage. When is another attending physician needed? When is a mid-level provider the best option? The most recent staffing trends will be discussed in light of the current increases in patient volume and acuity that many emergency departments are experiencing. Despite little scientific data, the current experiences of the most efficiently run emergency departments will be discussed. OBJECTIVES
• Demonstrate several methods available to an ED medical director to assist with staffing and scheduling issues.
• Discuss the staffing models of the most efficient emergency departments. • Explain the best ways to reconfigure staffing models as the volume increases. • List critical points of when another attending is required. • Explain how staffing affects efficiency, patient and provider satisfaction, cost-effective care, and
medical-legal safety. • Staffing and Scheduling Methodologies I
2/7/2020, 8:00 AM - 9:30 AM FACULTY: Jody Crane, MD, MBA DISCLOSURE: (+) No significant financial relationships to disclose
Emergency Department Directors Academy Phase I Spring 2020 Staffing and Scheduling Methodologies II DESCRIPTION The formation of an effective leadership structure can move idea and commitment to implementation and improvement. The panel will describe how to develop various forms successful to ED organizational leadership. The participants will be given ample time to ask questions and describe barriers to successful leadership in their own organization. Panel members will comment on and make suggestions for improvement. OBJECTIVES
• Identify critical departmental goals and integration strategies. • List various departmental leadership structures, successful and unsuccessful. • Identify essential participants in leadership group. • Define communication to and from leadership group. • Describe management of disagreement. • Staffing and Scheduling Methodologies II
2/7/2020, 9:45 AM - 11:15 AM FACULTY: Jody Crane, MD, MBA DISCLOSURE: (+) No significant financial relationships to disclose
© 2020, Crane, Noon
Outline
Academic PrinciplesCase StudyApproach to Staffing Optimization
Define DemandDefine CapacityContextualize
Case Study Wrap-upConclusions
© 2020, Crane, Noon
Outline
Academic PrinciplesCase StudyApproach to Staffing Optimization
Define DemandDefine CapacityContextualize
Case Study Wrap-upConclusions
© 2020, Crane, Noon
Queuing Theory - Agner Krarup Erlang
Copenhagen Telephone Company (KTAS), 1908
"Solution of some Problems in the Theory of Probabilities of Significance in Automatic Telephone Exchanges,” 1917
© 2019, Crane, Noon
Server
Queue(waiting line)Customer
Arrivals
CustomerDepartures
A Simple Queue
© 2020, Crane, Noon
Server
Queue(waiting line)Customer
Arrivals
CustomerDepartures
A Simple Queue
© 2020, Crane, Noon
A Simple Queue
Server
Queue(waiting line)Customer
Arrivals
CustomerDepartures
ArrivalRate (l )and Distribution
ServiceRate (µ )and Distribution
© 2020, Crane, Noon
A Simple Queue
Server
Queue(waiting line)Customer
Arrivals
CustomerDepartures
ArrivalRate (l )and Distribution
ServiceRate (µ )and Distribution
Avg Numberin Queue (Lq )
Avg. Wait Timein Queue (Wq )
Avg Time in System (W )Avg Number in System (L )
© 2020, Crane, Noon
Triage Example 1Suppose we have a triage operation staffed by a single nurse. Patients arrive and wait in the waiting area if the triage nurse is busy triaging other patients. When a patient is seen by the triage nurse, the triage activity occurs in a single encounter. Data was gathered and, on average, 6 patients arrive per hour. The average time it takes to triage a patient is 12 minutes.So, will there be any waiting? YES!
© 2020, Crane, Noon
Triage Example 2Suppose we have a triage operation staffed by a single nurse. Patients arrive and wait in the waiting area if the triage nurse is busy triaging other patients. When a patient is seen by the triage nurse, the triage activity occurs in a single encounter. Data was gathered and, on average, 4 patients arrive per hour. The average time it takes to triage a patient is 12 minutes (again, a “service rate” of 5 patients/hour).So, will there be any waiting? It Depends!
© 2020, Crane, Noon
On average, 4 patients arrive per hour. Assume 1 patient arrives every 15 minutes.
The time it takes the nurse to triage a patient averages 12 minutes (can triage 5 per hour).
Assume exactly 12 minutes per patient.
Sigma ED - Ideal Triage
© 2020, Crane, Noon
The nurse and patient arrive at 4pmThe first triage encounter lasts exactly 12 minThe nurse has exactly 3 min of idle timeThe next patient arrives at exactly 4:15And so on…
4:154:00 4:30 4:45
arrive1 arrive2 arrive3 arrive4
......triage1 triage2 triage3 triage4
Sigma ED - Ideal Triage
© 2020, Crane, Noon
Sigma ED Triage – Variation
On average, 4 patients arrive per hour. Assume 1 patient arrives every 15 minutes.
The time it takes the nurse to triage a patient averages 12 minutes (can triage 5 per hour).
Assume exactly 12 minutes per patient.
variation around service times
random arrival process.
© 2020, Crane, Noon
Arrival data from a real ED
ARRIVAL TIMES
660 690 720 750 780 810 840 870 900
Time
ARRIVAL TIMES
460 490 520 550 580 610 640 670 700
Time
Arrival data from a California hospital. Mondays, 2pm-6pm.
© 2020, Crane, Noon
Distribution of Actual ED Triage Times.Distribution of Observed Triage Times (n=777)
020406080100120140160180
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Minutes
Cou
nt
Average = 5.06Std.Dev. = 4.97
Time study data from MWH.
© 2020, Crane, Noon
Sigma ED Triage – Variation
On average, 4 patients arrive per hour. Assume 1 patient arrives every 15 minutes.
The time it takes the nurse to triage a patient averages 12 minutes (can triage 5 per hour).
Assume exactly 12 minutes per patient.
Will there be waiting, and if so, how much?
variation around service times
random arrival process.
© 2020, Crane, Noon
As Server Variation Increases…
© 2020, Crane, Noon
As Utilization Increases…
© 2020, Crane, Noon
Waiting
Physician
Theory of Constraints – FT Example
30 min/pt3pts/hr
=1) How many patients can my
clinic see per hour?
2) How can you improve this system?
3) if you can’t add resources….Nurse
TOC: The Theory of Constraints§ Bottleneck- A resource
that has the capacity equal to or less than the demand placed upon it
§ Non-bottleneck- A resource that has a capacity that is greater than the demand placed upon it
Outline
Academic PrinciplesCase StudyApproach to Staffing Optimization
Define DemandDefine CapacityContextualize
Case Study Wrap-upConclusions
© 2020, Crane, Noon
Case Study: 75,000-visit Peds ED
© 2020, Crane, Noon
You’re called into the CEO’s Office!Our ED really stinks!
© 2020, Crane, Noon
Peds ED Door to Doc by Month
© 2020, Crane, Noon
Peds ED LWOBS by Month
© 2020, Crane, Noon
Peds ED LWOBS vs. Peers
© 2020, Crane, Noon
You’re called into the CEO’s Office!Our ED really stinks!
YOU better fix this NOW!
© 2020, Crane, Noon
What are you going to do?
© 2020, Crane, Noon
What Information Do You Need?
© 2020, Crane, Noon
© 2020, Crane, Noon
PEDs ED Acuity Mix by ESI Level
© 2020, Crane, Noon
Peds ED Day of Week Arrivals
© 2020, Crane, Noon
Peds ED Hourly Arrivals
© 2020, Crane, Noon
Peds ED Seasonal Hourly Arrivals
© 2020, Crane, Noon
Peds ED Hourly LWOBS
© 2020, Crane, Noon
Peds ED LWOBS vs Door to Doc
© 2020, Crane, Noon
© 2020, Crane, Noon
Peds ED Low Acuity Arrivals
© 2020, Crane, Noon
Peds ED Low Acuity
Prod – 1.5 pts/hrVolume – 3 pts/hr
© 2020, Crane, Noon
Peds ED Low Acuity
Prod – 0.5 pts/hrVolume – 3 pts/hr
© 2020, Crane, Noon
Peds ED Main ED #1
Prod – 0.89 pts/hrVolume – 3 pts/hr
© 2020, Crane, Noon
Peds ED Main ED #1
Prod – 0.5 pts/hrVolume – 3 pts/hr
© 2020, Crane, Noon
© 2020, Crane, Noon
Outline
Academic PrinciplesCase StudyApproach to Staffing Optimization
Define DemandDefine CapacityContextualize
Case Study Wrap-upConclusions
© 2020, Crane, Noon
Basic Approach to Staffing
1. Define the arrival Demand2. Define and align the server Capacity
(physician, nurse, APC, resident, bed productivity)
3. Execute in the Context of your current operational environment
© 2020, Crane, Noon
Basic Approach to Staffing
1. Define the arrival Demand2. Define and align the server Capacity
(physician, nurse, midlevel, resident, bed productivity)
1. Understand your current productivity2. Benchmarking3. Max Productivity (Time Studies)
3. Execute in the Context of your current operational environment
© 2020, Crane, Noon
1. Define the Arrival DemandArrival demand defines the demand for healthcare deliveryIs the primary driver for physician, APC, and resident staffing
© 2020, Crane, Noon
1. Demand – Hour of Day Variation
Peak usually starts between 8a and 11amUsually ends between 9pm and 11pmTypically between 4:1 and 6:1 peak vs overnight arrivalsPediatrics and low acuity – higher evenings
Peak 10/hrLow 2/hr
© 2020, Crane, Noon
… but the actual count of arrivals for any given hour or day can vary considerably. This is arrival variation.
22 121 120 119 1 118 1 1 1 217 116 2 1 1 1 3 1 115 2 1 1 1 1 1 1 1 1 114 1 2 8 3 7 3 1 2 1 9 1 113 6 3 6 6 1 2 2 1 2 3 3 1 1 112 4 3 7 4 6 3 1 3 5 5 6 9 2 3 1 1
Count 11 3 4 6 5 8 4 6 5 5 4 2 4 4 2 1 210 1 7 10 5 4 6 7 5 6 3 7 6 9 2 3 3 19 1 1 1 2 4 7 5 8 5 3 6 10 14 5 4 4 8 10 12 48 3 2 1 6 3 5 6 5 10 11 6 5 8 8 6 11 9 6 57 4 1 2 1 1 3 6 3 1 5 4 4 7 6 6 6 4 7 9 6 8 66 4 6 4 3 2 3 12 8 4 7 1 5 5 1 5 4 5 1 4 3 9 5 85 12 5 6 1 3 1 4 5 5 7 5 2 2 4 3 3 3 5 5 3 1 54 10 15 12 10 10 5 4 6 3 2 3 3 3 2 1 3 2 2 5 133 8 13 11 16 12 17 10 9 1 2 1 1 1 1 1 2 6 52 9 6 14 15 11 11 20 8 4 1 1 1 1 1 11 3 3 5 8 10 10 6 1 10 1 7 6 1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23Hour of Day (Mondays only)
Copyright Jody Crane, MD, MBA, Chuck Noon, PhD 2008© 2020, Crane, Noon
1. Demand – Hour of Week Variation
Volume varies significantly by day of week in most institutionsWeekend volume is usually lower than weekday volumeMondays are usually the busiest and also have the highest acuityPediatrics will have much higher weekends and evenings
© 2020, Crane, Noon
From One of My Directors…
“We had a 250-patient Sunday this week, which was the highest volume day of the week. This is why you can’t staff to averages, because ED volume is unpredictable.”
© 2020, Crane, Noon
© 2020, Crane, Noon
1. Demand – Hour of Week Variation
Volume varies significantly by day of week in most institutionsWeekend volume is usually lower than weekday volumeMondays are usually the busiest and also have the highest acuityPediatrics will have much higher weekends and evenings
1. Would you bet $1,000 this Mon will have more arrivals than this Sun?2. Would you staff Mon differently than Sun?
© 2020, Crane, Noon
226
256 255
243241
229
222
Sun Mon Tue Wed Thur Fri Sat
Average Volume by Day of Week 12/14-5/31Mon ≈ Tue
Wed ≈ Thur
Sat ≈ Sun Sat ≈ Sun
1. Would you bet $1,000 this Mon will have more arrivals than this Sun?2. Would you staff Mon differently than Sun?
© 2020, Crane, Noon
150
170
190
210
230
250
270
290
0 1 2 3 4 5 6 7 8
Scatter Plot Day of Week 2/1/15 - 5/31/15
• 100% of the Sundays fall below the Monday average • 50% of the Sundays fall below the lowest volume Monday• Monday and Tuesday averages are 35 patients per day higher than Saturday/Sunday• The 5 highest volumes fall on Mon and Tue• Note the 2 busiest days in the sample (Mon/Tue) of the sample had 30+ more patients than
the busiest Sunday, 50 more than the Sunday average.
Mon ≈ Tue Wed ≈ Thur Sat ≈ Sun
1. Would you bet $1,000 this Mon will have more arrivals than this Sun?2. Would you staff Mon differently than Sun?
© 2020, Crane, Noon
1. Demand - Seasonal Variation
Seasonal Variation can be problematic if not consideredUltimately affects the size of your ED and the operational approachPeds follows this profileNeed specific strategies to staff appropriately –part time staffing, preferential vacations, snowbird scheduling
Summer10/hr
Winter12/hr
© 2020, Crane, Noon
Basic Approach to Staffing
1. Define the arrival Demand2. Define and align the server Capacity
(physician, nurse, midlevel, resident, bed productivity)
3. Execute in the Context of your current operational environment
© 2020, Crane, Noon
2. Define Server Capacity1. Assess the volume
over a week and divide by the total staffing hours
1400 pts/wk700 doc hrs/wk = 2 pts/hr
© 2020, Crane, Noon
2. Capacity – Average Service Rate1. Assess the volume
over a week and divide by the total staffing hours
2. Peak productivity will usually be higher as lower overnight volumes tend to drive the overall average down
© 2020, Crane, Noon
1400 pts/wk700 doc hrs/wk = 2 pts/hr
1100 pts/wk500 doc hrs/wk = 2.2 pts/hr
Benchmarks are ScarceNursing
No source for ideal productivityMost recommendations are from nurse advocate organizationsGrowing evidence that lower nurse staffing results in increased morbidity, mortality, and cost
PhysicianNo source for ideal productivityACEP, SAEM, AAEM all have position statementsOther studies are largely inaccurate, outdated
Recommended Benchmarking Sources: ACEP; Premier; EDBA; VHA
© 2020, Crane, Noon
3.26
2.4
2.6 - 3.1
2.8
© 2020, Crane, Noon
For moderate Acuity EDs, 2.5 patients per hour should not be exceeded.
© 2020, Crane, Noon
1.8 to 2.8 patients per hour2.1 to 2.2 patients per hour, you should consider increasing staffingMaximize the lowest cost staffing alternatives first
© 2020, Crane, Noon
EDBA Actual PPH
Based on 2013 data© 2020, Crane, Noon
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
020406080
100120140160180200
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9 2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9 3
Mor
e
EDBA Actual Provider Productivity
Frequency Cumulative %
Physician
Theory of Constraints – FT Example
30 min/pt3pts/hr
=1) How many patients can my
clinic see per hour?
2) How can you improve this system?
3) if you can’t add resources….Nurse
EDBA Actual PPH
Based on 2013 data© 2020, Crane, Noon
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
020406080
100120140160180200
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9 2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9 3
Mor
e
EDBA Actual Provider Productivity
Frequency Cumulative %
Higher prod = ↑ queuingLower prod = ↓ queuing
Must take system flow into account!
© 2020, Crane, Noon
What’s Possible???
© 2020, Crane, Noon
2. Capacity – Time Studies
1. Perform a time study2. Follow nurses and
physicians around as they work throughout the week and time everything they do
3. This will give you how much time they spend on patients
4. And…where to improve
Nurse Doc Nurse DocCap Hill 1.8 1.1 44 28 Largo 1.6 1.0 39 25 Tysons 1.6 0.9 38 21
Miles/Shift Min/Shift
© 2020, Crane, Noon
2. Capacity – Time Studies
1. Perform a time study2. Follow nurses and
physicians around as they work throughout the week and time everything they do
3. This will give you how much time they spend on patients
4. And…where to improve
© 2020, Crane, Noon
MinutesCTAS 1 73.6CTAS 2 38.9CTAS 3 26.3CTAS 4 15CTAS 5 10.9 Pts/HrWeighted Avg 26.0 2.3
120% 31.2 1.9
Dreyer, JF, et. al. “Physician workload and the Canadian Emergency Department Triage and Acuity Scale: the Predictors of Workload in the Emergency Room (POWER) Study,” CJEM 2009;11(4):321-329
*Over 11,000 visits
2. Capacity - EM Time Studies
© 2020, Crane, Noon
4,000 Clicks
• 43% of time on data entry• 28% on direct care• 12% Results review• 13% Communication• 3% Other
© 2020, Crane, Noon
Scribes
© 2020, Crane, Noon
© 2020, Crane, Noon
Scribes – Outback Style
• Increased productivity 0.32 pts/hr (0.16-0.65)• Provider income increased $105 Aus ($80 US)
per scribed hour
© 2020, Crane, Noon
Productivity – Before and After Scribes
17%
© 2020, Crane, Noon
© 2020, Crane, Noon
EDBA Impact of Scribes
© 2020, Crane, Noon
Scribes vs Voice Dictation
© 2020, Crane, Noon
2. Nurse Capacity
© 2020, Crane, Noon
Assess the volume over a week and divide by the total staffing hours
Productivity Targets1400 pts/wk
700 doc hrs/wk = 2.0 pts/hr
665 pts/wk1,000 RN hrs/wk= 0.67 pts/hr
84
© 2020, Crane, Noon
EDBA Nurse Productivity
© 2020, Crane, Noon
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
0
20
40
60
80
100
120
140
0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00 More
Nurse PPH
Frequency Cumulative %
Higher prod = ↑ queuingLower prod = ↓ queuing
Worked Hours per Patient Visit (whppv)Nursing worked hours per patient visit:WHPPV is just the inverse of the calculation we use for provider pts/hr
Total worked hours per patient visit is calculated similarly, but includes all other staff as well as nurse admin FTEs.
© 2020, Crane, Noon
1400 pts/wk700 doc hrs/wk = 2
pts/hrPts/
hr
Whp
pv 1000 RN hrs/wk600 pts/wk = 1.67
whppvinve
rse
EDBA WHPPV – All Sites
*This data set does not include admin FTE
© 2020, Crane, Noon
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
010203040506070
1.001.20
1.401.60
1.802.00
2.202.40
2.602.80
3.003.20
3.403.60
3.804.00
4.204.40
4.604.80
5.00
Freq
uenc
y
Bin
Nurse, Tech, UC - WHPPV, All (No Admin)
Frequency Cumulative %
Higher prod = ↑ queuingLower prod = ↓ queuing
EDBA WHPPV – All Sites
*This data set does not include admin FTE
© 2020, Crane, Noon
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
010203040506070
1.001.20
1.401.60
1.802.00
2.202.40
2.602.80
3.003.20
3.403.60
3.804.00
4.204.40
4.604.80
5.00
Freq
uenc
y
Bin
Nurse, Tech, UC - WHPPV, All (No Admin)
Frequency Cumulative %
Higher prod = ↑ queuing Lower prod = ↓ queuing
© 2020, Crane, Noon
2. Capacity – Nurse Staffing Ratios
© 2020, Crane, Noon
3. Capacity Alignment – Nurse Staffing Ratios
© 2020, Crane, Noon
2. Capacity – Nurse Staffing Ratios
1. Many nurse staffing paradigms are driven off of bed ratios (4 beds per nurse)
2. Nurse staffing will depend on occupancy
© 2020, Crane, Noon
2. Capacity – Nurse Staffing Ratios
1. Many nurse staffing paradigms are driven off of bed ratios (4 beds per nurse)
2. Nurse staffing will depend on occupancy
© 2020, Crane, Noon
2. Capacity – Nurse Staffing Ratios
1. Many nurse staffing paradigms are driven off of bed ratios (4 beds per nurse)
2. Nurse staffing will depend on occupancy
Caution!!! Every hospital I have ever worked with budgets nurse FTEs based on worked hours per patient visit (nurse budget is based on volume, not occupancy).
© 2020, Crane, Noon
Example - Baseline
4 pts/hr
2 hour LOS
8 beds
2RNs
© 2020, Crane, Noon
Example – 1hr ↑LOS
4 pts/hr
2 hour LOS
8 beds
2RNs
© 2020, Crane, Noon
12
33
50% more RN hours needed with no additional volume!What are examples of things that cause ↑LOS?
Example – The Good News
4 pts/hr
2 hour LOS
8 beds
2RNs
1
4
© 2020, Crane, Noon
© 2020, Crane, Noon
Dynamic Capacity Alignment
Steady state staffing is straightforwardRamp up and ramp down is more difficult
© 2020, Crane, Noon
1 hour 1 hour1 hour 1 hour
3-hour Length Of Stay
MD spends 30 minutes per patient,but when?
Assume all 30
minutes in first hour?
Copyright Jody Crane, MD, MBA, Chuck Noon, PhD 2008
MD Demand – 2 pts/hr
© 2020, Crane, Noon
1 hour 1 hour1 hour 1 hour
3-hour Length Of Stay
MD spends 30 minutes per patient,but when?
10 Minutes in first hour
10 Minutes in second
hour
10 Minutes in third
hour
Copyright Jody Crane, MD, MBA, Chuck Noon, PhD 2008
MD Demand – 2 pts/hr
© 2020, Crane, Noon
1 hour 1 hour1 hour 1 hour
3-hour Length Of Stay
MD spends 30 minutes per patient,but when?
15 Minutes in first hour
6 Minutes in second
hour
9 Minutes in third
hour
50% in first 33% 20% in second 33% 30% in third 33%
Copyright Jody Crane, MD, MBA, Chuck Noon, PhD 2008
MD Demand – 2 pts/hr
© 2020, Crane, Noon
Optimizing the Alignment
© 2020, Crane, Noon
Nursing Demand/Capacity by HOW
© 2020, Crane, Noon
APC Demand/Capacity by HOW
© 2020, Crane, Noon
Physician Demand/Capacity by HOW
© 2020, Crane, Noon
Provider Demand/Capacity by HOW
© 2020, Crane, Noon
Basic Approach to Staffing
1. Define the arrival Demand2. Define and align the server Capacity
(physician, nurse, midlevel, resident, bed productivity)
3. Execute in the Context of your current operational environment
© 2020, Crane, Noon
Geography, Process, and People
© 2020, Crane, Noon
This ED is a lot harder to staff….
© 2020, Crane, Noon
Than this ED….
Turbo Care/Results Waiting
Laboratory
Public EntryIntakeWaiting
Continuous Care
TraumaD Pod
EMS Access
© 2020, Crane, Noon
Arrival Acuity by HOD
© 2020, Crane, Noon
There are Really Only 3 Typesof ED Patients…
SickEasy Complicated
© 2020, Crane, Noon
Optimizing Streams
© 2020, Crane, Noon
Assessment
SickEasy Complicated
Walk-in Arrivals
Ambulance Arrivals
10 pts/hr“Vertical”
Super Track
8 pts/hr“Horizontal”
Main ED
4 pts/hr“Vertical”
Intake/RME
© 2020, Crane, Noon
Low Acuity Arrivals = ESI 4,5
2.5 Vertical 6 Horizontal
© 2020, Crane, Noon
Assessment
SickEasy Complicated
Walk-in Arrivals
Ambulance Arrivals
2.5 pts/hr“Vertical”
Super Track
6 pts/hr“Horizontal”
Main ED© 2020, Crane, Noon
© 2020, Crane, Noon
“Super Track”
Fast Track located in or near triage for the purpose of promptly treating patients who require very low resource utilization
Treatment Room 1
Treatment Room 2
Procedure Chair
Entrance/Exit1 MD/APC1 Nurse1 Tech
Results Waiting
© 2020, Crane, Noon
Doc – 1.5x Nurse – 4x
Intake Arrivals – ESI 4, 5, 33% ESI 3
4 Vertical 4.5 Horizontal
© 2020, Crane, Noon
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
6'-3/8"
13'-3
"
42 43 44 4645
4948
47
23
24
2526
OR 1
Lab - Phlebotomy
50
OR 2OR 3
OR 4
TR 9
TR 8
TR 7
TR 5
TR 6
16 15 14
13
12
10
11
18
19
20
21
22
28
29
31 30 17
27
32
33
39
38
37
36
35
34
41
40Peds WR
Rainbow Room
(Internal Waiting)
Treatment
Intake
Team 1
Team 2
Rad Room
SuperMini
Triage
TrackDischarge
Intake
Treatment
Treatment
Treatment
Results Waiting
3
1
2
4
5
6
7
Intake Systems
© 2020, Crane, Noon
Doc 1.25x Nurse 3x
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
2'-8
7/8
"
6'-5 5/8"
6'-3/8"
13'-3
"
42 43 44 4645
4948
47
23
24
2526
OR 1
Lab - Phlebotomy
50
OR 2OR 3
OR 4
TR 9
TR 8
TR 7
TR 5
TR 6
16 15 14
13
12
10
11
18
19
20
21
22
28
29
31 30 17
27
32
33
39
38
37
36
35
34
41
40Peds WR
Rainbow Room
(Internal Waiting)
Treatment
Intake
Team 1
Team 2
Rad Room
SuperMini
Triage
TrackDischarge
Intake
Treatment
Treatment
Treatment
Results WaitingRN
Tech
RN
2 RN, 1 Doc, 1 APC, 1 tech, 2 Scribes
2 RN
Know Your Staff Needs
© 2020, Crane, Noon
Symptoms:Elevated patient throughput timesHigh left-without-being-seen rateLow patient satisfactionClinician behavior in a stressful environmentLow clinician satisfaction and retention
The four key drivers of patient satisfaction:
Length of stay Quality of the interactions with providers Quality of the explanations Pain management
© 2020, Crane, Noon
A Tale of 2 Cities
© 2020, Crane, Noon
ED #1: 20,000 Visits, 200min LOS
ED #2: 20,000 Visits, 100min LOS
Outline
Academic PrinciplesCase StudyApproach to Staffing Optimization
Define DemandDefine CapacityContextualize
Case Study Wrap-upConclusions
© 2020, Crane, Noon
Case Study - Future Directions
© 2020, Crane, Noon
Low Acuity Option 2
© 2020, Crane, Noon
Sun Mon Tues Wed Thur Fri Sat Sun Mon Tues Wed Thur Fri Sat Sun Mon Tues Wed Thur Fri Sat7.0 7.0 7.0 7.0 6.0 6.0 7.0 8.0 8.0 8.0 8.0 7.0 7.0 8.0 1.0 1.0 1.0 1.0 1.0 1.0 1.06.0 6.0 6.0 6.0 5.0 5.0 6.0 7.0 7.0 7.0 7.0 6.0 6.0 7.0 1.0 1.0 1.0 1.0 1.0 1.0 1.05.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.04.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.04.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.04.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.05.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 1.0 1.0 1.0 1.0 1.0 1.0 1.05.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 8.0 7.0 7.0 7.0 7.0 7.0 2.0 3.0 2.0 2.0 2.0 2.0 2.06.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 9.0 8.0 8.0 8.0 8.0 8.0 2.0 3.0 2.0 2.0 2.0 2.0 2.06.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 9.0 8.0 8.0 8.0 8.0 8.0 2.0 3.0 2.0 2.0 2.0 2.0 2.06.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 9.0 8.0 8.0 8.0 8.0 8.0 2.0 3.0 2.0 2.0 2.0 2.0 2.06.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 9.0 8.0 8.0 8.0 8.0 8.0 2.0 3.0 2.0 2.0 2.0 2.0 2.08.0 8.0 8.0 8.0 8.0 8.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 1.0 1.0 1.0 1.0 1.0 1.0 1.08.0 8.0 8.0 8.0 8.0 8.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 1.0 1.0 1.0 1.0 1.0 1.0 1.08.0 8.0 8.0 8.0 8.0 8.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 1.0 1.0 1.0 1.0 1.0 1.0 1.08.0 9.0 9.0 8.0 9.0 9.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 1.0 0.0 0.0 1.0 0.0 0.0 1.08.0 9.0 9.0 8.0 9.0 9.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 1.0 0.0 0.0 1.0 0.0 0.0 1.09.0 9.0 9.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 0.0 0.0 0.0 1.0 0.0 0.0 0.09.0 9.0 9.0 8.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 9.0 0.0 0.0 0.0 1.0 0.0 0.0 0.08.0 8.0 8.0 7.0 8.0 8.0 8.0 9.0 9.0 9.0 8.0 9.0 9.0 9.0 1.0 1.0 1.0 1.0 1.0 1.0 1.07.0 7.0 7.0 6.0 7.0 7.0 7.0 8.0 8.0 8.0 7.0 8.0 8.0 8.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
152.0 154.0 154.0 148.0 152.0 152.0 152.0 170.0 175.0 170.0 168.0 168.0 168.0 170.0 18.0 21.0 16.0 20.0 16.0 16.0 18.0
Recommended Profile Change from CurrentCurrent Staffing Profile
1,064.0 1,189.0 125.0
Overall Provider
Assumes PA Prod = Future (2.0 pts/hr)
© 2020, Crane, Noon
Overall Nursing
Sun Mon Tues Wed Thur Fri Sat Sun Mon Tues Wed Thur Fri Sat Sun Mon Tues Wed Thur Fri Sat24.0 24.0 24.0 24.0 24.0 24.0 24.0 22.0 24.0 25.0 24.0 24.0 25.0 25.0 -2.0 0.0 1.0 0.0 0.0 1.0 1.024.0 24.0 24.0 24.0 24.0 24.0 24.0 22.0 22.0 25.0 24.0 24.0 25.0 25.0 -2.0 -2.0 1.0 0.0 0.0 1.0 1.024.0 24.0 24.0 24.0 24.0 24.0 24.0 20.0 20.0 22.0 20.0 20.0 22.0 22.0 -4.0 -4.0 -2.0 -4.0 -4.0 -2.0 -2.022.0 22.0 22.0 22.0 22.0 22.0 22.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 -4.0 -4.0 -4.0 -4.0 -4.0 -4.0 -4.018.0 18.0 18.0 18.0 18.0 18.0 18.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.018.0 18.0 18.0 18.0 18.0 18.0 18.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.018.0 18.0 18.0 18.0 18.0 18.0 18.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.018.0 18.0 18.0 18.0 18.0 18.0 18.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.018.0 18.0 18.0 18.0 18.0 18.0 18.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.018.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 0.0 0.0 0.0 0.0 0.0 0.0 0.018.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 18.0 0.0 0.0 0.0 0.0 0.0 0.0 0.019.0 19.0 19.0 19.0 19.0 19.0 19.0 18.0 20.0 20.0 20.0 20.0 20.0 18.0 -1.0 1.0 1.0 1.0 1.0 1.0 -1.019.0 19.0 19.0 19.0 19.0 19.0 19.0 20.0 24.0 23.0 23.0 23.0 23.0 20.0 1.0 5.0 4.0 4.0 4.0 4.0 1.019.0 19.0 19.0 19.0 19.0 19.0 19.0 20.0 24.0 23.0 23.0 23.0 23.0 20.0 1.0 5.0 4.0 4.0 4.0 4.0 1.019.0 19.0 19.0 19.0 19.0 19.0 19.0 20.0 24.0 23.0 23.0 23.0 23.0 20.0 1.0 5.0 4.0 4.0 4.0 4.0 1.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.024.0 24.0 24.0 24.0 24.0 24.0 24.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 0.0 1.0 0.0 0.0 1.0 1.0 0.025.0 25.0 25.0 25.0 25.0 25.0 25.0 24.0 25.0 24.0 24.0 25.0 25.0 24.0 -1.0 0.0 -1.0 -1.0 0.0 0.0 -1.0
513.0 513.0 513.0 513.0 513.0 513.0 513.0 497.0 522.0 516.0 512.0 521.0 525.0 505.0 -16.0 9.0 3.0 -1.0 8.0 12.0 -8.0
Change from CurrentRecommended ProfileCurrent Staffing Profile
3,591.0 3,598.0 7.0
Assumes Nurse Prod = Current (0.8pts/hr)
SummSched
© 2020, Crane, Noon
© 2020, Crane, Noon
What Are You Sinking About?
© 2020, Crane, Noon
ConclusionsOptimizing staffing in the emergency department requires understanding core flow concepts like queuing theory and the theory of constraintsAn accurate assessment of demand, capacity, and variation is necessary to be successfulA consistent approach to staffing is necessary to achieve consistent resultsPhysician staffing cannot be looked at in isolation and must be contextualized relative to nurse staffing, bed constraints, physical space, skill mix and acuity mix
© 2020, Crane, Noon
Additional Information
© 2020, Crane, Noon
Common Mistakes
Under capacitating low acuityNot having a well-designed segmentation schemeNot having a dedicated front-end processMissing the ramp-upIncorrect skill mixIncorrect assumptions about physician workflow and productivity
© 2019, Crane, Noon
1. Demand – Arrivals vs OccupancyArrival demand defines the demand for healthcare deliveryIs the primary driver for physician, midlevel, and resident staffingIs only part of the equation for nurses as occupancy and boarding must be considered
© 2020, Crane, Noon
Potential Flaws in Staffing Optimization
We are calculating physician productivity based on 1 week’s worth of data which does not account for overnight, peak, or maximum sustainable productivity We are assuming all of the work occurs at the point of the patient arrival – bad ideaWe are not accounting for inter-physician productivity variationWe are only looking at physicians or nurses in isolation
© 2020, Crane, Noon
2. Capacity – Peak Service Rate
Waiting Room Count Start
Waiting Room Count End
Total Patients / Total Physician hours
[Total Arrivals - (WR Count End – WR Count Start)]-------------------------------------------------------------------
Total Provider Hours
© 2020, Crane, Noon
2. Capacity – Peak Service Rate
0 patients 12 patients4 patients per hour btwn11am and 11pm with
double provider coverage
© 2020, Crane, Noon
2. Capacity – Peak Service Rate
36--------
24
[48 pts - (12pts – 0 pts)]-------------------------------------
24 provider hours1.5 pts/hr= =
© 2020, Crane, Noon
2. Capacity – Peak Service Rate
36--------
24
[48 pts - (12pts – 0 pts)]-------------------------------------
24 provider hours1.5 pts/hr= =
This is 60 min / 1.5 pts or 40 min per patient
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
Existing Patients
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
Total Physician Minutes
© 2020, Crane, Noon
Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00
Approach to Staffing by Hour
Patient #1Patient #2Patient #3Patient #4Patient #5Patient #6Sum Doc Hours
20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20
Variables2 arrivals/hr3 hour LOS1.5 pts/hr40 min/pt50%/25%/25%
Total Number of Physicians Needed
# Docs Needed 2 2 2 1 0.5
© 2020, Crane, Noon
MD demand/ capacity mismatch
Missing ramp-up in main EDMaximal utilization for the rest of the day in Main and FTResulting prolonged waiting that doesn’t recover until early AM (if ever)
© 2020, Crane, Noon
Graphical representation of Main ED and FT Doc and Nurse
demand relative to capacity by
hour of day
Nurse and Doc Staffing vs. Patient Demand
© 2020, Crane, Noon
Demand/capacity mismatching –MD/RN
Nurses miss ramp-up and miss throughout the dayDoc perfectly staffedDecreasing RN to MD indicating worsening RN bottleneck
VolumeYearly ED volume 67,246% ambulance arrivals 28%% ED patients are admitted 16%% of total hospital admissions from ED 67%
© 2020, Crane, Noon
Approach to Staffing AdjustmentsFirst, look at low acuity patients and establish number of providers by looking at acuity and volume by hour of week.
Is there sufficient 4,5 volume to sustain one or more APCs?
© 2017, Crane
Approach to Staffing AdjustmentsFirst, look at low acuity patients and establish number of providers by looking at acuity and volume by hour of week.
Is there sufficient 4,5 volume to sustain one or more PAs?If not, look at 4,5, vertical 3’s (25-50% of level 3’s). This should be managed by an MD/APC team.
© 2019, Crane, Noon
Approach to Staffing AdjustmentsFirst, look at low acuity patients and establish number of providers by looking at acuity and volume by hour of week.
Is there sufficient 4,5 volume to sustain one or more PAs?If not, look at 4,5, vertical 3’s (25-50% of level 3’s). This should be managed by an MD/PA team.
Make sure your low acuity area is busy at all times, otherwise, step up your approach to next higher acuity classLook at remaining volume and err on the side of staffing “fat” to handle fluctuations in acuity and volumeAdapt - Once you have demand of providers, then you must fit it into an operational framework – beds, geography, back end flow, nurse staffing, etc.
Schedules Need to Be:Equitable, fairConsistentMaintain work-life balance (don’t have shifts that are all over the map or insane shift durations or total hours)Patient needs-based (as opposed to provider)Able to minimize variation between providers (slow-fast, medium-medium, not slow-slow)
© 2019, Crane, Noon
The Most Common Type
Time Off RequestVacation
Specific DaysNights
Weekends
ComplicatedIf manual, nearly impossibleSchedule posting delays
© 2019, Crane, Noon
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Doctor #1 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off OffDoctor #2 Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7aDoctor #3 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off OffDoctor #4 Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11pDoctor #5 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off OffDoctor #6 Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p
Day of Month
8-hour Template
24/7 single provider coverage = 4.2 FTE at 40 hours per weekTemplate #1 = 32 hours per week = 5.25 Docs
Easy Template Scheduling
© 2020, Crane, Noon
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Doctor #1 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off OffDoctor #2 Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7aDoctor #3 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off OffDoctor #4 Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11pDoctor #5 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off OffDoctor #6 Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p
Day of Month
8-hour Template
• Forward shift progression• Blocks of time off• Can drop 4 days and have 12 days off• One cycle on/off should not = 7 days• Can manage on Google Docs or Dropbox
Easy Template Scheduling
© 2020, Crane, Noon
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Doctor #1 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off OffDoctor #2 Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7aDoctor #3 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off OffDoctor #4 Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11pDoctor #5 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p Off Off Off OffDoctor #6 Off Off Off Off 3p-11p 3p-11p 3p-11p 3p-11p Off Off Off Off 11p-7a 11p-7a 11p-7a 11p-7a Off Off Off Off 7a-3p 7a-3p 7a-3p 7a-3p
Day of Month
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Doctor #1 7a-7p 7a-7p 7a-7p 7a-7p Off Off Off Off 7p-7a 7p-7a 7p-7a 7p-7a Off Off Off Off 7a-7p 7a-7p 7a-7p 7a-7p Off Off Off OffDoctor #2 7p-7a 7p-7a 7p-7a 7p-7a Off Off Off Off 7a-7p 7a-7p 7a-7p 7a-7p Off Off Off Off 7p-7a 7p-7a 7p-7a 7p-7a Off Off Off OffDoctor #3 Off Off Off Off 7a-7p 7a-7p 7a-7p 7a-7p Off Off Off Off 7p-7a 7p-7a 7p-7a 7p-7a Off Off Off Off 7a-7p 7a-7p 7a-7p 7a-7pDoctor #4 11p-7a 11p-7a 11p-7a 11p-7a 7p-7a 7p-7a 7p-7a 7p-7a Off Off Off Off 7a-7p 7a-7p 7a-7p 7a-7p Off Off Off Off 7p-7a 7p-7a 7p-7a 7p-7a
Day of Month
12-hour Template
8-hour Template
24/7 single provider coverage = 4.2 FTE at 40 hours per weekTemplate #1 = 32 hours per week = 5.25 DocsTemplate #2 = 42 hours per week = 4 Docs
Relationship between Schedule and FTE Needs – Choose Your Poison
© 2020, Crane, Noon
It can get Complicated…Don’t be Cheap
Once you move to multiple provider types and/or multiple sites, scheduling gets much more complexMost use scheduling software
Varying, but similar approaches and featuresSome handle multi-site better than othersVarying pricesSwaps and trades vastly superior
© 2020, Crane, Noon
Breakout #1
© 2020, Crane, Noon
Breakout #1 – Questions #1, #2The physicians staff this ED with the following shifts: 7a-4p, 3p-1a, 11p-8a, 3p-11p. The thought is that they would like to have 1 hour shift overlap to clean up their patients and they would like to double-cover the time when the ED is anecdotally the busiest.
Figure 2 represents the average demand and physician staffing by hour of week. 1) Calculate the average physician service rate. 2) Do you think the capacity matches demand? Be prepared to explain your answer.
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Break Out #1, Figure #2
© 2020, Crane, Noon
Breakout #1 – Questions #1, #2The physicians staff this ED with the following shifts: 7a-4p, 3p-1a, 11p-8a, 3p-11p. The thought is that they would like to have 1 hour shift overlap to clean up their patients and they would like to double-cover the time when the ED is anecdotally the busiest.
Figure 2 represents the average demand and physician staffing by hour of week. 1) Calculate the average physician service rate. 2) Do you think the capacity matches demand? Be prepared to explain your answer.
= 64pts/36 doc hrs = 1.8 pts/hr
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Break Out #1, Question #3What is the peak service rate between 11am and 8pm if the ED is full and the waiting room empty at 11am and there are 6 patients in the waiting room at 8pm?
© 2020, Crane, Noon
Break Out #1, Question #3What is the peak service rate between 11am and 8pm if the ED is full and the waiting room empty at 11am and there are 6 patients in the waiting room at 8pm?
(Total arrivals between 11am and 8pm – WR net change census)Total physician hours between 11am and 8pm
36 - 615
= 2 pts/hr
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Basic Approach to Staffing
1. Define the arrival Demand2. Define the server Capacity
(physician, nurse, midlevel, resident, bed productivity)
3. Execute in the Context of your current environment
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Example
4 pts/hr
4 hour LOS
16 beds
4RNs
2
8
2
© 2020, Crane, Noon
Example
4 pts/hr
4 hour LOS
16 beds
4RNs
© 2020, Crane, Noon
Example
4 pts/hr
4 hour LOS
16 beds
4RNs
2
8
2
Same amount of work that 4 nurses
had!
© 2020, Crane, Noon
Break Out #2 – Question #4If physicians can see 2 patients per hour, fill in the missing hourly physician demand if the LOS is 3 hours and the demand is distributed in the following manner: 1/3 over the first hour, 1/3 over the second hour, and 1/3 over the 3rd hour.
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Hour of Arrival 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00Patient Arrivals 1 1 1 2 3 4 4 46am Pt Demand7am Pt Demand8am Pt demand9am Pt1 Demand9am Pt2 Demand10am Pt1 Demand10am Pt2 Demand10am Pt3 Demand11am Pt1 Demand11am Pt2 Demand11am Pt3 Demand11am Pt4 Demand12n Pt1 Demand12n Pt2 Demand12n Pt3 Demand12n Pt4 Demand1pm Pt1 Demand1pm Pt2 Demand1pm Pt3 Demand1pm Pt4 DemandTotal Doc Minutes 0 0 0 0 0 0Total Docs (min/60) 0.0 0.0 0.0 0.0 0.0 0.0Rounded Docs 0.0 0.0 0.0 0.0 0.0 0.0
Break Out #2 – Question #4
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Hour of Arrival 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00Patient Arrivals 1 1 1 2 3 4 4 46am Pt Demand 10 10 107am Pt Demand8am Pt demand9am Pt1 Demand9am Pt2 Demand10am Pt1 Demand10am Pt2 Demand10am Pt3 Demand11am Pt1 Demand11am Pt2 Demand11am Pt3 Demand11am Pt4 Demand12n Pt1 Demand12n Pt2 Demand12n Pt3 Demand12n Pt4 Demand1pm Pt1 Demand1pm Pt2 Demand1pm Pt3 Demand1pm Pt4 DemandTotal Doc Minutes 10 0 0 0 0 0Total Docs (min/60) 0.2 0.0 0.0 0.0 0.0 0.0Rounded Docs 0.0 0.0 0.0 0.0 0.0 0.0
Break Out #2 – Question #4
© 2020, Crane, Noon
Hour of Arrival 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00Patient Arrivals 1 1 1 2 3 4 4 46am Pt Demand 10 10 107am Pt Demand8am Pt demand9am Pt1 Demand9am Pt2 Demand10am Pt1 Demand10am Pt2 Demand10am Pt3 Demand11am Pt1 Demand11am Pt2 Demand11am Pt3 Demand11am Pt4 Demand12n Pt1 Demand12n Pt2 Demand12n Pt3 Demand12n Pt4 Demand1pm Pt1 Demand1pm Pt2 Demand1pm Pt3 Demand1pm Pt4 DemandTotal Doc Minutes 10 0 0 0 0 0Total Docs (min/60) 0.2 0.0 0.0 0.0 0.0 0.0Rounded Docs 0.0 0.0 0.0 0.0 0.0 0.0
Break Out #2 – Question #4
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Hour of Arrival 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00Patient Arrivals 1 1 1 2 3 4 4 46am Pt Demand 10 10 107am Pt Demand 10 10 108am Pt demand9am Pt1 Demand9am Pt2 Demand10am Pt1 Demand10am Pt2 Demand10am Pt3 Demand11am Pt1 Demand11am Pt2 Demand11am Pt3 Demand11am Pt4 Demand12n Pt1 Demand12n Pt2 Demand12n Pt3 Demand12n Pt4 Demand1pm Pt1 Demand1pm Pt2 Demand1pm Pt3 Demand1pm Pt4 DemandTotal Doc Minutes 20 10 0 0 0 0Total Docs (min/60) 0.3 0.2 0.0 0.0 0.0 0.0Rounded Docs 0.0 0.0 0.0 0.0 0.0 0.0
Break Out #2 – Question #4
Pleas
e Fill
in The R
est
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Hour of Arrival 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00Patient Arrivals 1 1 1 2 3 4 4 46am Pt Demand 10 10 107am Pt Demand 10 10 108am Pt demand 10 10 109am Pt1 Demand 10 10 109am Pt2 Demand 10 10 1010am Pt1 Demand 10 10 1010am Pt2 Demand 10 10 1010am Pt3 Demand 10 10 1011am Pt1 Demand 10 10 1011am Pt2 Demand 10 10 1011am Pt3 Demand 10 10 1011am Pt4 Demand 10 10 1012n Pt1 Demand 10 10 1012n Pt2 Demand 10 10 1012n Pt3 Demand 10 10 1012n Pt4 Demand 10 10 101pm Pt1 Demand 10 10 101pm Pt2 Demand 10 10 101pm Pt3 Demand 10 10 101pm Pt4 Demand 10 10 10Total Doc Minutes 30 40 60 90 110 120Total Docs (min/60) 0.5 0.7 1.0 1.5 1.8 2.0Rounded Docs 1.0 1.0 1.0 2.0 2.0 2.0
Break Out #2 – Question #4
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Break Out – Question #55) Please design a shift configuration for the average day based on your calculated need relative to demand:
Make a schedule for this ED using only 12hr shifts, 4-on, 4-off. a) How many doctors would you need? How many hours would they be working per week?
© 2020, Crane, Noon
Break Out – Question #55) Please design a shift configuration for the average day based on your calculated need relative to demand:
Make a schedule for this ED using only 12hr shifts, 4-on, 4-off. a) How many doctors would you need? How many hours would they be working per week? b) If you could only use 8-hour shifts, how many doctors would you need? What are the challenges with only sticking to an 8-hour rotation?
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