Alarm Management in Intensive Care: Qualitative Triangulation Study.

BACKGROUND: The high number of unnecessary alarms in intensive care settings leads to alarm fatigue among staff and threatens patient safety. To develop and implement effective and sustainable solutions for alarm management in intensive care units (ICUs), an understanding of staff interactions with the patient monitoring system and alarm management practices is essential. OBJECTIVE: This study investigated the interaction of nurses and physicians with the patient monitoring system, their perceptions of alarm management, and smart alarm management solutions. METHODS: This explorative qualitative study with an ethnographic, multimethods approach was conducted in an ICU of a German university hospital. Using triangulation in data collection, 102 hours of field observations, 12 semistructured interviews with ICU staff members, and the results of a participatory task were analyzed. The data analysis followed an inductive, grounded theory approach. RESULTS: Nurses and physicians reported interacting with the continuous vital sign monitoring system for most of their work time and tasks. There were no established standards for alarm management; instead, nurses and physicians stated that alarms were addressed through ad hoc reactions, a practice they viewed as problematic. Staff members' perceptions of intelligent alarm management varied, but they highlighted the importance of understandable and traceable suggestions to increase trust and cognitive ease. CONCLUSIONS: Staff members' interactions with the omnipresent patient monitoring system and its alarms are essential parts of ICU workflows and clinical decision-making. Alarm management standards and workflows have been shown to be deficient. Our observations, as well as staff feedback, suggest that changes are warranted. Solutions for alarm management should be designed and implemented with users, workflows, and real-world data at the core.

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.

A brief questionnaire for measuring alarm fatigue in nurses and physicians in intensive care units.

When exposed to hundreds of medical device alarms per day, intensive care unit (ICU) staff can develop "alarm fatigue" (i.e., desensitisation to alarms). However, no standardised way of quantifying alarm fatigue exists. We aimed to develop a brief questionnaire for measuring alarm fatigue in nurses and physicians. After developing a list of initial items based on a literature review, we conducted 15 cognitive interviews with the target group (13 nurses and two physicians) to ensure that the items are face valid and comprehensible. We then asked 32 experts on alarm fatigue to judge whether the items are suited for measuring alarm fatigue. The resulting 27 items were sent to nurses and physicians from 15 ICUs of a large German hospital. We used exploratory factor analysis to further reduce the number of items and to identify scales. A total of 585 submissions from 707 participants could be analysed (of which 14% were physicians and 64% were nurses). The simple structure of a two-factor model was achieved within three rounds. The final questionnaire (called Charité Alarm Fatigue Questionnaire; CAFQa) consists of nine items along two scales (i.e., the "alarm stress scale" and the "alarm coping scale"). The CAFQa is a brief questionnaire that allows clinical alarm researchers to quantify the alarm fatigue of nurses and physicians. It should not take more than five minutes to administer.

Staff perspectives on the influence of patient characteristics on alarm management in the intensive care unit: a cross-sectional survey study.

BACKGROUND: High rates of clinical alarms in the intensive care unit can result in alarm fatigue among staff. Individualization of alarm thresholds is regarded as one measure to reduce non-actionable alarms. The aim of this study was to investigate staff's perceptions of alarm threshold individualization according to patient characteristics and disease status. METHODS: This is a cross-sectional survey study (February-July 2020). Intensive care nurses and physicians were sampled by convenience. Data was collected using an online questionnaire. RESULTS: Staff view the individualization of alarm thresholds in the monitoring of vital signs as important. The extent to which alarm thresholds are adapted from the normal range varies depending on the vital sign monitored, the reason for clinical deterioration, and the professional group asked. Vital signs used for hemodynamic monitoring (heart rate and blood pressure) were most subject to alarm individualizations. Staff are ambivalent regarding the integration of novel technological features into alarm management. CONCLUSIONS: All relevant stakeholders, including clinicians, hospital management, and industry, must collaborate to establish a "standard for individualization," moving away from ad hoc alarm management to an intelligent, data-driven alarm management. Making alarms meaningful and trustworthy again has the potential to mitigate alarm fatigue - a major cause of stress in clinical staff and considerable hazard to patient safety. TRIAL REGISTRATION: The study was registered at ClinicalTrials.gov (NCT03514173) on 02/05/2018.

A Standardized Clinical Data Harmonization Pipeline for Scalable AI Application Deployment (FHIR-DHP): Validation and Usability Study.

BACKGROUND: Increasing digitalization in the medical domain gives rise to large amounts of health care data, which has the potential to expand clinical knowledge and transform patient care if leveraged through artificial intelligence (AI). Yet, big data and AI oftentimes cannot unlock their full potential at scale, owing to nonstandardized data formats, lack of technical and semantic data interoperability, and limited cooperation between stakeholders in the health care system. Despite the existence of standardized data formats for the medical domain, such as Fast Healthcare Interoperability Resources (FHIR), their prevalence and usability for AI remain limited. OBJECTIVE: In this paper, we developed a data harmonization pipeline (DHP) for clinical data sets relying on the common FHIR data standard. METHODS: We validated the performance and usability of our FHIR-DHP with data from the Medical Information Mart for Intensive Care IV database. RESULTS: We present the FHIR-DHP workflow in respect of the transformation of "raw" hospital records into a harmonized, AI-friendly data representation. The pipeline consists of the following 5 key preprocessing steps: querying of data from hospital database, FHIR mapping, syntactic validation, transfer of harmonized data into the patient-model database, and export of data in an AI-friendly format for further medical applications. A detailed example of FHIR-DHP execution was presented for clinical diagnoses records. CONCLUSIONS: Our approach enables the scalable and needs-driven data modeling of large and heterogenous clinical data sets. The FHIR-DHP is a pivotal step toward increasing cooperation, interoperability, and quality of patient care in the clinical routine and for medical research.

Pleural effusions are associated with adverse outcomes after cardiac surgery: a propensity-matched analysis.

BACKGROUND: Pleural effusions commonly occur in patients recovering from cardiac surgery; however, the impact on outcomes is not well characterized. The purpose of this study is to characterize the clinical outcomes of cardiac surgery patients with pleural effusion. METHODS: All patients undergoing cardiac surgery between 2006 and 2019 at a tertiary care university hospital were included in this observational, cross-sectional analysis using propensity matching. RESULTS: Of 11,037 patients that underwent cardiac surgery during the study period, 6461 (58.5%) had no pleural effusion (Group 0), 3322 (30.1%) had pleural effusion only (Group 1), and 1254 (11.4%) required at least one secondary drainage procedure after the index operation (Group 2). After propensity matching, the mortality of patients who underwent secondary drainage procedures was 6.1% higher than in Group 1 (p < 0.001). Intensive care unit (ICU) stay was longer for those with pleural effusions (18 [IQR 9-32] days in Group 2, 10 [IQR 6-17] days for Group 1, and 7 [IQR 4-11] days for Group 0, p < 0.001). Patients with pleural effusions had a higher incidence of hemodialysis (246 [20.0%] in Group 2, 137 [11.1%] in Group 1, 98 [7.98%] in Group 0), and a longer ventilation time in the ICU (57 [IQR 21.0-224.0] hours in Group 2, 25.0 [IQR 14.0-58.0] hours in Group 1, 16.0 [IQR 10.0-29.0] hours in Group 0). CONCLUSION: Pleural effusions, especially those that require a secondary drainage procedure during recovery, are associated with significantly worse outcomes including increased mortality, longer length of stay, and higher complication rates. These insights may be of great interest to scientists, clinicians, and industry leaders alike to foster research into innovative methods for preventing and treating pleural effusions with the aim of improving outcomes for patients recovering from cardiac surgery.

The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study.

Intensive care units (ICU) are often overflooded with alarms from monitoring devices which constitutes a hazard to both staff and patients. To date, the suggested solutions to excessive monitoring alarms have remained on a research level. We aimed to identify patient characteristics that affect the ICU alarm rate with the goal of proposing a straightforward solution that can easily be implemented in ICUs. Alarm logs from eight adult ICUs of a tertiary care university-hospital in Berlin, Germany were retrospectively collected between September 2019 and March 2021. Adult patients admitted to the ICU with at least 24 h of continuous alarm logs were included in the study. The sum of alarms per patient per day was calculated. The median was 119. A total of 26,890 observations from 3205 patients were included. 23 variables were extracted from patients' electronic health records (EHR) and a multivariable logistic regression was performed to evaluate the association of patient characteristics and alarm rates. Invasive blood pressure monitoring (adjusted odds ratio (aOR) 4.68, 95%CI 4.15-5.29, p < 0.001), invasive mechanical ventilation (aOR 1.24, 95%CI 1.16-1.32, p < 0.001), heart failure (aOR 1.26, 95%CI 1.19-1.35, p < 0.001), chronic renal failure (aOR 1.18, 95%CI 1.10-1.27, p < 0.001), hypertension (aOR 1.19, 95%CI 1.13-1.26, p < 0.001), high RASS (aOR 1.22, 95%CI 1.18-1.25, p < 0.001) and scheduled surgical admission (aOR 1.22, 95%CI 1.13-1.32, p < 0.001) were significantly associated with a high alarm rate. Our study suggests that patient-specific alarm management should be integrated in the clinical routine of ICUs. To reduce the overall alarm load, particular attention regarding alarm management should be paid to patients with invasive blood pressure monitoring, invasive mechanical ventilation, heart failure, chronic renal failure, hypertension, high RASS or scheduled surgical admission since they are more likely to have a high contribution to noise pollution, alarm fatigue and hence compromised patient safety in ICUs.

The medical profession transformed by artificial intelligence: Qualitative study.

Background: Healthcaare delivery will change through the increasing use of artificial intelligence (AI). Physicians are likely to be among the professions most affected, though to what extent is not yet clear. Objective: We analyzed physicians' and AI experts' stances towards AI-induced changes. This concerned (1) physicians' tasks, (2) job replacement risk, and (3) implications for the ways of working, including human-AI interaction, changes in job profiles, and hierarchical and cross-professional collaboration patterns. Methods: We adopted an exploratory, qualitative research approach, using semi-structured interviews with 24 experts in the fields of AI and medicine, medical informatics, digital medicine, and medical education and training. Thematic analysis of the interview transcripts was performed. Results: Specialized tasks currently performed by physicians in all areas of medicine would likely be taken over by AI, including bureaucratic tasks, clinical decision support, and research. However, the concern that physicians will be replaced by an AI system is unfounded, according to experts; AI systems today would be designed only for a specific use case and could not replace the human factor in the patient-physician relationship. Nevertheless, the job profile and professional role of physicians would be transformed as a result of new forms of human-AI collaboration and shifts to higher-value activities. AI could spur novel, more interprofessional teams in medical practice and research and, eventually, democratization and de-hierarchization. Conclusions: The study highlights changes in job profiles of physicians and outlines demands for new categories of medical professionals considering AI-induced changes of work. Physicians should redefine their self-image and assume more responsibility in the age of AI-supported medicine. There is a need for the development of scenarios and concepts for future job profiles in the health professions as well as their education and training.

Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review.

Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms. With this systematic review, we are following the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist in order to summarise scientific efforts that aimed to develop IT systems to reduce alarm fatigue in ICUs. 69 peer-reviewed publications were included. The majority of publications targeted the avoidance of technically false alarms, while the remainder focused on prediction of patient deterioration or alarm presentation. The investigated alarm types were mostly associated with heart rate or arrhythmia, followed by arterial blood pressure, oxygen saturation, and respiratory rate. Most publications focused on the development of software solutions, some on wearables, smartphones, or headmounted displays for delivering alarms to staff. The most commonly used statistical models were tree-based. In conclusion, we found strong evidence that alarm fatigue can be alleviated by IT-based solutions. However, future efforts should focus more on the avoidance of clinically non-actionable alarms which could be accelerated by improving the data availability. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233461, identifier: CRD42021233461.

Utilizing Intensive Care Alarms for Machine Learning.

Alarms help to detect medical conditions in intensive care units and improve patient safety. However, up to 99% of alarms are non-actionable, i.e. alarm that did not trigger a medical intervention in a defined time frame. Reducing their amount through machine learning (ML) is hypothesized to be a promising approach to improve patient monitoring and alarm management. This retrospective study presents the technical and medical pre-processing steps to annotate alarms into actionable and non-actionable, creating a basis for ML applications.

Artificial Intelligence Competencies in Postgraduate Medical Training in Germany.

Routine medical care is to be transformed by the introduction of artificial intelligence (AI), requiring medical professionals to acquire a novel set of skills. We assessed the density of AI learning objectives and the availability of courses containing AI content in postgraduate medical education in Germany. The results reveal general paucity in AI learning objectives and content across (sub-)specialty training and continuing medical education (CME) in Germany. Innovative and regulatory solutions are needed to herald an era of physicians competent in navigating medical AI applications.

Artificial Intelligence in Undergraduate Medical Education.

AI will take on an increasingly important role in medicine. Therefore, AI competencies should be taught in medical school. We investigated the inventory of AI-related courses at German medical schools. The majority of faculty offer courses on AI, but mainly at the elective and introductory levels. Regarding the topic of AI, there is a gap in German medical education that should be closed.

Creation of an Evidence-Based Implementation Framework for Digital Health Technology in the Intensive Care Unit: Qualitative Study.

BACKGROUND: Digital health technologies such as continuous remote monitoring and artificial intelligence-driven clinical decision support systems could improve clinical outcomes in intensive care medicine. However, comprehensive evidence and guidelines for the successful implementation of digital health technologies into specific clinical settings such as the intensive care unit (ICU) are scarce. We evaluated the implementation of a remote patient monitoring platform and derived a framework proposal for the implementation of digital health technology in an ICU. OBJECTIVE: This study aims to investigate barriers and facilitators to the implementation of a remote patient monitoring technology and to develop a proposal for an implementation framework for digital health technology in the ICU. METHODS: This study was conducted from May 2018 to March 2020 during the implementation of a tablet computer-based remote patient monitoring system. The system was installed in the ICU of a large German university hospital as a supplementary monitoring device. Following a hybrid qualitative approach with inductive and deductive elements, we used the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change to analyze the transcripts of 7 semistructured interviews with clinical ICU stakeholders and descriptive questionnaire data. The results of the qualitative analysis, together with the findings from informal meetings, field observations, and previous explorations, provided the basis for the derivation of the proposed framework. RESULTS: This study revealed an insufficient implementation process due to lack of staff engagement and few perceived benefits from the novel solution. Further implementation barriers were the high staff presence and monitoring coverage in the ICU. The implementation framework includes strategies to be applied before and during implementation, targeting the implementation setting by involving all ICU stakeholders, assessing the intervention's adaptability, facilitating the implementation process, and maintaining a vital feedback culture. Setting up a unit responsible for implementation, considering the guidance of an implementation advisor, and building on existing institutional capacities could improve the institutional context of implementation projects in the ICU. CONCLUSIONS: Implementation of digital health in the ICU should involve a thorough preimplementation assessment of the ICU's need for innovation and its readiness to change, as well as an ongoing evaluation of the implementation conditions. Involvement of all stakeholders, transparent communication, and continuous feedback in an equal atmosphere are essential, but leadership roles must be clearly defined and competently filled. Our proposed framework may guide health care providers with concrete, evidence-based, and step-by-step recommendations for implementation practice, facilitating the introduction of digital health in intensive care. TRIAL REGISTRATION: ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173.

A Remote Patient-Monitoring System for Intensive Care Medicine: Mixed Methods Human-Centered Design and Usability Evaluation.

BACKGROUND: Continuous monitoring of vital signs is critical for ensuring patient safety in intensive care units (ICUs) and is becoming increasingly relevant in general wards. The effectiveness of health information technologies such as patient-monitoring systems is highly determined by usability, the lack of which can ultimately compromise patient safety. Usability problems can be identified and prevented by involving users (ie, clinicians). OBJECTIVE: In this study, we aim to apply a human-centered design approach to evaluate the usability of a remote patient-monitoring system user interface (UI) in the ICU context and conceptualize and evaluate design changes. METHODS: Following institutional review board approval (EA1/031/18), a formative evaluation of the monitoring UI was performed. Simulated use tests with think-aloud protocols were conducted with ICU staff (n=5), and the resulting qualitative data were analyzed using a deductive analytic approach. On the basis of the identified usability problems, we conceptualized informed design changes and applied them to develop an improved prototype of the monitoring UI. Comparing the UIs, we evaluated perceived usability using the System Usability Scale, performance efficiency with the normative path deviation, and effectiveness by measuring the task completion rate (n=5). Measures were tested for statistical significance using a 2-sample t test, Poisson regression with a generalized linear mixed-effects model, and the N-1 chi-square test. P<.05 were considered significant. RESULTS: We found 37 individual usability problems specific to monitoring UI, which could be assigned to six subcodes: usefulness of the system, response time, responsiveness, meaning of labels, function of UI elements, and navigation. Among user ideas and requirements for the UI were high usability, customizability, and the provision of audible alarm notifications. Changes in graphics and design were proposed to allow for better navigation, information retrieval, and spatial orientation. The UI was revised by creating a prototype with a more responsive design and changes regarding labeling and UI elements. Statistical analysis showed that perceived usability improved significantly (System Usability Scale design A: mean 68.5, SD 11.26, n=5; design B: mean 89, SD 4.87, n=5; P=.003), as did performance efficiency (normative path deviation design A: mean 8.8, SD 5.26, n=5; design B: mean 3.2, SD 3.03, n=5; P=.001), and effectiveness (design A: 18 trials, failed 7, 39% times, passed 11, 61% times; design B: 20 trials, failed 0 times, passed 20 times; P=.002). CONCLUSIONS: Usability testing with think-aloud protocols led to a patient-monitoring UI with significantly improved usability, performance, and effectiveness. In the ICU work environment, difficult-to-use technology may result in detrimental outcomes for staff and patients. Technical devices should be designed to support efficient and effective work processes. Our results suggest that this can be achieved by applying basic human-centered design methods and principles. TRIAL REGISTRATION: ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173.

Telemedicine in Intensive Care Units: Scoping Review.

BACKGROUND: The role of telemedicine in intensive care has been increasing steadily. Tele-intensive care unit (ICU) interventions are varied and can be used in different levels of treatment, often with direct implications for the intensive care processes. Although a substantial body of primary and secondary literature has been published on the topic, there is a need for broadening the understanding of the organizational factors influencing the effectiveness of telemedical interventions in the ICU. OBJECTIVE: This scoping review aims to provide a map of existing evidence on tele-ICU interventions, focusing on the analysis of the implementation context and identifying areas for further technological research. METHODS: A research protocol outlining the method has been published in JMIR Research Protocols. This review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). A core research team was assembled to provide feedback and discuss findings. RESULTS: A total of 3019 results were retrieved. After screening, 25 studies were included in the final analysis. We were able to characterize the context of tele-ICU studies and identify three use cases for tele-ICU interventions. The first use case is extending coverage, which describes interventions aimed at extending the availability of intensive care capabilities. The second use case is improving compliance, which includes interventions targeted at improving patient safety, intensive care best practices, and quality of care. The third use case, facilitating transfer, describes telemedicine interventions targeted toward the management of patient transfers to or from the ICU. CONCLUSIONS: The benefits of tele-ICU interventions have been well documented for centralized systems aimed at extending critical care capabilities in a community setting and improving care compliance in tertiary hospitals. No strong evidence has been found on the reduction of patient transfers following tele-ICU intervention. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19695.

Patient Monitoring Alarms in an Intensive Care Unit: Observational Study With Do-It-Yourself Instructions.

BACKGROUND: As one of the most essential technical components of the intensive care unit (ICU), continuous monitoring of patients' vital parameters has significantly improved patient safety by alerting staff through an alarm when a parameter deviates from the normal range. However, the vast number of alarms regularly overwhelms staff and may induce alarm fatigue, a condition recently exacerbated by COVID-19 and potentially endangering patients. OBJECTIVE: This study focused on providing a complete and repeatable analysis of the alarm data of an ICU's patient monitoring system. We aimed to develop do-it-yourself (DIY) instructions for technically versed ICU staff to analyze their monitoring data themselves, which is an essential element for developing efficient and effective alarm optimization strategies. METHODS: This observational study was conducted using alarm log data extracted from the patient monitoring system of a 21-bed surgical ICU in 2019. DIY instructions were iteratively developed in informal interdisciplinary team meetings. The data analysis was grounded in a framework consisting of 5 dimensions, each with specific metrics: alarm load (eg, alarms per bed per day, alarm flood conditions, alarm per device and per criticality), avoidable alarms, (eg, the number of technical alarms), responsiveness and alarm handling (eg alarm duration), sensing (eg, usage of the alarm pause function), and exposure (eg, alarms per room type). Results were visualized using the R package ggplot2 to provide detailed insights into the ICU's alarm situation. RESULTS: We developed 6 DIY instructions that should be followed iteratively step by step. Alarm load metrics should be (re)defined before alarm log data are collected and analyzed. Intuitive visualizations of the alarm metrics should be created next and presented to staff in order to help identify patterns in the alarm data for designing and implementing effective alarm management interventions. We provide the script we used for the data preparation and an R-Markdown file to create comprehensive alarm reports. The alarm load in the respective ICU was quantified by 152.5 (SD 42.2) alarms per bed per day on average and alarm flood conditions with, on average, 69.55 (SD 31.12) per day that both occurred mostly in the morning shifts. Most alarms were issued by the ventilator, invasive blood pressure device, and electrocardiogram (ie, high and low blood pressure, high respiratory rate, low heart rate). The exposure to alarms per bed per day was higher in single rooms (26%, mean 172.9/137.2 alarms per day per bed). CONCLUSIONS: Analyzing ICU alarm log data provides valuable insights into the current alarm situation. Our results call for alarm management interventions that effectively reduce the number of alarms in order to ensure patient safety and ICU staff's work satisfaction. We hope our DIY instructions encourage others to follow suit in analyzing and publishing their ICU alarm data.

Interdisciplinary Online Hackathons as an Approach to Combat the COVID-19 Pandemic: Case Study.

BACKGROUND: The COVID-19 outbreak has affected the lives of millions of people by causing a dramatic impact on many health care systems and the global economy. This devastating pandemic has brought together communities across the globe to work on this issue in an unprecedented manner. OBJECTIVE: This case study describes the steps and methods employed in the conduction of a remote online health hackathon centered on challenges posed by the COVID-19 pandemic. It aims to deliver a clear implementation road map for other organizations to follow. METHODS: This 4-day hackathon was conducted in April 2020, based on six COVID-19-related challenges defined by frontline clinicians and researchers from various disciplines. An online survey was structured to assess: (1) individual experience satisfaction, (2) level of interprofessional skills exchange, (3) maturity of the projects realized, and (4) overall quality of the event. At the end of the event, participants were invited to take part in an online survey with 17 (+5 optional) items, including multiple-choice and open-ended questions that assessed their experience regarding the remote nature of the event and their individual project, interprofessional skills exchange, and their confidence in working on a digital health project before and after the hackathon. Mentors, who guided the participants through the event, also provided feedback to the organizers through an online survey. RESULTS: A total of 48 participants and 52 mentors based in 8 different countries participated and developed 14 projects. A total of 75 mentorship video sessions were held. Participants reported increased confidence in starting a digital health venture or a research project after successfully participating in the hackathon, and stated that they were likely to continue working on their projects. Of the participants who provided feedback, 60% (n=18) would not have started their project without this particular hackathon and indicated that the hackathon encouraged and enabled them to progress faster, for example, by building interdisciplinary teams, gaining new insights and feedback provided by their mentors, and creating a functional prototype. CONCLUSIONS: This study provides insights into how online hackathons can contribute to solving the challenges and effects of a pandemic in several regions of the world. The online format fosters team diversity, increases cross-regional collaboration, and can be executed much faster and at lower costs compared to in-person events. Results on preparation, organization, and evaluation of this online hackathon are useful for other institutions and initiatives that are willing to introduce similar event formats in the fight against COVID-19.

Telemedicine in Intensive Care Units: Protocol for a Scoping Review.

BACKGROUND: Telemedicine has been deployed to address issues in intensive care delivery, as well as to improve outcome and quality of care. Implementation of this technology has been characterized by high variability. Tele-intensive care unit (ICU) interventions involve the combination of multiple technological and organizational components, as well as interconnections of key stakeholders inside the hospital organization. The extensive literature on the benefits of tele-ICUs has been characterized as heterogeneous. On one hand, positive clinical and economical outcomes have been shown in multiple studies. On the other hand, no tangible benefits could be detected in several cases. This could be due to the diverse forms of organizations and the fact that tele-ICU interventions are complex to evaluate. The implementation context of tele-ICUs has been shown to play an important role in the success of the technology. The benefits derived from tele-ICUs depend on the organization where it is deployed and how the telemedicine systems are applied. There is therefore value in analyzing the benefits of tele-ICUs in relation to the characteristics of the organization where it is deployed. To date, research on the topic has not provided a comprehensive overview of literature taking both the technology setup and implementation context into account. OBJECTIVE: We present a protocol for a scoping review of the literature on telemedicine in the ICU and its benefits in intensive care. The purpose of this review is to map out evidence about telemedicine in critical care in light of the implementation context. This review could represent a valuable contribution to support the development of tele-ICU technologies and offer perspectives on possible configurations, based on the implementation context and use case. METHODS: We have followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist and the recommendations of the Joanna Briggs Institute methodology for scoping reviews. The scoping review and subsequent systematic review will be completed by spring 2021. RESULTS: The preliminary search has been conducted. After removing all duplicates, we found 2530 results. The review can now be advanced to the next steps of the methodology, including literature database queries with appropriate keywords, retrieval of the results in a reference management tool, and screening of titles and abstracts. CONCLUSIONS: The results of the search indicate that there is sufficient literature to complete the scoping review. Upon completion, the scoping review will provide a map of existing evidence on tele-ICU systems given the implementation context. Findings of this research could be used by researchers, clinicians, and implementation teams as they determine the appropriate setup of new or existing tele-ICU systems. The need for future research contributions and systematic reviews will be identified. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19695.

Correction: Undergraduate Medical Competencies in Digital Health and Curricular Module Development: Mixed Methods Study.

[This corrects the article DOI: 10.2196/22161.].

Undergraduate Medical Competencies in Digital Health and Curricular Module Development: Mixed Methods Study.

BACKGROUND: Owing to an increase in digital technologies in health care, recently leveraged by the COVID-19 pandemic, physicians are required to use these technologies appropriately and to be familiar with their implications on patient care, the health system, and society. Therefore, medical students should be confronted with digital health during their medical education. However, corresponding teaching formats and concepts are still largely lacking in the medical curricula. OBJECTIVE: This study aims to introduce digital health as a curricular module at a German medical school and to identify undergraduate medical competencies in digital health and their suitable teaching methods. METHODS: We developed a 3-week curricular module on digital health for third-year medical students at a large German medical school, taking place for the first time in January 2020. Semistructured interviews with 5 digital health experts were recorded, transcribed, and analyzed using an abductive approach. We obtained feedback from the participating students and lecturers of the module through a 17-item survey questionnaire. RESULTS: The module received overall positive feedback from both students and lecturers who expressed the need for further digital health education and stated that the field is very important for clinical care and is underrepresented in the current medical curriculum. We extracted a detailed overview of digital health competencies, skills, and knowledge to teach the students from the expert interviews. They also contained suggestions for teaching methods and statements supporting the urgency of the implementation of digital health education in the mandatory curriculum. CONCLUSIONS: An elective class seems to be a suitable format for the timely introduction of digital health education. However, a longitudinal implementation in the mandatory curriculum should be the goal. Beyond training future physicians in digital skills and teaching them digital health's ethical, legal, and social implications, the experience-based development of a critical digital health mindset with openness to innovation and the ability to assess ever-changing health technologies through a broad transdisciplinary approach to translate research into clinical routine seem more important. Therefore, the teaching of digital health should be as practice-based as possible and involve the educational cooperation of different institutions and academic disciplines.