Emergency Department Directors Academy Phase I Spring 2020 … · 2020-01-23 · Emergency...

Emergency Department Directors Academy Phase I Spring 2020 Engineering Patient Flow I: Theory, Metrics, and Application DESCRIPTION Your ability to operate an efficient emergency department is paramount to your success and tenure. This becomes one of our greatest management challenges. The speaker will describe methodologies to identify barriers and bottlenecks that compromise efficient patient flow. A discussion of queuing theory, crowding, and essential metrics will help you develop strategies to improve workflow, build effective relationships with ancillary providers, and incorporate structural redesign into the already complicated picture. The manner in which informed participatory decisions can improve operational efficiency and throughput also will be discussed. OBJECTIVES

• Describe queuing theory. • Discuss issues of crowding. • List common ED operation metrics. • Describe the application of metrics to the ED. • Identify ED technologies that can help improve patient flow. • Engineering Patient Flow I: Theory, Metrics, and Application

2/3/2020, 2:00 PM - 3:30 PM FACULTY: Kirk B. Jensen, MD, MBA, FACEP DISCLOSURE: (+) No significant financial relationships to disclose

Emergency Department Directors Academy Phase I Spring 2020 Engineering Patient Flow II: Directing Change DESCRIPTION Once the director has analyzed the patient flow issue, the next step is to make improvements. The director must be able to implement specific changes to remove barriers a�n�d� �a�v�o�i�d� �t�h�e� �c�l�o�g�g�i�n�g� �p�o�i�n�t�s� �o�f� �h�i�s�/�h�e�r� �E�D�.� �S�e�v�e�r�a�l� �s�p�e�c�i�f�i�c� �c�a�s�e� �e�x�a�m�p�l�e�s� �w�i�l�l� �b�e� �p�r�o�v�i�d�e�d� �t�o� �d�e�m�o�n�s�t�r�a�t�e� �e�f�f�e�c�t�i�v�e� �� b�e�s�t� �p�r�a�c�t�i�c�e�s�� t�h�a�t� �c�a�n� �b�e� �u�s�e�d� �t�o� �i�m�p�r�o�v�e� �p�a�t�i�e�n�t� �t�u�r�n�a�r�o�u�n�d� �t�i�m�e� �a�n�d� �p�a�t�i�e�n�t� �a�n�d� OBJECTIVES

• Describe improvement processes and concepts of "benchmarking" and "best practices". • Describe implementation programs to reduce delays, improve patient throughput, and enhance patient

and provider satisfaction, such as rapid triage and bedside registration; documentation methodologies, handwritten chart, templated systems, scribes, dictation, etc.; triage and nursing protocols; expedited laboratory and diagnostic imaging processes; streamlined admission process, and implementation of ED technologies that enhance patient flow.

• Discuss methods to create “buy-in” from administration. • Engineering Patient Flow II: Directing Change

2/3/2020, 3:45 PM - 5:15 PM FACULTY: Kirk B. Jensen, MD, MBA, FACEP DISCLOSURE: (+) No significant financial relationships to disclose

1/8/2020

1

© Kirk B. Jensen. All rights reserved.

Engineering Patient Flow in Your Emergency Department:

I: Theory, Metrics, and ApplicationII: Directing Change

ACEP EDDA Phase IFebruary 2020

Final

Kirk Jensen, MD, MBA, FACEPChief Innovation Officer, EmCare, Inc.

Chief Medical Officer, BestPractices, Inc.IHI Faculty Member

Former Chair-IHI Improving Flow through Acute Care Settings Former Chair-IHI Operational and Clinical Improvement in the Emergency

DepartmentStuder Faculty Member and National Speaker

Urgent Matters Faculty and Advisory Board


Our Goals and Objectives:• A Focus on Emergency Department

patient flow and operations management• Strategies and tactics to optimize your

practice environment • Highlights of selected innovative practices • A clinical department and a hospital that

works for your patients, your healthcare team, and for you…

1

0

1

1/8/2020

2

© Kirk B. Jensen. All rights reserved.2© Kirk B. Jensen. All rights reserved.

2


We…our patients and our team members…deserve Emergency Departments and health care systems

that work…

© Kirk B. Jensen. All rights reserved

2

3

1/8/2020

3

Slide 4© Kirk B. Jensen, MD, MBA, FACEP



We Know We Compete for “Scarce” Resources…

Direct Admits Admissions Inpatients

Discharges

5

4

5

1/8/2020

4


There are Multiple Opportunities for Bottlenecks and Discontinuous Flow

• Door To Triage• Door To Doctor• Door To Bed

Front End

• Data to Decision• Decision to Dispo

Middle • Discharge to Home

• Discharge to Admit

Back End

6


Demographic Drivers: The Baby Boomers are Here…

Demographic growth is driven by the elderly:The 65 and older age cohort will experience a 28% growth in the next decade• One baby-boomer turns 50 every 18 seconds and one baby-

boomer turns 60 every 7 seconds (10,000 a day)

• This will continue for the next 18 years

In 2016 - This cohort comprised 15% of the total population

A higher proportion of patients in this cohort, in comparison to other age groups, are triaged with an emergent condition

One-quarter of Medicare beneficiaries have five or more chronic conditions, sees an average of 13 physicians per year, and fills 50 prescriptions per year…

7

6

7

1/8/2020

5


88

8© Kirk B. Jensen. All rights reserved.


TJC and Hospital-Wide Patient Flow

2005 -TJC and the Hospital-Wide Patient Flow Committee:

JCR Leadership Standard LD.3.10.10

• The leaders develop and implement plans to identify and mitigate impediments to efficient patient flow throughout the hospital.

• Effective for all accredited hospitals on January 1, 2005

2013 - The Joint Commission says “Boarding in the ED requires a hospital-wide solution.”*

*As reported in ACEP NEWS– January 14, 2013

• Performance standards put into effect Jan 1, 2013 require hospital leaders – namely the chief executive officer, medical staff and other senior hospital managers – to set specific goals to:– Improve patient flow– Ensure availability of patient beds– Maintain proper throughput in labs, ORs,

inpatient units, telemetry, radiology and post-anesthesia care units

9

“We want to make sure that organizations are looking at patient flow hospital‐wide, even if the manifestation of a flow problem seems to be in the emergency room.”

~ Lynne Bergero, The Joint Commission

8

9

1/8/2020

6

© Kirk B. Jensen. All rights reserved.10


© Kirk B. Jensen. All rights reserved. 11

10

11

1/8/2020

7

© Kirk B. Jensen. All rights reserved.© Kirk B. Jensen. All rights reserved 12

© Kirk B. Jensen. All rights reserved.rk B. Jensen. All rights reserved

13

12

13

1/8/2020

8


Optimizing Patient Intakeand Throughput… 14© Kirk B. Jensen. All rights reserved.


The ED Is An Example Of A Production System.

15

14

15

1/8/2020

9


Demand & Capacity Planning and Management

• Demand is the number of

requests for a service, task, skill

or machine.

• Capacity is the maximum level

of value-added activity that a

process can achieve under

normal operating conditions

over a period of time.

16


The Capacity of the ED is

Largely a Function of its

Processes, Staffing Levels,

Physical Space and

Equipment Capacity…


17

16

17

1/8/2020

10


We want to be fast at fast things and slow at slow

things…and wise enough to know the difference…

18


We Can’t Store Service Capacity…

19© Kirk B. Jensen. All rights reserved

18

19

1/8/2020

11


Maximizing the Effectiveness of Our Critical Servers:

20

*Doctors/APPs *Nurses *Beds© Kirk B. Jensen. All rights reserved.

© Kirk B. Jensen. All rights reserved. 21© Kirk B. Jensen. All rights reserved

20

21

1/8/2020

12


Understanding Overall Demand & Leveraging Streaming of Our Incoming Patient Flows:

Patient Segmentation, Streaming and Patient Flow…

22


Patient Arrivals Can Be Broken Down By Stream, Or Segment…

Arrivals can be analyzed by: Acuity, or Presenting complaint (e.g.

chest pain) Diagnoses (e.g. asthma) , Resource needs, Healthcare resource grouping

(product family), Or any other split (e.g.

pediatrics), depending on need.

23

22

23

1/8/2020

13


Capacity Planning: Leveraging Streaming (or

Patient Segmentation)

• In manufacturing terms, streamscan be thought of as production ‘cells’: areas of a factory where similar processes are undertaken in a dedicated fashion.

• One should understand overall demand for each stream by HOD, DOW, and by season….

24


Triage

Brief RN Assessment:ESI Evaluation / Evaluation of Acuity

High AcuityPathway

ESI Levels 1 + 2

Moderate AcuityPathway

Most ESI Level 3s

Low AcuityPathway

ESI Levels 5, 4,+ some 3s

Segmenting Our Incoming Patient Flows and Matching Our Service Delivery Tracks & Capacity to Our Incoming Patient Streams –

Segmentation, Streaming, & Split Flow…

25

24

25

1/8/2020

14


Patient Flow Models

ARRIVALS

Main ED

Streamlined Care• Vertical 3s/Split‐Flow

Track• Fast Track

• Super Track/Low‐Acuity Track

• Results‐waiting

CRITICAL CAREIncoming Patient Streams/

Patient Segmentation

ESI 1s, ESI 2s

ESI 3s

ESI 4s, ESI 5s

Physician Intake/Clinician‐in‐Triage

��

��

� ��

26


Breaking Down Service or

Patient Care Demand into Streams

• You need to decide how you are going to organize your ED in terms of incoming streams.

• In order to maintain optimal flow these areas should ideally run independently of each other.

• Streams should work separately, and they therefore need to be staffed separately.

27

26

27

1/8/2020

15


Leveraging the ED’s Points of Entry –Optimizing the Value and Impact of Triage and the

Front End of our EDs

A Step-Wise Approach to Segmenting and “Fast-Tracking” our incoming patient streams:

1. Efficiently and Effectively Fast-Tracking our Low-Acuity Patients: ESI 5s and 4s

2. Mid-Acuity Management - ESI Level 3 Fast Tracking

3. A Plan and Process for our High-Acuity Patients

28


29

© 2017 Kirk B. Jensen, All Rights Reserved

Patient Acuity: Higher acuity patients require additional staffing resources for evaluation, management, treatment and disposition…

Patient Length of Stay (LOS): Longer patient LOSs require more staffing time and attention…Although not necessarily more clinical staff…

Service Line Considerations:

Make sure the low acuity service line (ESI 5s,4s, and select 3s) is adequately resourced (space, staff, supplies) and busy at all times

Staffing for your ESI 2s, 3s, and 4s - err on the side of staffing “fat” or “heavy” to handle variations in volume and acuity

Boarded Patients: If you are responsible for “boarded patients” (those awaiting admission to an inpatient unit but who are still located in the ED), then:

Your staffing resources will be reallocated in order to monitor and treat these patients.

Your bed capacity will be reallocated to monitor and treat these patients.

Your ability to meet incoming patient demand is effectively reduced.

© Kirk Jensen, All Rights Reserved

29

28

29

1/8/2020

16


Hardwiring Emergency Department Patient Flow:Process Redesign - We Have a Number of Field-Tested Options Available To

Us…

ED Flow & Operations: Enhanced Triage

Direct Bedding (“Pull ‘til Full”)

Bedside Registration

Advanced Triage Orders/Treatment Protocols

Fast-Tracking Low-Acuity Patients:

Super-Track (ESI 5’s + simple 4’s)

Fast-Track (ESI 5’s, 4’s, and simple 3’s)

“A Fast Track on Steroids”

ESI Level 3 Fast Tracks

Clinician in Triage:

APP Provider in Triage

MD in Triage

Team Triage (Multi-disciplinary assessment and treatment team)

A Results-Waiting Area

Efficiently Managing Admissions and Discharges

30


Front End Patient Flow Service LinesDefinitions and Descriptions

• Fast Track-The role of the Fast Track is to segment and serve those patients that are uncomplicated or relatively easy to treat. (ESI 5’s, 4’s, and simple 3’s)

• Super Track- A “Super” Fast Track located in or near triage for the purpose of promptly treating patients who require very low resource utilization (ESI 5’s + simple 4’s)

• Vertical Flow – ESI Level 3 Fast-Tracking - Establishing a process (or set of processes), people, and a place (or places) to fast track your “vertical 3” patients

• Clinician in Triage/RME/ or “Team Triage”- Front-loading a team of providers utilizing an “Intake Team” mentality for promptly assessing, treating, and either placing or discharging ESI level 3 patients, and perhaps ESI 4s and 5s…

– Midlevel Provider in Triage

– MD in Triage

– Team Triage (Multi-disciplinary assessment and treatment team)

31

30

31

1/8/2020

17


Front-End Patient Flow: A Portfolio of Options

• Advanced Triage Orders/Treatment Protocols

• Fast-Tracking Low-Acuity Patients:

– Super-Track (ESI 5’s + simple 4’s)

– Fast-Track (ESI 5’s, 4’s, and simple 3’s)

• Clinician in Triage:

– Midlevel Provider in Triage

– MD in Triage

– Team Triage (Multi-disciplinary assessment and treatment team)

32

A Black Box Warning: There is a Portfolio of Options available to you to be deployed as patient volume and demand either requires it or can justify it. The front-end flow

tactics(s) are selectively and scientifically implemented at certain hours of the day and days of the week based upon your demand-capacity modeling of

incoming patient flow.

The Science of Service Operations:Getting it Right at the Front End

•Measure patient demand (and acuity) by hour of the day and day of the week and design a system to handle it•Commit to the right staffing mix—and the right staff•Make sure your triage processes enhance flow, not form a bottleneck

- Triage is a process and not a place…•Use a simple and reliable system to segment patient flow

- Keep your vertical patients vertical and moving…- Not all patients need beds…

•Match your service delivery options to your incoming patient streams- Remove all work that does not add value…- Fast Track is a verb and not a noun…


3333

32

33

1/8/2020

18


Click to edit Master title style

Demand-Capacity Analysis & Management: Planning for our critical servers – Docs (APPs), Nurses and Beds (Treatment Spaces) …

Getting it right on average…

Managing peak loads…

Leveraging our ED’s Points of Entry - Optimizing the value and impact of Triage and the Front End of our EDs

Segmenting and “Fast-Tracking” our incoming patient streams

Efficiently and Effectively Fast-Tracking our Low-Acuity Patients: ESI 5s and 4s

Mid-Acuity Management - ESI Level 3 Fast Tracking

A Plan and Process for our High-Acuity Patients

Making the most of Teams and Team-Based Care

Addressing flow Into, Through, and Out of our Hospitals…

Patient Flow & Throughput –Key Tactical Leverage Points: A Summary

34


Selected Illustrative Examples -Deploying Our Key Operational

Management Tactics…

34

35

1/8/2020

19


General Operational Strategies for Front-End Patient Flow by Volume Band: An Illustrative Example

No triage, Immediate bedding, bedside registration for all

No Segmentation –Clear signals to identify low acuity patients

A results waiting process and place…

36

• Peak arrivals are just over 3 pts/hr, FT arrivals 1.2-1.5 pts/hr, 10-20 beds

• Providers– Volume too low for 2 docs– FT volume too low for effective segmentation

(Super Track)– MD/APP sharing the entire ED– 4 Main ED Nurses

• Operational approach– Immediate bedding, docs go from high to low

acuity, PA from low to high– No triage– Results waiting area or space

© Kirk B. Jensen & Jody Crane - All rights reserved.

20,000 ED Visits per Year and Below…


SIZE MATTERS: The lower the yearly ED patient volume, the more one should think about the ED as one giant intake team…

For a helpful write-up of this approach applied to a low-volume ED see: Patient Flow Improvements to Boost Efficiency in Small Emergency Departments

ACEP Now, June 19, 2017 by Shari Welch, MD, FACEP

Opportunities in Low‐Volume EDs Include:

Redesigning Patient Intake

Repurposing triage as a rapid treatment unit (RTU) for your low‐acuity service line

Re‐engineering patient flow for high‐flow/low‐flow times of the day

Developing a night plan in conjunction with the hospitalist

37

36

37

1/8/2020

20


General Operational Strategies for Front-End Patient Flow by Volume Band – 40k Per Year:

Quick Look Triage to segment, Quick/Bedside Registration for all

For ERs with low acuity/low admit: Super Track (9a-11p) with 1-2 MLP with committed resources for lab/rad

For ERs with high acuity/high admit: Intake Team (9a-11p) with 1 doc, 1 APP with committed resources for lab/rad

A results waiting process and place…

38

• Peak arrivals 6-7 pts/hr, FT arrivals 2.5-3 pts/hr, 20-40 beds

• Providers

– 3-4 docs for traditional staffing

– If low acuity/low admit ED - FT volume perfect to implement a

Super Track

– If 30,000-40,000 ED - Intake Team strategy may supersede

Super Track due to more effective resource pooling

– 8 Main ED nurses during peak times

• Operational approach

– Quick Look Triage, Quick/Bedside Reg

– Super Track(9a-11p) with Team-based care in the Main ED for

low acuity/low admit ED

– Intake Team (9a-11p) with 1 doc, 1 APP with committed

resources for lab/rad high acuity/high admit ED

– Immediate bedding

– Results waiting © Kirk B. Jensen & Jody Crane - All rights reserved.

40,000 ED Visits per Year


80,000 Visits per Year:

• Peak arrivals just over 12-15 pts/hr, FT arrivals 5-7 pts/hr, 40-80 beds• Providers

– 7-8 providers for traditional staffing– 2 Super Tracks– 1-2 Intake teams with 2-4 providers (mix of MD/PA)– 12-16 Main ED nurses during peak times

• Operational approach– Quick Look Triage, Quick/Bedside Reg– 2 Super Track(7a-1a,9a-1a), 1-2 MD/APP Intake Team(9a-11p,11a-2p,6p-9p)– Immediate bedding for Level 1 & 2 patients, Main ED Teams, Intake/Super

Track for others – Results waiting

39

General Operational Strategies for Front-End Patient Flow by Volume Band:

© Kirk B. Jensen & Jody Crane - All rights reserved.

38

39

1/8/2020

21


Triage is a process, not a place…


40

41

1/8/2020

22


Triage Should Add Value

Does it… Improve Throughput?

Increase Safety?

Improve Quality?

Increase Satisfaction?

Increase Revenue?

Decrease Cost?

If Not…Why Not…Change It…Now!

42


“Name, Rank, and Serial Number…”

Name

Limited chief complaint

Vital signs

Pain score

“Sick or Not Sick”

43

42

43

1/8/2020

23


Get the patient and the Doctor/APP together as quickly and as

efficiently as possible…

43


Quick Bedside

Registration and Direct Pullback…


44

45

1/8/2020

24


Nurse Initiated Order Sets:The use of evidence‐based,

standardized order sets has been shown to improve the timeliness of care and reduce medical errors…



Fast Track is a Verb and Not a Noun …

• Code Blue

• Code STEMI

• Code Stroke

• Code Sepsis

• Code Vascular

• Code…

47

46

47

1/8/2020

25

48

Optimize Bed Capacity and Bed Utilization

Patients should be in a bed only if it is medically necessary

andonly as long as medically necessary…


49

TABLE TURNS - How many times a table in a restaurant is used to serve a new customer


48

49

1/8/2020

26

50

Bed Turns-How Many Patients a Bed Can Serve per Unit of Time



Bed Turns and Results Waiting

• 6 Hour ALOS=4 patients per bed per day

• 4 Hour ALOS=6 patients per bed per day

• A key rate limiting server

• A key component of care

• A key “member” of your team

…Park bench…or MVP?

51

50

51

1/8/2020

27


Optimizing ED Bed Capacity and Utilization

Patients should be in a bed only if it is medically necessary andonly for as long as it is medically necessary…

• Optimizing or maximizing bed capacity and bed turns:

– Does bed capacity match the patient demand for beds?

– Does the patient actually need a bed?

– If a bed is needed, are patients in bed for the shortest amount of time that is medically necessary?

– Are there boarded patients or outpatients in ED Beds?

52


Leveraging Clinical Talent, Time, and Performance

-The clinical talent should be roving intellects engaged in value-added activities at all times

- The role of the clinical staff is to make diagnostic and treatment decisions and to manage the team and patient flow

-Anything else is non-value added activity…

53

– Optimize the MD/APP/RN mix

– Scribes to leverage the MDs

– Patient flow coordinator

– Board huddles/rounds in the ED

– Team assignments/geographic zones

– The right clinical support mix

– Tailor the hours and staff to the facility and to patient flow

53

52

53

1/8/2020

28


Teamwork and Crew Resource Management (CRM)– Training– Team structure and climate– Planning and problem solving– Communication within the team – Managing the workload

• Situational awareness– Team improvement strategies

Teams and Teamwork:Working Together

Teams and Teamwork: It’s About Your People…

The A-Team:• Hire right-Decide in haste

or repent at leisure-it’s your call…

• Try to put your "A” Team on the floor at all times!

55


54

55

1/8/2020

29

Making the Most of Teams and Teamwork…


• Scribes• Effective use of APPs• Clinical Care Teams,

Teamwork Training and Coaching…

• Teams and Patient Assignments…

• Practicing at the Top of Our Licenses…


Innovative And Perhaps Disruptive Approaches To Flow and Operations…


56

57

1/8/2020

30


How about no triage at all….59


58

59

1/8/2020

31



Remote Clinician in Triage from

a Command Center:

Command Center Tele-Triage Results:

One physician serving entire acute care networks

Remotely treating up to 25 patients per hour…

Our average wait time for a triage consult using an in person model is 12‐14 minutes. With the remote triage provider it is 40seconds.

‐ Dr. Ethan Booker, MedStar Director for ED QI

At Aurora Health Care Tele‐triage reduced door‐to‐doctor times by 75%

Staff Productivity Doubles vs. Traditional PIT

62

60

61

1/8/2020

32




63


Remote Triage from a Command Center:

One “Pod” – A single clinician managing up to 140,000 combined visits

Hosp A – 70,000 annual visits

FSED C – 20,000 visits

FSED D – 20,000 visits

Hosp B – 30,000 annual visits

Copyright© 2016 EmOpti, Inc. All Rights Reserved 64

62

63

1/8/2020

33


Leveraging Command Center Medicineto Improve Flow

Urgent Care Facilities

Emergency Departments

Hospitalists Inpatient Care

Exit PointsEntry Points

Remote Clinical Staff

Copyright EmOpti, Inc. All Rights Reserved 65


Command Center Medicine Demand-Capacity Management & Operational Excellence

Carillion Clinic’s Command Center


64

65

1/8/2020

34


Telemedicine may impact timeliness of care through several pathways:

• First and most obvious, telemedicine can provide a rapid response capability in remote and frontier hospitals with no in‐house emergency physician. In these cases, therapy can be ordered by telemedicine providers even before local providers arrive in the hospital.

• Second, telemedicine may provide surge capacity in busy rural EDs when a provider is caring for other competing patients. While many rural facilities do not often have full waiting rooms, local events may quickly overwhelm available resources. For instance, motor vehicle crashes with multiple victims may stretch a provider in a typically low volume hospital to deliver simultaneous care to multiple critically injured patients.

• Telemedicine providers may be able to help risk stratify patients during times of high volume—conducting triage in parallel with the local emergency provider to help allocate limited resources. In many cases, telemedicine providers can be activated based on ambulance reports and can help to organize the care team and prepare equipment to improve the ability for a timely response on patient arrival.

• Provide the availability of scarce specialty and subspecialty services

Emergency Department Telemedicine Shortens Rural Time-to-Provider and Emergency Department Transfer Times

68

© Kirk B. Jensen. All rights reserved.© Kirk B. Jensen. All rights reserved. 67

66

67

1/8/2020

35



Break…


Advanced Flow Concepts

© Kirk B. Jensen. All rights reserved.© Kirk B. Jensen. All rights reserved. 71

68

69

1/8/2020

36


Peter Drucker – Select Observations on Hospitals and Leadership …

“The hospital is altogether the most complex human organization

ever devised.”

" Only three things happen naturally in organizations: friction,

confusion, and underperformance. Everything

else requires leadership."

70


The Science of ED Operations Management as a Route to Operational Excellence…

• Get clear about the key drivers of system performance:– Demand - Capacity management– Queuing – Variation

• Define the high-leverage interventions:– Theory of Constraints

• Deploy a method for improvement: Lean, Six Sigma, TQM…

• Where waiting exists - applying The Psychology of Waiting Lines

73

70

71

1/8/2020

37


Forecasting DemandHow many Friday nights does it take…

How many Monday mornings does it take…How many flu seasons does it take…


74


Patient Flow

is Predictable…

72

73

1/8/2020

38


Patient Flow is Predictable-Classic ED Patient Flow Demand Curves

Emergency Department Admission Times : 1 Hour Increments

0

50

100

150

200

250

300

350

400

[Trend-Star Data : Q-1 FY04 & 05

Number

Of Pts

FY2004 Q-1 154 149 120 81 83 79 99 153 166 269 253 277 235 260 274 268 294 307 332 352 345 299 278 211

FY2005 Q-1 160 119 107 83 71 76 85 106 156 208 226 230 260 243 260 260 304 286 302 333 287 270 260 198

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00

74


Patient Flow (Demand) is Predictable

and

Capacity (Staff, Space, Supplies, and Service…) is

Manageable…*

*i.e. …is a management responsibility

75

74

75

1/8/2020

39


Demand-Capacity and Scientific Management:Arrivals vs. Staffing

Arrivals vs. Staffing - TWTF

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour of Day

# o

f A

rriv

als

0

1

2

3

Average Arrivals Staffing

76

Over-ResourcedUnder-Resourced

Catching-Up

0

1

2

3

4

5

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

OverResourced

UnderResourced

PlayingCatch Up

Demand-Capacity Modeling & Management:

Patient Arrivals (Demand) vs. Staffing (Capacity)


Patient Arrivals

Staffing

76

77

1/8/2020

40



79

Arrival Volume, Acuity and Variation as Key Drivers of Staffing…


78

79

1/8/2020

41


Who's Coming, When Are They Coming,

And What Are They Going To Need… One needs to understand demand (volume and complexity) by hour of the day

(HOD), day of the week (DOW), and by season (if applicable)…

© Kirk B. Jensen. All rights reserved82


Demand-Capacity Management: Modeling and Matching Staffing (Capacity)

to Predicted Patient Arrivals (Demand)

83

80

81

1/8/2020

42


Key Questions:• How many patients are

coming?

• When are they coming?

• What are they going to need?

• Is our service capacity going to match patient demand?

And what are we/you going to do about it if it doesn’t?...


Patient Arrivals: You should know the ED’s patient arrival volumes, acuity, and patterns.

• Patient arrivals and acuity by hour of the day (HOD) and day of the week (DOW).

Knowing the patient arrival curve(s) by HOD and DOW, one can schedule ED staffing to stay ahead of patient arrivals andacuity.

• Identify "heavy” (greater than average) and “light” (less than average) days.

• Although Sundays, Mondays, and the day following a holiday are generally heavier‐volume days, you will want tocompare average volumes and variation from the average for each day of the week.

Review average daily visit volume for each of the most recent 24 months to determine seasonal fluctuations.

Review annual arrivals over the past five years in order to understand trended historic growth and anticipate futuregrowth.

Benchmarking ‐ Establish targets for how many patients per hour the practice can realistically or comfortably see.

Perhaps consider stretch goals for PPH and LOS.


82

83

1/8/2020

43


Demand-Capacity (DCM) Analysis – Key Questions in More Detail…

• With the appropriate use of Demand-Capacity Management (DCM) analytics and tools, the EDoperations team is best equipped to answer the following questions*:

- How many physicians, APPs, and scribes do I need to meet the demand of incoming patients?

- How many nurses do I need to meet the demand of incoming patients?

- How many beds do I need in my department to meet the demand of incoming and boardedpatients?

- Do I have the right staffing levels, staffing mixes, and staffing hours?

- How do scribes & techs optimize physician, APP, and nursing productivity?

- Is there an opportunity to operationalize a Fast Track/Low-Acuity Track or some other Front-End Patient Flow model?

*The suggestions should be based off arrivals, acuity, and productivity by hour of the day (HOD) andday of the week (DOW), and even by season of the year…as well as service times and targetedperformance measures.

86


0

1

2

3

4

5

Demand vs. Capacity Recognizing MismatchesExample – Main ED Area

Modeled Demand Average Demand Capacity

Missed ramp up + understaffing

FINDINGS - The patient arrival and staffing (Demand-Capacity) graph above highlights the following mismatches:

Main – Understaffing - missing the patient arrival ramp-up (begins at 1000) and overstaffing twice later in the day (1400 and 2200)…

Overstaffing

87

84

85

1/8/2020

44


• Volume varies significantly by day of week – 10%+ variation between heavy and light days

• Saturday, Sunday and Monday are heavier days

When matching capacity with demand, varying staffing by day of

week is essential

Demand/Capacity Management:Volume Variation by Day of Week

86


Scientific Management-Planning for Admissions

0

1

2

3

4

5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Nu

mb

er o

f A

dm

issi

on

s

Hour of Day

Forecasting Hospital Admissions from the ED by HOD

Admissions

87

86

87

1/8/2020

45

© Kirk B. Jensen. All rights reserved 90


Demand ‐ Capacity Planning & Management

Analysis of emergency department demand and capacity is the critical first step towards effective workforce planning and process redesign.


88

89

1/8/2020

46


Real-Time Monitoring of Patient Flow


Leveraging Real-Time Operational Dashboards…You wouldn’t drive your car at

high speeds and in the dark without one...

So why do we manage our EDs this way…

91

90

91

1/8/2020

47





92

93

1/8/2020

48


Example chart. Do not use this background.



Kirk B Jensen All rights reserved97

94

95

1/8/2020

49



© Kirk B. Jensen. All rights reserved.97© Kirk B. Jensen. All rights reserved.

96

97

1/8/2020

50


Queuing: A queue is due to the combination of the queue (demand sitting in

the waiting room), patients undergoing assessment or treatment (patients in process), and patients waiting for beds (exit block).

Patients in any of these groups constitute work in progress.

By the time queues have built up they are hard to clear.

Stopping queues building up, making processes more efficient and reducing exit block will all increase effective capacity.


Queuing and Queuing Systems

Queuing Theory - A Definition: The Science of Waiting -The art and science of matching fixed resources to unscheduled demand

A “queuing system” is one where customers arrive at undetermined, but normally distributed, times. Classic examples include call centers, grocery lines, and

emergency departments101© Kirk B. Jensen. All rights reserved.

98

99

1/8/2020

51

© Kirk B. Jensen. All rights reserved. Courtesy: Chuck Noon, PhD, PEMBA UTK 100© Kirk B. Jensen. All rights reserved


A queueing system combines the components of arrival time, service time, and the number of serversallowing one to model (predictive modeling or forecasting…) demand and capacity, as well as characterizing

the impact of natural variation.

Queuing Parameters:

Number of Servers (n)

Average Arrival Rate ()

Average Service Rate ()

Population

Arrive Depart

Queue

Servers

Enter Service

Queuing System

The key servers in the emergency department are beds, clinicians, and nurses

Patient Velocity – the rate at which patients are treated

In healthcare this population boxrepresents all potential patients

BalkRenege

103

100

101

1/8/2020

52


Queuing Systems Have Distinct Characteristics

• In a queuing system, the waiting time for the key server skyrockets as the number of arrivals per hour approaches system/server capacity

• At high levels of utilization small changes can lead to big improvements in service…

• A queue will persist until ongoing capacity is sufficient to deal with both ongoing demand and the backlog.

• When staffing for a queuing system, and accommodating for variation, it is critical to target a utilization of approximately 80% - 85%, on average

104


40

20

0

60

80

140

120

100

160

180

200

5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95%

Utilization

32 minutes80%

82 minutes

Average Minutes

Waiting Time

Notice how a slight increase instaff yields a much greater reduction in waiting time

90%

On the surface, it might seem that health care managers would seek 100% utilization of servers; however,increases in utilization are only achieved by increases in the length of the waiting line and the average waitingtime. This is because as utilization approaches 100% waiting times increase in a highly non-linear fashion.

Graph created by Envisions’s Innovation Group based on concepts in Hellstern, Ronald. “Emergency Department Provider Staffing.” Strauss and Mayer’s Emergency Department Management. McGraw-Hill Education, 2014. 127-132.

103

102

103

1/8/2020

53


40

20

0

60

80

140

120

100

160

180

200

5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95%

Utilization

Average Minutes Waiting

Time

Notice how a slightincrease in staff (capacity)

yields a much greater reduction in waiting time

As utilization approaches 100% waiting times for the server increase in a highly non-linear fashion.

104

• Systems serving unscheduled (uncontrolled) arrivals behave in a characteristic fashion.

• When (patient) inflow and service times are random, their response to increasing utilization is non‐linear.

• As utilization rises above 80‐85%, waits and rejections increase exponentially.

At high levels of utilization small changes can lead to big improvements…

Small changes in server utilization or capacity can lead to big changes

in service and throughput

Queuing Systems Have Distinct Characteristics



104

105

1/8/2020

54


You must plan for and manage variability…(Unless you have unlimited capacity)

Demand Capacity Clinical variability Flow & Process variability Professional variability Staff – hours , mix,

capabilities, speed..

106

Variation Sources of Variation


Variability in a Queuing System An Example:

The Performance of a Telephone Answering System

• A call lasts an average of two minutes.

• Calls are answered by one full time person…

Question: Can the system handle 30 calls an hour without putting people on hold?

107109

106

107

1/8/2020

55


Effect of Variation on QueuesPerformance of a Telephone Answering System

0

2

4

6

8

10

12

14

16

18

20

Ave

rag

e N

um

ber

of

Peo

ple

on

Ho

ld

Variation of Call Length

Calls/hr=29

Calls/hr=28

Calls/hr=25

MediumLow High

Calls/hr=27

Note: -An avg call lasts 2 minutes.-Calls are answered by one person full time.

-Therefore, Avg. service rate = 30 calls/hr

(Util = 97%)

(Util = 83%)

108


Walk‐in (Unscheduled ) Urgent Care: Arrival Rate of 10/hour, Service Rate of 12/hour, and Server Utilization of 83.33%

Maximal server variation

No server variation

109Chuck Noon, PhD UTK PEMBA

108

109

1/8/2020

56


As managers it is important to distinguish between the two different types of variation. Much variation is due tonon-valued added activities and inefficient processes that can be controlled. However, there are other types ofvariation outside of our control that are often overlooked and not well understood. All variation should considered indecision making.

Artificial Controllable Variation – non-random, non-predictable variation which, in many cases, ispreventable. Unlike natural variation, it should not be managed. Rather, it should be identified andeliminated/reduced.

• The human factor: Artificial variation is often affected by human actions, individual preference,and artificial “rules” created by humans

Natural Statistical Variation – statistical variation inherent in any process.It cannot be eliminated or even reduced. Instead, it must be properly managed.

• Three Types of Natural Variability1.Patient Flow (arrival time variation)2.Clinical Presentations (service time variation)

3.Professional Variability (service time variation)

Although natural variation is outside our control, we can manage it using methods that evaluate theimpact of natural variation on key performance metrics such as patient velocity, length of stay, andwaiting time. One such powerful tool is queueing theory.

Litvak, Eugene. “Optimizing Patient Flow by Managing It Variability.” From Front Office to Front Line: Essential Issues forHealth Care Leaders. Ed. Steven Berman IHI, 2005. 91-111.

Patient Driven

110


Max = 12

Average = 6

The role that variationplays in congestion anddelay in the emergency

department is well known,but is typically ignored in

day-to-day planning andscheduling.

The common practice of“staffing to averages” inthe emergency department

often leads to anoverworked staff and

inordinate waiting times forour patients.

Hour of Day

Pat

ien

tArr

iva

ls

Graph created by Envision’s Innovation Group 111

Variation In Our Arrivals…

110

111

1/8/2020

57


…the actual count of arrivals for any given hour or day can vary considerably. This is Patient 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 and PEMBA112


112

113

1/8/2020

58


The Impact of Variation in Our Processes: A Hypothetical…

• Imagine a relatively simple structure where patients arrive and wait to check in, then wait to be seen for diagnostic tests, and then wait for a consultation with the emergency physician. Your records tell you that a new patient arrives on average every 10 minutes, and spends 10 minutes each with intake, diagnostics, and the doctor, so you plan your workflow accordingly.

• Now, if everything runs perfectly and you get one patient arriving every 10 minutes and moving to the next stage of the process at an average pace, it all works out beautifully. By the end of an average day, with every patient exactly 10 minutes after each other, the simulation shows that none of the patients waits more than half an hour at any point, and everyone gets through the system in less than an hour.

• Now let's see what happens when you introduce just a small amount of variability to your averages. The Cardiff mathematicians modeled what happens when 90 percent of patients spend that average 10 minutes at each stage of the process, five percent of patients finish within five minutes, and five percent are still being served after 15 minutes.

• Patients' average time waiting in the system goes from 30 minutes to 119 minutes — half an hour to two hours — and only seven percent of patients are in the system less than an hour.

• “That shows the danger of planning services just incorporating average measures,” said Paul Harper, PhD, a professor of operational research at the Cardiff University School of Mathematics, whose team is using data to forecast demand and build simulation models for emergency departments and emergency medical services in the United Kingdom.

116

© Kirk B. Jensen. All rights reserved. 115© Kirk B. Jensen. All rights reserved.

114

115

1/8/2020

59


The rate determining step is the slowest step of a chemical reaction that determines the speed (rate) at which the overall

reaction proceeds. The rate determining step can be compared to the neck of a funnel.

Rate Determining Step – Chemwiki chemwiki.ucdavis.edu

University of California, Davis Oct 10, 2015



The Rate Determining Step or

the Rate-Limiting Step

=The Narrowest

Funnel in the Series

Khan Academy

116

117

1/8/2020

60



The Theory of Constraints

• By Eliyahu Goldratt• A business novel• Theory of Constraints:

– Constraints limit performance– To improve performance, focus

on improving constraints

Goldratt: A system’s constraints limit its performance or progression toward its goal (throughput/flow)

Two Types of Resources

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

119

118

119

1/8/2020

61


The Theory of Constraints (TOC)

The Theory of Constraints (TOC)

• Patient care is network of queues and service transitions

• An hour lost at a bottleneck is an hour lost for the whole system

• Time saved at a non-bottleneck is a mirage

• Efforts spent improving a non-critical bottleneck will not improve the overall performance of your process or system

120

In highly variable systems (i.e. the ED), the bottlenecks can appear to jump around…


Optimizing a Bottleneck:TOC & The Five Focusing steps:

• Identify the system’s constraint(s)– What limits the productivity of the entire system?– Look for a long queue of work or long processing times

• Decide how to exploit the system’s constraint(s)– Make decisions on how to modify or redesign the task/activity/process so that work can be

performed more effectively• Subordinate everything else to the above decision

– Make implementing step 2 one of your highest priorities• Elevate the system’s constraints

– Add capacity or off-load demand• Warning-If, in the previous step, a constraint has been broken, go back to step 1 but do not allow

inertia to cause a new constraint– Set-up a process of ongoing improvement. A new bottleneck will always be identified. Apply

the above steps to this new bottleneck.

121

120

121

1/8/2020

62


Managing Waits

and

the Psychology of Waiting…


1. Unoccupied Time Feels Longer than Occupied Time.

2. Pre‐Process Waits Feel Longer Than In‐Process Waits.

3. Anxiety Makes Waits Seem Longer.4. Uncertain Waits are Longer than Known, Finite

Waits.5. Unexplained Waits are Longer than Explained

Waits.6. Unfair Waits are Longer than Equitable Waits.7. The More Valuable the Service, the Longer I will

Wait.8. Solo Waits Feel Longer Than Group Waits.

David Maister‐ The Psychology of Waiting

The Psychology of Waiting

123

122

123

1/8/2020

63



Unoccupied time feels longer than occupied time TVs, magazines, health care material Company-Friends and family ROS forms, kiosks, pre-work Frequent “ touches”

Pre-process waits feel longer than in-process waits Immediate bedding No triage AT/AI (Advanced Treatment/ Advanced Initiatives) Team Triage

Anxiety makes waits seem longer Making the Customer Service Dx and Rx Address the obvious - pre-thought out and sincerely deployed

scripts Patient and Leadership Rounding

Uncertain waits are longer than known, finite waits Previews of what to expect Green-Yellow-Red grading and information system Traumas, CPRs-Informed delays Patient and Leadership Rounding

Unexplained waits are longer than explained waits

In-process preview and review

Family and friends

Address the obvious—pre-thought out and sincerely deployed scripts

Patient and Leadership Rounding

Unfair waits are longer than equitable waits

Announce Codes

Fast Track Criteria known and transparent

The more valuable the service, the longer the customer will wait

- The Value Equation

Maximize benefits for the patient and significant others

Eliminate burdens for the patient and significant others

Solo waits feel longer than group waits

Your Visitor Policy-The Deputy Sheriff takes a furlough

125

The Psychology of Waiting:David Maister’s Eight Principles and their ED Service Equivalents

124

125

1/8/2020

64


126

© 2017 Kirk B. Jensen, All Rights Reserved

The Science of ED Service Operations in a Nutshell:

• Get Clear About The Key Drivers Of System Performance:

• Demand - Capacity Management• Queuing • Variation

• Define The High-leverage Interventions:

• Theory of Constraints

• Deploy A Method For Improvement: Lean, Six Sigma, TQM…

• Where Waiting Exists - applying The Psychology of Waiting Lines

128

The Science of Service Operations -Getting it Right at the Front End:

•Measure patient demand (and acuity) by hour of the day and day of the week and design a system to handle it•Commit to the right staffing mix—and the right staff•Make sure your triage processes enhance flow, not form a bottleneck

- Triage is a process and not a place…•Use a simple and reliable system to segment patient flow

- Keep your vertical patients vertical and moving…- Not all patients need beds…

•Match your service delivery options to your incoming patient streams- Remove all work that does not add value…- Fast Track is a verb and not a noun…


126

127

1/8/2020

65



Demand-Capacity Analysis & Management: Planning for our critical servers – Docs (APPs), Nurses and Beds (Treatment Spaces) …

Getting it right on average…

Managing peak loads…

Leveraging our ED’s Points of Entry - Optimizing the value and impact of Triage and the Front End of our EDs

Segmenting and “Fast-Tracking” our incoming patient streams

Efficiently and Effectively Fast-Tracking our Low-Acuity Patients: ESI 5s and 4s

Mid-Acuity Management - ESI Level 3 Fast Tracking

A Plan and Process for our High-Acuity Patients

Making the most of Teams and Team-Based Care

Addressing flow Into, Through, and Out of our Hospitals…

Patient Flow & Throughput –Key Tactical Leverage Points: A Summary

130


“Every system is perfectly designed to get precisely the results it gets.”

Dr. Paul Batalden

129

128

129

1/8/2020

67


You can do this…

132


Take a look at your ED…-What will work for you…

-Get creative…

-Be persistent…

133

132

133

1/8/2020

68


“Leveraging the Science, the Art and the Business

of Emergency Medicine to Achieve Our Aims” –

A clinical department and a hospital that works for your patients, your healthcare team, and for you…

© Kirk B. Jensen. All rights reserved 135


134

135

1/8/2020

69

136

THE BENEFITS OF FLOW TO YOUR BOTTOM LINE

Monetizing Flow © Kirk B. Jensen. All rights reserved.

137

ER Patients Results40,000 ED Visits x 1 Hr Reduction in LOS 40,000 Hours of ED Capacity/

Year40,000 Hours of ED Capacity/2 Hours per ED Visit

20,000 potential new visits/year

20,000 new ED visits x $100/visit in physician revenue ($150-200/visit??)

$2,000,000 new revenue for the group

20,000 new ED visits @ $400/visit for the hospital $8,000,00 new revenue per year for the hospital

New hospital admissions at $3,000 - $7500 per admission

1 more admission per day (365) X $3,000-$7500/ patient admission=$1,095,00-2,737,500/year

*(AHRQ-only 6.2% of admissions through the ED are uninsured)

There is a Compelling Business Case for Flow-A Case Study


136

137

1/8/2020

70


The Business Case for Flow Continued…If you assume an average $150 NCR MD income for every walkaway ($150-200 NCR??)

If you assume an average $500 in hospital income for every walkaway

For a 50,000 visit ED= $75,000 in new MD revenue (no increased overhead) for every 1% reduction in LWBS/LWBTs

A 1% reduction in walkaways = $250,000 in new outpatient hospital revenue

• In 2007, 1.9 million people – representing 2% of all ED visits – left the ED before being seen (LWBS), typically because of long waits

• These walk-outs represent significant lost revenue for hospitals

• A crowded ED limits the ability to accept referrals

© Kirk B. Jensen, MD, MBA, FACEP

138


Service

139

138

139

1/8/2020

71

THE COST – IT ADDS UP

In 2007, 1.9 million people –representing 2% of all ED visits –

left the ED before being seen.

These walk-outs represent

significant lost revenue for

hospitals.

A 2006 study found that each

hour of ambulance

diversion was associated with

$1,086 in foregonehospital

revenues.

A recent study showed that a 1-

hour reduction in ED boarding time

would result in over $9,000 of

additional revenue by

reducing ambulance

diversion and patients who left

without being seen.

1.9 million $1,086$9,000

Source: Ambulance Diversion: Economic and Policy Considerations, 14 July 2006 Robert M. Williams Annals of Emergency Medicine December 2006 (Vol. 48, Issue 6, Pages 711-712) Retrieved from http://www.annemergmed.com/article/S0196-0644(06)00621-4/abstract April 29, 2014.



The Hidden Cost of Implementing an EMR(One point of view…)

• Hospital A treats 100 patients per day• Staffed hours = five 8 hour physician shifts and one 10 hour shift per day• Current throughput =180 minutes on average• Daily coverage cost = $7,500 (each physician salary+ benefits of

$150/hour)• Calculation of increased time =100 pts/day x 5 minutes/pt=500 minutes or

8.33 hours of increased physician work per 24 hour period• Additional EP cost to maintain patient throughput at current level: 8.33

hours x $150/hr = $1250/day or $456,000 annually

141

Courtesy Bryan Vineyardin EM News

140

141

1/8/2020

72


4000 Clicks: A Productivity Analysis of Electronic Medical Records in

a Community Hospital ED. Am J Emerg Med. 2013 Sep 20.

pii: S0735-6757(13)00405-1. doi: 10.1016/j.ajem.2013.06.028.

Hill RG Jr, Sears LM, Melanson SW. Emergency Department,

St Luke's University Health Network, Allentown, PA 18104.

Abstract

OBJECTIVE:

We evaluate physician productivity using electronic medical records in a community hospital

emergency department.

METHODS:

Physician time usage per hour was observed and tabulated in the categories of direct patient contact, data and order entry, interaction with colleagues, and review of test results and old records.

RESULTS:

The mean percentage of time spent on data entry was 43% (95% confidence interval, 39%-47%). The mean percentage of time spent in direct contact with patients was 28%. The pooled weighted average time allocations were 44% on data entry, 28% in direct patient care, 12% reviewing test results and records, 13% in discussion with colleagues, and 3% on other activities. Tabulation was made of the number of mouse clicks necessary for several common emergency department charting functions and for selected patient encounters. Total mouse clicks approach 4000 during a busy 10-hour shift.

CONCLUSION:

Emergency department physicians spend significantly more time entering data into electronic medical records than on any otheractivity, including direct patient care. Improved efficiency in data entry would allow emergency physicians to devote more time to patient care, thus increasing hospital revenue.

© 2013.

142

Average ED MD time allocations: • 44% on data entry • 28% in direct patient care (time with

patients)• 12% reviewing test results and records, • 13% in discussion with colleagues, and• 3% on other activities.

Total mouse clicks approach 4000 during a busy 10-hour shift.



The True Cost of a Complaint:

• The cost to manage the complaint

• The impact of one unhappy customer (client) multiplied out over a year

• The lifetime value of a customer


142

143

1/8/2020

73


The True Cost of a Patient Complaint

Physician time for record review and follow-up with patient 1 hour $ 200

Medical Director time for record review 60 minutes $ 200

Secretary checking ED charge 15 minutes $ 20

ED Manager time 30 minutes $ 60

Administrative time to review (if needed) 30 minutes $ 70

Patient Relations initial complaint, investigation, referral, f/u 2 hours $ 80

Supplies $ 20

Bill adjustments $ 150

--------

TOTAL: $800

144


The Patient Complaint: Quick Facts• Each disappointed patient who complains represents 6 others who are unhappy

about a similar experience– Therefore each complaint represents 7 unhappy patients

• Each unhappy patient tells 8-10 other people about their unhappy experience– Therefore 63 people now know about these unhappy experiences

• ¼ of these 63 people (16) will act on what they hear and will choose not to do business with you

– 16 patients x average revenue/patient x #visits/patient/lifetime = lost revenue per type of complaint

– 16 patients x $500/patient x 5 lifetime visits= $40,000• Just to handle the average complaint costs your institution at least $375.00 per

complaint– (Or $19,500 per year)

• If 5% of inpatients opt not to return each year, the revenue at risk is $2,500,000 per year.

• 95% of customers will be satisfied, surprised and tell others if the problem is resolved on the spot

• 95% of dissatisfied customers never complain• It is 6 times more expensive to attract a new patient than it is to keep an old one

Source-A Dissatisfied Customer? Do the Math by Patricia Weber www.epinc.com

145

144

145

1/8/2020

74


Optimizing Staffing Patterns for Service and Safety

146

Physician $125

Nurse $40 Nurse $40

Tech $15

Nurse $40

Clerk $15

Physician $125

Nurse $40

Tech $15 Tech $15

Nurse $40

Tech $15

Clerk $15Scribe

$15

Traditional Staffing Model = $270/Hr

Contemporary Staffing Model= $280/Hr

Courtesy Rick Bukata, MD

REFERENCES &RESOURCES


146

147

1/8/2020

75


Metric Driven Management:Everybody Wants Data-

Benchmarking Resources

Where to find data:

– Your neighbors

• Call and/or visit

– ED Benchmarking Alliance

• www.edbenchmarking.org

– ACEP

• http://www.acep.org

– Premier

• www.premier.com

– VHA

• www.vha.com

– UHC

• www.uhc.org

Be sure to compare hospitals with similar acuity and similar volume…

© Kirk B. Jensen. All rights reserved. 149© Kirk B. Jensen. All rights reserved. 151

148

149

1/8/2020

76


Flow Resources

KJ150


Sentara Leigh Hospital, a 70,000+ visit Emergency Department in Norfolk, VA, developed and implemented a care delivery model based on lessons learned from a Kaiser Sacramento-based Emergency Department.

William D. Browder MD, FACEP, Ralph Rosignolo, Jr MBA BSN RN CEN NE-BC, Jason Morgan MSN RN CEN, Melissa Escano BS, Mike Marra BS, Sentara Healthcare, Norfolk VA, Jamil Bhitar MD FACEP, Maurice Makrham MD FACEP, UBQ Cooperation, Sacramento CA

153

150

151

1/8/2020

77


References• Arthur, J. Lean Six Sigma DeMYSTIFIED: a Self-Teaching Guide. New York, NY, McGraw Hill: 2006.• Arthur, J. Lean Six Sigma for Hospitals. New York, McGraw-Hill: 2011.• Arthur, J. Lean Six Sigma: Simple Steps to Fast, Affordable, Flawless Healthcare. New York, NY,

McGraw Hill: 2011.• Bandura A. Social Foundations of Thought and Action. Englewood Cliffs, N.J.: Prentice Hall, Inc.

1986.• Bazarian J. J., and S. M. Schneider, et al. “Do Admitted Patients Held in the Emergency Department

Impair Throughput of Treat and Release Patients?” Acad Emerg Med. 1996; 3(12): 1113-1118.• Berry LL, Seltman KD. Management Lessons from the Mayo Clinic: Prescriptions for Success. New

York, NY; McGraw-Hill, 2008.• Berry, LL. Discovering the Soul of Service. New York, NY, Free Press: 1999.• Berry, LL. The Soul of Service. New York, NY; Free Press, 2004.• Berwick D. “A primer on leading the improvement of systems.” BMJ 1996; 312: 619-622.• Berwick DM, Nolan TW. “Physicians as Leaders in Improving Healthcare.” Ann Inter. Med. 1998; 128

(4):289-292.• Bisognano, M, Kenney, C. Pursuing the Triple Aim: Seven Innovators to Show the Way to Better Care,

Better Health, and Lower Costs. San Francisco, CA, John Wiley & Sons: 2012.• Black, J, Miller, D. The Toyota Way to Healthcare Excellence: Increase Efficiency and Improve Quality

with Lean. Chicago, IL, Health Administration Press, 2008.

152


References• Black, J. “Transforming the patient care environment with lean six sigma and realistic evaluation.”

J Health Qual 2009; 31-29-35.• Building the Clockwork ED: Best Practices for Eliminating Bottlenecks and Delays in the ED.

HWorks. An Advisory Board Company. Washington D.C. 2000. • Caldwell, C. et al. Lean-Six Sigma for Healthcare: A Senior Leader Guide to Improving Cost and

Throughput. Milwaukee, WI, Quality Press: 2005.• Chalice, R. Improving Healthcare Using Toyota Lean Production Methods. 2nd ed. Milwaukee, WI:

ASQ Quality Press, 2007.• Christensen, C, J Grossman, and J Hwang. The Innovator's Prescription: A Disruptive Solution for

Health Care. New York, NY, McGraw-Hill: 2009.• Cottington, S, Forst, S. Lean Healthcare: Get Your Facility into Shape. Marblehead, MA, HCPro:

2010.• Crane, J, Noon, C. The Definitive Guide to ED Operational Improvement. New York, NY, CRC

Press: 2011.• Cutting, D. The Celebrity Experience: Insider Secrets to Delivering Red Carpet Customer Service.

John Wiley and Sons, New York, 2008.• Derlet R, et al. “Expectations of Patients Arriving in an Emergency Department.” Society for

Academic Emergency Medicine Annual Meeting. Chicago, IL, May, 1998.• Dickson, E, et al. “Application of lean manufacturing techniques in the emergency department.” J

Emerg Med 2009; 37:177-82.

153

152

153

1/8/2020

78


References• Dickson, EW, et al. “Use of lean in the emergency department: A case series of 4 hospitals.”

Ann Emerg Med 2009; doi:10.1016/j.annemergmed.2009.03.024• Doing More with Less: Lean Thinking and Patient Safety in Health Care. 2006, Joint

Commission Resources.• Edwards N, Kornacki MJ, Silversin J. “Unhappy Doctors: what are the causes and what can

be done?” BMJ 2002; 324: 835-38• Fisher, Ury, Patton. Getting to Yes, 2nd Ed. New York, NY; Penguin, 1991.• Fitzsimmons J., and M. Fitzsimmons. Service Management: Operations, Strategy,

Information Technology. 5th ed. Boston: McGraw-Hill, 2006.• Forster, AJ, et al. “The Effect of Hospital Occupancy on Emergency Department Length of

Stay and Patient Disposition.” Acad Emerg Med 2003; 10: 127-133• Forster, Alan, et al. "The Effect of Hospital Occupancy on Emergency Department Length of

Stay and Patient Disposition." Academy of Emergency Medicine 10.2 (2003): 127-133.• Full Capacity Protocol. www.viccellio.com/overcrowding.htm• Galliour F; “Healthcare Transformation Parts I, II, III;” Health Leaders News; February 2003• Gawande, Atul. The Checklist Manifesto-How to Get Things Right. New York, NY,

Metropolitan Books: 2009.• Giuliani, Rudolph. Leadership. New York, New York: Hyperion, 2002.• Goldratt, E. The Goal. Great Barrington, MA: North River Press, 1986.

154


References• Graban, M. Lean Hospitals: Improving Quality, Patient Safety, and Employee Satisfaction.

New York, NY, Productivity Press: 2009.• Hadfield, D, et al. Lean Healthcare-Implementing 5s in Lean or Six Sigma Projects.

Chelsea, MI, MCS Media: 2006.• Heifetz. R. Leadership Without Easy Answers. Cambridge, MA; Harvard University Press,

1994.• Holland, L., L. Smith, et al. “Reducing Laboratory Turnaround Time Outliers Can Reduce

Emergency Department Patient Length of Stay.” Am J Clin Pathol 2005; 125 (5): 672-674.• Holland, L., L. Smith, et al. 2005. “Reducing Laboratory Turnaround Time Outliers Can

Reduce Emergency Department Patient Length of Stay.” Am J Clin Pathol 125 (5): 672-674.• Hollingsworth J, et al. “How do Physicians and Nurses Spend Their Time in the Emergency

Department?” Ann Emerg Med 1998(1):97-91.• Husk, G., and D. Waxman. “Using Data from Hospital Information Systems to Improve

Emergency Department Care.” SAEM 2004; 11(11): 1237-1244.• Institute for Healthcare Improvement (IHI). Optimizing Patient Flow: Moving Patients

Smoothly Through Acute Care Settings. Innovation Series 2003. • Jensen, Kirk and Thom Mayer. Hardwiring Flow: Systems and Processes for Seamless

Patient Care. Gulf Breeze, FL, Fire Starter Publishing: 2009. • Jensen, Kirk, and Daniel Kirkpatrick. The Hospital Executive's Guide to Emergency

Department Management. Marblehead, MA, HCPro: 2010.

155

154

155

1/8/2020

79


References• Jensen, Kirk, and Jody Crane. "Improving patient flow in the emergency department." Healthcare

Financial Management Nov. 2008: I-IV. • Jensen, Kirk, Thom Mayer, Shari Welch, and Carol Haraden. Leadership for Smooth Patient Flow.

Chicago, IL, Health Administration Press: 2007. • Jensen, Kirk. “Expert Consult: Interview with Kirk Jensen.” ED Overcrowding Solutions Premier

Issue. Overcrowdingsolutions.com. 2011.• Kaplan, RS, Porter, M. “The Big Idea: How to Solve the Cost Crisis in Healthcare.” Harvard

Business Review, 2011, Sept 1.• Kelley, M.A. “The Hospitalist: A New Medical Specialty.” Ann Intern Med. 1999; 130:373-375.• Kotler P., Roberto E. Social Marketing: Strategies for Changing Public Behavior. New York, NY:

Free Press, 1989.• Kotter, J. What Leaders Really Do. Harvard Business Review; 1947; 1999.• Krafci, JF. “Triumph of the Lean Production System.” Sloan Management Review 1988; 30: 41-45.• Langley J, Moen R, Nolan K, Nolan T, Norman C, Provost L. The Improvement Guide. 2nd Edition.

San Francisco: Jossey-Bass: 2009.• Lee, Thomas. Chaos and Organization in Health Care. Cambridge, MA, MIT Press: 2009.• Liu, SW, et al. “A Pilot Study Examining Undesirable Events Among Emergency Department -

Boarded Patients Awaiting Inpatient Beds.” Annals of Emergency Medicine, Vol 54, No 3 September 2009 p 381.

156


References• MacLean SL, Fong M, Desy P, et al:”2001 ENA National Benchmark Guide: Emergency

Departments” Emergency Nurses Association: 2002.• Manos et al. “Inter-observer agreement using the Canadian Emergency Department Triage and

Acuity Scale.” CJEM; 2002:16-22.• Mayer T, Jensen K. “Flow and return on investment in healthcare.” 2008, Int J Six Sigma and

Comp Adv, 4: 192-195.• Mayer, Thom, and Jensen Kirk. "The Business Case for Patient Flow." Healthcare Executive

July-Aug. 2012: 50-53. • Mayer, Thom, and Robert Cates. Leadership for Great Customer Service: Satisfied Patients,

Satisfied Employees. Chicago, IL: Health Administration Press: 2004.• Mayer, Thom. Applying the Principles of Lean Management to Healthcare. PowerPoint

Presentation, BestPractices, Inc. 2011.• Meade, Christine, Julie Kennedy, and Jay Kaplan. "The Effects of Emergency Department Staff

Rounding on Patient Safety and Satisfaction." JEM 2010; 38.5: 666-674.• Optimizing Patient Flow: Moving Patients Smoothly Through Acute Care Settings. IHI

Innovation Series white paper. Boston: Institute for Healthcare Improvement; 2003. (Available on www.IHI.org).

• Peters, T. Re-imagine! Business Excellence in a Disruptive Age. London, DK Ltd.,2003. • Peters, T. Talent: Develop it, Sell it, Be it. London: Dorling Kindersley Limited, 2005.

157

156

157

1/8/2020

80


References• Prochaska J., Norcross J., Diclemente C. “In Search of How People Change.” American Psychologist, September,

1992.

• Reinertsen J, Pugh M, Bisognano M. Seven Leadership Leverage Points; Innovation Series 2005 whitepaper, www.ihi.org

• Richardson, DB. “The Access Block Effect: Relationship between Delay to Reaching an Inpatient Bed and Inpatient Length of Stay.” Med J Australia 2002; 177:492.

• Rogers, E. Diffusion of Innovations. New York: The Free Press, 1995. Addressing the human side of change

• Savary, L, Crawford-Mason, C. The Nun and the Bureaucrat: How They Found an Unlikely cure for America’s Sick Hospitals. Washington, DC, CC-M Productions: 2006.

• Schull et al. “Emergency Department Contributors to Ambulance Diversion: a Quantitative Analysis.” Annals of Emergency Medicine 41:4 April 2003; 467-476.

• Serrano, L, Slunecka, FW. “Lean processes improve patient care.” Healthcare Executive 2006; 21: 36-38.

• Shook, J. Managing to Lean: Using the A3 management process to solve problems, gain agreement, mentor and lead. Cambridge, MA, Lean Enterprise Institute: 2008.

• Silversin J, Kornaki MJ. “Leading Physicians Through Change: How to Achieve and Sustain Results.” American College of Physician Executives, 2000.

• Sirkin, H., Keenan P., & Jackson A. The Hard Side of Change Management, Harvard Business Review, October 2005.

• Smith, A. et al. Going Lean, Busting Barriers to Patient Flow. Chicago, IL, Health Administration Press: 2008.

• Spear, S. “Learning to Lead at Toyota.” Harvard Business Review, 2004; 82:78-86.

158


References

• Spear, S. Chasing the Rabbit: How Market Leaders Outdistance the Competition and How Great Companies Can Catch Up and Win. New York, NY, McGraw Hill: 2009.

• Studer, Q. Results that Last. Hoboken, NJ, John Wiley & Sons: 2008.

• Thompson, et al. “How Accurate are Waiting Time Perceptions of Patient in the Emergency Department?” Ann Emerg Med, 1996(12).

• Toussaint, J, Gerard, R. On the Mend. Cambridge, MA, Lean Enterprise Institute: 2011.

• Tufte, E., The Visual Display of Quantitative Information, (Cheshire, CT:Graphics Press,1983)

• Wears, RL. “Patient Satisfaction and the Curse of Kelvin.” Annual Emergency Medicine 2005: 46; 11-12.

• Wilson, M., and Nguyen, K. Bursting at the Seams: Improving Patient Flow to Help America’s Emergency Departments. Urgent Matters White Paper. September, 2004.

• Womack, J, Jones, D. Lean Thinking: Banish Waste and Create Wealth in Your Corporation. New York, NY, Simon & Schuster: 1996.

• Worster A, Gilboy N, Fernandes CM, Eitel D, Eva K, Geisler R, Tanabe P. Assessment of inter-observer reliability of two five -level triage and acuity randomized controlled trial. Can J Emerg Med 2004;6(4):240-5.

159

158

159

1/8/2020

81


References:The Psychology of Waiting

• Fitzsimmons J., and M. Fitzsimmons. Service Management: Operations, Strategy, Information Technology. 5th ed. Boston: McGraw-Hill. 2006.

• Maister, D. The Psychology of Waiting Lines. In J. A. Czepiel, M. R. Solomon & C. F. Surprenant (Eds.), The Service encounter: managing employee/customer interaction in service businesses. Lexington, MA: D. C. Heath and Co, Lexington Books. 1985.

• Norman, D. A. “Designing waits that work.” MIT Sloan Management Review 2009; 50.4:23-28.

• Norman, D. A. The Psychology of Waiting Lines. PDF version is an excerpt from a draft chapter entitled "Sociable Design" for a new book-www.jnd.org/dn.mss/the_psychology_of_waiting_lines. 2008.

• Meade, Christine, Julie Kennedy, and Jay Kaplan. "The Effects of Emergency Department Staff Rounding on Patient Safety and Satisfaction." JEM 2010; 38.5: 666-674.



Improving Patient Flow In the Emergency Department

160

161

1/8/2020

82


Strauss and Mayer's Emergency Department Management

• Robert W. Strauss MD, Thom A. Mayer, MD, Senior Editors

• Kirk B Jensen, MD, MBA, FACEP, Associate Editor

ISBN-13: 9780071762397 Publisher: McGraw-Hill Professional PublishingPublication date: 12/20/2013


The Patient Flow Advantage: How Hardwiring Hospital-Wide Flow Drives Competitive Performance

Kirk Jensen/Thom Mayer FireStarter Publishing, January 2015

The Patient Flow Advantage: How Hardwiring Hospital-Wide Flow Drives Competitive Performance

Foreword Introduction

Section 1 — Framing the Flow MandateChapter 1: Why Flow Matters Chapter 2: Defining Flow: Establishing the Foundations Chapter 3: Strategies and Tools to Hardwire Hospital-Wide Flow Chapter 4: Lessons from Other Industries

Section 2 — Advanced Flow ConceptsChapter 5: Emergency Department Solutions to Flow: Fundamental PrinciplesChapter 6: Advanced Emergency Department Solutions to FlowChapter 7: Hospital Systems to Improve FlowChapter 8: Hospital Medicine and Flow Chapter 9: Real-Time Demand and Capacity Management

Section 3 — Frontiers of FlowChapter 10: Hardwiring Flow in Critical CareChapter 11: Smoothing Surgical FlowChapter 12: Acute Care Surgery and FlowChapter 13: Integrating Anesthesia Services into the Flow Equation Chapter 14: The Role of Imaging Services in Expediting FlowChapter 15: The Future of Flow

ReferencesAbout the AuthorsAcknowledgments Additional ResourcesAdditional Reading by Authors

163

162

163

1/8/2020

83


Emergency Department Leadership and Management

Best Principles and PracticeEditors:

• Stephanie Kayden, Brigham and Women’s Hospital, Harvard Medical School, Boston

• Philip D. Anderson, Brigham and Women’s Hospital, Harvard Medical School, Boston

• Robert Freitas, Brigham and Women’s Hospital, Harvard Medical School, Boston

• Elke Platz, Brigham and Women’s Hospital, Harvard Medical School, Boston

Publication planned for: November 2014 format: Hardback

164

Table of Contents

Foreword Gautam G. BodiwalaPart I. Leadership Principles:

1. Leadership in emergency medicine Robert L. Freitas2. Identifying and resolving conflict in the workplace Robert E. Suter and Jennifer R. Johnson3. Leading change: an overview of three dominant strategies of change Andrew Schenkel4. Building the leadership team Peter Cameron5. Establishing the emergency department's role within the hospital Thomas Fleischmann6. Strategies for clinical team building: the importance of teams in medicine Matthew M. RicePart II. Management Principles:

7. Quality assurance in the emergency department Philip D. Anderson and J. Lawrence Mottley8. Emergency department policies and procedures Kirsten Boyd9. A framework for optimal emergency department risk management and patient safety Carrie Tibbles and Jock

Hoffman10. Emergency department staff development Thomas Fleischmann11. Costs in emergency departments Matthias Brachmann12. Human resource management Mary Leupold13. Project management Lee A. Wallis, Leana S. Wen and Sebastian N. Walker14. How higher patient, employee and physician satisfaction lead to better outcomes of care Christina Dempsey,

Deirdre Mylod and Richard B. Siegrist, Jr15. The leader's toolbox: things they didn't teach in nursing or medical school Robert L. FreitasPart III. Operational Principles:

16. Assessing your needs Manuel Hernandez17. Emergency department design Michael P. Pietrzak and James Lennon18. Informatics in the emergency department Steven Horng, John D. Halamka and Larry A. Nathanson19. Triage systems Shelley Calder and Elke Platz20. Staffing models Kirk Jensen, Dan Kirkpatrick and Thom Mayer21. Emergency department practice guidelines and clinical pathways Jonathan A. Edlow22. Observation units Christopher W. Baugh and J. Stephen Bohan23. Optimizing patient flow through the emergency department Kirk Jensen and Jody Crane24. Emergency department overcrowding Venkataraman Anantharaman and Puneet Seth25. Practice management models in emergency medicine Robert E. Suter and Chet Schrader26. Emergency nursing Shelley Calder and Kirsten BoydPart IV. Special Topics:

27. Disaster operations management David Callaway28. Working with the media Peter Brown29. Special teams in the emergency department David Smith and Nadeem Qureshi30. Interacting with prehospital systems Scott B. Murray31. Emergency medicine in basic medical education Julie Welch and Cherri Hobgood32. Emergency department outreach Meaghan Cussen33. Planning for diversity Tasnim KhanIndex.


Hardwiring FlowSystems and Processes for Seamless Patient Care

Thom Mayer, MD, FACEP, FAAP Kirk Jensen, MD, MBA, FACEP

Why patient flow helps organizations maximize the “Three Es”: Efficiency, Effectiveness, and Execution

How to implement a proven methodology for improving patient flow

Why it’s important to engage physicians in the flow process (and how to do so)

How to apply the principles of better patient flow to emergency departments, inpatient experiences, and surgical processes

164

165

1/8/2020

84

Patient Flow: Reducing Delay in Healthcare Delivery , Second Edition:

1. Modeling Patient Flows Through the Healthcare System,RANDOLPH HALL, DAVID BELSON, PAVAN MURALI AND MAGED DESSOUKY

2. Hospital-wide System Patient Flow-ALEXANDER KOLKER3. Hospitals And Clinical Facilities, Processes And Design For Patient Flow

MICHAEL WILLIAMS4. Emergency Department Crowding-KIRK JENSEN5. Patient Outcomes Due to Emergency Department Delays- MEGHAN MCHUGH6. Access to Surgery and Medical Consequences of delays BORIS SOBOLEV,

ADRIAN LEVY AND LISA KURAMOTO 7. Breakthrough Demand-Capacity Management Strategies to Improve Hospital

Flow, Safety, and Satisfaction-LINDA KOSNIK8. Managing Patient Appointments in Primary Care-SERGEI SAVIN9. Waiting Lists for Surgery-EMILIO CERDÁ, LAURA DE PABLOS, MARIA V.

RODRÍGUEZ-URÍA 10. Triage and Prioritization for Non-Emergency Services-KATHERINE HARDING 11. Personnel Staffing and Scheduling-MICHAEL WARNER12. Discrete-Event Simulation Of Health Care Systems

SHELDON H. JACOBSON, SHANE N. HALL AND JAMES R. SWISHER13. Using Simulation to Improve Healthcare: Case Study-BORIS SOBOLEV14. Information Technology Design to Support Patient Flow

KIM UNERTL, STUART WEINBERG15. Forecasting Demand for Regional Healthcare-PETER CONGDON16. Queueing Analysis in Healthcare -LINDA GREEN17. Rapid Distribution of Medical Supplies - MAGED DESSOUKY, FERNANDO

ORDÓÑEZ, HONGZHONG JIA, AND ZHIHONG SHEN18. Using a Diagnostic to Focus Hospital Flow Improvement Strategies

ROGER RESAR19. Improving Patient Satisfaction Through Improved Flow- KIRK JENSEN20. Continuum of Care Program- MARK LINDSAY21. A Logistics Approach for Hospital Process Improvement-JAN VISSERS22. Managing a Patient Flow Improvement Project-DAVID BELSON

Patient Flow: Reducing Delay in Healthcare Delivery, Second Edition Randolph Hall, PhD EditorSpringer, January 2014



The Hospital Executive’s Guide to Emergency Department ManagementSecond edition HcPro April 2014

Kirk B. Jensen, MD, FACEPDaniel G. Kirkpatrick, MHA, FACHE

Table of Contents:Chapter 1: A Design for Operational Excellence Chapter 2: Leadership Chapter 3: Affordable Care Act Impact—What Healthcare

Reform Means for the ED Chapter 4: The Impact of Specialized Groups and

Populations on the EDChapter 5: Fielding Your Best Team Chapter 6: Improving Patient Flow Chapter 7: Ensuring Patient Satisfaction Chapter 8: Implementing the Plan Chapter 9: Culture and Change Management Chapter 10: Patient Safety and Risk Reduction Chapter 11: The Role and Necessity of the Dashboard Chapter 12: Physician Compensation: Productivity‐Based

Systems Chapter 13: Billing, Coding, and Collections Chapter 14: The Business Case

167

166

167

1/8/2020

85


Leadership for Smooth Patient Flow:Improved Outcomes, Improved Service, Improved Bottom Line

Kirk B. Jensen, MD, FACEP Thom A. Mayer, MD, FACEP, FAAP Shari J. Welch, MD, FACEP Carol Haraden, PhD, FACEP

The heart of the book focuses on the practical information and leadershiptechniques you can use to foster change and remove the barriers to smoothpatient flow.

You will learn how to: Break down departmental silos and build amultidisciplinary patient flow team Use metrics and benchmarking data toevaluate your organization and set goals Create and implement a rewardsystem to initiate and sustain good patient flow behaviors Improve patientflow through the emergency department—the main point of entry into yourorganization The book also explores what healthcare institutions can learnfrom other service organizations including Disney, Ritz-Carlton, and Starbucks.It discusses how to adapt their successful demand management and customerservice techniques to the healthcare environment.

“This book marks a milestone in the ability to explain and explore flow asa central, improvable property of healthcare systems. The authors aremasters of both theory and application, and they speak from realexperiences bravely met.”

Donald M. Berwick, MDPresident and CEO

Institute for Healthcare Improvement (from the foreword)

ACHE + Institute for Healthcare Improvement


Managing Patient Flow in Hospitals: Strategies and Solutions, Second Edition

169

168

169

1/8/2020

86


Real-Time Demand Capacity Management and Hospital-Wide Patient Flow

The Joint Commission Journal on Quality and Patient SafetyMay 2011 Volume 37 Number 5


The Definitive Guide to Emergency Department Operational Improvement

171

170

171

1/8/2020

87


2014 Michael A. Silverman, MD, FACEPChairman of EM at the Virginia Hospital CenterEmergency Medicine Associates Columnist - Emergency Physicians Monthly


The Improvement Guide and Rapid-Cycle Testing

173

Langley GL, Nolan KM, Nolan TW, Norman CL, Provost LP.

The Improvement Guide: A Practical Approach to Enhancing Organizational Performance (2nd edition).

San Francisco: Jossey-Bass Publishers; 2009.

172

173

1/8/2020

88


Leadership for Great Customer Service

Leadership for Great Customer Service: Satisfied Employees, Satisfied Patients

Second Edition 2014

(ACHE Management)

• Thom A. Mayer, MD

• Robert J Cates, MD

174

Emergency Department Directors Academy Phase I Spring 2020 … · 2020-01-23 · Emergency...

Documents

Transcript of Emergency Department Directors Academy Phase I Spring 2020 … · 2020-01-23 · Emergency...