Evaluation of Telemetry Utilization on Medical Surgical...
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Evaluation of Telemetry Utilization on Medical Surgical Floors JoAnne Phillips, DNP, RN, CPPS Co-chair, Alarm Safety Committee The Hospital of the University of Pennsylvania
Transcript of Evaluation of Telemetry Utilization on Medical Surgical...
Evaluation of Telemetry Utilization on Medical
Surgical Floors
JoAnne Phillips, DNP, RN, CPPS Co-chair, Alarm Safety Committee The Hospital of the University of
Pennsylvania
21st Century
Technology
Acuity Regulatory
Complexity
Session Objectives O Understand the concept of alarm fatigue O Review the process for understanding the use of telemetry on
medical surgical floors O Discuss the data obtained by evaluating the use of telemetry
on medical surgical floors O What did I learn that will help to improve alarm safety at my
organization?
Adult Admissions 36,737
Outpatient Visits 1,515,612
ED Visits 63,365
Births 4,221
Professional Nurses 1,880
The Hospital of the University of Pennsylvania
O Telemetry model O Nurse accountability model
O Telemetry on every unit (except post partum)
O Perception O Overuse of telemetry O Non-value added care O Truth or perception ?
Noise
No EB indication for monitoring Alarms not customized Poor electrode adherence Wires disconnected Inadequate staffing Inadequate education
Non-actionable alarms
Physiologic Consequences: Heart rate Blood pressure Dyspnea Gastric acid Anxiety Cardiac dysrhythmias
Impact on Staff: Anxiety Negative job performance Burn out Annoyance Frustration Impatience
Alarm Fatigue
Ignoring Disabling Delayed response
Alarm Safety – Focus?
Alarm Fatigue
Ryher, Okcu, Ackerman, Zimring, & Persson, 2012
Problem Statement
Telemetry not based on
EBP guidelines
Alarm Fatigue
Disabling Silencing Ignoring
• To promote an evidence based approach to telemetry utilization in a medical-surgical setting
Purpose
• Examine practice patterns for the ordering and discontinuation of telemetry monitoring on two medical-surgical units at a university medical center
• Examine nurses’ attitudes and practices related to alarm safety on two medical-surgical units at a university medical center
Aims
Background O Evidence Based Indications for Telemetry
OAmerican Heart Association (AHA) guidelines for telemetry: oRecommend telemetry use for defined patient
populations oRecommend the duration of time on telemetry
based on the clinical scenario
Drew, et al., 2004
Impact: Population and System Population System
O Patients on medical-surgical floors on telemetry that do not have an evidence based indication receiving potentially non-value added care
O Evaluation of practice patterns on the use of telemetry O Telemetry not supported by the
AHA guidelines will impact O Nursing care time O Transport resources O Supplies
O Other organizations O Patient flow
Significance
Bitan, Meyer, Shinar, & Zamora, 2004; Blake, 2014; Christensen, et al., 2014; Cvach, 2012; Feder & Funk, 2013; Görges, Markewitz, & Westenskow, 2009; Graham & Cvach, 2010; Sendelbach & Funk, 2013
Nurses could spend 16 to 35% of their time responding to alarms
Overuse of telemetry may contribute to nuisance alarms
Noise from nuisance alarms can overwhelm caregivers
Potentially true alarms will be missed
Synthesis of the Evidence O Database searches
O Pub Med; CINAHL; Ovid
O Key search terms O Alarm fatigue; cardiac telemetry; alarm safety; clinical alarms
Synthesis of the Evidence Telemetry Use Outside the
AHA Guidelines Telemetry for Patients in the
ED with Chest Pain O Feder & Funk, 2013 O Benjamin, et al., 2013 O Dressler, et al., 2014; O Henriques-Forsythe, et al.,
2009 O Kanwar, et al., 2008 O Schull, & Redelmeier, 2000
O Dhillon, et al., 2009 O Gatien, et al., 2007 O Grossman, et al., 2011 O Henriques-Forsythe, et. al., 2009 O Hollander, Sites, Pollack, & Shofer,
2004 O Leighton, Kianfar, Serynek, & Kerwin,
2013 O Perkins, McCurdy, Vilke, Al-Marshad,
2013
Synthesis of the Evidence
Strengths • Four studies brought
telemetry use to within the guidelines with no adverse outcomes (Benjamin, et al., 2013; Dressler, et. al., 2014, Kansara, 2015; and Kanwar, et. al., 2008)
• Five studies have suggested that telemetry monitoring does not contribute to early detection of critical arrhythmias or clinical deterioration (Feder & Funk, 2013; Gazarian, 2014; Kansara, et al., 2015; Kanwar, et al., 2008)
Weaknesses
• The evidence based practice guidelines (Drew, et. al., 2004) • Guidelines based on
expert opinion • 10 years old • Only guideline available
Gaps in the Evidence
Drew, et al., (2004), Funk, M., Clark, T., Bauld, T. J., Ott J. C., and Coss, P. (2014); Funk, et al., (2014)
Telemetry Utilization Guidelines based on expert opinion, are mainly for cardiology patients, and are out of date
Attitudes & practices r/t alarms Study did not aggregate nurse’s responses
Theoretical Framework O Theory of Planned Behavior (TPB)
O Social cognitive theory O Behavior intention is the most important determinant of behavior O Influenced by
O Attitudes O Subjective / social norms O Behavioral control
O The stronger the attitudes and social norms, the greater the perceived
behavioral control, and the more likely the person is to perform a particular behavior.
O Application of TPB O Why might a provider order telemetry or not discontinue it if it is not indicated by the EBP
guidelines? O Nurse’s attitudes toward alarm response
(Ajzan, 1991; Javidi, 2013; Perkins, et al., 2007)
Project Design: Process Improvement
Define
Measure
Analyze Improve
Control
DMAIC Methodology Define: Problem identification and benefit analysis Measure: Translation of the problem into a measurable form and assess the current status Analyze: Understand root causes of why defects occur; identify key process variables that cause defects Improve: Design and implement adjustments to the process to improve the critical issues Control: Desired improvements have been made, a system needs to be put in place to ensure sustainability
American Society for Quality, 2012
Define
Measure
Analyze Improve
Control
Established a team • Stakeholder Analysis • Assigned roles on the
team
Created a charter • Defined the problem,
business case, & scope • Defined the goal statement
and success metrics
Work plan • Defined timelines and
milestones
The American Heart Association has EBP guidelines for the use of telemetry. Telemetry use outside the guidelines may result in excessive alarms, leading to alarm fatigue. This project will examine practice patterns for telemetry utilization on 2 medical surgical floors to determine if they are congruent with the EBP guidelines.
Project Charter Title: Evaluation of Telemetry Utilization on Medical Surgical Floors
Goal Statement/Success Metrics 1. Analyze telemetry practice patters for ordering and discontinuation related to EBP guidelines 2. Review results of HTF survey on attitudes and practices related to alarm safety 3. Use both sets of data to develop countermeasures
Business Impact •The evidence suggests a 35% overutilization of telemetry on
medical surgical floors. •By decreasing telemetry overutilization by 25% on one medical
surgical floor at HUP could save an estimated $85,532 in non-capitol expenses
Project Scope This project will examine telemetry utilization practice patterns on one
medicine floor (Silverstein 11) and one surgical floor (Ravdin 9). To understand staff attitudes and practices with alarms, the Health Care Technology Foundation survey will be administered to all registered nurses on both floors.
Team (Please Place Initials by Name)
• Executive Sponsor(s): Regina Cunningham, PhD, RN AOCN
• Champion(s): Kate Fitzpatrick, DNP, RN;
• Betty Ann Boczar, MSN, RN
• Clinical Leader(s): JoAnne Phillips
• Process Owner(s): Nicole Pavone / Janelle Harris
• Team Leader(s): UBCL Physician Leads
• Mentor/Facilitator(s): JoAnne Phillips
• Team Members:
• Nicole Pavone
• Diana Santangelo
• Melissa Trolene
• Sitha Dy
• Alexandra Rineer
• Janelle Harris
• Adriana Boyle
• Subject Matter Experts(s):
Problem/Opportunity Statement
Project Milestones
1. Results of HTF survey on alarm attitudes and practices
2. Completion of 4 weeks of data collection on ordering and discontinuation practices for telemetry
5.26.15
Define
Measure
Analyze Improve
Control
Created a high level process map • Workflow for telemetry ordering
/ discontinuation
Discussed metrics • Predicted length of monitoring
versus actual monitoring
• Assess practice patterns for telemetry ordering
Define
Measure
Analyze Improve
Control
Telemetry Utilization Data were collected daily for 4 weeks – 94 patients • Evaluation of each telemetry order • Data collected from the EMR
All data were de-identified
Data Points Collected O Subject ID
O All data were de-identified O Age O Gender O AHA Class I, II, or III O Indication from the EMR O Primary diagnosis O Congruence between primary
diagnosis and order
O Discipline who ordered O Predicted length of monitoring O Date / time of original order O Date / time of discontinuation
order O Actual hours on telemetry O Non-indicated hours of
telemetry
Define
Measure
Analyze Improve
Control
All data were de-identified
Attitudes and Practices related to Alarms • All registered nurse staff were invited to take the online
survey • 66 RNs (60%) participation
All data were de-identified
Telemetry Utilization O Descriptive data were analyzed
O Age, gender, primary diagnosis, class of telemetry order based on the AHA guidelines (class I, II, III), discipline that ordered telemetry
O Congruence of order with the clinical status
O Telemetry hours of monitoring O Predicted number of hours on
telemetry O Actual number of hours on
telemetry O Gap: non-indicated time on
telemetry
Define
Measure
Analyze Improve
Control
Age Mean: 59.8 years SD 14.4 years
Gender Male 58.5% Female 41.5%
N= 94
Class Number Not AHA indication 64
Class I 8
Class II 22
Class III 3
Congruence Yes – 42.8% No – 57.1%
0
10
20
30
40
50
60
70
Physician Nurse Practitioner Physician's Assistant
69
17 8
Provider Role for Telemetry Order
Number of patients
AHA Class
Electrolytes 20 None Post operative 16 None Palpitations 16 None QT prolonging medications 7 II Atrial tachyarrhythmias 6 None CHF – Active 4 II Syncope 4 II
Intermediate/high risk chest pain 4 II
Stroke 3 None
Low risk chest pain 3 II
Arrhythmias with unstable hemodynamics
3 I
Unrestricted 3 None
Unstable hemodynamics 2 I
Acute coronary syndrome 2 II
Critical care patient 1 I
Telemetry Orders
Electrolytes Analysis Magnesium 1.7 Oral magnesium; IV potassium
Potassium, calcium and magnesium normal No repletion Calcium 8.8 Calcium ordered Calcium 8.8 No repletion / changes Calcium 8.2 Magnesium 1.7 Calcium and magnesium ordered
Calcium 7.3 Potassium and magnesium ordered Magnesium 1.5 - 1.7; potassium 3.6-3.9 No repletion / changes Calcium 10.5 (renal failure) No repletion / repletion Potassium normal Calcium 7.7 Potassium ordered Potassium 5.4 Lactulose ordered Potassium 2.8 Potassium ordered Calcium 8.4 No repletion / changes Potassium calcium and magnesium normal No repletion / changes No electrolytes ordered No repletion / changes Potassium 3.4 Calcium 8.4; Magnesium 1.3 Magnesium and potassium ordered Calcium 7.5 No repletion / changes Potassium 5.4; Calcium 8.2 No repletion / changes Potassium 3.6 No repletion / changes Potassium 3.5 Calcium 7.7 No repletion / changes Potassium 3.6 No repletion / changes
All data were de-identified
• 68% of the telemetry orders were not supported by the AHA guidelines
• 42.8% of the orders demonstrated congruence with the patient’s clinical status
• The mean time difference between the predicted and actual length of monitoring was over 43 hours
• Pts monitored longer than predicted, gap was 58 hours
• Pts monitored shorter than predicted, gap was -13 hours
What did we learn from tele data?
Define
Measure
Analyze Improve
Control
All data were de-identified
O Electrolyte imbalance was the most frequent reason for ordering tele – O Only 1 pt had critical values
O QTc prolongation O Meds and pre-exisiting QTc
prolongation O Only 1 of 8 pts
What did we learn from tele data?
Define
Measure
Analyze Improve
Control
All data were de-identified
What does it mean?
• The electronic order set needs to be reviewed
• Lack of congruence –Need better understanding why
• Patients monitored significantly longer than is supported by the evidence
Define
Measure
Analyze Improve
Control
Healthcare Technology Foundation Survey
O Administered to staff on both units via survey monkey O 67 participants (60%)
O All but 1 respondent RN
Healthcare Technology Foundation Survey Alarm Safety Issue Score Frequent false alarms, which lead to reduced attention or response to alarms when they occur
3.45
Difficulty in hearing alarms when they occur 4.46
Difficulty in identifying the source of an alarm 4.76
Difficulty in understanding the priority of an alarm 4.88
Inadequate staff to respond to alarms as they occur 5
Difficulty in understanding the priority of an alarm 5.14
Noise competition from non-clinical alarms and pages 5.3
Difficulty in setting alarms properly 5.74
Lack of training on alarm systems 6.19
All data were de-identified
What did we learn from the Alarm Survey?
• Nuisance alarms occur frequently, disrupt patient care and reduce trust
• Frequent false alarms are the most important alarm safety issue
• The data on both units were similar
Define
Measure
Analyze Improve
Control
All data were de-identified
What did the survey tell us?
• Strategies to minimize nuisance alarms need to be developed
• Need to identify the barriers to safe alarm management
Define
Measure
Analyze Improve
Control
Define
Measure
Analyze Improve
Control
Impact of Results on Practice
Follow the EBP
guidelines
Number of pts on
telemetry
Time / # of pts on
telemetry
Nuisance alarms
Alarm Fatigue
Strengths and Limitations
Strengths Weaknesses O 60% response to the survey
O Strong staff involvement O Data collected over 4 weeks by
one data collector O Data collected will help to
inform initiatives to decrease telemetry utilization
O One hospital; two units O Telemetry delivery model O Congruence is based on
documentation in the EMR O Unable to complete the
improve and control aspects of the project
Improve and Control
OBeyond the scope of this project O Collaborate with UBCL to plan next steps O Transition leadership on next steps in
process improvement methodology
Alarm Fatigue: Brought on by…
Clinical deficiencies Technical Deficiencies
Evidence based indications
Nurse’s Knowledge
Nursing Practice standards: Electrode management Customization Alarm response Handoffs
Unreliable process for RN notification
Monitor safety features not optimized
Monitor set ups not standardized
Defaults not customized
Standards of Practice / Education: Nurses, respiratory therapists, engineers Competency Assessment Technology standardization
Actionable alarms Blake, 2014; Cvach, 2012; Feder & Funk, 2013; Graham & Cvach, 2010; Sendelbach, 2012; Sendelbach & Funk, 2013.
Resulting In:
Resolved Through:
Bringing it Together….. O Alarm Fatigue O Review the process for understanding the use of telemetry on
medical surgical floors O Discuss the data obtained by evaluating the use of telemetry
on medical surgical floors O What did I learn that will help to improve alarm safety at my
organization?
What Can You do?
O Resources available O NACNS Toolkit O AAMI Website O AACN Website
O Identify barriers to success!
References Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. American Society for Quality (2012, November) To DMAIC or not to DMAIC? Retrieved from: http://asq.org/quality-progress/2012/11/back-to-basics/to-dmaic-or-not-to-dmaic.html Benjamin, E. M., Klugman, R. A., Luckmann, R., Fairchild, D. G., & Abookire, S. A. (2013). Impact of cardiac telemetry on patient safety and cost. American Journal of Managed Care, 19(6), e225-32. Bitan, Y., Meyer, J., Shinar, D., & Zmora, E. (2004). Nurses’ reactions to alarms in a neonatal intensive care unit. Cognition, Technology & Work, 6(4), 239-246. Blake, N. (2014). The effect of alarm fatigue on the work environment. AACN Advanced Critical Care, 25(1), 18-19. Christensen, M., Dodds, A., Sauer, J., & Watts, N. (2014). Alarm setting for the critically ill patient: A descriptive pilot survey of nurses’ perceptions of current practice in an Australian regional critical care unit. Intensive and Critical Care Nursing, 30(4), 204-210. Cvach, M. (2012). Monitor alarm fatigue: an integrative review. Biomedical Instrumentation & Technology, 46(4), 268-277. Dhillon, S. K., Rachko, M., Hanon, S., Schweitzer, P., & Bergmann, S. R. (2009). Telemetry monitoring guidelines for efficient and safe delivery of cardiac rhythm monitoring to noncritical hospital inpatients. Critical Pathways in Cardiology, 8(3), 125-126.
References Dressler, R., Dryer, M. M., Coletti, C., Mahoney, D., Doorey, A. J. (2014, September 22). Altering overuse of cardiac telemetry in non–intensive care unit settings by hardwiring the use of American Heart Association guidelines. JAMA Internal Medicine Online. Retrieved from: http://archinte.jamanetwork.com/article.aspx?articleid=1906998 Drew, B. J., Califf, R. M., Funk, M., Kaufman, E. S., Krucoff, M. W., Laks, M. M., ... & Van Hare, G. F. (2004). Practice standards for electrocardiographic monitoring in hospital settings: an American Heart Association scientific statement from the Councils on Cardiovascular Nursing, Clinical Cardiology, and Cardiovascular Disease in the Young: endorsed by the International Society of Computerized Electrocardiology and the American Association of Critical-Care Nurses. Circulation, 110(17), 2721-2746. Feder, S., & Funk, M. (2013). Over-monitoring and alarm fatigue: For whom do the bells toll? Heart & Lung: The Journal of Acute and Critical Care, 42(6), 395-396. The Food and Drug Administration. (2014, March 12). Medical devices. Retrieved from: http://www.fda.gov/medicaldevices/safety/reportaproblem/default.htm Funk, M., Clark, J. T., Bauld, T. J., Ott, J. C., & Coss, P. (2014). Attitudes and practices related to clinical alarms. American Journal of Critical Care, 23(3), e9-e18.
References Gazarian, P. K. (2014). Nurses’ response to frequency and types of electrocardiography alarms in a non-critical care setting: A descriptive study. International Journal of Nursing Studies, 51(2), 190-197. Görges, M., Markewitz, B. A., & Westenskow, D. R. (2009). Improving alarm performance in the medical intensive care unit using delays and clinical context. Anesthesia & Analgesia, 108(5), 1546-1552. doi:10.1213/ane.0b013e31819bdfbb Graham, K. C., & Cvach, M. (2010). Monitor alarm fatigue: standardizing use of physiological monitors and decreasing nuisance alarms. American Journal of Critical Care, 19(1), 28-34. Grossman, S. A., Shapiro, N. I., Mottley, J. L., Sanchez, L., Ullman, E., & Wolfe, R. E. (2011). Is telemetry useful in evaluating chest pain patients in an observation unit? Internal and Emergency Medicine, 6(6), 543-546. Henriques-Forsythe, M. N., Ivonye, C. C., Jamched, U., Kamuguisha, L. K. K., Olejeme, K. A., & Onwuanyi, A. E. (2009). Is telemetry overused? Is it as helpful as thought? Cleveland Clinic Journal of Medicine, 76(6), 368-372. Hollander, J. E., Sites, F. D., Pollack Jr, C. V., & Shofer, F. S. (2004). Lack of utility of telemetry monitoring for identification of cardiac death and life-threatening ventricular dysrhythmias in low-risk patients with chest pain. Annals of Emergency Medicine, 43(1), 71-76.
References Hsu, S. M., Ko, W. J., Liao, W. C., Huang, S. J., Chen, R. J., Li, C. Y., & Hwang, S. L. (2010). Associations of exposure to noise with physiological and psychological outcomes among post-cardiac surgery patients in ICUs. Clinics, 65(10), 985-989. Hsu, T., Ryherd, E., Waye, K. P., & Ackerman, J. (2012). Noise pollution in hospitals: impact on patients. Journal Clinical Outcomes Management, 19(7), 301-9. Javadi, M., Kadkhodaee, M., Yaghoubi, M., Maroufi, M., & Shams, A. (2013). Applying theory of planned behavior in predicting of patient safety behaviors of nurses. Materia socio-medica, 25(1), 52. The Joint Commission, Patient Safety Advisory Group. (2013, April 8). Sentinel Event Alert. Medical device alarm safety in hospitals. Number 50. Retrieved from: http://www.jointcommission.org/sentinel_event.aspx Kansara, P., Jackson, K., Dressler, R., Werner, H., Kerzner, R., Weintraub, W. S., Doorey, A. (2015, June 15). Potential of missing life threatening arrhythmias after limiting the use of cardiac telemetry. JAMA. doi: 10.1001/jamainternalmed.2015.2387. Kanwar, M., Fares, R., Minnick, S., Rosman, H. S., & Saravolatz, L. (2008). Inpatient cardiac telemetry monitoring: are we overdoing it?. JCOM, 15(1).
References Perkins, M. B., Jensen, P. S., Jaccard, J., Gollwitzer, P., Oettingen, G., Pappadopulos, E., & Hoagwood, K. E. (2007). Applying theory-driven approaches to understanding and modifying clinicians' behavior: What do we know?. Psychiatric Services, 58(3), 342-348. Ryherd, E. E., Okcu, S., Ackerman, J., Zimring, C., & Persson, K. (2012). Noise pollution in hospitals: impacts on staff. Journal of Clinical Outcomes Management, 19(11), 301-309 Sendelbach, S. (2012). Alarm fatigue. Nursing Clinics of North America, 47(3), 375-382. Sendelbach, S., & Funk, M. (2013). Alarm fatigue: A patient safety concern. AACN Advanced Critical Care, 24(4), 378-386. Whalen, D. A., Covelle, P. M., Piepenbrink, J. C., Villanova, K. L., Cuneo, C. L., & Awtry, E. H. (2013). Novel approach to cardiac alarm management on telemetry units. The Journal of Cardiovascular Nursing. Advance online publication. doi: 10.1097/JCN.0000000000000114
