Triage Reliability Impact On Ed Patient Flow

Triage Reliability Impact on ED Pa6ent Flow !

Edward A. Popovich, Ph.D. Dave Eitel, MD

[email protected] [email protected]

Sterling Enterprises International, Inc. © www.SterlingAcademy.com

Presenta6on Topics

•  ESI Triage Overview •  Major Pa6ent Flow Steps in the ED •  Pa6ent / Family Expecta6ons •  Triage – Gatekeeper or Flow Facilitator •  Is Triage reliable? •  Case Study: Triage reliability – Background / approach / results

•  Triage improvement benefits


ESI Triage Overview

•  Emergency Severity Index –  Emergency Department triage tool –  Algorithm to categorize pa6ents by

•  Acuity of pa6ent •  Resource(s) needed to deliver care •  Stra6fica6on from 1 (most urgent) to 5 (least urgent)

–  Developed to yield rapid, reproducible, opera6onally and clinically relevant pa6ent stra6fica6on

•  1998 -‐ original concept developed by emergency physicians Richard Wuerz and Dave Eitel

•  hZp://www.ahrq.gov/research/esi/esifig3-‐1a.htm


Pa6ent Flow Steps in the ED

•  Step 1 -‐ Door to Doctor –  Sign in / registra6on – Wai6ng Room -‐ what does the name tell us about the process?

–  Triage •  Step 2 -‐ Doctor to Decision

–  Pa6ent staying or going home?

•  Step 3 -‐ Decision to Disposi6on –  Discharge home (“treat to street”) –  Admission to main hospital for care


ED Pa6ent Expecta6ons

•  Why do Pa6ents go to an Emergency Department?


“Martha, I am not feeling too well. Maybe we should go over to the ER

and get triaged!!”

ED Pa6ent Expecta6ons (2)

•  When pa6ent arrives at an ED what do they want? –  They want to see a caregiver, usually physician, right away

•  What stands in the way? –  Assessment of pa6ent condi6on and need

–  Others who are “ahead” of them

•  What can go wrong?


Dying Man Robbed in Philadelphia ER

•  December 2, 2009 AP News •  hZp://news.aol.com/ar6cle/dying-‐joaquin-‐rivera-‐robbed-‐in/791569

–  PHILADELPHIA (Dec. 1) -‐-‐ A school counselor suffering an apparent heart aZack died in a Philadelphia emergency room afer wai6ng nearly 80 minutes for help -‐ and a trio of homeless drug addicts nearby stole his watch instead of seeking aid, police said.

–  Joaquin Rivera, 63, died before seeing a triage nurse at Atria Health's Frankford Campus over the weekend, police said.

–  Registered at 10:45 PM, passed out an hour later, pronounced dead at 12:04 AM, video caught watch being stolen


Common Triage Objec6ve

•  Rapid, reproducible, opera6onally and clinically relevant pa6ent stra6fica6on

•  Timely assignment of appropriate resources to provide pa6ent care – One resource that is in demand are BEDS – Ofen those needing liZle if any resources are asked to wait for a Bed as they are needed by others

– “Sacred cow” – each pa6ent needs a bed – Makes sense if you don’t think about it too much


Triage Reliability?

•  What if Triage is not reliable? – Will resources be allocated reliably? – Will pa6ent receive appropriate care?

– Will pa6ent receive 6mely care? •  Is Triage a boZleneck (gatekeeper)?

–  Pa6ent flow issues? •  Is Triage facilita6ng pa6ent throughput?

–  Is Lef Without Being Seen (LWBS) an issue?


Case Study Assessing Triage Reliability

•  Background •  Approach to assessing reliability •  Results •  Conclusions


Case Study Background

•  PinnacleHealth System in Harrisburg, PA in 2008 –  Decided to focus on pa6ent flow in the ED of one of their hospitals

–  Chose Lean Six Sigma Black Belt training to facilitate this project

–  Project facilitated by Ed Popovich with Dave Eitel suppor6ng ED expert as an Emergency Medicine physician

–  PinnacleHealth team consisted of 3 Black Belt candidates with one focused on the Door to Doctor process


Case Study Approach

•  DEFINE Goals – Reduce ED Length of Stay (LOS) – Reduce LWBS

•  MEASURE – Baseline Measures of LOS by ESI Triage Level – Establish Triage reliability


Case Study -‐ Triage Reliability

•  MEASURE -‐ AZribute Agreement Analysis •  ESI Triage is based on an ordinal (ranked) scale of

assessment •  AZribute Agreement Analysis was used to study the

repeatability and reproducibility of triage nurses •  AZribute Agreement Analysis used to assess:

–  Reproducibility -‐ how consistent are different nurses in ra6ng the same cases?

–  Repeatability -‐ over 6me how consistent is the same nurse in ra6ng the same cases?

–  Expert (Standard) Agreement -‐ how consistent are the ra6ngs of each nurse with that of the “expert” rater?


Case Study Steps -‐ Triage Reliability

•  Methodology –  15 Nurses who conduct triage were studied –  1 Nurse was termed the “expert” as she was a trainer for ESI Triage

–  All 15 nurses were provided 30 case studies in order to independently assign ESI Triage ra6ngs to each case.

–  ESI Triage refresher training conducted –  All 15 nurses re-‐rated each of the 30 cases several weeks later


Case Study Trial 1 Results Assessing Triage Case Agreement

•  Triage Agreement -‐ for 15 nurses only Cases 2, 16 and 29 had 100% agreement across all nurses


Case Study Trial 1 Triage Nurse Agreement 95% Confidence Intervals

•  Confidence Intervals for Nurse Agreement


Case Study Trial 1 Assessing Triage Agreement with Expert

•  Expert Ra6ngs vs. Nurse Ra6ngs – 148 incorrect nursing ra6ngs out of 450 possible ra6ngs


Expert Assigned Rating

Incorrect

1

Nursing

2

Assigned

3

Ratings

4

5 1 . 0 0 0 0 2 39 . 2 0 0 3 2 47 . 11 0 4 0 1 13 . 22 5 0 1 0 10 .

Case Study Trial 1 Assessing Individual Triage Nurse Agreement

•  Which nurses differ with experts – Nurse correct and incorrect ra6ngs


Rater Correct(1) Correct(2) Correct(3) Correct(4) Correct(5) Total Correct

Incorrect(1) Incorrect(2) Incorrect(3) Incorrect(4) Incorrect(5) Grand Total

Nurse 1 2 3 5 4 1 15 4 3 2 2 4 30

Nurse 2 4 1 6 4 5 20 2 5 1 2 0 30

Nurse 3 0 2 5 6 3 16 6 4 2 0 2 30

Nurse 4 5 6 7 6 4 28 1 0 0 0 1 30

Nurse 5 2 1 7 5 4 19 4 5 0 1 1 30

Nurse 6 2 2 6 4 4 18 4 4 1 2 1 30

Nurse 7 0 2 7 6 4 19 6 4 0 0 1 30

Nurse 8 4 2 6 4 4 20 2 4 1 2 1 30

Nurse 9 3 4 5 3 4 19 3 2 2 3 1 30

Nurse 10 2 2 6 4 4 18 4 4 1 2 1 30

Nurse 11 6 4 5 6 4 25 0 2 2 0 1 30

Nurse 12 6 2 6 5 3 22 0 4 1 1 2 30

Nurse 13 5 3 7 4 3 22 1 3 0 2 2 30

Nurse 14 5 3 7 5 2 22 1 3 0 1 3 30

Nurse 15 3 4 5 3 4 19 3 2 2 3 1 30

Case Study Trial 2 Afer Training Was Triage training effec6ve?

•  Afer Training the number of cases upon which all nurses ra6ngs agreed increased from 3 to 14 out of a possible 30 cases.


Case Study Trial 2 Afer Training Triage Nurse Agreement Confidence Intervals

•  Afer training nurse ra6ng agreement rose from around 60% -‐ 70% up to 80% -‐ 95%


Case Study Trial 2 Afer Training Assessing Triage Nurse Agreement with Expert

•  Expert vs. Nurses Ra6ngs – Afer training the number of incorrect ra6ngs dropped from 148 to 35 out of 450 possible ra6ngs


Expert Assigned Rating

Incorrect

1

Nursing

2

Assigned

3

Ratings

4

5 1 . 0 0 0 0 2 1 . 3 0 0 3 0 3 . 17 0 4 0 0 3 . 3 5 0 0 0 5 .

Case Study Before and Afer What about Repeatability?

•  If the pre-‐training Trial 1 and afer-‐afer training Trial 2 were both done afer training then the two trials would represent replicates (repeated experiment) under the same condi6on –  In this situa6on repeatability can be studied to determine individual nurse ra6ng consistency over 6me


Case Study Results Assessing Triage Repeatability

•  A two trial study would have demonstrated only 2 cases out of 30 had ra6ng agreement



•  Repeatability agreement for individual nurses from around 40% to 90% -‐ not good


Agreement within Raters Rater Number Inspected Number Matched Rater Score 95% Lower CI 95% Upper CI Nurse 1 30 17 56.67 39.1973 72.6225 Nurse 2 30 20 66.67 48.7801 80.7695 Nurse 3 30 13 43.33 27.3775 60.8027 Nurse 4 30 27 90.00 74.3789 96.5400 Nurse 5 30 20 66.67 48.7801 80.7695 Nurse 6 30 15 50.00 33.1541 66.8459 Nurse 7 30 18 60.00 42.3204 75.4094 Nurse 8 30 21 70.00 52.1242 83.3353 Nurse 9 30 20 66.67 48.7801 80.7695 Nurse 10 30 19 63.33 45.5136 78.1261 Nurse 11 30 27 90.00 74.3789 96.5400 Nurse 12 30 20 66.67 48.7801 80.7695 Nurse 13 30 23 76.67 59.0717 88.2076 Nurse 14 30 19 63.33 45.5136 78.1261 Nurse 15 30 19 63.33 45.5136 78.1261


•  In our example, Repeatability was low. Is this Bad –  Repeatability is expected to be low in this study due to having several nurses with incorrect ra6ngs prior to training

–  Having increased Expert Agreement afer the training also demonstrates that Training was very helpful.

•  In general, if repeatability is low for no apparent reason then nurses with low results are not consistent at ra6ng Triage.

•  For nurses with low repeatability do not use them to conduct Triage un6l improvement is demonstrated!


ESI Triage Improvement

•  Benefit of Triage reliability study: –  Determine which, if any, Triage personnel are consistent with the expert rater

–  Determine which, if any, Triage personnel are inconsistent with Triage ra6ng

–  Determine which case(s) are causing inconsistency in ra6ngs

–  Put an improvement plan in place


Uniqueness of our Approach

•  U6lizes proven techniques that have been shown to improve processes outside of healthcare to processes within healthcare (e.g., Six Sigma)

•  Combines the experience and knowledge of a Triage expert with a process quality expert


Benefits of Approach

•  ESI Triage reliability is improved –  Recall it was created to provide a reliable algorithm to stream pa6ents to the appropriate ED resources to provide care on a 6mely basis

•  Provides a plaporm for enhancing pa6ent flow in the ED and increases awareness of approaches such as Lean Six Sigma

•  Risk of Li6ga6on due to inconsistent prac6ces are reduced


Other ways to reduce Triage Impact?

•  What if each pa6ent saw a provider (e.g., MD) right afer they arrive at the ED? – Would Triage Reliability be as cri6cal?

•  Effec6ve ED Pa6ent Flow Models – Remove “Sacred Cow” of every pa6ent gets a bed

•  MX.com provides healthcare solu6ons •  Banner Health Door to Doctor Toolkit •  qTrack – Dr. Joe Guarisco, Ochsner Medical, New Orleans


Documents

Triage Reliability Impact On Ed Patient Flow