Technical article: Overview of hospital-based data capture systems that acquire continuous ECG and physiologic data.

Data capture systems that acquire continuous hospital-based electrocardiographic (ECG) and physiologic (vital signs) data can foster robust research (i.e., large sample sizes from consecutive patients). However, the application of these systems and the data generated are complex and requires careful human oversight to ensure that accurate and high quality data are procured. This technical article will describe two different data capture systems created by our research group designed to examine false alarms associated with alarm fatigue in nurses. The following aspects regarding these data capture systems will be discussed: (1) history of development; (2) summary of advantages, challenges, and important considerations; (3) their use in research; (4) their use in clinical care; and (5) future developments.

Hospital-Based Electrocardiographic Monitoring: The Good, the Not So Good, and Untapped Potential.

Continuous electrocardiographic (ECG) monitoring was first introduced into hospitals in the 1960s, initially into critical care, as bedside monitors, and eventually into step-down units with telemetry capabilities. Although the initial use was rather simplistic (ie, heart rate and rhythm assessment), the capabilities of these devices and associated physiologic (vital sign) monitors have expanded considerably. Current bedside monitors now include sophisticated ECG software designed to identify myocardial ischemia (ie, ST-segment monitoring), QT-interval prolongation, and a myriad of other cardiac arrhythmia types. Physiologic monitoring has had similar advances from noninvasive assessment of core vital signs (blood pressure, respiratory rate, oxygen saturation) to invasive monitoring including arterial blood pressure, temperature, central venous pressure, intracranial pressure, carbon dioxide, and many others. The benefit of these monitoring devices is that continuous and real-time information is displayed and can be configured to alarm to alert nurses to a change in a patient's condition. I think it is fair to say that critical and high-acuity care nurses see these devices as having a positive impact in patient care. However, this enthusiasm has been somewhat dampened in the past decade by research highlighting the shortcomings and unanticipated consequences of these devices, namely alarm and alert fatigue. In this article, which is associated with the American Association of Critical-Care Nurses' Distinguished Research Lecture, I describe my 36-year journey from a clinical nurse to nurse scientist and the trajectory of my program of research focused primarily on ECG and physiologic monitoring. Specifically, I discuss the good, the not so good, and the untapped potential of these monitoring systems in clinical care. I also describe my experiences with community-based research in patients with acute coronary syndrome and/or heart failure.

Occurrence of Transient Myocardial Ischemic Events Among Non-ST Segment Elevation Acute Coronary Syndrome Patients Before or After Invasive Coronary Angiography.

BACKGROUND: The occurrence of transient myocardial ischemia (TMI) is an important pathology in patients with non-ST elevation acute coronary syndrome (NSTE-ACS), yet studies are scarce regarding when TMI occurs during hospitalization, particularly in relation to invasive coronary angiography (ICA). This study examined: (1) TMI before or after ICA; (2) patient characteristics and ischemic burden by TMI group (before or after ICA); and (3) major in-hospital complications (transfer to critical care, death) and length of stay by TMI group (before or after ICA). METHODS: Secondary data analysis in hospitalized NSTE-ACS patients with TMI event(s) identified from 12-lead electrocardiographic Holter. Patient records were reviewed to assess ischemic burden [TMI time (min) ÷ hours recording duration], outcomes, and TMI timing, before or after ICA. RESULTS: In 38 patients, 3 (8%) had TMI before and after ICA. Of the remaining 35 patients (92%), TMI occurred before ICA (16; 46%), and after ICA (9; 26%), and 10 (28%) did not have ICA. Patient characteristics, untoward outcomes, and TMI duration (minutes) did not differ by group. Ischemic burden was higher in patients with TMI after ICA (7.29 ± 8.82 min/h) compared to before ICA (2.54 ± 2.11 min/h), P = 0.039. Hospital length of stay by TMI group was 113 ± 113 (before), 226 ± 244 (after), and 85 ± 65 hours (no ICA); P = 0.172. CONCLUSIONS: Almost half of the sample had TMI before ICA; one-third had TMI but did not have ICA. Patients with TMI after an ICA had a higher ischemic burden. Future studies with larger sample sizes are needed to investigate further the short- and long-term clinical significance of TMI among NSTE-ACS patients.

Interdisciplinary collaboration in critical care alarm research: A bibliometric analysis.

BACKGROUND: Alarm fatigue in nurses is a major patient safety concern in the intensive care unit. This is caused by exposure to high rates of false and non-actionable alarms. Despite decades of research, the problem persists, leading to stress, burnout, and patient harm resulting from true missed events. While engineering approaches to reduce false alarms have spurred hope, they appear to lack collaboration between nurses and engineers to produce real-world solutions. The aim of this bibliometric analysis was to examine the relevant literature to quantify the level of authorial collaboration between nurses, physicians, and engineers. METHODS: We conducted a bibliometric analysis of articles on alarm fatigue and false alarm reduction strategies in critical care published between 2010 and 2022. Data were extracted at the article and author level. The percentages of author disciplines per publication were calculated by study design, journal subject area, and other article-level factors. RESULTS: A total of 155 articles with 583 unique authors were identified. While 31.73 % (n = 185) of the unique authors had a nursing background, publications using an engineering study design (n = 46), e.g., model development, had a very low involvement of nursing authors (mean proportion at 1.09 %). Observational studies (n = 58) and interventional studies (n = 33) had a higher mean involvement of 52.27 % and 47.75 %, respectively. Articles published in nursing journals (n = 32) had the highest mean proportion of nursing authors (80.32 %), while those published in engineering journals (n = 46) had the lowest (9.00 %), with 6 (13.04 %) articles having one or more nurses as co-authors. CONCLUSION: Minimal involvement of nursing expertise in alarm research utilizing engineering methodologies may be one reason for the lack of successful, real-world solutions to ameliorate alarm fatigue. Fostering a collaborative, interdisciplinary research culture can promote a common publication culture across fields and may yield sustainable implementation of technological solutions in healthcare.

Ventricular tachycardia and in-hospital mortality in the intensive care unit.

Background: Continuous electrocardiographic (ECG) monitoring is used to identify ventricular tachycardia (VT), but false alarms occur frequently. Objective: The purpose of this study was to assess the rate of 30-day in-hospital mortality associated with VT alerts generated from bedside ECG monitors to those from a new algorithm among intensive care unit (ICU) patients. Methods: We conducted a retrospective cohort study in consecutive adult ICU patients at an urban academic medical center and compared current bedside monitor VT alerts, VT alerts from a new-unannotated algorithm, and true-annotated VT. We used survival analysis to explore the association between VT alerts and mortality. Results: We included 5679 ICU admissions (mean age 58 ± 17 years; 48% women), 503 (8.9%) experienced 30-day in-hospital mortality. A total of 30.1% had at least 1 current bedside monitor VT alert, 14.3% had a new-unannotated algorithm VT alert, and 11.6% had true-annotated VT. Bedside monitor VT alert was not associated with increased rate of 30-day mortality (adjusted hazard ratio [aHR] 1.06; 95% confidence interval [CI] 0.88-1.27), but there was an association for VT alerts from our new-unannotated algorithm (aHR 1.38; 95% CI 1.12-1.69) and true-annotated VT(aHR 1.39; 95% CI 1.12-1.73). Conclusion: Unannotated and annotated-true VT were associated with increased rate of 30-day in-hospital mortality, whereas current bedside monitor VT was not. Our new algorithm may accurately identify high-risk VT; however, prospective validation is needed.

Agreement of Computerized QT and QTc Interval Measurements Between Both Bedside and Expert Nurses Using Electronic Calipers.

BACKGROUND: In hospitalized patients, QT/QTc (heart rate corrected) prolongation on the electrocardiogram (ECG) increases the risk of torsade de pointes. Manual measurements are time-consuming and often inaccurate. Some bedside monitors automatically and continuously measure QT/QTc; however, the agreement between computerized versus nurse-measured values has not been evaluated. OBJECTIVE: The aim of this study was to examine the agreement between computerized QT/QTc and bedside and expert nurses who used electronic calipers. METHODS: This was a prospective observational study in 3 intensive care units. Up to 2 QT/QTc measurements (milliseconds) per patient were collected. Bland-Altman test was used to analyze measurement agreement. RESULTS: A total of 54 QT/QTc measurements from 34 patients admitted to the ICU were included. The mean difference (bias) for QT comparisons was as follows: computerized versus expert nurses, -11.04 ± 4.45 milliseconds (95% confidence interval [CI], -2.3 to -19.8; P = .016), and computerized versus bedside nurses, -13.72 ± 6.70 (95% CI, -0.70 to -26.8; P = .044). The mean bias for QTc comparisons was as follows: computerized versus expert nurses, -12.46 ± 5.80 (95% CI, -1.1 to -23.8; P = .035), and computerized versus bedside nurses, -18.49 ± 7.90 (95% CI, -3.0 to -33.9; P = .022). CONCLUSION: Computerized QT/QTc measurements calculated by bedside monitor software and measurements performed by nurses were in close agreement; statistically significant differences were found, but differences were less than 20 milliseconds (on-half of a small box), indicating no clinical significance. Computerized measurements may be a suitable alternative to nurse-measured QT/QTc. This could reduce inaccuracies and nurse burden while increasing adherence to practice recommendations. Further research comparing computerized QT/QTc from bedside monitoring to standard 12-lead electrocardiogram in a larger sample, including non-ICU patients, is needed.

Evaluation of premature ventricular complexes during in-hospital ECG monitoring as a predictor of ventricular tachycardia in an intensive care unit cohort.

In-hospital electrocardiographic (ECG) monitors are typically configured to alarm for premature ventricular complexes (PVCs) due to the potential association of PVCs with ventricular tachycardia (VT). However, no contemporary hospital-based studies have examined the association of PVCs with VT. Hence, the benefit of PVC monitoring in hospitalized patients is largely unknown. This secondary analysis used a large PVC alarm data set to determine whether PVCs identified during continuous ECG monitoring were associated with VT, in-hospital cardiac arrest (IHCA), and/or death in a cohort of adult intensive care unit patients. Six PVC types were examined (i.e., isolated, bigeminy, trigeminy, couplets, R-on-T, and run PVCs) and were compared between patients with and without VT, IHCA, and/or death. Of 445 patients, 48 (10.8%) had VT; 11 (2.5%) had IHCA; and 49 (11%) died. Isolated and run PVC counts were higher in the VT group (p = 0.03 both), but group differences were not seen for the other four PVC types. The regression models showed no significant associations between any of the six PVC types and VT or death, although confidence intervals were wide. Due to the small number of cases, we were unable to test for associations between PVCs and IHCA. Our findings suggest that we should question the clinical relevance of activating PVC alarms as a forewarning of VT, and more work should be done with larger sample sizes. A more precise characterization of clinically relevant PVCs that might be associated with VT is warranted.

Ischemic Pre-Conditioning is Present in Patients with Non-ST Elevation Myocardial Infarction and ECG Derived Moderate Obstructive Sleep Apnea.

Background: Obstructive Sleep Apnea (OSA) is associated with an increased risk of cardiovascular events, including Acute Coronary Syndrome (ACS). There is conflicting evidence that suggests OSA has a cardioprotective effect (i.e., lower troponin), via ischemic pre-conditioning, in patients with ACS. Purpose: This study had two aims: (1) compare peak troponin between non-ST elevation (NSTE) ACS patients with and without moderate OSA identified using a Holter derived respiratory disturbance index (HDRDI); and (2) determine the frequency of transient myocardial ischemia (TMI) between NSTE-ACS patients with and without moderate HDRDI. Method: This was a secondary analysis. OSA events were identified from 12-lead ECG Holter recordings using QRSs, R-R intervals, and the myogram. Moderate OSA was defined as an HDRDI ≥15 events per/hour. TMI was defined as ≥1 millimeter of ST-segment ↑ or ↓, in ≥ 1 ECG lead, ≥ 1 minute. Results: In 110 NSTE-ACS patients, 39% (n=43) had moderate HDRDI. Peak troponin was higher in patients with moderate HDRDI (6.8 ng/ml yes vs. 10.2 ng/ml no; p=0.037). There was a trend for fewer TMI events, but there were no differences (16% yes vs. 30% no; p=0.081). Conclusions: NSTE-ACS patients with moderate HDRDI have less cardiac injury than those without moderate HDRDI measured using a novel ECG derived method. These findings corroborate prior studies suggesting a possible cardioprotective effect of OSA in ACS patients via ischemic pre-condition. There was a trend for fewer TMI events in moderate HDRDI patients, but there was no statistical difference. Future research should explore the underlying physiologic mechanisms of this finding.

An annotated ventricular tachycardia (VT) alarm database: Toward a uniform standard for optimizing automated VT identification in hospitalized patients.

BACKGROUND: False ventricular tachycardia (VT) alarms are common during in-hospital electrocardiographic (ECG) monitoring. Prior research shows that the majority of false VT can be attributed to algorithm deficiencies. PURPOSE: The purpose of this study was: (1) to describe the creation of a VT database annotated by ECG experts and (2) to determine true vs. false VT using a new VT algorithm created by our group. METHODS: The VT algorithm was processed in 5320 consecutive ICU patients with 572,574 h of ECG and physiologic monitoring. A search algorithm identified potential VT, defined as: heart rate >100 beats/min, QRSs > 120 ms, and change in QRS morphology in >6 consecutive beats compared to the preceding native rhythm. Seven ECG channels, SpO2 , and arterial blood pressure waveforms were processed and loaded into a web-based annotation software program. Five PhD-prepared nurse scientists performed the annotations. RESULTS: Of the 5320 ICU patients, 858 (16.13%) had 22,325 VTs. After three levels of iterative annotations, a total of 11,970 (53.62%) were adjudicated as true, 6485 (29.05%) as false, and 3870 (17.33%) were unresolved. The unresolved VTs were concentrated in 17 patients (1.98%). Of the 3870 unresolved VTs, 85.7% (n = 3281) were confounded by ventricular paced rhythm, 10.8% (n = 414) by underlying BBB, and 3.5% (n = 133) had a combination of both. CONCLUSIONS: The database described here represents the single largest human-annotated database to date. The database includes consecutive ICU patients, with true, false, and challenging VTs (unresolved) and could serve as a gold standard database to develop and test new VT algorithms.

Premature ventricular complexes during continuous electrocardiographic monitoring in the intensive care unit: Occurrence rates and associated patient characteristics.

AIMS AND OBJECTIVES: This study examined the occurrence rate of specific types of premature ventricular complex (PVC) alarms and whether patient demographic and/or clinical characteristics were associated with PVC occurrences. BACKGROUND: Because PVCs can signal myocardial irritability, in-hospital electrocardiographic (ECG) monitors are typically configured to alert nurses when they occur. However, PVC alarms are common and can contribute to alarm fatigue. A better understanding of occurrences of PVCs could help guide alarm management strategies. DESIGN: A secondary quantitative analysis from an alarm study. METHODS: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed. Seven PVC alarm types (vendor-specific) were described, and included isolated, couplet, bigeminy, trigeminy, run PVC (i.e. VT >2), R-on-T and PVCs/min. Negative binomial and hurdle regression analyses were computed to examine the association of patient demographic and clinical characteristics with each PVC type. RESULTS: A total of 797,072 PVC alarms (45,271 monitoring hours) occurred in 446 patients, including six who had disproportionately high PVC alarm counts (40% of the total alarms). Isolated PVCs were the most frequent type (81.13%) while R-on-T were the least common (0.29%). Significant predictors associated with higher alarms rates: older age (isolated PVCs, bigeminy and couplets); male sex and presence of PVCs on the 12-lead ECG (isolated PVCs). Hyperkalaemia at ICU admission was associated with a lower R-on-T type PVCs. CONCLUSIONS: Only a few distinct demographic and clinical characteristics were associated with the occurrence rate of PVC alarms. Further research is warranted to examine whether PVCs were associated with adverse outcomes, which could guide alarm management strategies to reduce unnecessary PVC alarms. RELEVANCE TO CLINICAL PRACTICE: Targeted alarm strategies, such as turning off certain PVC-type alarms and evaluating alarm trends in the first 24 h of admission in select patients, might add to the current practice of alarm management.

Thoracic Impedance Pneumography-Derived Respiratory Alarms and Associated Patient Characteristics.

BACKGROUND: Respiratory rate (RR) alarms alert clinicians to a change in a patient's condition. However, RR alarms are common occurrences. To date, no study has examined RR alarm types and associated patient characteristics, which could guide alarm management strategies. OBJECTIVES: To characterize RR alarms by type, frequency, duration, and associated patient demographic and clinical characteristics. METHODS: A secondary data analysis of alarms generated with impedance pneumography in 461 adult patients admitted to either a cardiac, a medical/surgical, or a neurological intensive care unit (ICU). The RR alarms included high parameter limit (≥30 breaths/min), low parameter limit (≤5 breaths/min), and apnea (no breathing ≥20 s). The ICU type; total time monitored; and alarm type, frequency, and duration were evaluated. RESULTS: Of 159 771 RR alarms, parameter limit alarms (n = 140 975; 88.2%) were more frequent than apnea alarms (n = 18 796; 11.8%). High parameter limit alarms were most frequent (n = 131 827; 82.5%). After ICU monitoring time was controlled for, multivariate analysis showed that alarm rates were higher in patients in the cardiac and neurological ICUs (P = .001), patients undergoing mechanical ventilation (P = .005), and patients without a ventricular assist device or pacemaker (P = .02). Male sex was associated with low parameter limit (P = .01) and apnea (P = .005) alarms. CONCLUSION: High parameter limit RR alarms were most frequent. Factors associated with RR alarms included monitoring time, ICU type, male sex, and mechanical ventilation. Although these factors are not modifiable, these data could be used to guide management strategies.