1 ed overcrowding solutions: reducing variation r. scott altman, md, mph, mba managing consultant,...
TRANSCRIPT
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ED Overcrowding Solutions:Reducing Variation
R. Scott Altman, MD, MPH, MBA
Managing Consultant,Joint Commission International
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Overview
Predicting variation Using data to plan ahead
Reducing variation Smoothing and Queuing Theory
Managing variation Who’s in charge Triggered tiered response plan
All in advance New Accreditation standard
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Variation in The ER
Demand management (input) Resource mobilization (throughput) Discharge planning (output)
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Emergency Severity Index (ESI Triage) Wuerz, Eitel, et al. ESI Triage Category is Associated with
Six Month Survival. AEM. 2001; 8:61-4 Manual available at http://www.ena.org/
Smoothing theory Queuing theory Alternative creation and community education
Demand Management
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Emergency Severity Index(ESI Triage)
none one many
vital signs
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2
5 4
3
yes
consider
no
no
yes
patient dying?
shouldn’t wait?
no
how many resources?
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Demand Management
Demand Prediction & Response
Number of historical same-day visits this season
Adjusted for recent trend (eg: multiply by percent occupancyof staffed available beds)
Prepare for the expectation(staff, supplies, capacity)
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Demand Management(continued)
Establish fixed triggers in advance for calling in additional staff.
Too often asking for help is seen as a failure rather than an appropriate management tool.
“ED volume ebbs and flows with consistency”
Mike Williams, President The Abaris Group
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0
500
1000
1500
2000
2500
3000
S M T W T F S S M T W T F S S M T W T F S S M T W T F S S M T
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 31
Date and Day of Week
Nu
mb
er o
f A
dm
iss
ion
s
Emergent
Urgent
Elective
Newborn
Total
AdmissionsOctober 2000
Source: MA DHCFP
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Ancillary Service Expansion Turn around time
From sample/patient received until results available to user
Peak is more important than averageExpectations for average and peak should be
mutually agreed uponExpectations should be based upon clinical needTracking will be retrospective unless part of
computerized tracking system
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Ancillary Service Expansion Triggered responses
Green: meeting average TAT expectationsYellow: sample exceeds average, but meets peak
Example: ancillary resources shiftedRed: Sample exceeds peak
Example: extra ancillary resources mobilizedBlack: more than one sample exceeds peak
Example: ED reviews orders for need; Ancillary service opens backup operation(s)
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Bed Management Predict demand by hour of day Triggered responses
Green: eight hours of beds are currently availableYellow: drop below historical peak
Example: manual bed count, identify patients for movement
Red: drop below historical averageExample: begin moving patients (discharges /
transfers)
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Bed Management
Black: First bed request w/o identified bedExamples: Call in staff & prepare alternative site; contact neighbor hospital for potential direct
admit transfers; inform medical staff that office patients should
be admitted to an alternative site, not sent to the ED;
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Bed ManagementConvert “Push” system to “Pull” systemTrack by root causeDelayed admission
Patient waiting more than two hours for bed assignment
Example Response: Turn care responsibility to inpatient medical staff
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Bed Management
BoardingPatient still in the ER two hours after bed
assignmentExample Responses: turn care
responsibility to floor team – financially, physically, or managerially
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Copyright© 2003 ibex Healthdata Systems, Inc. All rights reserved.
Tiered Triggered Response Plan
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Smoothing Theory
Eugene Litvak, Ph.D.
Boston University School of ManagementProgram for Management of Variability in Health Care Deliveryhttp://management.bu.edu/research/hcmrc/mvp/index.asp
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Time
# of
Pat
ients
Demand vs. Capacity
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Variability Methodology:
Litvak E., Long MC. Cost and Quality Under Managed Care: Irreconcilable Differences?, American Journal of Managed Care, 2000; 6:305-312
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What Makes Hospital Census Variable?
If ED cases are 50% of admissions
and… Elective-scheduled OR cases are 30% of
admissions
then… Which would you expect to be the largest
source of census variability?
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The Answer Is…
The ED and Elective-Scheduled OR have approximately equal effects on census variability.
Why? Because of another (hidden) type of
variability...
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Artificial VariabilitySPC: Special Causes of Variation
Non-random Non-predictable (driven by unknown
individual priorities) Should not be managed, must be identified
and eliminated
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Litvak E, Long MC, Cooper AB, McManus ML. Emergency Department Diversion: Causes and Solutions. Academic Emergency Medicine, November 2001, 8, No11, pp. 1108--1110
ED Diversions Study Under DPH Grant
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ED Diversions Study Under DPH Grant
Between two hospitals42 days of information 6000 admissions 8000+ ED visits 2000 staffing/capacity data points 300,000+ patient movement/status data
points
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ResultsRoot Cause Analysis of ED Crowding and Ambulance Diversion in Mass, BU, 2002:
Correlation between # of ED arrivals (or ED census) and average minutes of diversion is either negative or insignificant.
Correlation between time interval from “time into slot” and “time admitting called” (or time orders received) and diversions is negative.
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ResultsRoot Cause Analysis of ED Crowding and Ambulance Diversion in Mass, BU, 2002:
Correlation between average number of ED patients waiting for hospital beds and average minutes of diversion is high.
When the scheduled demand is significant, there was much stronger correlation between scheduled admissions and diversions than between ED demand and diversions
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Elective Surgical Requests vs Total Refusals
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elective surgical patients seeking ICU admission patients diverted or rejected from the ICU
McManus, M.L., MD, MPH; Long, M.C., MD; Cooper, A; Mandell, J., MD; Litvak, E., Ph.D. Impact of Variability in Surgical Caseload on Access to Intensive Care ServicesASA Meeting Abstracts; Oct 2002
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Smoothing Elective Case Load: Benefits and Conditions
Benefits:Better utilization of resourcesReduced hours of ED diversions Staff and patient satisfaction More staffing resources: better tolerating peak loads Reduced medical errors Reduced length of stay Increased hospital throughput Increased surgical throughput
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Conditions
Smoothing elective case volume requires physicians’ cooperation
Smoothing elective case volume requires administrative leadership
There might be a need for financial incentives
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Capping Admissions: Luther Midelfort Mayo Health System Study
300 Beds community hospital (March-Dec ‘01) Increased patient throughput through better
utilization of hospital capacities (the opportunity that was previously lost) resulted in the increased revenue of about $200,000/month.
Increased percent of patients put into bed within 1 hour from 23% to 40%
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Capping Admissions: Luther Midelfort Mayo Health System Study
Emergency Department diversions have been reduced from 12% to 1-2%
Overall number of open nursing positions decreased from about 10% to 1%
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Conclusions Separation of “scheduled” and “unscheduled”
beds will not affect the overall scheduled surgical case volume, and would allow to reduce diversion hours and to calculate the necessary additional beds to satisfy the demand
Neither ED diversion, nor nursing retention or medical errors problems will be satisfactorily resolved unless artificial flow variability is smoothed
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Proposed New Standard(Domestic US)
LD.3.4 (NEW – as of August 25, 2003)The leaders develop and implement plans
to identify and mitigate impediments to efficient patient flow through hospital processes.
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Elements of Performance
1. Leadership assesses the scope of patient flow issues within the organization, including the ED, the impact of those issues on patient safety, and engages in planning to mitigate that impact.
2. Planning encompasses the delivery of appropriate and adequate care to admitted patients who must be held in temporary bed locations, e.g. PACU and ED areas.No longer includes: “These temporary locations must be outside of the Emergency Department and in an appropriate patient care area.”
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Elements of Performance
3. Planning includes the delivery of adequate care and services to those patients in the ED who are placed in overflow locations, such as hallways.
4. Specific critical performance indicators are identified and measured that enable leadership to monitor the efficiency and safety of support services and patient care and treatment areas that are part of the patient flow processes for ED patients.
5. Performance indicators are reported to leadership on a regular basis and are available to those individuals who are accountable for processes that support patient flow.
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Elements of Performance6. The organization improves those processes identified
by leadership as essential in the efficient movement of patients through the organization.
7. Planning includes collaboration with the Medical Staff to assess and develop processes that support efficient patient flow.
8. Criteria are written and defined for diversion decisions.
9. The organization defines criteria for clarification of negative outcomes as sentinel event classification in ED patient.
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What Should We Do?(Practical Steps)
Identify, classify, and measure types of variability.
Distinguish and eliminate artificial variability.
Separate remaining natural variability into homogeneous sub-groups and optimally manage.
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And Create a Tiered Triggered Response Plan
ED Staffing & Equipping Ancillary Support Turn Around Times
LaboratoryRadiologyPharmacy
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And Create a Tiered Triggered Response Plan
In-Patient Bed AvailabilityCritical CareStep-downGeneral Medical SurgicalPediatric
