myths and barriers to optimizing ed patient flow … · a randomized controlled trial acad emerg...
TRANSCRIPT
MYTHS AND BARRIERS TO OPTIMIZING ED PATIENT
FLOW
PART 2
Joseph Twanmoh, MD, MBA Senior Vice President, MS2
Information Release Date: December 10, 2013 Termination Date: December 10, 2013 Hardware/Software Requirements PC Microsoft Windows 2000 SE or above. Internet Explorer (v5.5 or greater), or Firefox Flash Player Plug-in (9.0 or later) Check your version here. Sound Card & Speakers 800 x 600 Minimum Monitor Resolution (1024 x 768 Recommended) Adobe Acrobat Reader* MAC MAC OS 10.2.8 Safari or Firefox Flash Player Plug-in (9.0 or later) Check your version here. Sound Card & Speakers 800 x 600 Minimum Monitor Resolution (1024 x 768 Recommended) Adobe Acrobat Reader* Internet Explorer is not supported on the Macintosh. * Required to view printable (PDF) version of the lesson.
Information Contact Information The George Washington University Office of Continuing Education in the Health Professions (CEHP) Em: [email protected] Ph: (202) 994-4285 Policy on Privacy & Confidentiality http://www.gwu.edu/privacy-policy Copyright http://www.gwu.edu/copyright
Accreditation Information Accreditation The George Washington University School of Medicine and Health Sciences is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The George Washington University School of Medicine and Health Sciences designates this live internet activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Instructions for Obtaining Credit At the end of this webinar, you will receive an email for completing the online course evaluation. Your certificate of credit will be available immediately after you complete the evaluation.
Disclosure Statement In accordance with the Accreditation Council for Continuing Medical Education's Standards for Commercial Support, The George Washington University Office of Continuing Education in the Health Professions (CEHP) requires that all individuals involved in the development and presentation of CME activity content disclose any relevant financial relationships with commercial interest(s). CEHP identifies and resolves all conflicts of interest prior to an individual’s participation in an educational activity. The following faculty, planners, and staff report that they have no relevant financial relationships with commercial interest(s): Joseph Twanmoh , MD, MBA Jesse Pines, MD (Course Director) Danielle Lazar (Staff) Leticia Hall (Staff)
Commercial Support This activity received no commercial support.
Objectives
• Review the most commonly used strategies to improve ED patient flow.
• Does the evidence support the practice? • Where are they applicable? • Why does it fail?
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 2
Recap Part 1
• Direct to Bed – 1,500 patients/bed
• Bigger ED • Fast Tracks
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 3
Myth vs. Reality?
• Advanced Triage Protocols • Provider Triage • PCOT • Advanced front end flow
model
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 4
Advanced Triage Protocols Survey
• Are you using advanced nursing triage protocols?
• How effective have they been at reducing waiting times and LOS?
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 5
The Role of Triage Nurse Ordering on Mitigating Overcrowding in Emergency Departments: A Systematic Review
Academic Emergency Medicine, Vol.18, Issue 12:1349-57 Dec. 2011
• 14,000 potentially relevant studies • 14 in the systematic review • 37-minute reduction in ED LOS in one
RCT • 51-minute reduction was observed in
non-RCTs
CONCLUSIONS: Overall, TNO appears to be an effective intervention to reduce ED LOS Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 6
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 7
AUTHOR (YEAR) LOCATION SAMPLE STUDY
PERIOD STUDY DESIGN
TRIAGE NURSE INTERVENTION
Bliss 1971 US 100 Unknown Retro cohort Distal limb XR Stiell 1993 Canada 1,180 5 mos. B-A Foot/ankle XR
Lee 1996 Hong Kong 1,633 3 mos. Pro cohort XR
Thurston 1996 UK 1,833 NR RCT XR
Parris 1999 Australia 175 3.25
mos. CCT XR
Ching 1999 Singapore 276 3 mos. C-C Limb/skull XR
Lindley-Jones 2000 UK 675 2 weeks RCT XR Winn 2001 US 40 2 mos. Retro cohort Diagnostic tests Cheung 2002 Canada 250 NR B-A XR/Blood work
Australia 1,806 12 mos. Pro cohort Ext. XR
Fan 2006 Canada 130 3 mos. RCT XR
Pedersen 2009 Denmark 106 NR Pro cohort XR
Rosmulder 2010 Dutch 704 22 days B-A Foot/ankle XR Retezar 2011 US 15,188 2 yrs. Retro C-C Diagnostic tests
An Advanced Triage System Accident and Emergency Nursing, (2002) 10, 10-16
• Centenary Health Center, Toronto, Canada
• 9 Algorithms (6 incl. testing) • 4 hour training sessions • Emergent, Urgent, Non-Urgent
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 8
Results
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 9
Accident and Emergency Nursing, (2002) 10, 10-16
STUDY LIMITATIONS
• 250 random charts one year later • N=43; N=22; • Study period not defined • Hours of operation • Triage methodology not defined • No statistical analysis
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 10
The Effect of Triage Diagnostic Standing Orders on Emergency Department Treatment Time
Annals of Emergency Medicine, Vol. 57 (2) 88:89 Feb. 2011
• Chest Pain – Troponin, INR/PT/PTT
• Shortness of Breath – Troponin, CXR
• Abdominal Pain – UA, Urine Pregnancy, Lipase, Amylase
• Genitourinary – UA, Urine Pregnancy – Did not include OB-Gyn complaints
• Door to Disposition
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 11
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 12
“Patients were more likely to receive triage standing orders when a technician was present at triage (75% versus 49%).”
“Diagnostic testing at triage was associated with a substantial reduction in ED treatment time for 4 common
chief complaints.”
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 13
PARTIAL VS. FULL TSO
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 14
Conclusions: Advanced Triage Nurse Protocols
• Useful for extremity x-rays • May be useful for chest pain, SOB,
and GU complaints under a protocol
• Partial protocol adherence negatively impacts patient flow
• Value for other complaints TBD • Should not be a primary strategy
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 15
Provider Triage Survey
• Are you using provider triage? • What type of providers are you
using? – APP (NP or PA) – Physician – Combination of physician and APP
• What has been the impact on ED throughput and LOS?
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 16
Faculty Triage Shortens Emergency Department Length of Stay,
ACADEMIC EMERGENCY MEDICINE October 2001, Volume 8, Number 10
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 17
Results
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 18
“At our institution, faculty triage appears to improve ED efficiency as demonstrated by a decreased ED length of stay.”
Return on Investment
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 19
Annual Costs
Revenue @
$300/pt.
ROI Revenue @ $400/pt.
ROI
Mondays only $124,800 $89,700 ($35,100) $119,600 ($5,200) Mon-Fri
$624,000 $448,500 ($175,500) $598,000 ($26,000)
7 days/week $873,600 $627,900 ($245,700) $837,200 ($36,400)
Assume: 12 hr./day @ $200/hr. = $2,400/day 5.75 pts. discharged per shift Represents new patient charges
Impact of a Triage Liaison Physician on Emergency Department Overcrowding and Throughput:
A Randomized Controlled Trial ACAD EMERG MED August 2007, Vol. 14, No. 8
• Answer all incoming physician calls • Support and assist triage nurses • Evaluate ambulance patients awaiting ED bed • Initiate clinical patient evaluation and
diagnostic studies • Initiate treatment if appropriate • Deal with administrative issues should they
arise. • Not designed with a goal of ‘‘see and treat”
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 20
University of Alberta Hospital 55,000 adult ED
Results
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 21
“…a TLP reduces LOS and, to a lesser degree, the number of patients LWBS in an overcrowded ED.”
Evaluation of a ‘see and treat’ pilot study introduced to an emergency department,
Accident and Emergency Nursing, Vol. 12 Issue 1, 24-27, Jan 2004
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 22
Results
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 23
CONCLUSION: ‘See and Treat’ reduces waiting times for patients with minor injuries and illnesses and has a positive effect on waiting times for patients elsewhere in the department.
CONCLUSIONS FOR PROVIDER TRIAGE
• Many different models exist • Additional provider staffing can be
cost prohibitive • Patient screening models can lead
to over-ordering of tests
Myths and Barriers to Optimizing ED Patient Flow | Part 1 |
24
PCOT Survey
• Are you using PCOT in your ED? • Which PCOT do you utilize?
– UA, Urine Preg, or Strep screen – Cardiac Enzymes – Chemistries, Lactate, and others – All of the above
• What has been the effect on ED LOS?
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 25
i-STAT Accelerates Door-to-ResultDecision Times in the ED
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 26
https://www.abbottpointofcare.com
Reducing lab TAT outliers improves ED LOS Holland, LL, et al. Am J Clin Pathology 2005;124:672-674
• ED LOS decreased from 4.1 to 3.2 hours as lab outliers decreased from 14.4% to 4.9%
• Outpatient labs only • Lab TAT not defined
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 27
Implementation of a point-of-care satellite laboratory in the emergency department of an academic medical center. Impact on test turnaround time and patient emergency department length of
stay. Lee-Lewandrowski, et. al., Arch Pathol Lab Med. 2003 Apr;127(4):456-60.
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 28
369 patients pre/post pilot study 162 patients (43.9%) admitted
But did it impact LOS?
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 29
“Our data showed a statistically significant change in the ED LOS for patients having
POCT.”
Use of a Comprehensive Metabolic Panel Point-of Care Test to Reduce Length of Stay in the Emergency Department: A
Randomized Controlled Trial Jang, et. Al. Ann. Emer. Med, Feb. 2013
• 54,000 visits, urban academic ED • Randomized, non-blinded study • Piccolo Xpress Chemistry Analyzer • 5154 test/ 5090 control • CBC and coags sent to central lab
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 30
Results
Lab (min.) PCOT (min.)
Difference Percent Reduction
Lab TAT 55 12 (43) 78%
ED LOS 372 350 (22) 6%
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 31
“No statistical difference in LOS for contrast CT studies”
28,000 visit Peds ED 144 test group 111 control
5 month study using i-STAT cartridges
A Randomized Trial to Assess the Efficacy of Point-of Care Testing in Decreasing Length of Stay in a Pediatric Emergency
Department Hsaio, et. al. Pediatric Emerg Care Jul. 2007
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 32
Results
LAB PCOT Difference Percent Reduction
LAB TAT 70 min. 5 min. (65 min.) 93%
ED LOS 224 min. 185.5 min (38.5 min) 17%
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 33
A Multicenter Randomized Controlled Trial Comparing Central Laboratory and Point-of-Care Cardiac Marker Testing
Strategies: The Disposition Impacted by Serial Point of Care Markers in Acute Coronary Syndromes (DISPO-ACS) Trial
Ryan, et. al., Annals of Emer. Med. March 2009
2,000 pt. 4-center randomized trial Used i-STAT troponin Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 34
DISPO-ACS Results
Lab PCOT Change
Lab TAT 52.8 min. 15 min. (37.8 min.)
Admitted 5.50 hr. 5.35 hr. (9 min.)
Discharged 4.62 hr. 4.50 hr. (7.2 min.)
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 35
“Across all sites, point-of-care testing did not decrease time to disposition for admitted or discharged patients”
PCOT Conclusions
• Time savings from lab do not directly translate to LOS.
• Enormously expensive – Assume $3 for lab vs. $19 for PCOT – 10,000 tests= $160,000 difference
• Use wisely and selectively – UA – Urine pregnancy testing – Strep screen – Rapid Influenza, RSV
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 36
What doesn’t work
Costly Physical Capacity Expansion
Dysfunctional Fast Tracks
Inappropriate Immediate Bedding
Wasteful Advanced Triage Protocols
Inefficient Provider “Triage”
Expensive Point of Care Testing*
*Except Urine HCG, UA, or Rapid Strep
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 37
Advanced Front-end Flow
Lean Intake System
Rapid Clinical Evaluation Unit
Dedicated Processing area
Intermediate Care conversion
Transit (Results Waiting) Area
Exit Registration
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 38
Questions?
Joseph Twanmoh, MD, MBA [email protected]
Myths and Barriers to Optimizing ED Patient Flow | Part 1 | 39
www. ms2group.com