Evidence-based Health Informatics Research Articles

Machine Learning Models and Technologies for Evidence-Based Telehealth and Smart Care: A Review

Background: Over the past few years, clinical studies have utilized machine learning in telehealth and smart care for disease management, self-management, and managing health issues like pulmonary diseases, heart failure, diabetes screening, and intraoperative risks. However, a systematic review of machine learning’s use in evidence-based telehealth and smart care is lacking, as evidence-based practice aims to eliminate biases and subjective opinions. Methods: The author conducted a mixed methods review to explore machine learning applications in evidence-based telehealth and smart care. A systematic search of the literature was performed during 16 June 2023–27 June 2023 in Google Scholar, PubMed, and the clinical registry platform ClinicalTrials.gov. The author included articles in the review if they were implemented by evidence-based health informatics and concerned with telehealth and smart care technologies. Results: The author identifies 18 key studies (17 clinical trials) from 175 citations found in internet databases and categorizes them using problem-specific groupings, medical/health domains, machine learning models, algorithms, and techniques. Conclusions: Machine learning combined with the application of evidence-based practices in healthcare can enhance telehealth and smart care strategies by improving quality of personalized care, early detection of health-related problems, patient quality of life, patient-physician communication, resource efficiency and cost-effectiveness. However, this requires interdisciplinary expertise and collaboration among stakeholders, including clinicians, informaticians, and policymakers. Therefore, further research using clinicall studies, systematic reviews, analyses, and meta-analyses is required to fully exploit the potential of machine learning in this area.

One Health: Insights from Organizational & Social, Technology Assessment and Human Factors Perspectives.

To offer diverse but complementary perspectives on how biomedical and health informatics can be informed by and help to achieve the vision of One Health. Overview of key considerations and critical discussion of common themes, barriers and opportunities, based on collaborative review by International Medical Informatics Association (IMIA) working group members active in related fields. Health and care systems are complex sociotechnical systems that need explicit design and implementation strategies to align with the goals of One Health. The evidence-based health informatics paradigm and associated frameworks for evaluation of digital health technologies need to broaden their scope to take full account of the One Health approach. Informatics has specific contributions to make to One Health, for example by improved user experience reducing energy consumption and effective app design enhancing medication adherence. One Health is inherently intertwined with ergonomic, sociotechnical and evaluation perspectives in biomedical and health informatics. Health is a planetary issue that requires interdisciplinary collaborative action. The theories and principles of biomedical and health informatics offer many opportunities to transform digital health technology to better serve the One Health agenda.

Machine Learning Tools and Platforms in Clinical Trial Outputs to Support Evidence-Based Health Informatics: A Rapid Review of the Literature

Background: The application of machine learning (ML) tools (MLTs) to support clinical trials outputs in evidence-based health informatics can be an effective, useful, feasible, and acceptable way to advance medical research and provide precision medicine. Methods: In this study, the author used the rapid review approach and snowballing methods. The review was conducted in the following databases: PubMed, Scopus, COCHRANE LIBRARY, clinicaltrials.gov, Semantic Scholar, and the first six pages of Google Scholar from the 10 July–15 August 2022 period. Results: Here, 49 articles met the required criteria and were included in this review. Accordingly, 32 MLTs and platforms were identified in this study that applied the automatic extraction of knowledge from clinical trial outputs. Specifically, the initial use of automated tools resulted in modest to satisfactory time savings compared with the manual management. In addition, the evaluation of performance, functionality, usability, user interface, and system requirements also yielded positive results. Moreover, the evaluation of some tools in terms of acceptance, feasibility, precision, accuracy, efficiency, efficacy, and reliability was also positive. Conclusions: In summary, design based on the application of clinical trial results in ML is a promising approach to apply more reliable solutions. Future studies are needed to propose common standards for the assessment of MLTs and to clinically validate the performance in specific healthcare and technical domains.

Impacts on Context Aware Systems in Evidence-Based Health Informatics: A Review.

Background: The application of Context Aware Computing (CAC) can be an effective, useful, feasible, and acceptable way to advance medical research and provide health services. Methods: This review was conducted in accordance with the principles of the development of a mixed methods review and existing knowledge in the field via the Synthesis Framework for the Assessment of Health Information Technology to evaluate CAC implemented by Evidence-Based Health Informatics (EBHI). A systematic search of the literature was performed during 18 November 2021–22 January 2022 in Cochrane Library, IEEE Xplore, PUBMED, Scopus and in the clinical registry platform Clinicaltrials.gov. The author included the articles in the review if they were implemented by EBHI and concerned with CAC technologies. Results: 29 articles met the inclusion criteria and refer to 26 trials published between 2011 and 2022. The author noticed improvements in healthcare provision using EBHI in the findings of CAC application. She also confirmed that CAC systems are a valuable and reliable method in health care provision. Conclusions: The use of CAC systems in healthcare is a promising new area of research and development. The author presented that the evaluation of CAC systems in EBHI presents positive effects on the state of health and the management of long-term diseases. These implications are presented in this article in a detailed, clear, and reliable manner.

Developing Evidence-based Population Health Informatics curriculum: Integrating competency based model and job analysis.

With the rapid pace of technological advancements, public health professions require a core set of informatics skills. The objective of the study is to integrate informatics competencies and job analysis to guide development of an evidence-based curriculum framework and apply it towards creation of a population health informatics program. We conducted content analysis of the Population Health Informatics related job postings in the state of New York between June and July 2019 using the Indeed job board. The search terms included "health informatics" and "population health informatics." The initial search yielded 496 job postings. After removal of duplicates, inactive postings and that did not include details of the positions' responsibilities resulted in 306 jobs. Information recorded from the publicly available job postings included job categories, type of hiring organization, educational degree preferred and required, work experience preferred and required, salary information, job type, job location, associated knowledge, skills and expertise and software skills. Most common job title was that of an analyst (21%, n=65) while more than one-third of the hiring organizations were health systems (35%, n=106). 95% (n=291) of the jobs were fulltime and nearly half of these jobs were in New York City (47%, n=143). Data/statistical analysis (68%, n=207), working in multidisciplinary teams (35%, n=108), and biomedical/clinical experience (30%, n=93) were the common skills needed. Structured query language (SQL), Python, and R language were common programming language skills. A broad framework of integrating informatics competencies, combined with analysis of the skills the jobs needed, and knowledge acquisition based on global health informatics projects guided the development of an online population health informatics curriculum in a rapidly changing technological environment.

Evidence-Based Health Informatics as the Foundation for the COVID-19 Response: A Joint Call for Action.

Background As a major public health crisis, the novel coronavirus disease 2019 (COVID-19) pandemic demonstrates the urgent need for safe, effective, and evidence-based implementations of digital health. The urgency stems from the frequent tendency to focus attention on seemingly high promising digital health interventions despite being poorly validated in times of crisis. Aim In this paper, we describe a joint call for action to use and leverage evidence-based health informatics as the foundation for the COVID-19 response and public health interventions. Tangible examples are provided for how the working groups and special interest groups of the International Medical Informatics Association (IMIA) are helping to build an evidence-based response to this crisis. Methods Leaders of working and special interest groups of the IMIA, a total of 26 groups, were contacted via e-mail to provide a summary of the scientific-based efforts taken to combat COVID-19 pandemic and participate in the discussion toward the creation of this manuscript. A total of 13 groups participated in this manuscript. Results Various efforts were exerted by members of IMIA including (1) developing evidence-based guidelines for the design and deployment of digital health solutions during COVID-19; (2) surveying clinical informaticians internationally about key digital solutions deployed to combat COVID-19 and the challenges faced when implementing and using them; and (3) offering necessary resources for clinicians about the use of digital tools in clinical practice, education, and research during COVID-19. Discussion Rigor and evidence need to be taken into consideration when designing, implementing, and using digital tools to combat COVID-19 to avoid delays and unforeseen negative consequences. It is paramount to employ a multidisciplinary approach for the development and implementation of digital health tools that have been rapidly deployed in response to the pandemic bearing in mind human factors, ethics, data privacy, and the diversity of context at the local, national, and international levels. The training and capacity building of front-line workers is crucial and must be linked to a clear strategy for evaluation of ongoing experiences.

Distributed Cognition: Understanding Complex Sociotechnical Informatics.

Distributed cognition theory posits that our cognitive tasks are so tightly coupled to the environment that cognition extends into the environment, beyond the skin and the skull. It uses cognitive concepts to describe information processing across external representations, social networks and across different periods of time. Distributed cognition lends itself to exploring how people interact with technology in the workplace, issues to do with communication and coordination, how people's thinking extends into the environment and sociotechnical system architecture and performance more broadly. We provide an overview of early work that established distributed cognition theory, describe more recent work that facilitates its application, and outline how this theory has been used in health informatics. We present two use cases to show how distributed cognition can be used at the formative and summative stages of a project life cycle. In both cases, key determinants that influence performance of the sociotechnical system and/or the technology are identified. We argue that distributed cognition theory can have descriptive, rhetorical, inferential and application power. For evidence-based health informatics it can lead to design changes and hypotheses that can be tested.

The Need for Theory to Inform Clinical Information Systems and Professionalise the Health Informatics Discipline.

This chapter introduces the idea of theories in health informatics, defines what we mean by theory and distinguishes theories from models, frameworks and predictive principles. After explaining why theories and predictive principles are needed to help us professionalize our discipline, the chapter offers five criteria for a successful predictive principle, discusses how to evaluate predictive principles and theories and links this with the emerging field of evidence-based health informatics. The chapter concludes with three actions needed to move the discipline of theory-based health informatics forward.

How to Teach Health IT Evaluation: Recommendations for Health IT Evaluation Courses.

Systematic health IT evaluation studies are needed to ensure system quality and safety and to provide the basis for evidence-based health informatics. Well-trained health informatics specialists are required to guarantee that health IT evaluation studies are conducted in accordance with robust standards. Also, policy makers and managers need to appreciate how good evidence is obtained by scientific process and used as an essential justification for policy decisions. In a consensus-based approach with over 80 experts in health IT evaluation, recommendations for the structure, scope and content of health IT evaluation courses on the master or postgraduate level have been developed, supported by a structured analysis of available courses and of available literature. The recommendations comprise 15 mandatory topics and 15 optional topics for a health IT evaluation course.

Evidence-based health and clinical informatics: a systematic review on randomized controlled trials

Towards the provision of medical research and eHealth services, several Health Information Technology (HIT) platforms are blended with communication and software technologies (i.e. mobile and Web applications, wireless sensor networks, Internet of Things and cloud computing). However, an important research issue is whether and to what degree these technologies are efficiently and effectively integrated into medical practice. Accordingly, this study reviews recent literature on HITs that employ RCTs, which are acknowledged as a reliable solution by the community of health stakeholders. Furthermore, it examines the research efforts in the field and evaluates the relevant functionalities. The literature search strategy was based on PRISMA 2009 Checklist and the CONSORT-EHEALTH Checklist that are two standard methodologies for systematic reviews in Evidence Based Medicine and Health Information Technologies. The analysis of the studies included was performed according to the Cochrane Risk of Bias Assessment Tool. The sources considered in this research include the most common clinical trial registries and academic electronic databases. The studies considered were conducted from 2008 until 2016. The authors considered RCTs having published their results in at least one article. As a result, 55 articles from 42 different journals are considered in this review. The benefits of the HIT delivered interventions are clearly presented in the outcomes of the relevant studies. Significant improvements were observed in the findings of 31 trials from a total of 51 (60.78%) including the acceptance, satisfaction, reliability, usefulness, safety, effectiveness and financial benefit of HITs. The results of this review reveal that HIT and eHealth interventions achieve at least equally reliable and safe outcomes compared with the usual support methods of healthcare. Significantly encouraging results are noticed in interventions employing HIT over several healthcare fields.

Finding, Appraising and Interpreting the Evidence of Health IT.

Evidence-based health informatics can be described as a scientific approach to meeting the multiplicity of tasks involved in the development, implementation and sustainability of health information technologies (IT). The practice of evidence-based health informatics incorporates methods to help find, appraise and utilise research-based knowledge. The aim of this contribution is to describe the steps of finding, appraising and interpreting the evidence of health IT. It lists major sources of literature in the health field, and highlights a number of considerations for undertaking reviews, drawing on some key landmark reviews that have helped to shape the health informatics discipline. It also considers key issues highlighted by these reviews particularly in regard to the validity of findings, their generalisability and their impact on patient outcomes. The contribution also provides suggestions for tackling the challenge of potential publication bias, and how to deal with heterogeneous findings.

Theoretical Foundations for Evidence-Based Health Informatics: Why? How?

A scientific approach to health informatics requires sound theoretical foundations. Health informatics implementation would be more effective if evidence-based and guided by theories about what is likely to work in what circumstances. We report on a Medinfo 2015 workshop on this topic jointly organized by the EFMI Working Group on Assessment of Health Information Systems and the IMIA Working Group on Technology Assessment and Quality Development. We discuss the findings of the workshop and propose an approach to consolidate empirical knowledge into testable middle-range theories.

Theoretical Basis of Health IT Evaluation.

The focus of this contribution is on the theoretical principles and concepts behind evaluation of IT-based systems, discussing their presuppositions, implications and interrelationships; for instance in relation to a series of issues to consider: terminology for the concepts used as that is a reason for many disputes, bias as that is a common reason for less accuracy and trustworthiness in conclusions, culture as the tacit driver of everything we do and design, constructive evaluation as this has strict time and timing issues, preparing for meta-analyses as that is in the near future, and top-level issues in choice of methodology. Awareness in these respects will lead to avoidance of major pitfalls and perils at evaluation and thereby improve the validity and trustworthiness of an evaluation outcome, supporting the initiative towards evidence-based health informatics.

Evidence-based Health Informatics Frameworks for Applied Use.

Health Informatics frameworks have been created surrounding the implementation, optimization, adoption, use and evaluation of health information technology including electronic health record systems and medical devices. In this contribution, established health informatics frameworks are presented. Important considerations for each framework are its purpose, component parts, rigor of development, the level of testing and validation its undergone, and its limitations. In order to understand how to use a framework effectively, it's often necessary to seek additional explanation via literature, documentation, and discussions with the developers.

Developing an evidence-based public health informatics course.

This study assessed the need to develop a public health informatics (PHI) introductory course and determine contents of such a course. Community assessments employing focus group interviews and an online survey were utilized to determine course need and content. Results revealed a need to provide PHI training to graduate public health students and suggested broad course content requirements. Results indicated lack of awareness of libraries and librarians as sources of public health information. A graduate PHI course was developed and delivered. Additionally, implementation of a subject guide increased the library's profile.

Evidence-based Health Informatics: How Do We Know What We Know?

Health IT is expected to have a positive impact on the quality and efficiency of health care. But reports on negative impact and patient harm continue to emerge. The obligation of health informatics is to make sure that health IT solutions provide as much benefit with as few negative side effects as possible. To achieve this, health informatics as a discipline must be able to learn, both from its successes as well as from its failures. To present motivation, vision, and history of evidence-based health informatics, and to discuss achievements, challenges, and needs for action. Reflections on scientific literature and on own experiences. Eight challenges on the way towards evidence-based health informatics are identified and discussed: quality of studies; publication bias; reporting quality; availability of publications; systematic reviews and meta-analysis; training of health IT evaluation experts; translation of evidence into health practice; and post-market surveillance. Identified needs for action comprise: establish health IT study registers; increase the quality of publications; develop a taxonomy for health IT systems; improve indexing of published health IT evaluation papers; move from meta-analysis to meta-summaries; include health IT evaluation competencies in curricula; develop evidence-based implementation frameworks; and establish post-marketing surveillance for health IT. There has been some progress, but evidence-based health informatics is still in its infancy. Building evidence in health informatics is our obligation if we consider medical informatics a scientific discipline.

Discussion of “Evidence-based Health Informatics: How Do We Know What We Know?”

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Evidence-based Health Informatics: How Do We Know What We Know?" written by Elske Ammenwerth [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the Ammenwerth paper. In subsequent issues the discussion can continue through letters to the editor. With these comments on the paper "Evidence-based Health Informatics: How do we know what we know?", written by Elske Ammenwerth [1], the journal seeks to stimulate a broad discussion on the challenges of evaluating information processing and information technology in health care. An international group of experts has been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.

Are constructivist approaches in teaching health librarians effective? A reflective case study of teaching a course in health librarianship

This paper examines the use of constructivist teaching in a course on health librarianship. Offered at the School of Library, Archival and Information Studies (SLAIS) at the University of British Columbia (UBC), LIBR534 is an introduction to health information sources and services [2]. Since the early 1960s, the course has been offered in alternate years and taught by one or two professional health librarians [3]. Its purpose has always been to provide an introduction to health librarianship and the major information sources in medicine and allied areas. As the field has evolved, the course has responded and integrated topics such as evidence-based practice, health informatics, and digital reference services [4]. For practical reasons, the instructors have been able to foster relationships with students participating in the student interest group (SIG) of the Canadian Health Libraries Association / Association des bibliotheques de la sante du Canada (CHLA / ABSC) at SLAIS. The SIG provides opportunities for those students who want to meet professional health librarians (many of whom are alumni of our class). Further, those who want to explore advanced studies can do so with the instructors or arrange a practicum with the Health Libraries Association of British Columbia (HLABC) member libraries [5]. In 2008, after teaching LIBR534 several times, we discerned a need to make some changes to didactic structure and delivery. In previous course evaluations, students had clearly expressed their desire to work together and to examine information problems with their peers. We could see that SLAIS students were not unlike students in other professional programs in that they wanted more active, enquirybased learning experiences [6]. In planning for the 2008 offering, we restructured the course with this desire in mind. In modifying the course, we envisioned a learning environment where knowledge-based and problem-based learning (PBL) would be used (see Appendix A). On the one hand, time to gain the basic knowledge of the field was important, but skills such as analysis, synthesis, and evaluation were also critical. A balance would need to be found between conveying concepts and promoting the interpersonal skills and behaviours associated with professional practice. But with two pedagogical methods already in play, why introduce constructivist principles? “[I]n constructivism, students take responsibility for their own learning rather than relying on the teacher” [7,8]. We feel that this method was important for building autonomy in students. Even though adopting constructivist teaching can present a number of challenges for us as teachers, we felt ready to experiment. We are now taking time, as reflective practitioners, to consider and review our teaching of LIBR534 in 2008 when we used constructivist methods [9]. Using a case format, we orient readers in this paper to setting, participants, and content, and share information from our students’ evaluations. Throughout, we share our own informal observations about whether interactive, problem-based techniques were successful. We conclude by discussing our plans for LIBR534, next offered in January 2010.

Looking for the Evidence: Value of Health Informatics. Editorial

To provide an editorial introduction to the 2013 IMIA Yearbook of Medical Informatics with an overview of its contents and contributors. A brief overview of the main theme, and an outline of the purposes, contents, format, and acknowledgment of contributions. Health information technology (HIT) is currently widely implemented to improve healthcare quality and patient safety while reducing costs. Although these benefits are expected and largely advertised, the evidence for these benefits is still missing. Unintended consequences are often reported and some applications have been shown to be wasteful, harmful, and even fatal. Evidence-based health informatics has been defined as "the conscientious, explicit and judicious use of current best evidence when making decisions about the introduction and operation of information technology in a given health care setting". The 2013 issue of the IMIA Yearbook highlights important contributions about the significant challenges that arise from the assessment of HIT solutions. Progress towards evidence-based health informatics is identified to elicit what works, what doesn't work, and why. In an environment where resources are limited, budgets lower than in past years, and the need to improve care is becoming ever more pressing, focusing on this topic should guide institutions and providers in the implementation of the best health information technology. This overview of progress and current challenges across the spectrum of the discipline shows many great examples of evidence that have been gathered on the effectiveness of HIT. However, evidence remains limited and a significant work should be conducted to improve the development, testing, and implementation of HIT applications.

Evidence Based Health Informatics: 10 Years of Efforts to Promote the Principle

To present the importance of Evidence-based Health Informatics (EBHI) and the ethical imperative of this approach; to highlight the work of the IMIA Working Group on Technology Assessment and Quality Improvement and the EFMI Working Group on Assessment of Health Information Systems; and to introduce the further important evaluation and evidence aspects being addressed. Reviews of IMIA, EFMA and other initiatives, together with literature reviews on evaluation methods and on published systematic reviews. Presentation of the rationale for the health informatics domain to adopt a scientific approach by assessing impact, avoiding harm, and empirically demonstrating benefit and best use; reporting of the origins and rationale of the IMIA- and EQUATOR-endorsed Statement on Reporting of Evaluation Studies in Health Informatics (STARE-HI) and of the IMIA WG's Guideline for Good Evaluation Practice in Health Informatics (GEP-HI); presentation of other initiatives for objective evaluation; and outlining of further work in hand on usability and indicators; together with the case for development of relevant evaluation methods in newer applications such as telemedicine. The focus is on scientific evaluation as a reliable source of evidence, and on structured presentation of results to enable easy retrieval of evidence. EBHI is feasible, necessary for efficiency and safety, and ethically essential. Given the significant impact of health informatics on health systems, care delivery and personal health, it is vital that cultures change to insist on evidence-based policies and investment, and that emergent global moves for this are supported.