Emergency Department Directors Academy Phase I Spring 2020 ...€¦ · Emergency Department Directors Academy Phase I Spring 2020 Staffing and Scheduling Methodologies I DESCRIPTION

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

Staffing OptimizationI & II

JodyCrane,MD,[email protected]

This presenter has nothing to disclose

© 2020, Crane, Noon

Outline

Academic PrinciplesCase StudyApproach to Staffing Optimization

Define DemandDefine CapacityContextualize

Case Study Wrap-upConclusions


Outline





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


http://en.wikipedia.org/w/index.php?title=Copenhagen_Telephone_Company&action=edit&redlink=1

Server

Queue(waiting line)Customer

Arrivals

CustomerDepartures

A Simple Queue


Server


Arrivals

CustomerDepartures

A Simple Queue


A Simple Queue

Server


Arrivals

CustomerDepartures

ArrivalRate (l )and Distribution

ServiceRate (µ )and Distribution


A Simple Queue

Server


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 )


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!


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!


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


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



QueueCalc



QueueCalcSimple.xls

Sigma ED Triage – Variation




variation around service times

random arrival process.


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.


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.


Sigma ED Triage – Variation




Will there be waiting, and if so, how much?

variation around service times

random arrival process.


QueueCalc



QueueCalcSimple.xls

As Server Variation Increases…


As Utilization Increases…


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





Case Study: 75,000-visit Peds ED


You’re called into the CEO’s Office!Our ED really stinks!


Peds ED Door to Doc by Month


Peds ED LWOBS by Month


Peds ED LWOBS vs. Peers


You’re called into the CEO’s Office!Our ED really stinks!

YOU better fix this NOW!


What are you going to do?


What Information Do You Need?



PEDs ED Acuity Mix by ESI Level


Peds ED Day of Week Arrivals


Peds ED Hourly Arrivals


Peds ED Seasonal Hourly Arrivals


Peds ED Hourly LWOBS


Peds ED LWOBS vs Door to Doc



Peds ED Low Acuity Arrivals


Peds ED Low Acuity

Prod – 1.5 pts/hrVolume – 3 pts/hr


Peds ED Low Acuity



Peds ED Main ED #1



Peds ED Main ED #1




Outline





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




(physician, nurse, midlevel, resident, bed productivity)

1. Understand your current productivity2. Benchmarking3. Max Productivity (Time Studies)



1. Define the Arrival DemandArrival demand defines the demand for healthcare deliveryIs the primary driver for physician, APC, and resident staffing


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


… 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


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.”



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?


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



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. 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







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


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


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


3.26

2.4

2.6 - 3.1

2.8


For moderate Acuity EDs, 2.5 patients per hour should not be exceeded.


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


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


Higher prod = ↑ queuingLower prod = ↓ queuing

Must take system flow into account!


What’s Possible???


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


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


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


4,000 Clicks

• 43% of time on data entry• 28% on direct care• 12% Results review• 13% Communication• 3% Other


Scribes



Scribes – Outback Style

• Increased productivity 0.32 pts/hr (0.16-0.65)• Provider income increased $105 Aus ($80 US)

per scribed hour


Productivity – Before and After Scribes

17%



EDBA Impact of Scribes


Scribes vs Voice Dictation


2. Nurse Capacity


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


EDBA Nurse Productivity


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



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.


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


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)



EDBA WHPPV – All Sites

*This data set does not include admin FTE


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)


Higher prod = ↑ queuing Lower prod = ↓ queuing


2. Capacity – Nurse Staffing Ratios


3. Capacity Alignment – 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).


Example - Baseline

4 pts/hr

2 hour LOS

8 beds

2RNs


Example – 1hr ↑LOS

4 pts/hr

2 hour LOS

8 beds

2RNs


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



Dynamic Capacity Alignment

Steady state staffing is straightforwardRamp up and ramp down is more difficult


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





10 Minutes in first hour

10 Minutes in second

hour

10 Minutes in third

hour







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%




Optimizing the Alignment


Nursing Demand/Capacity by HOW


APC Demand/Capacity by HOW


Physician Demand/Capacity by HOW


Provider Demand/Capacity by HOW







Geography, Process, and People


This ED is a lot harder to staff….


Than this ED….

Turbo Care/Results Waiting

Laboratory

Public EntryIntakeWaiting

Continuous Care

TraumaD Pod

EMS Access


Arrival Acuity by HOD


There are Really Only 3 Typesof ED Patients…

SickEasy Complicated


Optimizing Streams


Assessment


Walk-in Arrivals

Ambulance Arrivals

10 pts/hr“Vertical”

Super Track

8 pts/hr“Horizontal”

Main ED

4 pts/hr“Vertical”

Intake/RME


Low Acuity Arrivals = ESI 4,5

2.5 Vertical 6 Horizontal


Assessment


Walk-in Arrivals

Ambulance Arrivals

2.5 pts/hr“Vertical”

Super Track

6 pts/hr“Horizontal”

Main ED© 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


Doc – 1.5x Nurse – 4x

Intake Arrivals – ESI 4, 5, 33% ESI 3

4 Vertical 4.5 Horizontal


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


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


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


A Tale of 2 Cities


ED #1: 20,000 Visits, 200min LOS

ED #2: 20,000 Visits, 100min LOS

Outline





Case Study - Future Directions


Low Acuity Option 2


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)


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



What Are You Sinking About?


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


Additional Information


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


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


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


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



0 patients 12 patients4 patients per hour btwn11am and 11pm with

double provider coverage



36--------

24

[48 pts - (12pts – 0 pts)]-------------------------------------

24 provider hours1.5 pts/hr= =



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


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%


Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20



Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20



Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20



Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20



Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20



Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20


Existing Patients


Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20


Total Physician Minutes


Arrivals 2 2 2 2 2Hour 0:00 1:00 2:00 3:00 4:00



20 10 1020 10 1010 20 10 1010 20 10 1010 10 20 10 1010 10 20 10 1080 80 80 40 20


Total Number of Physicians Needed

# Docs Needed 2 2 2 1 0.5


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)


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


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%


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


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.



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)


The Most Common Type

Time Off RequestVacation

Specific DaysNights

Weekends

ComplicatedIf manual, nearly impossibleSchedule posting delays


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



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



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


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


Breakout #1


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.


Break Out #1, Figure #2


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


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?


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



1. Define the arrival Demand2. Define the server Capacity


3. Execute in the Context of your current environment


Example

4 pts/hr

4 hour LOS

16 beds

4RNs

2

8

2


Example

4 pts/hr

4 hour LOS

16 beds

4RNs


Example

4 pts/hr

4 hour LOS

16 beds

4RNs

2

8

2

Same amount of work that 4 nurses

had!


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.


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


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



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



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


Pleas

e Fill

in The R

est


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 – 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?


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?


Documents

Emergency Department Directors Academy Phase I Spring 2020 ...€¦ · Emergency Department Directors Academy Phase I Spring 2020 Staffing and Scheduling Methodologies I DESCRIPTION