Alarm system management: evidence-based guidance encouraging direct measurement of informativeness to improve alarm response

Attention Among Health Care Professionals : A Scoping Review

BACKGROUND

The concept of attention can provide insight into the needs of clinicians and how health systems design can impact patient care quality and medical errors.

PURPOSE

To conduct a scoping review to 1) identify and characterize literature relevant to clinician attention; 2) compile metrics used to measure attention; and 3) create a framework of key concepts.

DATA SOURCES

Cumulated Index to Nursing and Allied Health Literature (CINAHL), Medline (PubMed), and Embase (Ovid) from 2001 to 26 February 2024.

STUDY SELECTION

English-language studies addressing health care worker attention in patient care. At least dual review and data abstraction.

DATA EXTRACTION

Article information, health care professional studied, practice environment, study design and intent, factor type related to attention, and metrics of attention used.

DATA SYNTHESIS

Of 6448 screened articles, 585 met inclusion criteria. Most studies were descriptive (n = 469) versus investigational (n = 116). More studies focused on barriers to attention (n = 387; 342 descriptive and 45 investigational) versus facilitators to improving attention (n = 198; 112 descriptive and 86 investigational). We developed a framework, grouping studies into 6 categories: 1) definitions of attention, 2) the clinical environment and its effect on attention, 3) personal factors affecting attention, 4) relationships between interventions or factors that affect attention and patient outcomes, 5) the effect of clinical alarms and alarm fatigue on attention, and 6) health information technology's effect on attention. Eighty-two metrics were used to measure attention.

LIMITATIONS

Does not synthesize answers to specific questions. Quality of studies was not assessed.

CONCLUSION

This overview may be a resource for researchers, quality improvement experts, and health system leaders to improve clinical environments. Future systematic reviews may synthesize evidence on metrics to measure attention and on the effectiveness of barriers or facilitators related to attention.

PRIMARY FUNDING SOURCE

None.

Auditory Sequences Presented With Spearcons Support Better Multiple Patient Monitoring Than Single-Patient Alarms: A Preclinical Simulation

OBJECTIVE

A study of auditory displays for simulated patient monitoring compared the effectiveness of two sound categories (alarm sounds indicating general risk categories from international alarm standard IEC 60601-1-8 versus event-specific sounds according to the type of nursing unit) and two configurations (single-patient alarms versus multi-patient sequences).

BACKGROUND

Fieldwork in speciality-focused high dependency units (HDU) indicated that auditory alarms are ambiguous and do not identify which patient has a problem. We tested whether participants perform better using auditory displays that identify the relevant patient and problem.

METHOD

During simulated patient monitoring of four patients in a respiratory HDU, 60 non-clinicians heard either (a) IEC risk categories as single-patient alarm sounds, (b) event-specific categories as single-patient alarm sounds, (c) IEC risk categories in multi-patient sequences or (d) event-specific categories in multi-patient sequences. Participants performed a perceptual-motor task while monitoring patients; after detecting abnormal events, they identified the patient and the event.

RESULTS

Participants hearing multi-patient sequences made fewer wrong patient identifications than participants hearing single-patient alarms. Advantages of event-specific categories emerged when IEC risk category sounds indicated more than one potential event. Even when IEC and event-specific sounds indicated the same unique event, spearcons supported better event identification than did auditory icon sounds.

CONCLUSION

Auditory displays that unambiguously convey which patient is having what problem dramatically improve monitoring performance in a preclinical HDU simulation.

APPLICATION

Time-compressed speech assists development of detailed risk categories needed in specific HDU contexts, and multi-patient sound sequences allow multiple patient wellbeing to be monitored.

Pediatric Characteristics Associated With Higher Rates of Monitor Alarms

Background: Continuous physiologic monitoring commonly is used in pediatric medical-surgical (med-surg) units and is associated with high alarm burden for clinicians. Characteristics of pediatric patients generating high rates of alarms on med-surg units are not known. Objective: To describe the demographic and clinical characteristics of pediatric med-surg patients associated with high rates of clinical alarms. Methods: We conducted a cross-sectional, single-site, retrospective study using existing clinical and alarm data from a children's hospital. Continuously monitored patients from med-surg units who had available alarm data were included. Negative binomial regression models were used to test the association between patient characteristics and the rate of clinical alarms per continuously monitored hour. Results: Our final sample consisted of 1,569 patients with a total of 38,501 continuously monitored hours generating 265,432 clinical alarms. Peripheral oxygen saturation (SpO2) low alarms accounted for 57.5% of alarms. Patients with medical complexity averaged 11% fewer alarms per hour than those without medical complexity (P < 0.01). Patients older than 5 years had up to 30% fewer alarms per hour than those who were younger than 5 years (P < 0.01). Patients using supplemental oxygen averaged 39% more alarms per hour compared with patients who had no supplemental oxygen use (P < 0.01). Patients at high risk for deterioration averaged 19% more alarms per hour than patients who were not high risk (P = 0.01). Conclusion: SpO2 alarms were the most common type of alarm in this study. The results highlight patient populations in pediatric medical-surgical units that may be high yield for interventions to reduce alarms. Most physiologic monitor alarms in pediatric medical-surgical (med-surg) units are not informative and likely could be safely eliminated to reduce noise and alarm fatigue.1-3 However, identifying and sustaining successful alarm-reduction strategies is a challenge. Research shows that 25% of patients in pediatric med-surg units produce almost three-quarters of all alarms.4 These patients are a potential high-yield target for alarm-reduction strategies; however, we are not aware of studies describing characteristics of pediatric patients generating high rates of alarms. The patient populations seen on pediatric med-surg units are diverse. Children of all ages are cared for on these units, with diagnoses ranging from acute respiratory infections, to management of chronic conditions, and to psychiatric conditions. Not all patients on pediatric med-surg units have physiologic parameters continuously monitored,4 but among those who do, understanding patient characteristics associated with high rates of alarms may help clinicians, healthcare technology management (HTM) professionals, and others working on alarm management strategies to develop targeted interventions. We conducted an exploratory retrospective study to describe patient characteristics associated with high rates of alarms in pediatric med-surg units.

The effect of intelligent management interventions in intensive care units to reduce false alarms: An integrative review

Objective

In intensive care units (ICU), frequent false alarms from medical equipment can cause alarm fatigue among nurses, which might lead to delayed or missed responses and increased risk of adverse patient events. This review was conducted to evaluate the effectiveness of intelligent management interventions to reduce false alarms in ICU.

Method

Following the framework of Whitmore and Knafl, the reviewers systematically searched six databases: PubMed, EMBASE, CINAHL, OVID, Cochrane Library, and Scopus, and studies included intelligent management of clinical alarms published in the English or Chinese language from the inception of each database to December 2022 were retrieved. The researchers used the PICOS framework to formulate the search strategy, developed keywords, screened literature, and assessed the studies' quality using the Joanna Briggs Institute-Meta-Analysis of Statistics, Assessment, and Review Instrument (JBI-MAStARI). The review was preregistered on PROSPERO (CRD42023411552).

Results

Seven studies met the inclusion criteria. The results showed that different interventions for intelligent management of alarms were beneficial in reducing the number of false alarms, the duration of alarms, the response time to important alarms for nurses, and the alarm fatigue levels among nurses. Positive results were found in practice after the application of the novel alarm management approaches.

Conclusion

Intelligent management intervention may be an effective way to reduce false alarms. The application of systems or tools for the intelligent management of clinical alarms is urgent in hospitals. To ensure more effective patient monitoring and less distress for nurses, more alarm management approaches combined with artificial intelligence will be needed in the future to enable accurate identification of critical alarms, ensure nurses are responding accurately to alarms, and make a real difference to alarm-ridden healthcare environments.

Creating safe environments: optimal acoustic alarming of laypeople in fire prevention

Hazards like fires occur regularly and can cost people's lives. Optimal auditory alarm signals enable laypeople to recognise dangers and to protect themselves. Existing fire alarm sound research focuses on alarm sounds and voice alerts presented singularly. We explored a combination of both and aimed to identify alarm signals that work optimally in everyday life. Thus, we conducted two online experiments: In Study 1 (N = 379), we tested eight alarm sounds regarding their typicality, their familiarity, their arousal, their valence, and their dominance. Siren-like alarm sounds were the most effective. In Study 2 (N = 206), we combined the four most effective alarm sounds with a voice alert. The voice alert reinforced ambiguity reduction, action motivation, and action intention. Hence, we suggest using alarm sounds with siren-like patterns. They should be combined with a voice alert to foster a quick and specific (target task-oriented) reaction.Practitioner summary: Warning laypeople is of great importance in time-critical hazards. In two remote testing studies (NTotal = 585), auditory alarm sounds with siren-like patterns resulted in the most distinct and emotional perception. Combining the alarm sound with a voice alert adds meaning to the alarm and fosters action intention.Abbreviations: DIN: Deutsches Institut für Normung [German Institute for Standardization]; ISO: International Organization for Standardization; Mixed MANOVA: mixed measures multivariate analysis of variance; rmMANOVA: repeated measures multivariate analysis of variance.

Patients with glenohumeral arthritis are more likely to be prescribed opioids in the emergency department or urgent care setting

OBJECTIVE

The objective is to quantify the rate of opioid and benzodiazepine prescribing for the diagnosis of shoulder osteoarthritis across a large healthcare system and to describe the impact of a clinical decision support intervention on prescribing patterns.

DESIGN

A prospective observational study.

SETTING

One large healthcare system.

PATIENTS AND PARTICIPANTS

Adult patients presenting with shoulder osteoarthritis.

INTERVENTIONS

A clinical decision support intervention that presents an alert to prescribers when patients meet criteria for increased risk of opioid use disorder.

MAIN OUTCOME MEASURE

The percentage of patients receiving an opioid or benzodiazepine, the percentage who had at least one risk factor for misuse, and the percent of encounters in which the prescribing decision was influenced by the alert were the main outcome measures.

RESULTS

A total of 5,380 outpatient encounters with a diagnosis of shoulder osteoarthritis were included. Twenty-nine percent (n = 1,548) of these encounters resulted in an opioid or benzodiazepine prescription. One-third of those who received a prescription had at least one risk factor for prescription misuse. Patients were more likely to receive opioids from the emergency department or urgent care facilities (40 percent of encounters) compared to outpatient facilities (28 percent) (p < .0001). Forty-four percent of the opioid prescriptions were for "potent opioids" (morphine milliequivalent conversion factor > 1). Of the 612 encounters triggering an alert, the prescribing decision was influenced (modified or not prescribed) in 53 encounters (8.7 percent). All but four (0.65 percent) of these encounters resulted in an opioid prescription.

CONCLUSION

Despite evidence against routine opioid use for osteoarthritis, one-third of patients with a primary diagnosis of glenohumeral osteoarthritis received an opioid prescription. Of those who received a prescription, over one-third had a risk factor for opioid misuse. An electronic clinic decision support tool influenced the prescription in less than 10 percent of encounters.

A grounded theory study of alarm fatigue among nurses in intensive care units

OBJECTIVES

The aim of this study was to explore the process of how nurses experienced and dealt with alarm fatigue in intensive care units based on Iranian nurses' perceptions and experiences.

BACKGROUND

Alarm fatigue is the overstimulation of senses due to the constant ringing of alarms in intensive care units. It is associated with nurses' desensitization to critical alarms that can directly influence patient safety and quality of care.

METHODS

A qualitative exploratory study using the grounded theory approach by Strauss and Corbin was carried out. Participants were 20 nurses working in intensive care units. The sampling process was started purposively and continued theoretically. Data were collected using semi-structured, in-depth, and individual interviews and continued to data saturation. The constant comparative analysis approach was used consisting of the following steps: open coding, developing concepts, analysing the context, entering the process into data analysis, integrating categories.

FINDINGS

The participants' main concern in the exposure to alarm fatigue was 'threat to personal balance'. The core category in this research was 'trying to create a holistic balance', which reflected a set of strategies that the nurses consistently and continuously used to deal with alarm fatigue and consisted of four main categories as follows: 'smart care', 'deliberate balancing', 'conditional prioritisation', and 'negligent performance'. Threat to personal balance was strengthened by 'inappropriate circuit of individual roles', 'distortion of the organisational structure', and 'insecurity of the infrastructure'. The consequences of this process was harm to the patient, burnout among nurse, and damage to the healthcare organisation.

CONCLUSIONS

The research findings have practical implications for healthcare management, policymaking, nursing education, research, and clinical practice. Mitigating staff shortages, improving staff competencies, enhancing nurses' authority for responding to alarms, modifying care routines, improving the physical environment, and removing problems related to alarm equipment can prevent alarm fatigue and its unappropriated consequences.

Alarm burden and the nursing care environment: a 213-hospital cross-sectional study

BACKGROUND

High rates of medical device alarms in hospitals are a well-documented threat to patient safety. Little is known about organisational features that may be associated with nurses' experience of alarm burden.

AIMS

To evaluate the association between nurse-reported alarm burden, appraisals of patient safety, quality of care and hospital characteristics.

METHODS

Secondary analysis of cross-sectional survey data from 3986 hospital-based direct-care registered nurses in 213 acute care hospitals in New York and Illinois, USA. We evaluated associations of alarm burden with appraisals of patient safety and quality of care and hospital characteristics (work environment, staffing adequacy, size, teaching status) using χ2 tests.

RESULTS

The majority of respondents reported feeling overwhelmed by alarms (83%), delaying their response to alarms because they were unable to step away from another patient/task (76%), and experiencing situations where a patient needed urgent attention but no one responded to an alarm (55%). Nurses on medical-surgical units reported these experiences at higher rates than nurses working in intensive care units (p<0.001). Alarm burden items were significantly associated with poorer nurse-reported patient safety, quality of care, staffing and work environment. Findings were most pronounced for situations where a patient needed urgent attention but no one responded to the alarm, which was frequently/occasionally experienced by 72% of those who rated their hospital's safety as poor versus 38% good, p<0.001; 80% who rated overall quality of care poor/fair versus 46% good/excellent, p<0.001 and 65% from poor work environments versus 42% from good work environments, p<0.001.

CONCLUSION

Most nurses reported feeling overwhelmed by medical device alarms, and our findings suggest that alarm burden may be more pronounced in hospitals with unfavourable working conditions and suboptimal quality and safety. Because this was a cross-sectional study, further research is needed to explore causal relationships and the role of modifiable systems factors in reducing alarm burden.

Toward alert triage: scalable qualitative coding framework for analyzing alert notes from the Telehealth Intervention Program for Seniors (TIPS)

Objective

Combined with mobile monitoring devices, telehealth generates overwhelming data, which could cause clinician burnout and overlooking critical patient status. Developing novel and efficient ways to correctly triage such data will be critical to a successful telehealth adoption. We aim to develop an automated classification framework of existing nurses' notes for each alert that will serve as a training dataset for a future alert triage system for telehealth programs.

Materials and Methods

We analyzed and developed a coding framework and a regular expression-based keyword match approach based on the information of 24 931 alert notes from a community-based telehealth program. We evaluated our automated alert triaging model for its scalability on a stratified sampling of 800 alert notes for precision and recall analysis.

Results

We found 22 717 out of 24 579 alert notes (92%) belonging to at least one of the 17 codes. The evaluation of the automated alert note analysis using the regular expression-based information extraction approach resulted in an average precision of 0.86 (SD = 0.13) and recall 0.90 (SD = 0.13).

Discussion

The high-performance results show the feasibility and the scalability potential of this approach in community-based, low-income older adult telehealth settings. The resulting coded alert notes can be combined with participants' health monitoring results to generate predictive models and to triage false alerts. The findings build steps toward developing an automated alert triaging model to improve the identification of alert types in remote health monitoring and telehealth systems.

Perceptually Discriminating the Highest Priority Alarms Reduces Response Time: A Retrospective Pre-Post Study at Four Hospitals

OBJECTIVE

Reduce nurse response time for emergency and high-priority alarms by increasing discriminability between emergency and all other alarms and suppressing redundant and likely false high-priority alarms in a secondary alarm notification system (SANS).

BACKGROUND

Emergency alarms are the most urgent, requiring immediate action to address a dangerous situation. They are clinician-triggered and have higher positive predictive value (PPV). High-priority alarms are automatically triggered and have lower PPV.

METHOD

We performed a retrospective pre-post study, analyzing data 15 months before and 25 months after a SANS redesign was implemented in four hospitals. For emergency alarms, we incorporated digitized human speech to distinguish them from automatically triggered alarms, leaving their onset and escalation pathways unchanged. For automatically triggered alarms, we suppressed some by delaying initial onset and escalation by 20 s. We used linear mixed models to assess the change in response time, Fisher's exact test for the proportion of response times longer than 120 s, and control charts for process stability.

RESULTS

Response time for emergency alarms decreased at all hospitals (main, from 26.91 s to 22.32 s, p < .001; cardiac, from 127.10 s to 52.43 s, p < .001; cancer, from 18.03 s to 15.39 s, p < .001). Improvements were sustained. Automatically triggered alarms decreased 25.0%. Response time for the three automatically triggered cardiac alarms increased at the four hospitals.

CONCLUSION

Auditory sound disambiguation was associated with a sustained reduced nurse response time for emergency alarms, but suppressing some high-priority automatically triggered alarms was not.

APPLICATION

Distinguishing and escalating urgent, actionable alarms with higher PPV improves response time.

Feasibility study of a clinical decision support system for polymedicated patients in primary care

Age-related changes in pharmacokinetics and pharmacodynamics, multimorbidity, frailty, and cognitive impairment represent challenges for drug treatments. Moreover, older adults are commonly exposed to polypharmacy, leading to increased risk of drug interactions and related adverse events, and higher costs for the healthcare systems. Thus, the complex task of prescribing medications to older polymedicated patients encourages the use of Clinical Decision Support Systems (CDSS). This paper evaluates the CDSS miniQ for identifying potentially inappropriate prescribing in poly-medicated older adults and assesses the usability and acceptability of the system in health care professionals, patients, and caregivers. The results of the study demonstrate that the miniQ system was useful for Primary Care physicians in significantly improving prescription, thereby reducing potentially inappropriate medication prescriptions for elderly patients. Additionally, the system was found to be beneficial for patients and their caregivers in understanding their medications, as well as usable and acceptable among healthcare professionals, patients, and caregivers, highlighting the potential to improve the prescription process and reduce errors, and enhancing the quality of care for elderly patients with polypharmacy, reducing adverse drug events, and improving medication management.

Establishment of a medical device adverse event management system for hospitals

Background

The management of medical device adverse event (MDAE) is one of the most important aspects of improving medical quality and safety management. Nonetheless, hospitals still lack standardized and unified initiatives to improve MDAE management.

Methods

This study, thus, established a MDAE monitoring system on May 1 in 2011 for suspected adverse events and designed a hospital-based dynamic warning system, aiming to standardize the process of MDAE handling and provide real-time monitoring for MDAEs in a hospital. This system was used in the First Affiliated Hospital of Zhejiang University School of Medicine. Numbers and the compound growth rate of MDAE reports from 2010 to 2020 were compared to test the effectiveness of the MDAE monitoring system. Numbers of MDAE reported to the National Adverse Event Monitoring System were also compared over 2013 to 2020, due to the loss of data before 2013 after shutdown of the old system. Efficacy and usability of the hospital-based dynamic warning system was then verified by analyzing risk and warning levels of MDAEs in 2020. Descriptive statistics was used for data analysis in this study.

Results

Results showed that the compound annual growth rates of MDAE reports and those submitted to the National Adverse Event Monitoring System from 2013 to 2020 were 35.0% and 31.5%, respectively. A standardized management of MDAE with full participant, timely response and effective feedback was formed in the hospital by establishment of the MDAE system.

Conclusions

This system effectively improved the monitoring level of MDAEs, helping to improve early detection, early warning, and early intervention of risk of medical device. This study may provide suggestions for medical institutions to establish a MDAE monitoring system, and may promote development of medical quality and safety management for hospitals to some extent.

A Bayesian Spatiotemporal Nowcasting Model for Public Health Decision-Making and Surveillance

As coronavirus disease 2019 (COVID-19) spread through the United States in 2020, states began to set up alert systems to inform policy decisions and serve as risk communication tools for the general public. Many of these systems included indicators based on an assessment of trends in numbers of reported cases. However, when cases are indexed by date of disease onset, reporting delays complicate the interpretation of trends. Despite a foundation of statistical literature with which to address this problem, these methods have not been widely applied in practice. In this paper, we develop a Bayesian spatiotemporal nowcasting model for assessing trends in county-level COVID-19 cases in Ohio. We compare the performance of our model with the approach used in Ohio and the approach included in decision support materials from the Centers for Disease Control and Prevention. We demonstrate gains in performance while still retaining interpretability using our model. In addition, we are able to fully account for uncertainty in both the time series of cases and the reporting process. While we cannot eliminate all of the uncertainty in public health surveillance and subsequent decision-making, we must use approaches that embrace these challenges and deliver more accurate and honest assessments to policy-makers.

Applying Human Factors Engineering to Address the Telemetry Alarm Problem in a Large Medical Center

OBJECTIVE

Address the alarm problem by redesigning, reorganizing, and reprioritizing to better discriminate alarm sounds and displays in a hospital.

BACKGROUND

Alarms in hospitals are frequently misunderstood, disregarded, and overridden.

METHOD

Discovery-oriented, intervention, and translational studies were conducted. Study objectives and measures varied, but had the shared goals of increasing positive predictive value (PPV) of critical alarms by reducing low-PPV alarms in the background, prioritizing alarms, redesigning alarm sounds to increase information content, and transparently conveying who initiated alarms. An alarm ontology was iteratively generated and refined until consensus was achieved.

RESULTS

The ontology distinguishes five levels of urgency that incorporate likely PPV, three categories for who initiates the alarm (hospital staff, patient, or machine), whether it is clinical or technical, and clinical functions.

CONCLUSION

This unique collaboration allowed us to make progress on the alarm problem by making unintuitive leaps, avoiding common missteps, and refuting conventional healthcare approaches.

APPLICATION

Hospitals can consistently redesign, reorganize, reprioritize, and better discriminate alarms by priority, PPV, and content to reduce nurse response times.

High expectancy influences the role of cognitive load in inattentional deafness during landing decision-making

Neglecting a critical auditory alarm is a major obstacle to maintaining a safe environment, especially in aviation. Earlier studies have indicated that tasks with a higher perceptual or cognitive load in the visual modality influence the processing of auditory stimuli. It is unclear, however, whether other factors, such as memory failure, active neglect, or expectancy influence the effect of cognitive load on auditory alarm detection sensitivity during aeronautical decision-making. In this study, we investigated this issue in three laboratory experiments using the technique of signal detection analysis, in which participants were asked to make a landing decision based on indicators of the instrument landing system while also trying to detect an audible alarm. We found that the sensitivity of auditory alarm detection was reduced under conditions of high cognitive load and that this effect persisted even when the auditory detection response occurred first (before the landing decision response) and when the probability of an auditory alarm was 40%. However, the sensitivity of auditory detection was not influenced by cognitive load under high expectancy conditions (60% probability of alarm presentation). Furthermore, the value of the response bias was reduced under high cognitive load conditions when the probability of an auditory alarm was low (20%). With an increase in the level of expectancy (40% and 60% probability of alarm presentation), it was found that cognitive load did not influence the response bias. These findings indicate that visual cognitive load affects the sensitivity to an auditory alarm only at a low expectancy level (20% and 40% probability of alarm presentation). The effect of cognitive load on the sensitivity to an auditory alarm was not due to memory failure or active neglect and the response bias was more sensitive to the expectancy factor.

Clinical Decision Support Systems

BACKGROUND

By combining up-to-date medical knowledge and steadily increasing patient data, a new level of medical care can emerge.

SUMMARY AND KEY MESSAGES

Clinical decision support systems (CDSSs) are an arising solution to handling rich data and providing them to health care providers in order to improve diagnosis and treatment. However, despite promising examples in many areas, substantial evidence for a thorough benefit of these support solutions is lacking. This may be due to a lack of general frameworks and diverse health systems around the globe. We therefore summarize the current status of CDSSs in medicine but also discuss potential limitations that need to be overcome in order to further foster future development and acceptance.

Nurses' use of auditory alarms and alerts in high dependency units: A field study

A fieldwork study conducted in six units of a major metropolitan Australian hospital revealed that nurses' attitudes towards alarms are influenced by each unit's physical layout and caseload. Additionally, nurses relied heavily on both non-actionable and actionable alarms to maintain their awareness of the status of their patients' wellbeing, and used auditory alarms beyond the scope of their intended design. Results suggest that before reducing or removing auditory alarms from the clinical environment to improve patient safety, it is important to understand how nurses in different clinical contexts use current alarm systems to extract meaningful information. Such an understanding could guide appropriate alarm reduction strategies and guide alternative design solutions to support nurses' situation awareness during monitoring.

Voice alerting as a medical alarm modality for next-generation patient monitoring: a randomised international multicentre trial

BACKGROUND

Acoustic alarms in medical devices are vital for patient safety. State-of-the-art patient monitoring alarms are indistinguishable and contribute to alarm fatigue. There are two promising new sound modalities for vital sign alarms. Auditory icons convey alarms as brief metaphorical sounds, and voice alerts transmit information using a clear-spoken language. We compared how reliably healthcare professionals identified alarms using these two modalities.

METHODS

This investigator-initiated computer-based multicentre simulation study included 28 anaesthesia providers who were asked to identify vital sign alarms in randomised order, once with voice alerts and once with auditory icons. We further assessed time to decision, diagnostic confidence, and perceived helpfulness. We analysed the results using mixed models, adjusted for possible confounders.

RESULTS

We assessed 14 alarms for each modality, resulting in 392 comparisons across all participants. Compared with auditory icons, healthcare providers had 58 times higher odds of correctly identifying alarms using voice alerts (odds ratio 58.0; 95% confidence interval [CI]: 25.1-133.6; P<0.001), made their decisions about 14 s faster (coefficient -13.9; 95% CI: -15.8 to -12.1 s; P<0.001), perceived higher diagnostic confidence (100% [392 of 392] vs 43% [169 of 392; P<0.001]), and rated voice alerts as more helpful (odds ratio 138.2; 95% CI: 64.9-294.1; P<0.001). The participants were able to identify significantly higher proportions of alarms with voice alerts (98.5%; P<0.001) and auditory icons (54.1%; P<0.001) compared with state-of-the-art alarms (17.9%).

CONCLUSIONS

Voice alerts were superior to auditory icons, and both were superior to current state-of-the-art auditory alarms. These findings demonstrate the potential that voice alerts hold for patient monitoring.

Quantifying the Impact of Infusion Alerts and Alarms on Nursing Workflows: A Retrospective Analysis

BACKGROUND

Smart infusion pumps affect workflows as they add alerts and alarms in an information-rich clinical environment where alarm fatigue is already a major concern. An analytic approach is needed to quantify the impact of these alerts and alarms on nursing workflows and patient safety.

OBJECTIVES

To analyze a detailed infusion dataset from a smart infusion pump system and identify contributing factors for infusion programming alerts, operational alarms, and alarm resolution times.

METHODS

We analyzed detailed infusion pump data across four hospitals in a health system for up to 1 year. The prevalence of alerts and alarms was grouped by infusion type and a selected list of 32 high-alert medications (HAMs). Logistic regression was used to explore the relationship between a set of risk factors and the occurrence of alerts and alarms. We used nonparametric tests to explore the relationship between alarm resolution times and a subset of predictor variables.

RESULTS

The study dataset included 745,641 unique infusions with a total of 3,231,300 infusion events. Overall, 28.7% of all unique infusions had at least one operational alarm, and 2.1% of all unique infusions had at least one programming alert. Alarms averaged two per infusion, whereas at least one alert happened in every 48 unique infusions. Eight percent of alarms took over 4 minutes to resolve. Intravenous fluid infusions had the highest rate of error-state occurrence. HAMs had 1.64 more odds for alerts than the rest of the infusions. On average, HAMs had a higher alert rate than maintenance fluids.

CONCLUSION

Infusion pump alerts and alarms impact clinical care, as alerts and alarms by design interrupt clinical workflow. Our study showcases how hospital system leadership teams can leverage infusion pump informatics to prioritize quality improvement and patient safety initiatives pertaining to infusion practices.

Lessons from the Glass Cockpit: Innovation in Alarm Systems to Support Cognitive Work

Nurses working in the hospital setting increasingly have become overburdened by managing alarms that, in many cases, provide low information value regarding patient health. The current trend, aided by disposable, wearable technologies, is to promote patient monitoring that does not require entering a patient's room. The development of telemetry alarms and middleware escalation devices adds to the continued growth of auditory, visual, and haptic alarms to the hospital environment but can fail to provide a more complete understanding of patient health. As we begin to innovate to both address alarm overload and improve patient management, perhaps using fundamentally different integration architectures, lessons from the aviation flight deck are worth considering. Commercial jet transport systems and their alarms have evolved slowly over many decades and have developed integration methods that account for operational context, provide multiple response protocol levels, and present a more integrated view of the airplane system state. We articulate three alarm system objectives: (1) supporting hazard management, (2) establishing context, and (3) supporting alarm prioritization. More generally, we present the case that alarm design in aviation can spur directions for innovation for telemetry monitoring systems in hospitals.

Reducing medical device alarms by an order of magnitude: A human factors approach

The intensive care unit (ICU) is one of the most technically advanced environments in healthcare, using a multitude of medical devices for drug administration, mechanical ventilation and patient monitoring. However, these technologies currently come with disadvantages, namely noise pollution, information overload and alarm fatigue—all caused by too many alarms. Individual medical devices currently generate alarms independently, without any coordination or prioritisation with other devices, leading to a cacophony where important alarms can be lost amongst trivial ones, occasionally with serious or even fatal consequences for patients. We have called this approach to the design of medical devices the single-device paradigm, and believe it is obsolete in modern hospitals where patients are typically connected to several devices simultaneously. Alarm rates of one alarm every four minutes for only the physiological monitors (as recorded in the ICUs of two hospitals contributing to this paper) degrades the quality of the patient’s healing environment and threatens patient safety by constantly distracting healthcare professionals. We outline a new approach to medical device design involving the application of human factors principles which have been successful in eliminating alarm fatigue in commercial aviation. Our approach comprises the networked-device paradigm, comprehensive alarms and humaniform information displays. Instead of each medical device alarming separately at the patient’s bedside, our proposed approach will integrate, prioritise and optimise alarms across all devices attached to each patient, display information more intuitively and hence increase alarm quality while reducing the number of alarms by an order of magnitude below current levels.

Identifying the fundamental structures and processes of care contributing to emergency general surgery quality using a mixed-methods Donabedian approach

BACKGROUND

Acute Care Surgery (ACS) was developed as a structured, team-based approach to providing round-the-clock emergency general surgery (EGS) care for adult patients needing treatment for diseases such as cholecystitis, gastrointestinal perforation, and necrotizing fasciitis. Lacking any prior evidence on optimizing outcomes for EGS patients, current implementation of ACS models has been idiosyncratic. We sought to use a Donabedian approach to elucidate potential EGS structures and processes that might be associated with improved outcomes as an initial step in designing the optimal model of ACS care for EGS patients.

METHODS

We developed and implemented a national survey of hospital-level EGS structures and processes by surveying surgeons or chief medical officers regarding hospital-level structures and processes that directly or indirectly impacted EGS care delivery in 2015. These responses were then anonymously linked to 2015 data from the American Hospital Association (AHA) annual survey, Medicare Provider Analysis and Review claims (MedPAR), 17 State Inpatient Databases (SIDs) using AHA unique identifiers (AHAID). This allowed us to combine hospital-level data, as reported in our survey or to the AHA, to patient-level data in an effort to further examine the role of EGS structures and processes on EGS outcomes. We describe the multi-step, iterative process utilizing the Donabedian framework for quality measurement that serves as a foundation for later work in this project.

RESULTS

Hospitals that responded to the survey were primarily non-governmental and located in urban settings. A plurality of respondent hospitals had fewer than 100 inpatient beds. A minority of the hospitals had medical school affiliations.

DISCUSSION

Our results will enable us to develop a measure of preparedness for delivering EGS care in the US, provide guidance for regionalized care models for EGS care, tiering of ACS programs based on the robustness of their EGS structures and processes and the quality of their outcomes, and formulate triage guidelines based on patient risk factors and severity of EGS disease.

CONCLUSIONS

Our work provides a template for team science applicable to research efforts combining primary data collection (i.e., that derived from our survey) with existing national data sources (i.e., SIDs and MedPAR).

Comparative Effectiveness of Best Practice Alerts with Active and Passive Presentations: A Retrospective Study

We assess the relationship of active or passive presentation of Best Practice Advisories (BPAs) for hospital clinicians with compliance rates of recommended actions. We identify the design characteristics of alerts that can be used to assess the effectiveness of design choices with superior usability. Alerts in Electronic Health Records (EHRs) are frequently overridden by healthcare providers. Identifying characteristics of effective alerts can increase the frequency that actions recommended in evidence-based care guidelines are done, reduce user frustration, and improve interface usability along with the willingness to use alerts. We conducted a retrospective analysis of data for 11 BPAs between June 2014 and May 2015. The outcome measure was the percent correspondence with recommended actions. A repeated measures regression model was used for the correlation of the BPA presentation type with the outcome measure. The BPA presentation type was significant such that the odds are 7.7 times greater that a recommended action would be taken by a provider with an active BPA presentation type after adjusting for whether an action was required. Active presentation alerts achieve higher compliance rates. CDS alerts that actively interrupted the provider’s workflow were associated with a higher compliance rate with recommended actions.

A Late Attempt to Involve End Users in the Design of Medication-Related Alerts: Survey Study

Background

When users of electronic medical records (EMRs) are presented with large numbers of irrelevant computerized alerts, they experience alert fatigue, begin to ignore alert information, and override alerts without processing or heeding alert recommendations. Anecdotally, doctors at our study site were dissatisfied with the medication-related alerts being generated, both in terms of volume being experienced and clinical relevance.

Objective

This study aimed to involve end users in the redesign of medication-related alerts in a hospital EMR, 4 years post implementation.

Methods

This work was undertaken at a private not-for-profit teaching hospital in Sydney, Australia. Since EMR implementation in 2015, the organization elected to implement all medication-related alert types available in the system for prescribers: allergy and intolerance alerts, therapeutic duplication alerts, pregnancy alerts, and drug-drug interaction alerts. The EMR included no medication administration alerts for nurses. To obtain feedback on current alerts and suggestions for redesign, a Web-based survey was distributed to all doctors and nurses at the site via hospital mailing lists.

Results

Despite a general dissatisfaction with alerts, very few end users completed the survey. In total, only 3.37% (36/1066) of doctors and 14.5% (60/411) of nurses took part. Approximately 90% (30/33) of doctors who responded held the view that too many alerts were triggered in the EMR. Doctors suggested that most alerts be removed and that alerts be more specific and less sensitive. In contrast, 97% (58/60) of the nurse respondents indicated that they would like to receive medication administration alerts in the EMR. Most nurses indicated that they would like to receive all the alert types available at all severity levels.

Conclusions

Attempting to engage with end users several years post implementation was challenging. Involving users so late in the implementation process may lead to clinicians viewing the provision of feedback to be futile. Seeking user feedback on usefulness, volume, and design of alerts is extremely valuable; however, we suggest this is undertaken early, preferably before system implementation.

Nursing staff's evaluation of facilitators and barriers during implementation of wireless nurse call systems in residential care facilities. A cross-sectional study

Background

Traditional nurse call systems used in residential care facilities rely on patients to summon assistance for routine or emergency needs. Wireless nurse call systems (WNCS) offer new affordances for persons unable to actively or consciously engage with the system, allowing detection of hazardous situations, prevention and timely treatment, as well as enhanced nurse workflows. This study aimed to explore facilitators and barriers of implementation of WNCSs in residential care facilities.

Methods

The study had a cross-sectional descriptive design. We collected data from care providers (n = 98) based on the Measurement Instrument for Determinants of Innovation (MIDI) framework in five Norwegian residential care facilities during the first year of WNCS implementation. The self-reporting MIDI questionnaire was adapted to the contexts. Descriptive statistics were used to explore participant characteristics and MIDI item and determinant scores. MIDI items to which ≥20% of participants disagreed/totally disagreed were regarded as barriers and items to which ≥80% of participants agreed/totally agreed were regarded as facilitators for implementation.

Results

More facilitators (n = 22) than barriers (n = 6) were identified. The greatest facilitators, reported by 98% of the care providers, were the expected outcomes: the importance and probability of achieving prompt call responses and increased safety, and the normative belief of unit managers. During the implementation process, 87% became familiar with the systems, and 86 and 90%, respectively regarded themselves and their colleagues as competent users of the WNCS. The most salient barriers, reported by 37%, were their lack of prior knowledge and that they found the WNCS difficult to learn. No features of the technology were identified as barriers.

Conclusions

Overall, the care providers gave a positive evaluation of the WNCS implementation. The barriers to implementation were addressed by training and practicing technological skills, facilitated by the influence and support by the manager and the colleagues within the residential care unit. WNCSs offer a range of advanced applications and services, and further research is needed as more WNCS functionalities are implemented into residential care services.

Continuous Cardiac Monitoring Policy Implementation: Three-year Sustained Decrease of Hospital Resource Utilization

Inappropriate cardiac monitoring leads to increased hospital resource utilization and alarm fatigue, which is ultimately detrimental to patient safety. Our institution implemented a continuous cardiac monitoring (CCM) policy that focused on selective monitoring for patients based on the American Heart Association (AHA) guidelines. The primary goal of this study was to perform a three-year median follow-up review on the longitudinal impact of a selective CCM policy on usage rates, length of stay (LOS), and mortality rates across the medical center. A secondary goal was to determine the effect of smaller-scale interventions focused on reeducating the nursing population on the importance of cardiac alarms. A system-wide policy was developed at The Ohio State University in December 2013 based on guidelines for selective CCM in all patient populations. Patients were stratified into Critical Class I, II, and III with 72 hours, 48 hours, or 36 hours of CCM, respectively. Pre- and post-implementation measures included average cardiac monitoring days (CMD), emergency department (ED) boarding rate, mortality rates, and LOS. A 12-week evaluation period was analyzed prior to, directly after, and three years after implementation. There was an overall decrease of 53.5% CMDs directly after implementation of selective CCM. This had remained stable at the three-year follow-up with slight increase of 0.5% (p = 0.2764). Subsequent analysis by hospital type revealed that the largest and most stable reductions in CMD were in noncardiac hospitals. The cardiac hospital CMD reduction was stable for roughly one year, then dipped into a lower stable level for nine months, then returned to the previous post-implementation levels. This change coincided with a smaller intervention to further reduce CMD in the cardiac hospital. There was no significant change in mortality rates with a slight decrease of 3.1% at follow-up (p = 0.781). Furthermore, there was no significant difference in LOS with a slight increase of 1.1% on follow-up (p = 0.649). However, there was a significant increase in ED boarding rate of 7.7% (p < 0.001) likely due to other hospital factors altering boarding times. Implementing selective CCM decreases average cardiac monitoring rate without affecting LOS or overall mortality rate. Selective cardiac monitoring is also a sustainable way to decrease overall hospital resource utilization and more appropriately focus on patient care.

Smooth or Stepped? Laboratory Comparison of Enhanced Sonifications for Monitoring Patient Oxygen Saturation

BACKGROUND

The pulse oximeter (PO) provides anesthesiologists with continuous visual and auditory information about a patient's oxygen saturation (SpO₂). However, anesthesiologists' attention is often diverted from visual displays, and clinicians may inaccurately judge SpO₂ values when relying on conventional PO auditory tones. We tested whether participants could identify SpO₂ value (e.g., "97%") better with acoustic enhancements that identified three discrete clinical ranges by either changing abruptly at two threshold values (stepped-effects) or changing incrementally with each percentage value of SpO₂ (smooth-effects).

METHOD

In all, 79 nonclinicians participated in a between-subjects experiment that compared performance of participants using the stepped-effects display with those who used the smooth-effects display. In both conditions, participants heard sequences of 72 tones whose pitch directly correlated to SpO₂ value, and whose value could change incrementally. Primary outcome was percentage of responses that correctly identified the absolute SpO₂ percentage, ±1, of the last pulse tone in each sequence.

RESULTS

Participants using the stepped-effects auditory tones identified absolute SpO₂ percentage more accurately (M = 53.7%) than participants using the smooth-effects tones (M = 47.9%, p = .038). Identification of range and detection of transitions between ranges showed even stronger advantages for the stepped-effects display (p < .005).

CONCLUSION

The stepped-effects display has more pronounced auditory cues at SpO₂ range transitions, from which participants can better infer absolute SpO₂ values. Further development of a smooth-effects display for this purpose is not necessary.

Using timbre to improve performance of larger auditory alarm sets

Identifiability and perceived urgency were compared for two sets of alarms in a healthcare inpatient setting. One contained currently used alarms where possible, with new sounds added as needed. The other was designed together, was more heterogenous, used timbre to encode intended similarities and explicitly encoded intended urgency across the set. Twenty nurses reported the identity and perceived urgency of the sounds in each set. Participants correctly identified the sound (0.89 vs. 0.77) and alarm category (0.93 vs. 0.82) more often in the new set than in the baseline set. In addition, multiple sounds in the new set were more identifiable. The new sounds also had a larger range of perceived urgency and better urgency match. The results indicate that timbre is well-suited to encode alarm groupings in larger alarm sets and that this, along with increased heterogeneity and explicit urgency mapping, improves alarm set performance. Practitioner summary: Clinical alarms are frequently misidentified. We found that making alarms more acoustically rich, using timbre to convey alarm groups, and explicitly encoding intended urgency improved identifiability and urgency match. These findings can be used to improve alarm performance across all safety-critical industries.

The impact of concurrent linguistic tasks on participants' identification of spearcons

Spearcons (time-compressed speech) may be a viable auditory display for patient monitoring; however, the impact of concurrent linguistic tasks remains unexamined. We tested whether different concurrent linguistic tasks worsen participants' identification of spearcons. Experiment 1 tested non-clinician participants' identification of multiple-patient spearcons representing 2 vital signs of 5 patients while participants performed no concurrent task, reading, or saying linguistic tasks. Experiment 2 tested non-clinician participants' identification of 48 single-patient spearcons while they performed no concurrent task, reading, listening, and saying linguistic tasks. In Experiment 1 the saying task worsened participants' identification of spearcons compared with no concurrent task or reading. In Experiment 2, the saying and listening tasks reduced participants' accuracy at identifying spearcons, but the reading task did not. Listening affected identification accuracy no differently than the saying task did. Concurrent auditory linguistic tasks worsen participants' identification of spearcons, probably due to auditory modality interference in verbal working memory.

A comparison of two designs for earcons conveying pulse oximetry information

We performed a randomised controlled trial comparing two kinds of earcons that could provide intermittent pulse oximetry information about a patient's oxygen saturation (SpO₂) and heart rate (HR). Timbre-earcons represented SpO₂ levels with different levels of timbre, and pitch-earcons with different levels of pitch. Both kinds of earcons represented HR with tremolo. Participants using pitch-earcons identified SpO₂ levels alone, and both SpO₂ plus HR levels, significantly better than participants using timbre-earcons: p < .001 in both cases. However, there was no difference between earcon conditions in how effectively HR was identified, p = .422. For both kinds of earcons, identification of SpO₂ levels was more compromised by simultaneous changes in HR than identification of HR levels was compromised by simultaneous changes in SpO₂, suggesting asymmetric integrality. Overall, pitch-earcons may provide a better intermittent auditory pulse oximetry display than timbre-earcons, especially for clinical contexts when quiet is needed.

Spearcon Sequences for Monitoring Multiple Patients: Laboratory Investigation Comparing Two Auditory Display Designs

OBJECTIVE

The aim was to compare the effectiveness of two auditory displays, implemented with spearcons (time-compressed speech), for monitoring multiple patients.

BACKGROUND

Sequences of sounds can convey information about patients' vital signs, such as oxygen saturation (SpO₂) and heart rate (HR). We tested whether participants could monitor five patients using spearcon-based sound sequences.

METHOD

A 2 × 3 within-subjects design was used. The first factor was interface, with two levels: the ALL interface used spearcons to convey vital signs for all five patients, whereas the ABN (abnormal) interface represented patients who had normal vital signs with a low-pitched single-tone sound and patients who had at least one abnormal vital sign with spearcons. The second factor was the number of patients who had at least one abnormal vital sign: there were one, two, or three such patients in each monitoring sequence. Participants were 40 nonclinicians.

RESULTS

Participants identified abnormal patients' SpO₂ and HR levels and located abnormal patients in the sound sequence more accurately with the ABN interface than the ALL interface. Accuracy declined as the number of abnormal patients increased. Participants associated ABN with easier identification of vital signs, resulting in higher ratings of confidence and pleasantness compared with ALL.

CONCLUSION

Sequences of spearcons may support effective eyes-free monitoring of multiple patients.

APPLICATION

Sequences of spearcons may be useful in monitoring multiple patients and the underlying design principles may extend to monitoring in other domains such as industrial process control or control of multiple autonomous vehicles.

Improving Human–Computer Interface Design through Application of Basic Research on Audiovisual Integration and Amplitude Envelope

Quality care for patients requires effective communication amongst medical teams. Increasingly, communication is required not only between team members themselves, but between members and the medical devices monitoring and managing patient well-being. Most human–computer interfaces use either auditory or visual displays, and despite significant experimentation, they still elicit well-documented concerns. Curiously, few interfaces explore the benefits of multimodal communication, despite extensive documentation of the brain’s sensitivity to multimodal signals. New approaches built on insights from basic audiovisual integration research hold the potential to improve future human–computer interfaces. In particular, recent discoveries regarding the acoustic property of amplitude envelope illustrate that it can enhance audiovisual integration while also lowering annoyance. Here, we share key insights from recent research with the potential to inform applications related to human–computer interface design. Ultimately, this could lead to a cost-effective way to improve communication in medical contexts—with signification implications for both human health and the burgeoning medical device industry.

Exploring the Effects of “Sound Shape” on Consumer Preference

Interfaces play a crucial role in a device’s success or failure. Although visual aspects generally receive more attention, findings from sonic interaction design increasingly illustrate the importance of auditory aesthetics in creating desirable products. Here we show that small changes to the amplitude envelope (i.e., “sound shape”) of tones affect user preference. Specifically, participants are willing to pay 9% more for products using sounds with decaying-amplitude envelopes rather than abruptly ending envelopes that are common in many device sounds. These findings hold important implications for cost-effective changes that could potentially improve a product’s desirability and perceived value.

Testing physiologic monitor alarm customization software to reduce alarm rates and improve nurses' experience of alarms in a medical intensive care unit

Background

Clinicians in intensive care units experience alarm fatigue related to frequent false and non-actionable alarms produced by physiologic monitors. To reduce non-actionable alarms, alarm settings may need to be customized for individual patients; however, nurses may not customize alarms because of competing demands and alarm fatigue.

Objective

To examine the effectiveness and acceptance of physiologic monitor software to support customization of alarms.

Methods

This pre/post intervention study was conducted in a 56-bed medical intensive care unit. IntelliVue^® Alarm Advisor customization support software for alarm limit violations was installed on all monitors and education on its use provided. For 2 months before and after implementation of the software, data were collected on patient characteristics from the electronic health record, alarm counts and duration from the monitoring system, and nurses’ experience of alarms from a survey.

Results

Medium-priority heart rate, respiratory rate, and arterial pressure alarms were significantly reduced after software implementation (9.3%, 11.8%, and 15.9% reduction respectively; p<0.001 for all). The duration of these alarms was also significantly shorter (7.8%, 13.3%, and 9.3% reduction respectively; p<0.05 for all). The number and duration of SpO₂ alarms did not decrease (p>0.05 for both). Patients post-intervention had worse Glasgow Coma Scale scores (p = 0.014), but otherwise were comparable to those pre-intervention. Nurses reported less time spent on non-actionable alarms post-intervention than pre-intervention (p = 0.026). Also lower post-intervention were the proportions of nurses who reported that alarms disturbed their workflow (p = 0.027) and who encountered a situation where an important alarm was ignored (p = 0.043). The majority (>50%) agreed that the software supported setting appropriate alarm limits and was easy to use.

Conclusion

Alarm customization software was associated with a reduction in alarms. Use of software to support nurses’ recognition of trends in patients’ alarms and facilitate changes to alarm settings may add value to alarm reduction initiatives.

Getting Better Hospital Alarm Sounds Into a Global Standard

The reserved set of audible alarm signals embodied within the global medical device safety standard, IEC 60601-1-8, is known to be problematic and in need of updating. The current alarm signals are not only suboptimal, but there is also little evidence beyond learnability (which is known to be poor) that demonstrates their performance in realistic and representative clinical environments. In this article, we describe the process of first designing and then testing potential replacement audible alarm signals for IEC 60601-1-8, starting with the design of several sets of candidate sounds and initial tests on learnability and localizability, followed by testing in simulated clinical environments. We demonstrate that in all tests, the alarm signals selected for further development significantly outperform the current alarm signals. We describe the process of collecting considerably more data on the performance of the new sounds than exists for the current sounds, which ultimately will be of use to end users. We also reflect on the process and practice of working with the relevant committees and other practical issues beyond the science, which also need constant attention if the alarms we have developed are to be included successfully in an updated version of the standard.

Gaps Between Alarm Capabilities and Decision-making Needs: An Observational Study of Detecting Patient Decompensation

Decompensation is a change in the overall ability to maintain physiological function in the presence of a stressor or disease. In the medical setting, clinicians utilize a wide range of technological tools to aid in their clinical decision making and to identify early warning signals for decompensation. However, many of these technologies have underperformed and are not aligned with the actual role of practitioners, resulting in unintended consequences and adverse events. The primary aim of this study is to explore how different nurses interpret early warning signs in order to anticipate decompensation. The secondary aim is to assess which technologies nurses rely on when anticipating decompensation, and if those technologies are adequately aiding them in their clinical decision making. Two researchers performed semi-structured ethnographic interviews that were recorded and transcribed during the summer of 2017. In total, 43 nurses were interviewed from different medical and surgical floors within the same hospital. Participants were asked questions focused on how they use and respond to alarms and how they anticipate patient decompensation. Constant Comparative Analysis was used to reveal patterns of responses between participants. Based on the qualitative analysis 6 major themes emerged:

 1. Anticipating patient decompensation requires creating a complete mental “picture of the patient” by the nurses

 2. Nurse-to-nurse communication and expertise is essential to understanding the patient’s history

 3. Warning signs for decompensation were largely determined by a patient’s baseline

 4. Change over time, or trends, is informative for anticipating decompensation. Numbers (regarding vital signs and labs) alone are not

 5. Consistent care of patients improved nurse’s confidence in decision making

 6. Anticipating decompensation requires “staying ahead of the machines

Our research suggests that there is a gap between the information practitioners need to accurately anticipate patient decompensation, and the information current alarm technologies provide. Alarms are the primary tool provided to nurses to aid them in detecting hazardous events, however, current alarms are not well-suited in supporting signals that anticipate patient decompensation before it happens.

Faster clinical response to the onset of adverse events: A wearable metacognitive attention aid for nurse triage of clinical alarms

Objective

This study evaluates the potential for improving patient safety by introducing a metacognitive attention aid that enables clinicians to more easily access and use existing alarm/alert information. It is hypothesized that this introduction will enable clinicians to easily triage alarm/alert events and quickly recognize emergent opportunities to adapt care delivery. The resulting faster response to clinically important alarms/alerts has the potential to prevent adverse events and reduce healthcare costs.

Materials and methods

A randomized within-subjects single-factor clinical experiment was conducted in a high-fidelity 20-bed simulated acute care hospital unit. Sixteen registered nurses, four at a time, cared for five simulated patients each. A two-part highly realistic clinical scenario was used that included representative: tasking; information; and alarms/alerts. The treatment condition introduced an integrated wearable attention aid that leveraged metacognition methods from proven military systems. The primary metric was time for nurses to respond to important alarms/alerts.

Results

Use of the wearable attention aid resulted in a median relative within-subject improvement for individual nurses of 118% (W = 183, p = 0.006). The top quarter of relative improvement was 3,303% faster (mean; 17.76 minutes reduced to 1.33). For all unit sessions, there was an overall 148% median faster response time to important alarms (8.12 minutes reduced to 3.27; U = 2.401, p = 0.016), with 153% median improvement in consistency across nurses (F = 11.670, p = 0.001).

Discussion and conclusion

Existing device-centric alarm/alert notification solutions can require too much time and effort for nurses to access and understand. As a result, nurses may ignore alarms/alerts as they focus on other important work. There has been extensive research on reducing alarm frequency in healthcare. However, alarm safety remains a top problem. Empirical observations reported here highlight the potential of improving patient safety by supporting the meta-work of checking alarms.

IDEA4PS: The Development of a Research-Oriented Learning Healthcare System

Leveraging opportunities to learn and then improve the delivery of care using experiences throughout the health care system is essential in efforts to transform health care delivery. The authors present the approach of one academic medical center in becoming a research-oriented Learning Healthcare System (ro-LHS). By reframing the role of research in improving outcomes, the organization was able to move beyond its focus on quality improvement to foster a culture in which feedback informs practice and research drives improvement. The patient safety learning laboratory, the Institute for the Design of Environments Aligned for Patient Safety, funded by the Agency for Healthcare Research and Quality, has provided foundational infrastructure to connect stakeholders across the medical center and university and conduct rigorous research in the context of practice. With this new focus, research now informs operations in a cycle of continuous improvement across the authors' ro-LHS.

Measurement of Physiological Monitor Alarm Accuracy and Clinical Relevance in Intensive Care Units

BACKGROUND

Alarm fatigue threatens patient safety by delaying or reducing clinician response to alarms, which can lead to missed critical events. Interventions to reduce alarms without jeopardizing patient safety target either inaccurate or clinically irrelevant alarms, so assessment of alarm accuracy and clinical relevance may enhance the rigor of alarm intervention studies done in clinical units.

OBJECTIVES

To (1) examine approaches used to measure accuracy and/or clinical relevance of physiological monitor alarms in intensive care units and (2) compare the proportions of inaccurate and clinically irrelevant alarms.

METHODS

An integrative review was used to systematically search the literature and synthesize resulting articles.

RESULTS

Twelve studies explicitly measuring alarm accuracy and/or clinical relevance on a clinical unit were identified. In the most rigorous studies, alarms were annotated retrospectively by obtaining alarm data and parameter waveforms rather than being annotated in real time. More than half of arrhythmia alarms in recent studies were inaccurate. However, contextual data were needed to determine alarms' clinical relevance. Proportions of clinically irrelevant alarms were high, but definitions of clinically irrelevant alarms often included inaccurate alarms.

CONCLUSIONS

Future studies testing interventions on clinical units should include alarm accuracy and/or clinical relevance as outcome measures. Arrhythmia alarm accuracy should improve with advances in technology. Clinical interventions should focus on reducing clinically irrelevant alarms, with careful consideration of how clinical relevance is defined and measured.

The heuristics of nurse responsiveness to critical patient monitor and ventilator alarms in a private room neonatal intensive care unit

Aim

Alarm fatigue is a well-recognized patient safety concern in intensive care settings. Decreased nurse responsiveness and slow response times to alarms are the potentially dangerous consequences of alarm fatigue. The aim of this study was to determine the factors that modulate nurse responsiveness to critical patient monitor and ventilator alarms in the context of a private room neonatal intensive care setting.

Methods

The study design comprised of both a questionnaire and video monitoring of nurse-responsiveness to critical alarms. The Likert scale questionnaire, comprising of 50 questions across thematic clusters (critical alarms, yellow alarms, perception, design, nursing action, and context) was administered to 56 nurses (90% response rate). Nearly 6000 critical alarms were recorded from 10 infants in approximately 2400 hours of video monitoring. Logistic regression was used to identify patient and alarm-level factors that modulate nurse-responsiveness to critical alarms, with a response being defined as a nurse entering the patient’s room within the 90s of the alarm being generated.

Results

Based on the questionnaire, the majority of nurses found critical alarms to be clinically relevant even though the alarms did not always mandate clinical action. Based on video observations, for a median of 34% (IQR, 20–52) of critical alarms, the nurse was already present in the room. For the remaining alarms, the response rate within 90s was 26%. The median response time was 55s (IQR, 37-70s). Desaturation alarms were the most prevalent and accounted for more than 50% of all alarms. The odds of responding to bradycardia alarms, compared to desaturation alarms, were 1.47 (95% CI = 1.21–1.78; <0.001) while that of responding to a ventilator alarm was lower at 0.35 (95% CI = 0.27–0.46; p <0.001). For every 20s increase in the duration of an alarm, the odds of responding to the alarm (within 90s) increased to 1.15 (95% CI = 1.1–1.2; p <0.001). The random effect per infant improved the fit of the model to the data with the response times being slower for infants suffering from chronic illnesses while being faster for infants who were clinically unstable.

Discussion

Even though nurses respond to only a fraction of all critical alarms, they consider the vast majority of critical and yellow alarms as useful and relevant. When notified of a critical alarm, they seek waveform information and employ heuristics in determining whether or not to respond to the alarm.

Conclusion

Amongst other factors, the category and duration of critical alarms along with the clinical status of the patient determine nurse-responsiveness to alarms.

Spearcons for Patient Monitoring: Laboratory Investigation Comparing Earcons and Spearcons

Objective We compared the effectiveness of single-tone earcons versus spearcons in conveying information about two commonly monitored vital signs: oxygen saturation and heart rate. Background The uninformative nature of many medical alarms-and clinicians' lack of response to alarms-is a widespread problem that can compromise patient safety. Auditory displays, such as earcons and spearcons (speech-based earcons), may help clinicians maintain awareness of patients' well-being and reduce their reliance on alarms. Earcons are short abstract sounds whose properties represent different types and levels of information, whereas spearcons are time-compressed spoken phrases that directly state their meaning. Listeners might identify patient vital signs more accurately with spearcons than with earcons. Method In Experiment 1 we compared how accurately 40 nonclinician participants using either (a) single-tone earcons differentiated by timbre and tremolo or (b) Cantonese spearcons recorded using a female Cantonese voice could identify both oxygen saturation and heart rate levels. In Experiment 2 we tested the identification performance of six further nonclinician participants with spearcons recorded using a male Cantonese voice. Results In Experiment 1, participants using spearcons identified both vital signs together more accurately than did participants using earcons. Participants using Cantonese spearcons also learned faster, completed trials faster, identified individual vital signs more accurately, and felt greater ease and more confident when identifying oxygen saturation levels. Experiment 2 verified the previous findings with male-voice Cantonese spearcons. Conclusion Participants identified vital signs more accurately using spearcons than with the single-tone earcons. Application Spearcons may be useful for patient monitoring in situations in which intermittently presented information is desirable.

Assessment of Nursing Response to a Real-Time Alerting Tool for Sepsis: A Provider Survey

Background

An information technology solution to provide a real-time alert to the nursing staff is necessary to assist in identifying patients who may have sepsis and avoid the devastating effects of its late recognition. The objective of this study is to evaluate the perception and adoption of sepsis clinical decision support.

Methods

A cross-sectional survey over a three-week period in 2015 was conducted in a major tertiary care facility. A sepsis alert was launched into five pilot units (including: surgery, medical-ICU, step-down, general medicine, and oncology). The pilot unit providers consisted of nurses from five inpatient units. Frequency, summary statistics, Chi-square, and nonparametric Kendall tests were used to determine the significance of the association and correlation between six evaluation domains.

Results

A total of 151 nurses responded (53% response rate). Questions included in the survey addressed the following domains: usability, accuracy, impact on workload, improved performance, provider preference, and physician response. The level of agreeability regarding physician response was significantly different between units (p=0.0136). There were significant differences for improved performance (p=0.0068) and physician response (p=0.0503) across levels of exposure to the alert. The strongest correlations were between questions related to usability and the domains of: accuracy (τ=0.64), performance (τ=0.66), and provider preference (τ=0.62), as well as, between the domains of: provider performance and provider preference (τ=0.67).

Discussion

Performance and preference of providers were evaluated to identify strengths and weaknesses of the sepsis alert. Effective presentation of the alert, including how and what is displayed, may offer better cognitive support in identifying and treating septic patients.

Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data

OBJECTIVE

The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability.

DESIGN

Observational cohort study.

SETTING

Twenty-four-bed trauma step-down unit.

PATIENTS

Two thousand one hundred fifty-three patients.

INTERVENTION

Noninvasive vital sign monitoring data (heart rate, respiratory rate, peripheral oximetry) recorded on all admissions at 1/20 Hz, and noninvasive blood pressure less frequently, and partitioned data into training/validation (294 admissions; 22,980 monitoring hours) and test sets (2,057 admissions; 156,177 monitoring hours). Alerts were vital sign deviations beyond stability thresholds. A four-member expert committee annotated a subset of alerts (576 in training/validation set, 397 in test set) as real or artifact selected by active learning, upon which we trained machine-learning algorithms. The best model was evaluated on test set alerts to enact online alert classification over time.

MEASUREMENTS AND MAIN RESULTS

The Random Forest model discriminated between real and artifact as the alerts evolved online in the test set with area under the curve performance of 0.79 (95% CI, 0.67-0.93) for peripheral oximetry at the instant the vital sign first crossed threshold and increased to 0.87 (95% CI, 0.71-0.95) at 3 minutes into the alerting period. Blood pressure area under the curve started at 0.77 (95% CI, 0.64-0.95) and increased to 0.87 (95% CI, 0.71-0.98), whereas respiratory rate area under the curve started at 0.85 (95% CI, 0.77-0.95) and increased to 0.97 (95% CI, 0.94-1.00). Heart rate alerts were too few for model development.

CONCLUSIONS

Machine-learning models can discern clinically relevant peripheral oximetry, blood pressure, and respiratory rate alerts from artifacts in an online monitoring dataset (area under the curve > 0.87).

Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system

BACKGROUND

Although alert fatigue is blamed for high override rates in contemporary clinical decision support systems, the concept of alert fatigue is poorly defined. We tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time.

METHODS

Retrospective cohort study using electronic health record data (both drug alerts and clinical practice reminders) from January 2010 through June 2013 from 112 ambulatory primary care clinicians. The cognitive overload hypotheses were that alert acceptance would be lower with higher workload (number of encounters, number of patients), higher work complexity (patient comorbidity, alerts per encounter), and more alerts low in informational value (repeated alerts for the same patient in the same year). The desensitization hypothesis was that, for newly deployed alerts, acceptance rates would decline after an initial peak.

RESULTS

On average, one-quarter of drug alerts received by a primary care clinician, and one-third of clinical reminders, were repeats for the same patient within the same year. Alert acceptance was associated with work complexity and repeated alerts, but not with the amount of work. Likelihood of reminder acceptance dropped by 30% for each additional reminder received per encounter, and by 10% for each five percentage point increase in proportion of repeated reminders. The newly deployed reminders did not show a pattern of declining response rates over time, which would have been consistent with desensitization. Interestingly, nurse practitioners were 4 times as likely to accept drug alerts as physicians.

CONCLUSIONS

Clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert. Reducing within-patient repeats may be a promising target for reducing alert overrides and alert fatigue.

The effectiveness of nurse education and training for clinical alarm response and management: a systematic review

AIMS AND OBJECTIVES

To identify the effectiveness of education interventions provided for nurses for clinical alarm response and management.

BACKGROUND

Some education has been undertaken to improve clinical alarm response, but the evidence for evaluating effectiveness for nurse education interventions is limited.

DESIGN

Systematic review.

METHODS

A systematic review of experimental studies published in English from 2005-2015 was conducted in four computerised databases (MEDLINE, EMBASE, CINAHL and Scopus). After identification, screening and appraisal using Joanna Briggs Institute instruments, quality research papers were selected, data extraction and analysis followed.

RESULTS

Five studies met the inclusion criteria for alarm response and no articles were concerned with clinical alarm education for management. All had different types and methods of interventions and statistical pooling was not possible. Response accuracy, response time and perceptions were consistent when different interventions were adopted. A positive effect was identified when learning about general alarms, single alarms, sequential alarms and medium-level alarms for learning as the primary task. Nurses who were musically trained had a faster and more accurate alarm response. Simulation interventions had a positive effect, but the effect of education provided in the care unit was greater. Overall, clinical alarm awareness was improved through education activities.

CONCLUSIONS

Nurses are the main users of healthcare alarms and work in complex environments with high numbers of alarms, including nuisance alarms and other factors. Alarm-related adverse events are common. The findings of a small number of experimental studies with diverse evidence included consideration of various factors when formulating education strategies. The factors which influence effectiveness of nurse education are nurse demographics, nurse participants with musical training, workload and characteristics of alarms. Education interventions based in clinical practice settings increase education effectiveness, although simulation can be effective. No study shows any type of intervention results in sustained improvement.

RELEVANCE TO CLINICAL PRACTICE

There are workload implications in education and the matching of load, number and type of alarms with nurse demographics which should be evaluated. There also needs to be a connection between education and the clinical setting to contribute to clinical alarm awareness for undergraduate nurses and practicing nurses. Education solely supported by employers is insufficient. Patient safety and long-term effects must be further explored.