Evaluation of Telemetry Utilization on Medical Surgical Floors

Transcription

1 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

2 21st Century Technology Complexity Acuity Regulatory

3 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?

4 Adult Admissions 36,737 Outpatient Visits 1,515,612 ED Visits 63,365 Births 4,221 Professional Nurses 1,880

5 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?

6 Alarm Safety Focus? No EB indication for monitoring Alarms not customized Poor electrode adherence Wires disconnected Inadequate staffing Inadequate education Physiologic Consequences: Heart rate Blood pressure Dyspnea Gastric acid Anxiety Cardiac dysrhythmias Non-actionable alarms Noise Alarm Fatigue Ignoring Disabling Delayed response Impact on Staff: Anxiety Negative job performance Burn out Annoyance Frustration Impatience

7 Alarm Fatigue Ryher, Okcu, Ackerman, Zimring, & Persson, 2012

8 Problem Statement Telemetry not based on EBP guidelines Alarm Fatigue Disabling Silencing Ignoring

9 Purpose To promote an evidence based approach to telemetry utilization in a medical-surgical setting Aims 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 medicalsurgical units at a university medical center

10 Background O Evidence Based Indications for Telemetry O American Heart Association (AHA) guidelines for telemetry: o Recommend telemetry use for defined patient populations o Recommend the duration of time on telemetry based on the clinical scenario Drew, et al., 2004

11 Impact: Population and System Population O Patients on medical-surgical floors on telemetry that do not have an evidence based indication receiving potentially non-value added care System 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

12 Significance Overuse of telemetry may contribute to nuisance alarms Noise from nuisance alarms can overwhelm caregivers Potentially true alarms will be missed Nurses could spend 16 to 35% of their time responding to alarms 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

13 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

14 Synthesis of the Evidence Telemetry Use Outside the AHA Guidelines 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 Telemetry for Patients in the ED with Chest Pain 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

15 Synthesis of the Evidence Strengths Weaknesses The evidence based practice Four studies brought guidelines (Drew, et. al., telemetry use to within the 2004) guidelines with no adverse outcomes (Benjamin, et al., 2013; Guidelines based on Dressler, et. al., 2014, Kansara, 2015; and expert opinion Kanwar, et. al., 2008) 10 years old Five studies have suggested that telemetry monitoring does not Only guideline available contribute to early detection of critical arrhythmias or clinical deterioration (Feder & Funk, 2013; Gazarian, 2014; Kansara, et al., 2015; Kanwar, et al., 2008)

16 Gaps in the Evidence Telemetry Utilization Attitudes & practices r/t alarms Guidelines based on expert opinion, are mainly for cardiology patients, and are out of date Study did not aggregate nurse s responses Drew, et al., (2004), Funk, M., Clark, T., Bauld, T. J., Ott J. C., and Coss, P. (2014); Funk, et al., (2014)

17 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)

18 Project Design: Process Improvement DMAIC Methodology Define Control Measure 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 Improve Analyze American Society for Quality, 2012 Control: Desired improvements have been made, a system needs to be put in place to ensure sustainability

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20 Established a team Define Stakeholder Analysis Assigned roles on the team Measur e Control Created a charter Defined the problem, business case, & scope Defined the goal statement and success metrics Improve Analyze Work plan Defined timelines and milestones

21 Project Charter Title: Evaluation of Telemetry Utilization on Medical Surgical Floors Problem/Opportunity Statement 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. 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 noncapitol 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. 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 Goal Statement/Success Metrics 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 1. 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):

22 Define Control Created a high level process map Workflow for telemetry ordering / discontinuation Measure Improve Analyze Discussed metrics Predicted length of monitoring versus actual monitoring Assess practice patterns for telemetry ordering

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24 Define Control Improve Measure Analyze 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

25 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

26 Define Control Improve Measure Analyze 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

27 Telemetry Utilization O Descriptive data were analyzed Define Control Improve O Age, gender, primary diagnosis, class Measure Analyze All data were de-identified 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

28 Age N= 94 Mean: 59.8 years SD 14.4 years Gender Male 58.5% Female 41.5% Class Number Not AHA indication 64 Class I 8 Class II 22 Class III 3 Congruence Yes 42.8% No 57.1%

29 Provider Role for Telemetry Order Physician Nurse Practitioner 8 Physician's Assistant

30 Number of patients 20 AHA Class 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 Unrestricted 3 I 3 None Unstable hemodynamics 2 I Acute coronary syndrome 2 II Critical care patient 1 I Telemetry Orders Electrolytes

31 Electrolytes Magnesium 1.7 Analysis 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 7.3 Magnesium ; potassium Calcium 10.5 (renal failure) Potassium normal Calcium 7.7 Potassium 5.4 Potassium 2.8 Calcium 8.4 Potassium calcium and magnesium normal No electrolytes ordered Potassium 3.4 Calcium 8.4; Magnesium 1.3 Calcium 7.5 Potassium 5.4; Calcium 8.2 Potassium 3.6 Potassium 3.5 Calcium 7.7 Potassium 3.6 Calcium and magnesium ordered Potassium and magnesium ordered No repletion / changes No repletion / repletion Potassium ordered Lactulose ordered Potassium ordered No repletion / changes No repletion / changes No repletion / changes Magnesium and potassium ordered No repletion / changes No repletion / changes No repletion / changes No repletion / changes No repletion / changes

32 What did we learn from tele data? 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 Define Control Measure Improve Analyze All data were de-identified

33 What did we learn from tele data? O Electrolyte imbalance was the Define most frequent reason for ordering tele O Only 1 pt had critical values O QTc prolongation Control Measure O Meds and pre-exisiting QTc prolongation O Only 1 of 8 pts Improve Analyze All data were de-identified

34 What does it mean? Define Control Improve 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 Measure Analyze All data were de-identified

35 Healthcare Technology Foundation Survey O Administered to staff on both units via survey monkey O 67 participants (60%) O All but 1 respondent RN

36 Healthcare Technology Foundation Survey Alarm Safety Issue Frequent false alarms, which lead to reduced attention or response to alarms when they occur Difficulty in hearing alarms when they occur Score 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

37 What did we learn from the Alarm Survey? Define Control Measure Improve Analyze All data were de-identified 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

38 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 Control Improve All data were de-identified Measure Analyze

39 Define Control Improve Measure Analyze

40 Impact of Results on Practice Follow the EBP guidelines Number of pts on telemetry Time / # of pts on telemetry Nuisance alarms Alarm Fatigue

41 Strengths and Limitations Strengths 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 Weaknesses 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

42 Improve and Control O Beyond the scope of this project O Collaborate with UBCL to plan next steps O Transition leadership on next steps in process improvement methodology

43 Clinical deficiencies Alarm Fatigue: Brought on by Technical Deficiencies Resolved Through: Evidence based indications Nurse s Knowledge Nursing Practice standards: Electrode management Customization Alarm response Handoffs Standards of Practice / Education: Nurses, respiratory therapists, engineers Competency Assessment Technology standardization Unreliable process for RN notification Monitor safety features not optimized Monitor set ups not standardized Defaults not customized Resulting In: Actionable alarms Blake, 2014; Cvach, 2012; Feder & Funk, 2013; Graham & Cvach, 2010; Sendelbach, 2012; Sendelbach & Funk, 2013.

44 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?

45 What Can You do? O Resources available O NACNS Toolkit O AAMI Website O AACN Website O Identify barriers to success!

46 Questions? Thank you!

47 References Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), American Society for Quality (2012, November) To DMAIC or not to DMAIC? Retrieved from: 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), e Bitan, Y., Meyer, J., Shinar, D., & Zmora, E. (2004). Nurses reactions to alarms in a neonatal intensive care unit. Cognition, Technology & Work, 6(4), Blake, N. (2014). The effect of alarm fatigue on the work environment. AACN Advanced Critical Care, 25(1), 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), Cvach, M. (2012). Monitor alarm fatigue: an integrative review. Biomedical Instrumentation & Technology, 46(4), 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),

48 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: 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), 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), The Food and Drug Administration. (2014, March 12). Medical devices. Retrieved from: 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.

49 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), 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), doi: /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), 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), 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), 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),

50 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), Hsu, T., Ryherd, E., Waye, K. P., & Ackerman, J. (2012). Noise pollution in hospitals: impact on patients. Journal Clinical Outcomes Management, 19(7), 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: 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: /jamainternalmed Kanwar, M., Fares, R., Minnick, S., Rosman, H. S., & Saravolatz, L. (2008). Inpatient cardiac telemetry monitoring: are we overdoing it?. JCOM, 15(1).

51 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), 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), Sendelbach, S. (2012). Alarm fatigue. Nursing Clinics of North America, 47(3), Sendelbach, S., & Funk, M. (2013). Alarm fatigue: A patient safety concern. AACN Advanced Critical Care, 24(4), 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: /JCN