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Introduction: The burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk populations and pre-emptive intervention using de-escalation techniques to prevent agitation. Time pressure, fluctuating work demands, and other systems-related factors pose challenges to efficient decision-making and adoption of best practice recommendations during an unfolding behavioural crisis. As such, we propose to design, develop and evaluate a computerised clinical decision support (CDS) system, Early Detection and Treatment to Reduce Events with Agitation Tool (ED-TREAT). We aim to identify patients at risk of agitation and guide ED clinicians through appropriate risk assessment and timely interventions to prevent agitation with a goal of minimising restraint use and improving patient experience and outcomes., Methods and Analysis: This study describes the formative evaluation of the health record embedded CDS tool. Under aim 1, the study will collect qualitative data to design and develop ED-TREAT using a contextual design approach and an iterative user-centred design process. Participants will include potential CDS users, that is, ED physicians, nurses, technicians, as well as patients with lived experience of restraint use for behavioural crisis management during an ED visit. We will use purposive sampling to ensure the full spectrum of perspectives until we reach thematic saturation. Next, under aim 2, the study will conduct a pilot, randomised controlled trial of ED-TREAT at two adult ED sites in a regional health system in the Northeast USA to evaluate the feasibility, fidelity and bedside acceptability of ED-TREAT. We aim to recruit a total of at least 26 eligible subjects under the pilot trial., Ethics and Dissemination: Ethical approval by the Yale University Human Investigation Committee was obtained in 2021 (HIC# 2000030893 and 2000030906). All participants will provide informed verbal consent prior to being enrolled in the study. Results will be disseminated through publications in open-access, peer-reviewed journals, via scientific presentations or through direct email notifications., Trial Registration Number: NCT04959279; Pre-results., Competing Interests: Competing interests: AHW reported receiving grants from National Institute of Health outside the conduct of the study. ERM reported receiving grants and contracts from the National Institute of Health, Agency for Healthcare Research and Quality, American Medical Association, and Centers for Medicare & Medicaid Services outside of this study. TM reported receiving grants from the National Institute of Health, Agency for Healthcare Research and Quality, and Google outside of this study. TM is a member of the Clinical Diversity Advisory Board at Woebot Health and Advisory Board at RACE Space. RH reported receiving salary support from the Centers for Medicare & Medicaid Services to develop, implement, and maintain clinical performance outcome measures that are publicly reported, in addition to receiving research support from the US Food and Drug Administration, Centers for Disease Control and Prevention, National Institute of Health, Connecticut Department of Public Health, and from the Community Health Network of Connecticut for her work as a medical consultant. All other authors declare no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder., Design: Pragmatic cluster randomized controlled trial (EMBED)., Setting: 18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform., Participants: 599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder., Intervention: A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral., Main Outcome Measures: Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework., Results: 1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01)., Conclusions: User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder., Trial Registration: ClinicalTrials.gov NCT03658642., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from the National Institute on Drug Abuse of the National Institutes of Health for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Despite considerable progress in tackling cardiovascular disease over the past 50 years, many gaps in the quality of care for cardiovascular disease remain. Multiple missed opportunities have been identified at every step in the prevention and treatment of cardiovascular disease, such as failure to make risk factor modifications, failure to diagnose cardiovascular disease, and failure to use proper evidence based treatments. With the digital transformation of medicine and advances in health information technology, clinical decision support (CDS) tools offer promise to enhance the efficiency and effectiveness of delivery of cardiovascular care. However, to date, the promise of CDS delivering scalable and sustained value for patient care in clinical practice has not been realized. This article reviews the evidence on key emerging questions around the development, implementation, and regulation of CDS with a focus on cardiovascular disease. It first reviews evidence on the effectiveness of CDS on healthcare process and clinical outcomes related to cardiovascular disease and design features associated with CDS effectiveness. It then reviews the barriers encountered during implementation of CDS in cardiovascular care, with a focus on unintended consequences and strategies to promote successful implementation. Finally, it reviews the legal and regulatory environment of CDS with specific examples for cardiovascular disease., Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and declare the following interests: HMK has received personal fees from UnitedHealth, Element Science, Aetna, Reality Labs, F-Prime, Siegfried & Jensen Law Firm, Martin/Baughman Law Firm, and Arnold and Porter Law Firm and grants from Johnson & Johnson; he is a co-founder of HugoHealth, a personal health information platform, and co-founder of Refactor Health, an enterprise healthcare artificial intelligence-augmented data management company, and he has contracts from Centers for Medicare & Medicaid Services Contracts, through Yale New Haven Hospital, to develop and maintain performance measures that are publicly reported outside the submitted work; YL is supported in part by the National Heart, Lung, and Blood Institute (K12HL138037) and the Yale Center for Implementation Science; ERM is supported in part by the National Institute On Drug Abuse of the National Institutes of Health under Award Number UH3DA047003. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Objectives: Adoption of emergency department (ED) initiation of buprenorphine (BUP) for opioid use disorder (OUD) into routine emergency care has been slow, partly due to clinicians' unfamiliarity with this practice and perceptions that it is complicated and time-consuming. To address these barriers and guide emergency clinicians through the process of BUP initiation, we implemented a user-centered computerized clinical decision support system (CDS). This study was conducted to assess the feasibility of implementation and to evaluate the preliminary efficacy of the intervention to increase the rate of ED-initiated BUP., Methods: An interrupted time series study was conducted in an urban, academic ED from April 2018 to February 2019 (preimplementation phase), March 2019 to August 2019 (implementation phase), and September 2019 to December 2019 (maintenance phase) to study the effect of the intervention on adult ED patients identified by a validated electronic health record (EHR)-based computable phenotype consisting of structured data consistent with potential cases of OUD who would benefit from BUP treatment. The intervention offers flexible CDS for identification of OUD, assessment of opioid withdrawal, and motivation of readiness to start treatment and automates EHR activities related to ED initiation of BUP (including documentation, orders, prescribing, and referral). The primary outcome was the rate of ED-initiated BUP. Secondary outcomes were launch of the intervention, prescription for naloxone at ED discharge, and referral for ongoing addiction treatment., Results: Of the 141,041 unique patients presenting to the ED over the preimplementation and implementation phases (i.e., the phases used in primary analysis), 906 (574 preimplementation and 332 implementation) met OUD phenotype and inclusion criteria. The rate of BUP initiation increased from 3.5% (20/574) in the preimplementation phase to 6.6% (22/332) in the implementation phase (p = 0.03). After the temporal trend of the number of physician's with X-waiver training and other covariates were adjusted for, the relative risk of BUP initiation rate was 2.73 (95% confidence interval [CI] = 0.62 to 12.0, p = 0.18). Similarly, the number of unique attendings who initiated BUP increased modestly 7/53 (13.0%) to 13/57 (22.8%, p = 0.10) after offering just-in-time training during the implementation period. The rate of naloxone prescribed at discharge also increased (6.5% preimplementation and 11.5% implementation; p < 0.01). The intervention received a system usability scale score of 82.0 (95% CI = 76.7 to 87.2)., Conclusion: Implementation of user-centered CDS at a single ED was feasible, acceptable, and associated with increased rates of ED-initiated BUP and naloxone prescribing in patients with OUD and a doubling of the number of unique physicians adopting the practice. We have implemented this intervention across several health systems in an ongoing trial to assess its effectiveness, scalability, and generalizability., (© 2020 The Authors. Academic Emergency Medicine published by Wiley Periodicals LLC on behalf of Society for Academic Emergency Medicine (SAEM).)

Introduction: The goal of this trial is to determine whether implementation of a user-centred clinical decision support (CDS) system can increase adoption of initiation of buprenorphine (BUP) into the routine emergency care of individuals with opioid use disorder (OUD)., Methods: A pragmatic cluster randomised trial is planned to be carried out in 20 emergency departments (EDs) across five healthcare systems over 18 months. The intervention consists of a user-centred CDS integrated into ED clinician electronic workflow and available for guidance to: (1) determine whether patients presenting to the ED meet criteria for OUD, (2) assess withdrawal symptoms and (3) ascertain and motivate patient willingness to initiate treatment. The CDS guides the ED clinician to initiate BUP and facilitate follow-up. The primary outcome is the rate of BUP initiated in the ED. Secondary outcomes are: (1) rates of receiving a referral, (2) fidelity with the CDS and (3) rates of clinicians providing any ED-initiated BUP, referral for ongoing treatment and receiving Drug Addiction Act of 2000 training. Primary and secondary outcomes will be analysed using generalised linear mixed models, with fixed effects for intervention status (CDS vs usual care), prespecified site and patient characteristics, and random effects for study site., Ethics and Dissemination: The protocol has been approved by the Western Institutional Review Board. No identifiable private information will be collected from patients. A waiver of informed consent was obtained for the collection of data for clinician prescribing and other activities. As a minimal risk implementation study of established best practices, an Independent Study Monitor will be utilised in place of a Data Safety Monitoring Board. Results will be reported in ClinicalTrials.gov and published in open-access, peer-reviewed journals, presented at national meetings and shared with the clinicians at participating sites via a broadcast email notification of publications., Trial Registration Number: NCT03658642; Pre-results., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Clinical decision support (CDS) hard-stop alerts-those in which the user is either prevented from taking an action altogether or allowed to proceed only with the external override of a third party-are increasingly common but can be problematic. To understand their appropriate application, we asked 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and unintended consequences of hard-stop alerts? (3) How do hard-stop alerts compare to soft-stop alerts?, Methods and Materials: Studies evaluating computerized hard-stop alerts in healthcare settings were identified from biomedical and computer science databases, gray literature sites, reference lists, and reviews. Articles were extracted for process outcomes, health outcomes, unintended consequences, user experience, and technical details., Results: Of 32 studies, 15 evaluated health outcomes, 16 process outcomes only, 10 user experience, and 4 compared hard and soft stops. Seventy-nine percent showed improvement in health outcomes and 88% in process outcomes. Studies reporting good user experience cited heavy user involvement and iterative design. Eleven studies reported on unintended consequences including avoidance of hard-stopped workflow, increased alert frequency, and delay to care. Hard stops were superior to soft stops in 3 of 4 studies., Conclusions: Hard stops can be effective and powerful tools in the CDS armamentarium, but they must be implemented judiciously with continuous user feedback informing rapid, iterative design. Investigators must report on associated health outcomes and unintended consequences when implementing IT solutions to clinical problems.

Background: The Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions., Objective: Our objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns., Methods: User-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage., Results: The Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool includes a patient injury evaluator based on the Canadian CT Head Rule and provides patient specific risks using pictographs with natural frequencies and cues for discussion about patient concerns., Conclusions: This tool was designed to align evidence-based practices about CT in minor head injury patients. It establishes trust, empowers active participation, and addresses patient concerns and uncertainty about their condition. We hypothesize that, when implemented, the Concussion or Brain Bleed app will support-not hinder-the clinician-patient relationship, safely reduce CT use, and improve the patient experience of care., (©Edward R Melnick, Erik P Hess, George Guo, Maggie Breslin, Kevin Lopez, Anthony J Pavlo, Fuad Abujarad, Seth M Powsner, Lori A Post. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.05.2017.)

Clinical practice guidelines are developed to reduce variations in clinical practice, with the goal of improving health care quality and cost. However, evidence-based practice guidelines face barriers to dissemination, implementation, usability, integration into practice, and use. The American College of Emergency Physicians (ACEP) clinical policies have been shown to be safe and effective and are even cited by other specialties. In spite of the benefits of the ACEP clinical policies, implementation of these clinical practice guidelines into physician practice continues to be a challenge. Translation of the ACEP clinical policies into real-time computerized clinical decision support systems could help address these barriers and improve clinician decision making at the point of care. The investigators convened an emergency medicine informatics expert panel and used a Delphi consensus process to assess the feasibility of translating the current ACEP clinical policies into clinical decision support content. This resulting consensus document will serve to identify limitations to implementation of the existing ACEP Clinical Policies so that future clinical practice guideline development will consider implementation into clinical decision support at all stages of guideline development., (Copyright © 2010 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.)