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Computer Driven Triage

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Title: Computer Driven Triage


1
Computer Driven Triage
  • An Evidenced Based Change

Erika Bartee, Julie Chenoweth, Deborah Graves,
Hannelore Hager
2
Emergency Department
Overload
  • In the United States, the Number of ED visits
    increased by 20 from 1995 to 2005 however the
    number of hospitals with an ED has decreased by
    9, which puts an even heavier load onto the
    remaining Emergency Departments (Gilboy Tanabe,
    2008).

3
Problem Defined
  • Overcrowding
  • Patients leave without being seen (LWS) (Chan et
    al., 2005).
  • Delays in treatment (Gilboy et al., 2005).
  • Triage drift (Dong et al., 2005).
  • Patient satisfaction (Dong et al., 2006).
  • Staff satisfaction (Gilboy Tanabe, 2008).

4
Problem Defined
  • Increases hospital liability
  • Loss of revenue (Gilboy Tanabe, 2008).
  • Potential loss of 3,881,506 annually (Falvo,
    Grove, Stachura, Zirkin, 2007)
  • Loss of 1,086 in potential revenue per hour of
    diversion status (McConnell, Richards,
    Daya, Weathers,  Lowe R.A).

5
Research Question
  • What is the efficacy of a computer-assisted
    emergency department triage system compared to
    traditional memory-led triage systems?

6
Patient Outcomes Definition
  • Accuracy and Reliability of triage Scores
  • Patient overall satisfaction.

7
Staff Satisfaction Defined
  • Staff confidence in the computer system
  • Ease of implementation
  • Effect on staff workload

8
Hospital Cost Defined
  • Improved Resource utilization
  • Prevention of lost Funds
  • Decrease in liability
  • Improved budget
  • projection

9
Review of Literature
  • Prospective, observational and retrospective
    studies to fill need for uniform and reliable
    triage method.

10
Benefits of Computerization
  • Predictive validity for rates of admission
    resource utilization (Dong et al 2007 a).
  • Decreased triage drift.

11
Disadvantages
  • Inability to determine acuity in the elderly and
    patients with dementia (Hwang Morrison, 2007).
  • Power outages

12
Patient Outcomes
  • Good interrater reliability
  • Good agreement between two nurses using e-TRIAGE
    (kappagt 0.8 CI95) (Dong et al., 2005).
  • Not affected by differing levels of overcrowding
    (Dong et al., 2005).
  • Exact agreement in 89 of patients (Maningas,
    2006).

13
Patient Outcomes
  • Good interrater reliability
  • Agreement with expert review panel
  • Memory-based fair (0.2lt klt 0.4)
  • e-TRIAGE moderate (0.4lt kappalt 0.6)
  • - (Dong et al., 2005).

14
Patient Outcomes
  • Average ED length of stay (LOS) improved from 163
    min to 126 min (Maningas, 2006).
  • Long wait times was number one reason for leaving
    the ED without being seen (Gilboy Tanabe, 2008).

15
Hospital Cost
  • 40 of those who LWS sought care at another ED
    (Gilboy Tanabe, 2008).
  • Predictive Validity
  • Significant differences in hospital charges
    (plt0.0001) (Maningas et al.,2006).

16
Hospital Cost
  • Predictive validity (cont.)
  • Cost (p0.05).
  • Odds for a specialist consultation and CT scan.
  • ED length of stay (plt0.001)
  • -(Dong et al., 2007).

17
Staff Satisfaction
  • No statistical data

18
Reliability During Peak Hours
  • Not affected by overcrowding (Dong et al., 2006)

19
Current ESI recomendations
  • Standardization of triage across all Emergency
    Departments in the U.S. by using the 5-Level
    Emergency Severity Index (Gilboy et al., 2005).

20
Local Variations
  • 5 hospitals with ED in Greater Tulsa
  • Varying triage systems.
  • Door to Floor
  • Level-3 paper triage
  • Level -4 paper triage
  • Level -5 paper triage
  • Level -5 computer assisted

21
  • Computer-assisted 5-level triage system.
  • Optional manual nurse override.
  • Training program.
  • Experienced triage Nurse.

22
Evaluation
  • Improved patient outcomes
  • Decreased wait times, improved patient acuity
    scores, and improved patient satisfaction.

23
Evaluation
  • Improved cost effectiveness
  • Resource utilization
  • Staff utilization
  • Did the ED budget fall within expected range?

24
Evaluation
  • Improved staff satisfaction with the
    implementation of the computer triage system.
  • Ease of implementation for the staff.
  • Affects on staff workload.
  • Staff satisfaction with the process.

25
Evaluation
  • Formal and informal
  • Quantitative data (Descriptive statistics, cost
    analysis, etc.).
  • Qualitative data (Follow-up calls/survey after
    discharge, suggestions in ED waiting room, etc.).

26
Planned Change
  • Lewins model of linear change.
  • Early and ongoing analysis of the barriers and
    facilitators for change (Yoder-Wise, 2007).

27
Lewins Stages of Change
  • Unfreezing awareness of a problem.
  • Experiencing incorporation of a new idea.
  • Refreezing change is accepted as standard.
  • (Yoder-Wise 2007).

28
Change Evaluation Involves
  • Surveys
  • Structured or Unstructured observation.
  • Analysis of the Implementation.
  • Identification of additional alterations.
  • (Yoder-Wise, 2007).

29
Evaluation of Effectiveness
  • Looks at all the outcomes.
  • Improved patient outcomes.
  • Cost effectiveness.
  • Staff satisfaction.

30
Recommendations for Study
  • Long term patient outcomes.
  • Actual effects on cost.
  • Effects on staff satisfaction.
  • Effects on different sized hospitals.
  • Universal measures of outcomes.

31
New research questions
  • What is the long term effect of using
    computerized triage on employee retention?
  • What is the long term effect of using
    computerized triage on the numbers of patients
    who leave the Emergency Department without being
    seen?

32
References
  • Aronsky, D., Jones, I., Raines, B., Hemphill, R.,
    Mayberry, S. R., Luther, M. A., Sluser, T.
    (2008). An integrated computerized triage system
    in the emergency department. AMIA Annual
    Symposium Proceedings 16-20.
  • Dong, S. L., Bullard, M. J., Meurer, D. P.,
    Colman, I., Blitz, S., Holroyd, B. R. et.al.
    (2005). Emergency triage Comparing a novel
    computer triage program with standard triage.
    Society of Academic Emergency Medicine. 12(6)
    502-507.
  • Dong, S., Bullard, M., Meurer, D., Blitz, S.,
    Ohinmaa, A., Holroyd, B. et.al. (2006).
    Reliability of computerized emergency triage.
    Society of Academic Emergency Medicine. 13(3)
    269-275.
  • Dong, S., Bullard, M., Meurer, D., Blitz, S.,
    Akhmetshin, E., Ohinmaa, A., et.al. (2007a).
    Predictive validity of a computerized emergency
    triage tool. Society of Academic Emergency
    Medicine. 14(1) 16-21.

33
References
  • Dong, S., Bullard, M., Meurer, D., Blitz, S.,
    Holroyd, B. Rowe, B. (2007b). The effect of
    training on nurse agreement using an electronic
    triage system. Canadian Journal of Emergency
    Medicine. 9(4) 260-266.
  • Falvo, T., Grove, L., Stachura, R., Zirkin, W.
    (2007). The financial impact of ambulance
    diversions and patient elopement. Society for
    Academic Emergency Medicine. 14(1) 58-62.
  • Gilboy, N. Tanabe, P. (2008). Who is leaving
    the emergency department without being seen?
    Advanced Emergency Nursing. 30(1) 3-10.
  • Gilboy, N., Tanabe, P., Travers, D. A., Rosenau,
    A. M. Eitel, D. R. (2005, May). Emergency
    Severity Index, Version 4 Implementation
    Handbook. (Publication No. 05-0046-2).
    Rockville, MD Agency for Healthcare Research
    and Quality.

34
References
  • Hwang Morrison. (2007). Models of geriatric
    care, quality improvement, and program
    dissemination. The Geriatric Emergency
    Department. 55(11) JAGS
  • Maningas, P. A., Hime, D. A., Parker, D. E.
    McMurray, T. A. (2006). Computers in emergency
    medicine The soterion rapid triage system
    Evaluation of inter-rater reliability and
    validity. Journal of Emergency Medicine. 30(4)
    461-469.
  • McConnell, J.K, Richards, C., Daya,
    M., Weathers, C.C., Lowe, R.A. (2006).
    Ambulance diversion and lost hospital revenues
    Abstract. Annals of emergency. 48(6) 702-710.
  • Yoder-Wise, P. S. (2007). Leading and managing in
    nursing (4th ed.). St. Louis, MO Mosby Elsevier.

35
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