Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: In the intensive care unit (ICU), continuous patient monitoring is essential to detect critical changes in the patients’ health statuses and to guide therapy. The implementation of digital health technologies for patient monitoring may further improve patient safety. However, most monitoring devices today are still based on technologies from the 1970s. Objective: Aim of this study was to evaluate statements of ICU staff on the current patient monitoring and their expectations for future technological developments in order to investigate clinical requirements and barriers to the implementation of a future patient monitoring. Methods: This prospective study was conducted at three intensive care units of a German university hospital. Guideline-based interviews with ICU staff (5 physicians, 6 nurses and 4 respiratory therapists) were recorded, transcribed and analyzed using the grounded theory approach. Results: We identified twelve theories within three categories that reflect the requirements of a future patient monitoring from the view of ICU staff: I) Current situation: monitoring of vital parameters intuitive, but advanced features difficult to set up; graphical visualization preferred over numeric display; trend analysis not used in patient monitoring; insufficient alarm management due to lack of resources and unsatisfactory training leads to false alarms, induces stress and endangers patient safety; entanglement of monitoring cables endangers patients. II) Future situation: in an emergency, intuitive patient monitoring more important than functionality; wireless, non-invasive and interoperable monitoring sensors needed; small tablets as remote patient monitoring could mitigate noise pollution and optimize alarm management; ambivalent attitudes towards clinical decision support systems, but if plausible – to estimate its validity – it could reduce false alarms. III) Barriers to implementation: lack of trust in novel technology; fear of losing clinical skills and increasing workload despite novel technology; lack of awareness of available digital technologies. Conclusions: This is the first qualitative study on patient monitoring that involves core statements of ICU staff. Findings may foster research projects and accelerate medical product development. Focusing on user-derived findings and enhancing digital literacy on ICU may promote a rapid and sustainable implementation of digital health solutions for a future patient monitoring in the ICU. Clinical Trial: NCT03514173

Background: Due to demographic change and, more recently, coronavirus disease (COVID-19), the importance of modern intensive care units (ICU) is becoming apparent. One of the key components of an ICU is the continuous monitoring of patients' vital parameters. However, existing advances in informatics, signal processing, or engineering that could alleviate the burden on ICUs have not yet been applied. This could be due to the lack of user involvement in research and development. Objective: This study focused on the satisfaction of ICU staff with current patient monitoring and their suggestions for future improvements. We aimed to identify aspects of monitoring that interrupt patient care, display devices for remote monitoring, use cases for artificial intelligence (AI), and whether ICU staff members are willing to improve their digital literacy or contribute to the improvement of patient monitoring. We further aimed to identify differences in the responses of different professional groups. Methods: This survey study was performed with ICU staff from 4 ICUs of a German university hospital between November 2019 and January 2020. We developed a web-based 36-item survey questionnaire, by analyzing a preceding qualitative interview study with ICU staff, about the clinical requirements of future patient monitoring. Statistical analyses of questionnaire results included median values with their bootstrapped 95% confidence intervals, and chi-square tests to compare the distributions of item responses of the professional groups. Results: In total, 86 of the 270 ICU physicians and nurses completed the survey questionnaire. The majority stated they felt confident using the patient monitoring equipment, but that high rates of false-positive alarms and the many sensor cables interrupted patient care. Regarding future improvements, respondents asked for wireless sensors, a reduction in the number of false-positive alarms, and hospital standard operating procedures for alarm management. Responses to the display devices proposed for remote patient monitoring were divided. Most respondents indicated it would be useful for earlier alerting or when they were responsible for multiple wards. AI for ICUs would be useful for early detection of complications and an increased risk of mortality; in addition, the AI could propose guidelines for therapy and diagnostics. Transparency, interoperability, usability, and staff training were essential to promote the use of AI. The majority wanted to learn more about new technologies for the ICU and required more time for learning. Physicians had fewer reservations than nurses about AI-based intelligent alarm management and using mobile phones for remote monitoring. Conclusions: This survey study of ICU staff revealed key improvements for patient monitoring in intensive care medicine. Hospital providers and medical device manufacturers should focus on reducing false alarms, implementing hospital alarm standard operating procedures, introducing wireless sensors, preparing for the use of AI, and enhancing the digital literacy of ICU staff. Our results may contribute to the user-centered transfer of digital technologies into practice to alleviate challenges in intensive care medicine. Trial Registration: ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173

Supervised intake of the alcohol deterrent (AD) disulfiram has proven to be an effective adjunct to biopsychosocial alcoholism therapy for more than 60 years. This article summarizes disulfiram literature between 1937 and 2000 and reviews 13 clinical trials of disulfiram in alcoholism treatment from the years 2000 to 2008. After giving an update of general safety issues and recent case reports concerning safety problems with disulfiram, we focus on the introduction of psychotherapeutic application of supervised disulfiram. The results of our review show: (1) Disulfiram proved to be an effective therapeutic tool in all clinical studies published from 2000 to 2008. (2) Comparisons with other pharmacological agents - naltrexone, acamprosate, topiramate and gamma-hydroxybutyrate - indicate that disulfiram was equal in two trials but superior in the majority of trials. (3) Therapy programs that make use of the psychological effects of supervised disulfiram have - independently of the dose - better results than programs that neglect psychological effects. As a consequence, we suggest that supervised low-dose disulfiram (not more than 100mg/d), will show highest success when it is carefully integrated into psychotherapeutic alcoholism therapy. The major program of psychotherapy with disulfiram comprises the steps “Initial psychoeducation about the effect of disulfiram and its therapeutic implications”, “Advanced psychoeducation”, and “Disulfiram as coping skill and extension of repertoire of coping skills”. As psychological mechanisms of supervised disulfiram we suggest: (1) deterrence; (2) (auto)suggestion; (3) therapeutic ritual around (4) a frequently renewed active decision process; (5) continuous reinforcement of a sober lifestyle and development of new coping skills.

Purpose Supporting the provision of intensive care medicine through telehealth potentially improves process quality. This may improve patient recovery and long-term outcomes. We investigated the effectiveness of a multifaceted telemedical programme on the adherence to German quality indicators (QIs) in a regional network of intensive care units (ICUs) in Germany. Methods We conducted an investigator-initiated, large-scale, open-label, stepped-wedge cluster randomised controlled trial enrolling adult ICU patients with an expected ICU stay of ≥ 24 h. Twelve ICU clusters in Berlin and Brandenburg were randomly assigned to three sequence groups to transition from control (standard care) to the intervention condition (telemedicine). The quality improvement intervention consisted of daily telemedical rounds guided by eight German acute ICU care QIs and expert consultations. Co-primary effectiveness outcomes were patient-specific daily adherence (fulfilled yes/no) to QIs, assessed by a central end point adjudication committee. Analyses used mixed-effects logistic modelling adjusted for time. This study is completed and registered with ClinicalTrials.gov (NCT03671447). Results Between September 4, 2018, and March 31, 2020, 1463 patients (414 treated on control, 1049 on intervention condition) were enrolled at ten clusters, resulting in 14,783 evaluated days. Two randomised clusters recruited no patients (one withdrew informed consent; one dropped out). The intervention, as implemented, significantly increased QI performance for “sedation, analgesia and delirium” (adjusted odds ratio (99.375% confidence interval [CI]) 5.328, 3.395–8.358), “ventilation” (OR 2.248, 1.198–4.217), “weaning from ventilation” (OR 9.049, 2.707–30.247), “infection management” (OR 4.397, 1.482–13.037), “enteral nutrition” (OR 1.579, 1.032–2.416), “patient and family communication” (OR 6.787, 3.976–11.589), and "early mobilisation" (OR 3.161, 2.160–4.624). No evidence for a difference in adherence to “daily multi-professional and interdisciplinary clinical visits” between both conditions was found (OR 1.606, 0.780–3.309). Temporal trends related and unrelated to the intervention were detected. 149 patients died during their index ICU stay (45 treated on control, 104 on intervention condition). Conclusion A telemedical quality improvement program increased adherence to seven evidence-based German performance indicators in acute ICU care. These results need further confirmation in a broader setting of regional, non-academic community hospitals and other healthcare systems.

The aim of this study was to synthesize quantitative research that identified ranking lists of the most severe stressors of patients in the intensive care unit, as perceived by patients, relatives, and health care professionals (HCP). We conducted a systematic literature search in PubMed, MEDLINE, EMBASE, PsycInfo, CINAHL, and Cochrane Library from 1989 to 15 May 2020. Data were analyzed with descriptive and semi-quantitative methods to yield summarizing ranking lists of the most severe stressors. We synthesized the results of 42 prospective cross-sectional observational studies from different international regions. All investigations had assessed patient ratings. Thirteen studies also measured HCP ratings, and four studies included ratings of relatives. Data indicated that patients rate the severity of stressors lower than HCPs and relatives do. Out of all ranking lists, we extracted 137 stressor items that were most frequently ranked among the most severe stressors. After allocation to four domains, a group of clinical ICU experts sorted these stressors with good to excellent agreement according to their stress levels. Our results may contribute to improve HCPs’ and relatives’ understanding of patients’ perceptions of stressors in the ICU. The synthesized stressor rankings can be used for the development of new assessment instruments of stressors.

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