Characterization of monitoring alarms in a community hospital intensive care unit

73 Pages·2017·1.97 MB·English

Characterization of monitoring alarms in a
community hospital intensive care unit
by Sarah Hensley
S.B., Massachusetts Institute of Technology (2017)
Submitted to the
Department of Electrical Engineering and Computer Science
in Partial Fulfillment of the Requirements for the degree of
Masters of Engineering in Electrical Engineering and Computer Science
at the
Massachusetts Institute of Technology
June 2018
○c 2018 Sarah Hensley. All rights reserved.
The author hereby grants to M.I.T. permission to reproduce and to
distribute publicly paper and electronic copies of this thesis document
in whole and in part in any medium now known or hereafter created.
Author:
Department of Electrical Engineering and Computer Science
May 25, 2018
Certified by:
Thomas Heldt, W.M. Keck Career Development Professor in Biomedical Engineering
May 25, 2018
Accepted by:
Katrina LaCurts, Chair, Master of Engineering Thesis Committee
2
Characterization of monitoring alarms in a community
hospital intensive care unit
by
Sarah Hensley
Submitted to the
Department of Electrical Engineering and Computer Science
on May 25, 2018, in partial fulfillment of the
requirements for the degree of
Masters of Engineering in Electrical Engineering and Computer Science
Abstract
Because the vast majority of monitoring alarms in the adult intensive care unit (ICU)
do not require intervention, care providers are slow to respond to all alarms, endan-
gering patients. We collect, characterize, and analyze alarms, alarm annotations
provided by clinical staff while responding to alarms, and physiological data from
a community hospital ICU. In order to suggest opportunities for suppressing irrele-
vant alarms, we examine monitoring device coverage across patients and analyze the
alarms observed by device, priority, and type. On average, we observe 196.3 alarms
per patient-day, for a total of 23,057 alarms. From these, the electrocardiogram and
pulse plethysmogram produce 86.1% of all alarms. The lowest priority alarms rep-
resent 81.1% of all alarms, while the highest priority alarms compose just 5.5% of
the total. While the rate of annotations is low, also just 5.5% of possible alarms, it
is comparable to the rate of care provider interactions with alarms, as measured by
alarm silencing, at 9.6%. Using these annotations, we find – surprisingly – that the
annotated nuisance threshold-violation alarms tend to have higher excursions than
actionable and advisory alarms, offering a statistic for separation. When focusing on
threshold-crossing alarms, we find that 22.5% of Heart Rate Low alarms may actually
indicate device error. Among ST segment alarms, 44.4% occur simultaneously with
at least one other ST segment alarm, producing redundant alarms. Addressing these
issues represent strategies for reducing excessive alarms in this community hospital
cohort of ICU patients.
Thesis Supervisor: Thomas Heldt
Title: W.M. Keck Career Development Professor in Biomedical Engineering
3
4
Acknowledgments
IwouldliketothankmyadvisorProfessorThomasHeldt,whoseguidanceandsupport
was invaluable. I would also like to thank Minoru Matsushima and Daisuke Horiguchi
for all their help in data collection and interpretation. This work was made possible
by Nihon Kohden Corporation, from support of this research and the efforts by staff
of Nihon Kohden Innovation Center to develop and deploy the data collection system
at Winchester Hospital.
5
6
Contents
1 Introduction 15
1.1 Motivation for Reducing Alarm Rates . . . . . . . . . . . . . . . . . . 15
1.1.1 High nuisance alarm rates . . . . . . . . . . . . . . . . . . . . 15
1.1.2 Dangers of high alarm rates . . . . . . . . . . . . . . . . . . . 16
1.2 Motivations for Specific Alarms . . . . . . . . . . . . . . . . . . . . . 17
1.2.1 Threshold alarms . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.2.2 Heart rate and oxygen saturation alarms . . . . . . . . . . . . 18
1.3 Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2 Background 21
2.1 Previous Observational Alarm-audit Studies . . . . . . . . . . . . . . 21
2.1.1 Studies of community hospitals . . . . . . . . . . . . . . . . . 22
2.2 Previous Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2.1 Alarm thresholds . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2.2 Alarm delays . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2.3 Median filter as a low-pass . . . . . . . . . . . . . . . . . . . . 25
2.2.4 Other algorithms . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.5 Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3 Data Collection 29
3.1 Hospital Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2 Data Collection System . . . . . . . . . . . . . . . . . . . . . . . . . . 31
7
3.3 Data Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4 Data Quality Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4 Data Statistics 37
4.1 Data Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2 Alarm Statistics and Alarm Rates . . . . . . . . . . . . . . . . . . . . 40
4.2.1 Alarm priorities and types . . . . . . . . . . . . . . . . . . . . 40
4.2.2 Alarms by device . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2.3 Alarms by active signals . . . . . . . . . . . . . . . . . . . . . 42
4.3 Threshold Alarms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.3.1 ST alarms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5 Threshold Alarm Analysis 47
5.1 Signal Thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2 Separating High and Low Alarms . . . . . . . . . . . . . . . . . . . . 49
5.3 Duration, Excursion, and Exposure . . . . . . . . . . . . . . . . . . . 49
5.3.1 SpO low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2
5.3.2 Heart rate high . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.3.3 Heart rate low . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5.3.4 ST segment high . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.3.5 ST segment low . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6 Alarm Annotations 57
6.1 Annotation Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
6.2 Annotated Threshold Alarms . . . . . . . . . . . . . . . . . . . . . . 59
6.3 Alarm Silencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
8
7 Conclusions and Future Work 63
7.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
A Alarms and Settings 67
9
10