Preparing for an Artificial Intelligence-Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings.

BACKGROUND: As new technologies emerge, there is a significant shift in the way care is delivered on a global scale. Artificial intelligence (AI) technologies have been rapidly and inexorably used to optimize patient outcomes, reduce health system costs, improve workflow efficiency, and enhance population health. Despite the widespread adoption of AI technologies, the literature on patient engagement and their perspectives on how AI will affect clinical care is scarce. Minimal patient engagement can limit the optimization of these novel technologies and contribute to suboptimal use in care settings. OBJECTIVE: We aimed to explore patients' views on what skills they believe health care professionals should have in preparation for this AI-enabled future and how we can better engage patients when adopting and deploying AI technologies in health care settings. METHODS: Semistructured interviews were conducted from August 2020 to December 2021 with 12 individuals who were a patient in any Canadian health care setting. Interviews were conducted until thematic saturation occurred. A thematic analysis approach outlined by Braun and Clarke was used to inductively analyze the data and identify overarching themes. RESULTS: Among the 12 patients interviewed, 8 (67%) were from urban settings and 4 (33%) were from rural settings. A majority of the participants were very comfortable with technology (n=6, 50%) and somewhat familiar with AI (n=7, 58%). In total, 3 themes emerged: cultivating patients' trust, fostering patient engagement, and establishing data governance and validation of AI technologies. CONCLUSIONS: With the rapid surge of AI solutions, there is a critical need to understand patient values in advancing the quality of care and contributing to an equitable health system. Our study demonstrated that health care professionals play a synergetic role in the future of AI and digital technologies. Patient engagement is vital in addressing underlying health inequities and fostering an optimal care experience. Future research is warranted to understand and capture the diverse perspectives of patients with various racial, ethnic, and socioeconomic backgrounds.

Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach.

BACKGROUND: Significant investments and advances in health care technologies and practices have created a need for digital and data-literate health care providers. Artificial intelligence (AI) algorithms transform the analysis, diagnosis, and treatment of medical conditions. Complex and massive data sets are informing significant health care decisions and clinical practices. The ability to read, manage, and interpret large data sets to provide data-driven care and to protect patient privacy are increasingly critical skills for today's health care providers. OBJECTIVE: The aim of this study is to accelerate the appropriate adoption of data-driven and AI-enhanced care by focusing on the mindsets, skillsets, and toolsets of point-of-care health providers and their leaders in the health system. METHODS: To accelerate the adoption of AI and the need for organizational change at a national level, our multistepped approach includes creating awareness and capacity building, learning through innovation and adoption, developing appropriate and strategic partnerships, and building effective knowledge exchange initiatives. Education interventions designed to adapt knowledge to the local context and address any challenges to knowledge use include engagement activities to increase awareness, educational curricula for health care providers and leaders, and the development of a coaching and practice-based innovation hub. Framed by the Knowledge-to-Action framework, we are currently in the knowledge creation stage to inform the curricula for each deliverable. An environmental scan and scoping review were conducted to understand the current state of AI education programs as reported in the academic literature. RESULTS: The environmental scan identified 24 AI-accredited programs specific to health providers, of which 11 were from the United States, 6 from Canada, 4 from the United Kingdom, and 3 from Asian countries. The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. CONCLUSIONS: Technologies are advancing more rapidly than organizations, and professionals can adopt and adapt to them. To help shape AI practices, health care providers must have the skills and abilities to initiate change and shape the future of their discipline and practices for advancing high-quality care within the digital ecosystem. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30940.

Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

BACKGROUND: As the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education. OBJECTIVE: With a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs' curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs' effectiveness. METHODS: After the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career). RESULTS: Of the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective. CONCLUSIONS: This review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction.

A cohort study of unstable overdose patients treated with intravenous lipid emulsion therapy.

OBJECTIVES: Intravenous lipid emulsion (ILE) has been used increasingly over the last decade for a range of drug overdoses. Although the use of ILE in local anesthetic toxicity (LAST) is well established, the hemodynamic effectiveness of ILE in non-LAST poisonings is still unclear. Thus, the primary objective of this study was to examine a cohort of poisoned patients in whom ILE was administered. METHODS: Consecutive patients were identified by calls to a regional poison center from May 1, 2012 to May 30, 2014. Patients were enrolled if they ingested a drug, developed hemodynamic instability, failed conventional treatment, and received ILE therapy. Data were collected by medical record review. The primary outcome was the change in mean arterial pressure (MAP) in the first hour after ILE administration. Secondary outcomes included survival, length of stay, and the effect of drug class on patient outcome. RESULTS: Thirty-six patients were enrolled. Agents ingested included calcium channel blockers and beta blockers (10/36, 27.8%), tricyclic antidepressants (5/36, 13.9%), bupropion (3/36, 8.3%), and antiepileptic agents (1/36, 2.8%). Seventeen patients (47.2%) ingested multiple agents. Twenty-five patients survived (69.0%). Overall, MAP increased by 13.79 mm Hg (95% CI 1.43-26.15); this did not meet our a priori definition of clinical significance. CONCLUSIONS: Our study did not find a clinically important improvement in MAP after ILE administration. Until future research is done to more definitively study its efficacy, ILE should remain a potential treatment option for hemodynamically unstable overdose patients only after conventional therapy has failed.

Adult small bowel obstruction.

BACKGROUND: Small bowel obstruction (SBO) is a clinical condition that is often initially diagnosed and managed in the emergency department (ED). The high rates of potential complications that are associated with an SBO make it essential for the emergency physician (EP) to make a timely and accurate diagnosis. OBJECTIVES: The primary objective was to perform a systematic review and meta-analysis of the history, physical examination, and imaging modalities associated with the diagnosis of SBO. The secondary objectives were to identify the prevalence of SBO in prospective ED-based studies of adult abdominal pain and to apply Pauker and Kassirer's threshold approach to clinical decision-making to the diagnosis and management of SBO. METHODS: MEDLINE, EMBASE, major emergency medicine (EM) textbooks, and the bibliographies of selected articles were scanned for studies that assessed one or more components of the history, physical examination, or diagnostic imaging modalities used for the diagnosis of SBO. The selected articles underwent a quality assessment by two of the authors using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Data used to compile sensitivities and specificities were obtained from these studies and a meta-analysis was performed on those that examined the same historical component, physical examination technique, or diagnostic test. Separate information on the prevalence and management of SBO was used in conjunction with the meta-analysis findings of computed tomography (CT) to determine the test and treatment threshold. RESULTS: The prevalence of SBO in the ED was determined to be approximately 2% of all patients who present with abdominal pain. Having a previous history of abdominal surgery, constipation, abnormal bowel sounds, and/or abdominal distention on examination were the best history and physical examination predictors of SBO. X-ray was determined to be the least useful imaging modality for the diagnosis of SBO, with a pooled positive likelihood ratio (+LR) of 1.64 (95% confidence interval [CI] = 1.07 to 2.52). On the other hand, CT and magnetic resonance imaging (MRI) were both quite accurate in diagnosing SBO with +LRs of 3.6 (5- to 10-mm slices, 95% CI = 2.3 to 5.4) and 6.77 (95% CI = 2.13 to 21.55), respectively. Although limited to only a select number of studies, the use of ultrasound (US) was determined to be superior to all other imaging modalities, with a +LR of 14.1 (95% CI = 3.57 to 55.66) and a negative likelihood ratio (-LR) of 0.13 (95% CI = 0.08 to 0.20) for formal scans and a +LR of 9.55 (95% CI = 2.16 to 42.21) and a -LR of 0.04 (95% CI = 0.01 to 0.13) for beside scans. Using the CT results of the meta-analysis for the 5- to 10-mm slice subgroup as well as information on intravenous (IV) contrast reactions and nasogastric (NG) intubation management, the pretest probability threshold for further testing was determined to be 1.5%, and the pretest probability threshold for beginning treatment was determined to be 20.7%. CONCLUSIONS: The potentially useful aspects of the history and physical examination were limited to a history of abdominal surgery, constipation, and the clinical examination findings of abnormal bowel sounds and abdominal distention. CT, MRI, and US are all adequate imaging modalities to make the diagnosis of SBO. Bedside US, which can be performed by EPs, had very good diagnostic accuracy and has the potential to play a larger role in the ED diagnosis of SBO. More ED-focused research into this area will be necessary to bring about this change.