UNASSIGNED: Cardiovascular (CV) disease continues to be a leading cause of morbidity and mortality with higher rates among cancer survivors than in the general population.
UNASSIGNED: This study was aimed to understand oncology providers\' attitudes toward a digital CV health tool, delivered via a tablet, to promote CV health in cancer survivors.
UNASSIGNED: Using qualitative methods, 14 oncologists, from community and academic practice sites, were interviewed while they used the tool. Interviews were videotaped then analyzed using NVivo 11 software. Themes were inductively developed from the interviews.
UNASSIGNED: Three major themes emerged from the interviews as follows: (1) system functionality, (2) facilitators and barriers to integration, and (3) appropriate end-users. Oncologists recognized the critical role of CV health promotion among cancer survivors and identified features about the tool that would be helpful for CV health promotion. Workflow (subtheme) was a barrier to tool use. This feedback enabled tool redesign for further testing in the context of survivorship care.
UNASSIGNED: Our findings emphasized the importance of identifying appropriate End-users which may include other survivorship care providers, patients, and primary care providers.
UNASSIGNED: Our research addresses the knowledge gap in the use of digital tools in cancer survivorship care, specifically digital tools to promote CV health. Future research is needed to evaluate digital tools in cancer survivorship care. Research investigating patients as users of digital tools may provide additional insight.

BACKGROUND: As a newly emerged concept and a product of the twenty-first century, health information governance is expanding at a rapid rate. The necessity of information governance in the healthcare industry is evident, given the significance of health information and the current need to manage it. The objective of the present scoping review is to identify the dimensions and components of health information governance to discover how these factors impact the enhancement of healthcare systems and services.
METHODS: PubMed, Scopus, Web of Science, ProQuest and the Google Scholar search engine were searched from inception to June 2024. Methodological study quality was assessed using CASP checklists for selected documents. Endnote 20 was utilized to select and review articles and manage references, and MAXQDA 2020 was used for content analysis.
RESULTS: A total of 37 documents, including 18 review, 9 qualitative and 10 mixed-method studies, were identified by literature search. Based on the findings, six core categories (including health information governance goals, advantages and applications, principles, components or elements, roles and responsibilities and processes) and 48 subcategories were identified to form a unified general framework comprising all extracted dimensions and components.
CONCLUSIONS: Based on the findings of this scoping review, health information governance should be regarded as a necessity in the health systems of various countries to improve and achieve their goals, particularly in developing and underdeveloped countries. Moreover, in light of the undesirable effects of the coronavirus disease 2019 (COVID-19) pandemic in various countries, the development and implementation of health information governance models at organizational, national and international levels are among the pressing concerns. Researchers can use the present findings as a comprehensive model for developing health information governance models. A possible limitation of this study is our limited access to some databases.

The twin pandemics of COVID-19 and structural racism brought into focus health disparities and disproportionate impacts of disease on communities of color. Health equity has subsequently emerged as a priority. Recognizing that the future of health care will be informed by advanced information technologies including artificial intelligence (AI), machine learning, and algorithmic applications, the authors argue that to advance towards states of improved health equity, health information professionals need to engage in and encourage the conduct of research at the intersections of health equity, health disparities, and computational biomedical knowledge (CBK) applications. Recommendations are provided with a means to engage in this mobilization effort.

BACKGROUND:  Over the past 30 years, the American Medical Informatics Association (AMIA) has played a pivotal role in fostering a collaborative community for professionals in biomedical and health informatics. As an interdisciplinary association, AMIA brings together individuals with clinical, research, and computer expertise and emphasizes the use of data to enhance biomedical research and clinical work. The need for a recognition program within AMIA, acknowledging applied informatics skills by members, led to the establishment of the Fellows of AMIA (FAMIA) Recognition Program in 2018.
OBJECTIVE:  To outline the evolution of the FAMIA program and shed light on its origins, development, and impact. This report explores factors that led to the establishment of FAMIA, considerations affecting its development, and the objectives FAMIA seeks to achieve within the broader context of AMIA.
METHODS:  The development of FAMIA is examined through a historical lens, encompassing key milestones, discussions, and decisions that shaped the program. Insights into the formation of FAMIA were gathered through discussions within AMIA membership and leadership, including proposals, board-level discussions, and the involvement of key stakeholders. Additionally, the report outlines criteria for FAMIA eligibility and the pathways available for recognition, namely the Certification Pathway and the Long-Term Experience Pathway.
RESULTS:  The FAMIA program has inducted five classes, totaling 602 fellows. An overview of disciplines, roles, and application pathways for FAMIA members is provided. A comparative analysis with other fellow recognition programs in related fields showcases the unique features and contributions of FAMIA in acknowledging applied informatics.
CONCLUSIONS:  Now in its sixth year, FAMIA acknowledges the growing influence of applied informatics within health information professionals, recognizing individuals with experience, training, and a commitment to the highest level of applied informatics and the science associated with it.

Evidence-based medicine (EBM) emerged from McMaster University in the 1980-1990s, which emphasizes the integration of the best research evidence with clinical expertise and patient values. The Health Information Research Unit (HiRU) was created at McMaster University in 1985 to support EBM. Early on, digital health informatics took the form of teaching clinicians how to search MEDLINE with modems and phone lines. Searching and retrieval of published articles were transformed as electronic platforms provided greater access to clinically relevant studies, systematic reviews, and clinical practice guidelines, with PubMed playing a pivotal role. In the early 2000s, the HiRU introduced Clinical Queries-validated search filters derived from the curated, gold-standard, human-appraised Hedges dataset-to enhance the precision of searches, allowing clinicians to hone their queries based on study design, population, and outcomes. Currently, almost 1 million articles are added to PubMed annually. To filter through this volume of heterogenous publications for clinically important articles, the HiRU team and other researchers have been applying classical machine learning, deep learning, and, increasingly, large language models (LLMs). These approaches are built upon the foundation of gold-standard annotated datasets and humans in the loop for active machine learning. In this viewpoint, we explore the evolution of health informatics in supporting evidence search and retrieval processes over the past 25+ years within the HiRU, including the evolving roles of LLMs and responsible artificial intelligence, as we continue to facilitate the dissemination of knowledge, enabling clinicians to integrate the best available evidence into their clinical practice.

BACKGROUND: Health system fragmentation directly contributes to poor health and social outcomes for older adults with multiple chronic conditions and their care partners. Older adults often require support from primary care, multiple specialists, home care, community support services, and other health-care sectors and communication between these providers is unstructured and not standardized. Integrated and interprofessional team-based models of care are a recommended strategy to improve health service delivery to older adults with complex needs. Standardized assessment instruments deployed on digital platforms are considered a necessary component of integrated care. The aim of this study was to develop strategies to leverage an electronic wellness instrument, interRAI Check Up Self Report, to support integrated health and social care for older adults and their care partners in a community in Southern Ontario, Canada.
METHODS: Group concept mapping, a participatory mixed-methods approach, was conducted. Participants included older adults, care partners, and representatives from: home care, community support services, specialized geriatric services, primary care, and health informatics. In a series of virtual meetings, participants generated ideas to implement the interRAI Check Up and rated the relative importance of these ideas. Hierarchical cluster analysis was used to map the ideas into clusters of similar statements. Participants reviewed the map to co-create an action plan.
RESULTS: Forty-one participants contributed to a cluster map of ten action areas (e.g., engagement of older adults and care partners, instrument\'s ease of use, accessibility of the assessment process, person-centred process, training and education for providers, provider coordination, health information integration, health system decision support and quality improvement, and privacy and confidentiality). The health system decision support cluster was rated as the lowest relative importance and the health information integration was cluster rated as the highest relative importance.
CONCLUSIONS: Many person-, provider-, and system-level factors need to be considered when implementing and using an electronic wellness instrument across health- and social-care providers. These factors are highly relevant to the integration of other standardized instruments into interprofessional team care to ensure a compassionate care approach as technology is introduced.

BACKGROUND: The National Institute of Health and Social Care Research (NIHR) Health Informatics Collaborative (HIC) for Hearing Health has been established in the UK to curate routinely collected hearing health data to address research questions. This study defines priority research areas, outlines its aims, governance structure and demonstrates how hearing health data have been integrated into a common data model using pure tone audiometry (PTA) as a case study.
METHODS: After identifying key research aims in hearing health, the governance structure for the NIHR HIC for Hearing Health is described. The Observational Medical Outcomes Partnership (OMOP) was chosen as our common data model to provide a case study example.
RESULTS: The NIHR HIC Hearing Health theme have developed a data architecture outlying the flow of data from all of the various siloed electronic patient record systems to allow the effective linkage of data from electronic patient record systems to research systems. Using PTAs as an example, OMOPification of hearing health data successfully collated a rich breadth of datapoints across multiple centres.
CONCLUSIONS: This study identified priority research areas where routinely collected hearing health data could be useful. It demonstrates integration and standardisation of such data into a common data model from multiple centres. By describing the process of data sharing across the HIC, we hope to invite more centres to contribute and utilise data to address research questions in hearing health. This national initiative has the power to transform UK hearing research and hearing care using routinely collected clinical data.

We aimed to use the digital platform maintained by the local health service providers in Southeast Sweden for integrated monitoring of disparities in vaccination and morbidity during the COVID-19 pandemic. The monitoring was performed in the adult population of two counties (n = 657,926) between 1 February 2020 and 15 February 2022. The disparities monitored were relocated (internationally displaced), substance users, and suffering from a psychotic disorder. The outcomes monitored were COVID-19 vaccination, SARS-CoV-2 test results, and hospitalization with COVID-19. Relocated residents displayed an increased likelihood of remaining unvaccinated and a decreased likelihood of testing as well as increased risks of primary SARS-CoV-2 infection and hospitalization compared with the general population. Suffering from a major psychiatric disease was associated with an increased risk of remaining unvaccinated and an increased risk of hospitalization but a decreased risk of SARS-CoV-2 infection. From the digital monitoring, we concluded that the relocated minority received insufficient protection during the pandemic, suggesting the necessity for comprehensive promotion of overall social integration. Persons with major psychiatric diseases underused vaccination, while they benefitted from proactively provided testing, implying a need for active encouragement of vaccination. Further research is warranted on legal and ethical frameworks for digital monitoring in vaccination programs.

Background: Shared decision making (SDM) is the process by which patients and clinicians exchange information and preferences to come to joint healthcare decisions. Clinical dashboards can support SDM by collecting, distilling, and presenting critical information, such as patient-reported outcomes (PROs), to be shared at points of care and in between appointments. We describe the implementation strategies and outcomes of a multistakeholder collaborative process known as \"co-design\" to develop a PRO-informed clinical dashboard to support SDM for patients with advanced cancer or chronic kidney disease (CKD). Methods: Across 14 sessions, two multidisciplinary teams comprising patients, care partners, clinicians, and other stakeholders iteratively co-designed an SDM dashboard for either advanced cancer (N = 25) or CKD (N = 24). Eligible patients, care partners, and frontline clinicians were identified by six physician champions. The co-design process included four key steps: (1) define \"the problem\", (2) establish context of use, (3) build a consensus on design, and (4) define and test specifications. We also evaluated our success in implementing the co-design strategy using measures of fidelity, acceptability, adoption, feasibility, and effectiveness which were collected throughout the process. Results: Mean (M) scores across implementation measures of the co-design process were high, including observer-rated fidelity and adoption of co-design practices (M = 19.1 on a 7-21 scale, N = 36 ratings across 9 sessions), as well as acceptability based on the perceived degree of SDM that occurred during the co-design process (M = 10.4 on a 0 to 12 adapted collaboRATE scale). Capturing the feasibility and adoption of convening multistakeholder co-design teams, min-max normalized scores (ranging from 0 to 1) of stakeholder representation demonstrated that, on average, 95% of stakeholder types were represented for cancer sessions (M = 0.95) and 85% for CKD sessions (M = 0.85). The co-design process was rated as either \"fully\" or \"partially\" effective by 100% of respondents, in creating a dashboard that met its intended objective. Conclusions: A co-design process was successfully implemented to develop SDM clinical dashboards for advanced cancer and CKD care. We discuss key strategies and learnings from this process that may aid others in the development and uptake of patient-centered healthcare innovations.

BACKGROUND: Pharmacogenetics can impact patient care and outcomes through personalizing the selection of medicines, resulting in improved efficacy and a reduction in harmful side effects. Despite the existence of compelling clinical evidence and international guidelines highlighting the benefits of pharmacogenetics in clinical practice, implementation within the National Health Service in the United Kingdom is limited. An important barrier to overcome is the development of IT solutions that support the integration of pharmacogenetic data into health care systems. This necessitates a better understanding of the role of electronic health records (EHRs) and the design of clinical decision support systems that are acceptable to clinicians, particularly those in primary care.
OBJECTIVE: Explore the needs and requirements of a pharmacogenetic service from the perspective of primary care clinicians with a view to co-design a prototype solution.
METHODS: We used ethnographic and think-aloud observations, user research workshops, and prototyping. The participants for this study included general practitioners and pharmacists. In total, we undertook 5 sessions of ethnographic observation to understand current practices and workflows. This was followed by 3 user research workshops, each with its own topic guide starting with personas and early ideation, through to exploring the potential of clinical decision support systems and prototype design. We subsequently analyzed workshop data using affinity diagramming and refined the key requirements for the solution collaboratively as a multidisciplinary project team.
RESULTS: User research results identified that pharmacogenetic data must be incorporated within existing EHRs rather than through a stand-alone portal. The information presented through clinical decision support systems must be clear, accessible, and user-friendly as the service will be used by a range of end users. Critically, the information should be displayed within the prescribing workflow, rather than discrete results stored statically in the EHR. Finally, the prescribing recommendations should be authoritative to provide confidence in the validity of the results. Based on these findings we co-designed an interactive prototype, demonstrating pharmacogenetic clinical decision support integrated within the prescribing workflow of an EHR.
CONCLUSIONS: This study marks a significant step forward in the design of systems that support pharmacogenetic-guided prescribing in primary care settings. Clinical decision support systems have the potential to enhance the personalization of medicines, provided they are effectively implemented within EHRs and present pharmacogenetic data in a user-friendly, actionable, and standardized format. Achieving this requires the development of a decoupled, standards-based architecture that allows for the separation of data from application, facilitating integration across various EHRs through the use of application programming interfaces (APIs). More globally, this study demonstrates the role of health informatics and user-centered design in realizing the potential of personalized medicine at scale and ensuring that the benefits of genomic innovation reach patients and populations effectively.