1 ED Overcrowding Solutions: Reducing Variation R. Scott Altman, MD, MPH, MBA Managing Consultant, Joint Commission International

2 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

3 Variation in The ER  Demand management (input)  Resource mobilization (throughput)  Discharge planning (output)

4  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  Smoothing theory  Queuing theory  Alternative creation and community education Demand Management

5 Emergency Severity Index (ESI Triage)

6 Demand Management Demand Prediction & Response  Number of historical same-day visits this season  Adjusted for recent trend (eg: multiply by percent occupancy of staffed available beds)  Prepare for the expectation (staff, supplies, capacity)

7 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

8 Admissions October 2000 Source: MA DHCFP

9 Ancillary Service Expansion  Turn around time  From sample/patient received until results available to user  Peak is more important than average  Expectations for average and peak should be mutually agreed upon  Expectations should be based upon clinical need  Tracking will be retrospective unless part of computerized tracking system

10 Ancillary Service Expansion  Triggered responses  Green: meeting average TAT expectations  Yellow: sample exceeds average, but meets peak  Example: ancillary resources shifted  Red: Sample exceeds peak  Example: extra ancillary resources mobilized  Black: more than one sample exceeds peak  Example: ED reviews orders for need; Ancillary service opens backup operation(s)

11 Bed Management  Predict demand by hour of day  Triggered responses  Green: eight hours of beds are currently available  Yellow: drop below historical peak  Example: manual bed count, identify patients for movement  Red: drop below historical average  Example: begin moving patients (discharges / transfers)

12 Bed Management  Black: First bed request w/o identified bed  Examples: 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;

13 Bed Management  Convert “Push” system to “Pull” system  Track by root cause  Delayed admission  Patient waiting more than two hours for bed assignment  Example Response: Turn care responsibility to inpatient medical staff

14 Bed Management  Boarding  Patient still in the ER two hours after bed assignment  Example Responses: turn care responsibility to floor team – financially, physically, or managerially

15 Copyright© 2003 ibex Healthdata Systems, Inc. All rights reserved. Tiered Triggered Response Plan

16 Smoothing Theory Eugene Litvak, Ph.D. Boston University School of Management Program for Management of Variability in Health Care Delivery

17 Demand vs. Capacity

18 Variability Methodology: Litvak E., Long MC. Cost and Quality Under Managed Care: Irreconcilable Differences?, American Journal of Managed Care, 2000; 6:

19 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?

20 The Answer Is… The ED and Elective-Scheduled OR have approximately equal effects on census variability.  Why?  Because of another (hidden) type of variability...

21 Artificial Variability SPC: Special Causes of Variation  Non-random  Non-predictable (driven by unknown individual priorities)  Should not be managed, must be identified and eliminated

22 Litvak E, Long MC, Cooper AB, McManus ML. Emergency Department Diversion: Causes and Solutions. Academic Emergency Medicine, November 2001, 8, No11, pp ED Diversions Study Under DPH Grant

23 ED Diversions Study Under DPH Grant  Between two hospitals  42 days of information  6000 admissions  ED visits  2000 staffing/capacity data points  300,000+ patient movement/status data points

24 Results Root 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.

25 Results Root 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

26 Elective Surgical Requests vs Total Refusals 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 Services ASA Meeting Abstracts; Oct 2002

27 Smoothing Elective Case Load: Benefits and Conditions  Benefits:  Better utilization of resources  Reduced 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

28 Conditions  Smoothing elective case volume requires physicians’ cooperation  Smoothing elective case volume requires administrative leadership  There might be a need for financial incentives

29 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%

30 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%

31 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

32 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.

33 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.”

34 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.

35 Elements of Performance 6.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.

36 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.

37 And Create a Tiered Triggered Response Plan  ED Staffing & Equipping  Ancillary Support Turn Around Times  Laboratory  Radiology  Pharmacy

38 And Create a Tiered Triggered Response Plan  In-Patient Bed Availability  Critical Care  Step-down  General Medical Surgical  Pediatric

39 Thank You