A Successful Rapid Response Team Model: Decreasing Cardiac Arrests by Utilizing STAT Nurses and Crew Resource Management Techniques

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1 A Successful Rapid Response Team Model: Decreasing Cardiac Arrests by Utilizing STAT Nurses and Crew Resource Management Techniques Karen R. Cox PhD, RN 1,2, Jean Howell 1, RN, BSN Joseph A. Johnson 1, RN, Justin DeLap 1, BA, MHA, Lori Johnson 1, RRT, MHA, Candy Shaw, RN, BC 1, Leslie W. Hall, 1,2 MD 1 University of Missouri Health Care System 2 University of Missouri Center for Health Care Quality Columbia, Missouri Key Contact [email protected] Background Joint Commission National Patient Safety Goals from 2007 include Rapid Response Team (RRT) implementation. Successful adoption and appropriate use of RRTs has varied 1,2,3,4. In his opening address at the 2007 Institute for Healthcare Improvement National Forum, Don Berwick cited conflicting evidence of RRT success/failure and argued that institutional context is a pivotal factor in predicting RRT success 5. At University of Missouri, we believe two contextual variables influenced our RRT team success. These are availability of a STAT Nurse and the discipline of conducting an after-action debrief with RRT members (Figure 1). Purpose of This Study To describe our unique STAT Nurse program and report results of RRT activations/de-briefs. Methods The STAT Nurse program was originally developed at University of Missouri in 1989 and was internally supported until ,7,8,9. In 2006, the program was redesigned and redeployed. Six critical care trained nurses comprise the STAT Nurse program, with availability of one STAT nurse 24/7 to provide acute care in patient care areas with sudden acuity surges or needs. STAT nurses serve as experienced clinicians who offer short term assistance for other nurses throughout the organization with issues ranging from consultation regarding perplexing clinical issues, assessment of unstable patients, assistance with transport, monitoring during sedation, and assistance with procedures. When the RRT design was being negotiated, it became clear that STAT nurses should have a key role in this process. Periodically, to evaluate effectiveness of the STAT Nurse program, work diaries were kept to record requests in terms of area, care rendered, and duration. To evaluate effectiveness of RRT activations, care details and the outcomes of debriefs were recorded. A summary of each activation and post-debrief improvement ideas were deliberated at monthly oversight meetings. Rates of adult code blues per discharges were monitored monthly. Results Assistance from STAT nurses was most often requested by the adult ICU s (36%) and med/surg areas (26%; Figure 2). While overall ER trauma and moderate sedation volume was low (Figure 3), these averaged longer than one hour (Figure 4). Nearly one in five requests (593/3,325) could not be met due to competing requests (but RRT activation was highest STAT nurse priority). Between January 2007 and June 2008 the RRT was activated an average of 2.2 times/week with 80

2 average response time of 2.2 minutes. Of 172 activations, 85% had debriefs with 32% identifying correctable issues. Sixty-four percent of RRT patients moved to higher level of care with 88% discharged alive. The facility s overall adult code blue rate in the 18 months postactivation of the RRT was reduced 34% from pre-rrt levels (Figure 4). Conclusions and Implications A consistent response by STAT nurses to RRT activations has enabled a culture of predictability, efficiency, maturity and mentoring while assisting the care team with at-risk patients and care decisions. The after-action debrief facilitated adoption of system-wide improvements in equipment, medications, and role redesign of ancillary support personnel. At MU, implementation of the RRT was successful in reducing code blue rates in adults by over onethird. References 1. Sharek P, Parast L, Leong K. (2007) Effect of a rapid response team on hospital-wide mortality and code rates outside the ICU in a Children s Hospital. JAMA. 2007; 298 (19): Hillman K, Chen, J., Cretikos, M., Bellomo, R., Brown, D., Doig, G., et al. (2005). Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet, 365(9477), Bellomo R, Goldsmith D, Uchino S, Buckmaster J, Hart G, Opdam H, et al. (2004). Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates. Crit Care Med, 32(4), Bellomo R, Goldsmith D, Uchino S, Buckmaster J, Hart GK, Opdam H, et al. (2003). A prospective before-and-after trial of a medical emergency team. Med J Aust, 179(6), Berwick, D. Eating soup with a fork. Keynote speech at the 2007 Institute for Healthcare Improvement National Forum. Source: ck.htm (accessed 9/5/08). 6. Stearley HE. Patients' outcomes: intrahospital transportation and monitoring of critically ill patients by a specially trained ICU nursing staff. American Journal of Critical Care, 998 Jul; 7(4): Stearley HE. STAT nursing - The final analysis. Nsg Mgmt, 1996 May; 27(5). 8. Stearley HE. Stat nursing -- alive and well... designed to alleviate short-term workload fluctuations occurring in the intensive care units. Nsg Economics, 1994 Mar-Apr; 12(2): 96-9, Stearley HE, Stafford CJ. STAT response: Consider a STAT nurse. Nsg Adm Qtrly, (4):

3 Figure 1. Rapid Response Team Debrief Documentation 82

4 Figure 2. Areas requesting STAT Nurse Assistance Groups Requesting STAT Nurse Assistance Source: Logs from 4/1/06-9/30/06 (n=5,722) and 11/21/07-2/20/08 (n=2.732) OTHER TEST 0.7% ER 14.5% OR/PACU 0.2% MED-SURG 25.8% RADIOLOGY 19.2% PEDS 3.2% ADULT ICUs 36.3% Figure 3. Type of Activities Nurses/Physicians Request STAT Nurse Assistance What STAT Nur ses Do Sour ce: Logs f r om 14/ 1/ 06-9/ 30/ 06 (n=5,809) and 1/ 21/ 07-2/ 20/ 08 (n=2,732) I V/ LAB DRAW, 18. 1% REPORT, 0.9% RAD/ PROCEDURE, % ROUNDS, 7. 4 % TRAUMA, 4.2% CODE BLUE+TI GER, 2. 5 % RELI EVE/ ASSI ST STAFF, % CURBSI DE CONSULT, 0. 4 % TRANSPORT, 27. 9% CONSCI OUS SEDATI ON, 4.6% 83

5 Figure 4. Length of time for average call by patient care activity Average Duration (In Minutes) for Patient Care Activities Average Minutes RAD/ PROCEDURE 31 CODE BLUE/ TIGER RELIEVE/ ASSIST STAFF CONSCIOUS SEDATION 73 CURBSIDE CONSULT TRANSPORT TRAUMA IV/LAB DRAW 22 4/1/06-9/30/06 (n=194,110 minutes) 11/21/07-2/20/08 (n=96,779 minutes) 84

6 Figure 5. Control chart comparing the number of adult patients per 1,000 discharges with a code blue 18 months pre (7/1/05-12/31/06) and post (1/1/07-6/30-08) RRT implementation (34% reduction in 18 month averages) UCL= CEN= LCL = Rate of Patients With A Code Blue Per 1000 Inpatient Discharges (Excl udes Peds and ER) UCL = CEN= LCL=