Alarms That Deserve Attention. Mike Rayo 3/29/2016

Transcription

1 Alarms That Deserve Attention Mike Rayo 3/29/2016

2 What I ll be covering Tackling Alarm Fatigue With Sound Design With Policy By Sharpening With Multimodal Design 2

3 Can t identify alarm Startle effect of alarms Too many alarms Worn out by alarms Desensitized Nuisance alarms Can t hear alarms Alarm fatigue is Tired Non-actionable alarms Overwhelmed Annoying alarms Patients can t sleep Can t remember what alarm is for 3 Can t discriminate alarms False alarms Alarms are too loud

4 Alarm fatigue words matter Researchers looked for alarm-induced fatigue Researchers FOUND alarm-reduced fatigue Healthcare Informatics Research journal published findings BUT Only used 7 of the 77 questions Unclear whether results are due to fatigue mechanism or something else Cho et. al.,

5 So, what is the problem? Sensory discriminability Can I hear the alarms? Can I identify what events they are meant to signify? Informativeness How often, historically, have the alarms (1) correctly identified a (2) hazardous event Attention Does the clinician have sufficient attentional resources required to respond to the alarms? Response Does the alarming system give the clinician sufficient information to respond appropriately to the event? 5

6 6 Addressing the alarm problem by making phone-based alerts discriminable and identifiable

7 Cisco / connexall tones: current state One tone associated with all events Telemetry low battery, Patient call, Asystole Alerts often routed to multiple phones 45% only go to primary phone 35% go to a second phone 20% go to second and third phone 7

8 Questions for intervention How many tones should we have? Fewer: easier to remember More: less ambiguous what tone is signifying Answer: few tone families, variations within family What should they be? Same already learned them (or have we?), and we already have them Different ability to improve them, but have to design them! How do we improve when and how alerts are routed from phone to phone? How will we get the answers to these questions? 8

9 Quick-cycling for learning Discovery Implementation Analysis Development Design 9

10 Quickening the learning cycle Large Implementation Small Pilot Research Study Heuristics Months Weeks Days Cycle length Years 10

11 Multiple tones project setup Tone design Research literature on memorability and encoding urgency Past experience with emotional aspect of sounds and what they mean Iterate! Learning experiment 2 weeks, current against new set Iterate! Pilot comparing 2 units with new tones, escalation paths to sister units for 3 months (Ross 7 and James 18 new tones, Ross 5 and 7 stayed the same) Iterate! Implement! Starting late March 11

12 Iterations of Cardiac Crisis Initial Designs Sketches Variations on Theme: CAR-DI-O-VAS-CU-LAR After Learning Experiment 12

13 Iteration of Code Blue Initial Designs Learning Experiment Pilot Then roughly 10 more sounds combined with 10 different human and synthetic voices After Pilot 13

14 Resultant tones Cardiac Crisis Asystole, Vfib, Vtac) Cardiac Other Technical High (Leads off, bed exit) Technical Low (Low battery) Code Blue Staff Assist Nurse Call 14

15 15 Listening experiment results - urgency

16 Listening experiment results - identification * * * * 16

17 Pilot results Intervention units: Reduced response time 8 seconds, 9% lower Reduced escalation 8% less to second phone 13% less to third phone Raised patient satisfaction scores Received top rating for alarms up 19% more often Varied with respect to nursing satisfaction with alarms

18 18 Addressing the alarm problem by decreasing false and nonactionable alarms

19 Cognitive Underpinnings of Alarm Problem 19 In high-tempo workplaces, many tasks and signals (e.g., alarms) compete for attention. Over time, clinicians determine (consciously and subconsciously) the informativeness of each of these signals. Informativeness is the likelihood that a signal is signifying what it is meant to signify (i.e., not false), and that what is signified is worthy of directing attention to (i.e., actionable). Non-actionable Alarm: Correctly identified by the system, but it has no clinical significance and/or results in no change in plan of care Asymptomatic Bradycardia) False Alarm: A triggered event that is invalid or incorrect Artifact; Asystole for a paced rhythm.

20 Informativeness Informativeness drops quickly when: There are a lot of false alarms There are a lot of non-actionable alarms Group alarms 1 signal meant to alarm for multiple different reasons 1 signal meant to alarm for multiple different urgencies Drops in signal informativeness result in: Proportional reduction in clinician response (i.e., 80% false alarms predicts 20% clinician response) Lack of response examples include ignoring, overriding, and disabling alarms (turn off, lower volume) NOTE: these responses are not due to a lack of vigilance or effort similar responses have been seen in animals, machines, and proven mathematically 20

21 Performance with varying D, resources n=5 n=15

22 Addressing the alarm problem by decreasing false and nonactionable alarms with Policy Changes 22

23 Policy: Low-risk patients off monitoring

24 Findings: Less Monitoring, False Alarms Fewer False Alarms Measure False Alarm Rate Before After p Value 18.8% 9.6% <0.001

25 Findings: Freed up Resources

26 Addressing the alarm problem by decreasing false and nonactionable alarms With Configuration Changes 26

27 SpO2 Alarms: Pre & Post System Changes 33% actual reduction in Pulse Oximetry alerts in the Medical Center Another ~52,000 alarms triggered for SpO2 of 88%. Future total reduction in Pulse Oximetry alerts in the Medical Center will be ~61%!!!!

28 Reality check: Are we there yet? SpO2 alarms default setting: less than 88% [2015] Results in heart hospital 3,400 alarms/day 1.24M alarms/year No, not there yet!

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30 Addressing the alarm problem by decreasing false and nonactionable alarms With Technology Design 30

31 Next steps: directly targeting informativeness! Using heuristics, experiments, and pilots to improve alarm algorithms Less false and non-actionable alarms Identifying hazardous events better Routing to additional clinicians only when needed Designing visual displays when sensor algorithms cannot get to high enough positive predictive value 31

32 32 Questions?

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