OBJECTIVE: The American Medical Informatics Association (AMIA) Task Force on Diversity, Equity, and Inclusion (DEI) was established to address systemic racism and health disparities in biomedical and health informatics, aligning with AMIA's mission to transform healthcare. AMIA's DEI initiatives were spurred by member voices responding to police brutality and COVID-19's impact on Black/African American communities. MATERIALS AND METHODS: The Task Force, consisting of 20 members across 3 groups aligned with AMIA's 2020-2025 Strategic Plan, met biweekly to develop DEI recommendations with the help of 16 additional volunteers. These recommendations were reviewed, prioritized, and presented to the AMIA Board of Directors for approval. RESULTS: In 9 months, the Task Force (1) created a logic model to support workforce diversity and raise AMIA's DEI awareness, (2) conducted an environmental scan of other associations' DEI activities, (3) developed a DEI framework for AMIA meetings, (4) gathered member feedback, (5) cultivated DEI educational resources, (6) created a Board nominations and diversity session, (7) reviewed the Board's Strategic Planning for DEI alignment, (8) led a program to increase diversity at the 2020 AMIA Virtual Annual Symposium, and (9) standardized socially-assigned race and ethnicity data collection. DISCUSSION: The Task Force proposed actionable recommendations that focused on AMIA's role in addressing systemic racism and health equity, helping the organization understand its member diversity. CONCLUSION: This work supported marginalized groups, broadened the research agenda, and positioned AMIA as a DEI leader while reinforcing the need for ongoing transformation within informatics.

OBJECTIVES: In 2023, AMIA's Inclusive Language and Context Style Guidelines (the "Guidelines") were approved by the Board of Directors and made a publicly available resource. This work began in 2021 through AMIA's DEI Task Force and subsequent DEI Committee; many members provided input, feedback, and time to create the Guidelines. In this paper, the authors provide a transparent account of the origin, development, contents, and dissemination of the Guidelines and share plans for their future development and use. MATERIALS AND METHODS: Our approach to drafting, refining, and distributing the Guidelines included consulting existing language guides, AMIA member reviews, external expert reviews, webinars, and workshops. Through an iterative approach to drafting and refining the Guidelines, the authors consulted relevant language guidelines and many experts throughout and beyond the AMIA community. RESULTS: The Inclusive Language Context Guidelines were formally approved by the AMIA Board of Directors on February 15, 2023. The Guidelines included four principles to be considered in scientific communications: Plurality, Precision, Transparency, and Destigmatization. DISCUSSION: A moment of vulnerability where an AMIA member raised concerns about the use of harmful language during a presentation resulted in the creation of a principled approach to support inclusive language within biomedical and health informatics communications. We envision that the Guidelines will support health equity by challenging dominant public narratives around health, fostering stronger interdisciplinary collaboration and critical thinking about the impact of language, and creating a more welcoming environment for the broader AMIA community. This work could not have been completed without the support of many AMIA members and other researchers in biomedical and health informatics. The Guidelines are a living document that will continue to be updated with input and feedback from the AMIA community into the future.

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging. OBJECTIVES: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients. MATERIALS AND METHODS: In May 2023, the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and the American Medical Informatics Association co-sponsored a working group on AI in healthcare. In August 2023, there were 4 webinars on AI topics and a 2-day workshop in September 2023 for consensus-building. The event included over 200 industry stakeholders, including clinicians, software developers, academics, ethicists, attorneys, government policy experts, scientists, and patients. The goal was to identify challenges associated with the trusted use of AI-enabled CDS in medical practice. Key issues were identified, and solutions were proposed through qualitative analysis and a 4-month iterative consensus process. RESULTS: Our work culminated in several key recommendations: (1) building safe and trustworthy systems; (2) developing validation, verification, and certification processes for AI-CDS systems; (3) providing a means of safety monitoring and reporting at the national level; and (4) ensuring that appropriate documentation and end-user training are provided. DISCUSSION: AI-enabled Clinical Decision Support (AI-CDS) systems promise to revolutionize healthcare decision-making, necessitating a comprehensive framework for their development, implementation, and regulation that emphasizes trustworthiness, transparency, and safety. This framework encompasses various aspects including model training, explainability, validation, certification, monitoring, and continuous evaluation, while also addressing challenges such as data privacy, fairness, and the need for regulatory oversight to ensure responsible integration of AI into clinical workflow. CONCLUSIONS: Achieving responsible AI-CDS systems requires a collective effort from many healthcare stakeholders. This involves implementing robust safety, monitoring, and transparency measures while fostering innovation. Future steps include testing and piloting proposed trust mechanisms, such as safety reporting protocols, and establishing best practice guidelines.

OBJECTIVES: Advances in informatics research come from academic, nonprofit, and for-profit industry organizations, and from academic-industry partnerships. While scientific studies of commercial products may offer critical lessons for the field, manuscripts authored by industry scientists are sometimes categorically rejected. We review historical context, community perceptions, and guidelines on informatics authorship. PROCESS: We convened an expert panel at the American Medical Informatics Association 2022 Annual Symposium to explore the role of industry in informatics research and authorship with community input. The panel summarized session themes and prepared recommendations. CONCLUSIONS: Authorship for informatics research, regardless of affiliation, should be determined by International Committee of Medical Journal Editors uniform requirements for authorship. All authors meeting criteria should be included, and categorical rejection based on author affiliation is unethical. Informatics research should be evaluated based on its scientific rigor; all sources of bias and conflicts of interest should be addressed through disclosure and, when possible, methodological mitigation.

After 25 years of service to the American Medical Informatics Association (AMIA), Ms Karen Greenwood, the Executive Vice President and Chief Operating Officer, is leaving the organization. In this perspective, we reflect on her accomplishments and her effect on the organization and the field of informatics nationally and globally. We also express our appreciation and gratitude for Ms Greenwood's role at AMIA.

OBJECTIVE: To conduct a systematic review identifying workplace interventions that mitigate physician burnout related to the digital environment including health information technologies (eg, electronic health records) and decision support systems) with or without the application of advanced analytics for clinical care. MATERIALS AND METHODS: Literature published from January 1, 2007 to June 3, 2020 was systematically reviewed from multiple databases and hand searches. Subgroup analysis identified relevant physician burnout studies with interventions examining digital tool burden, related workflow inefficiencies, and measures of burnout, stress, or job satisfaction in all practice settings. RESULTS: The search strategy identified 4806 citations of which 81 met inclusion criteria. Thirty-eight studies reported interventions to decrease digital tool burden. Sixty-eight percent of these studies reported improvement in burnout and/or its proxy measures. Burnout was decreased by interventions that optimized technologies (primarily electronic health records), provided training, reduced documentation and task time, expanded the care team, and leveraged quality improvement processes in workflows. DISCUSSION: The contribution of digital tools to physician burnout can be mitigated by careful examination of usability, introducing technologies to save or optimize time, and applying quality improvement to workflows. CONCLUSION: Physician burnout is not reduced by technology implementation but can be mitigated by technology and workflow optimization, training, team expansion, and careful consideration of factors affecting burnout, including specialty, practice setting, regulatory pressures, and how physicians spend their time.

The rapidly evolving science about the Coronavirus Disease 2019 (COVID-19) pandemic created unprecedented health information needs and dramatic changes in policies globally. We describe a platform, Watson Assistant (WA), which has been used to develop conversational agents to deliver COVID-19 related information. We characterized the diverse use cases and implementations during the early pandemic and measured adoption through a number of users, messages sent, and conversational turns (ie, pairs of interactions between users and agents). Thirty-seven institutions in 9 countries deployed COVID-19 conversational agents with WA between March 30 and August 10, 2020, including 24 governmental agencies, 7 employers, 5 provider organizations, and 1 health plan. Over 6.8 million messages were delivered through the platform. The mean number of conversational turns per session ranged between 1.9 and 3.5. Our experience demonstrates that conversational technologies can be rapidly deployed for pandemic response and are adopted globally by a wide range of users.

The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an expected progression from earlier work, the activities needed to appropriately manage and support the establishment and evolution of Adaptive CDS require new, coordinated initiatives and oversight that do not currently exist. In this AMIA position paper, the authors describe current and emerging challenges to the safe use of Adaptive CDS and lay out recommendations for the effective management and monitoring of Adaptive CDS.

OBJECTIVE: IBM(R) Watson for Oncology (WfO) is a clinical decision-support system (CDSS) that provides evidence-informed therapeutic options to cancer-treating clinicians. A panel of experienced oncologists compared CDSS treatment options to treatment decisions made by clinicians to characterize the quality of CDSS therapeutic options and decisions made in practice. METHODS: This study included patients treated between 1/2017 and 7/2018 for breast, colon, lung, and rectal cancers at Bumrungrad International Hospital (BIH), Thailand. Treatments selected by clinicians were paired with therapeutic options presented by the CDSS and coded to mask the origin of options presented. The panel rated the acceptability of each treatment in the pair by consensus, with acceptability defined as compliant with BIH's institutional practices. Descriptive statistics characterized the study population and treatment-decision evaluations by cancer type and stage. RESULTS: Nearly 60% (187) of 313 treatment pairs for breast, lung, colon, and rectal cancers were identical or equally acceptable, with 70% (219) of WfO therapeutic options identical to, or acceptable alternatives to, BIH therapy. In 30% of cases (94), 1 or both treatment options were rated as unacceptable. Of 32 cases where both WfO and BIH options were acceptable, WfO was preferred in 18 cases and BIH in 14 cases. Colorectal cancers exhibited the highest proportion of identical or equally acceptable treatments; stage IV cancers demonstrated the lowest. CONCLUSION: This study demonstrates that a system designed in the US to support, rather than replace, cancer-treating clinicians provides therapeutic options which are generally consistent with recommendations from oncologists outside the US.

Founded in 1984, the American College of Medical Informatics (ACMI) is a college of elected Fellows from the United States and abroad who have made significant and sustained contributions to the field of biomedical informatics. On November 4, 2018, the 2018 Cohort of Fellows was introduced to the College and attendees at the American Medical Informatics Association (AMIA) Annual Symposium as well as to the public through Tweets. This article includes the introduction for each Fellow in the 2018 Cohort, which was read by Christopher G. Chute (ACMI President), Suzanne Bakken (ACMI Past President), or William M. Tierney (ACMI President-Elect); a somewhat tongue-in-cheek Tweet created by Gretchen Purcell Jackson or James J. Cimino; and a link to their Journal of theAmerican Medical Informatics Association (JAMIA) and JAMIA Open publications. This is followed by the traditional closing remarks of welcome into ACMI. Gregory L. Alexander,PhD, RN, FAAN, FACMI Potter-Brinton Endowed Professor, Sinclair School of Nursing and Department of Health Management and Informatics, University of Missouri

Objective: The Vanderbilt Children's Hospital launched an innovative Technology-Based Patient and Family Engagement Consult Service in 2014. This paper describes our initial experience with this service, characterizes health-related needs of families of hospitalized children, and details the technologies recommended to promote engagement and meet needs. Materials and Methods: We retrospectively reviewed consult service documentation for patient characteristics, health-related needs, and consultation team recommendations. Needs were categorized using a consumer health needs taxonomy. Recommendations were classified by technology type. Results: Twenty-two consultations were conducted with families of patients ranging in age from newborn to 15 years, most with new diagnoses or chronic illnesses. The consultation team identified 99 health-related needs (4.5 per consultation) and made 166 recommendations (7.5 per consultation, 1.7 per need). Need categories included 38 informational needs, 26 medical needs, 23 logistical needs, and 12 social needs. The most common recommendations were websites (50, 30%) and mobile applications (30, 18%). The most frequent recommendations by need category were websites for informational needs (39, 50%), mobile applications for medical needs (15, 40%), patient portals for logistical needs (12, 44%), and disease-specific support groups for social needs (19, 56%). Discussion: Families of hospitalized pediatric patients have a variety of health-related needs, many of which could be addressed by technology recommendations from an engagement consult service. Conclusion: This service is the first of its kind, offering a potentially generalizable and scalable approach to assessing health-related needs, meeting them with technologies, and promoting patient and family engagement in the inpatient setting.

Objective: Sickle cell disease (SCD) is a chronic condition affecting over 100 000 individuals in the United States, predominantly from vulnerable populations. Clinical practice guidelines, written for providers, have low adherence. This study explored knowledge about guidelines; desire for guidelines; and how technology could support guideline awareness and adherence, examining current technology uses, and user preferences to inform design of a patient-centered guidelines application in a chronic disease. Methods: This cross-sectional mixed-methods study involved semi-structured interviews, surveys, and focus groups of adolescents and adults with SCD. We evaluated interest, preferences, and anticipated benefits or barriers of a patient-centered adaptation of SCD practice guidelines; prospective technology uses for health; and barriers to technology utilization. Results: Forty-seven individuals completed surveys and interviews, and 39 participated in three separate focus groups. Most participants (91%) were unaware of SCD guidelines, but almost all (96%) expressed interest in a guidelines application, identifying benefits (knowledge, activation, individualization, and rewards), and barriers (poor information, low motivation, and resource limitations). Current technology health uses included information access, care coordination, and reminders about health-related actions. Prospective technology uses included informational messaging and timely alerts. Barriers to technology use included lack of interest, lack of utility, and preference for direct communication. Conclusions: This study's findings can inform the design of clinical practice guideline applications, suggesting a promising role for technology to engage patients, facilitate care decisions and actions, and improve outcomes.

Vanderbilt University has a widely adopted patient portal, MyHealthAtVanderbilt, which provides an infrastructure to deliver information that can empower patient decision making and enhance personalized healthcare. An interdisciplinary team has developed Flu Tool, a decision-support application targeted to patients with influenza-like illness and designed to be integrated into a patient portal. Flu Tool enables patients to make informed decisions about the level of care they require and guides them to seek timely treatment as appropriate. A pilot version of Flu Tool was deployed for a 9-week period during the 2010-2011 influenza season. During this time, Flu Tool was accessed 4040 times, and 1017 individual patients seen in the institution were diagnosed as having influenza. This early experience with Flu Tool suggests that healthcare consumers are willing to use patient-targeted decision support. The design, implementation, and lessons learned from the pilot release of Flu Tool are described as guidance for institutions implementing decision support through a patient portal infrastructure.

Explicit guidelines are needed to develop safe and effective patient portals. This paper proposes general principles, policies, and procedures for patient portal functionality based on MyHealthAtVanderbilt (MHAV), a robust portal for Vanderbilt University Medical Center. We describe policies and procedures designed to govern popular portal functions, address common user concerns, and support adoption. We present the results of our approach as overall and function-specific usage data. Five years after implementation, MHAV has over 129,800 users; 45% have used bi-directional messaging; 52% have viewed test results and 45% have viewed other medical record data; 30% have accessed health education materials; 39% have scheduled appointments; and 29% have managed a medical bill. Our policies and procedures have supported widespread adoption and use of MHAV. We believe other healthcare organizations could employ our general guidelines and lessons learned to facilitate portal implementation and usage.