Human Factors and Organizational Issues Section Synopsis IMIA Yearbook 2021.

OBJECTIVE: To select the best papers that made original and high impact contributions in the area of human factors and organizational issues in biomedical informatics in 2020. METHODS: A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2020 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two section editors led to a total of 1,562 papers. These papers were discussed for a selection of 12 finalist papers, which were then reviewed by the two section editors, two chief editors, and by three external reviewers from internationally renowned research teams. RESULTS: The query process resulted in 12 papers that reveal interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces. This year three papers were clearly outstanding and help advance in the field. They provide examples of applying existing frameworks together in novel and highly illuminating ways, showing the value of theory development in human factors. Emerging themes included several which discussed physician burnout, mobile health, and health equity. Those concerning the Corona Virus Disease 2019 (Covid-19) were included as part of that section. CONCLUSION: The selected papers make important contributions to human factors and organizational issues, expanding and deepening our knowledge of how to apply theory and applications of new technologies in health.

Development of a data utility framework to support effective health data curation.

OBJECTIVES: The value of healthcare data is being increasingly recognised, including the need to improve health dataset utility. There is no established mechanism for evaluating healthcare dataset utility making it difficult to evaluate the effectiveness of activities improving the data. To describe the method for generating and involving the user community in developing a proposed framework for evaluation and communication of healthcare dataset utility for given research areas. METHODS: Aninitial version of a matrix to review datasets across a range of dimensions wasdeveloped based on previous published findings regarding healthcare data. Thiswas used to initiate a design process through interviews and surveys with datausers representing a broad range of user types and use cases, to help develop afocused framework for characterising datasets. RESULTS: Following 21 interviews, 31 survey responses and testing on 43 datasets, five major categories and 13 subcategories were identified as useful for a dataset, including Data Model, Completeness and Linkage. Each sub-category was graded to facilitate rapid and reproducible evaluation of dataset utility for specific use-cases. Testing of applicability to >40 existing datasets demonstrated potential usefulness for subsequent evaluation in real-world practice. DISCUSSION: Theresearch has developed an evidenced-based initial approach for a framework tounderstand the utility of a healthcare dataset. It likely to require further refinementfollowing wider application and additional categories may be required. CONCLUSION: The process has resulted in a user-centred designed framework for objectively evaluating the likely utility of specific healthcare datasets, and therefore, should be of value both for potential users of health data, and for data custodians to identify the areas to provide the optimal value for data curation investment.

Digital Health during COVID-19: Informatics Dialogue with the World Health Organization.

BACKGROUND: On December 16, 2020 representatives of the International Medical Informatics Association (IMIA), a Non-Governmental Organization in official relations with the World Health Organization (WHO), along with its International Academy for Health Sciences Informatics (IAHSI), held an open dialogue with WHO Director General (WHO DG) Tedros Adhanom Ghebreyesus about the opportunities and challenges of digital health during the COVID-19 global pandemic. OBJECTIVES: The aim of this paper is to report the outcomes of the dialogue and discussions with more than 200 participants representing different civil society organizations (CSOs). METHODS: The dialogue was held in form of a webinar. After an initial address of the WHO DG, short presentations by the panelists, and live discussions between panelists, the WHO DG and WHO representatives took place. The audience was able to post questions in written. These written discussions were saved with participants' consent and summarized in this paper. RESULTS: The main themes that were brought up by the audience for discussion were: (a) opportunities and challenges in general; (b) ethics and artificial intelligence; (c) digital divide; (d) education. Proposed actions included the development of a roadmap based on the lessons learned from the COVID-19 pandemic. CONCLUSIONS: Decision making by policy makers needs to be evidence-based and health informatics research should be used to support decisions surrounding digital health, and we further propose next steps in the collaboration between IMIA and WHO such as future engagement in the World Health Assembly.

Health Information Management Reimagined: Assessing Current Professional Skills and Industry Demand.

This paper examines the changes affecting the health information management (HIM) professional skill set and industry demand to determine differences affecting practitioners. As the industry continues to experience technological innovation, the responsibilities of the HIM professional are in flux, affecting the required skill set of the changing environment. This research used the American Health Information Management Association salary survey and current job postings to determine whether the workforce has experienced deskilling and whether a theory-practice-gap exists. It also assesses if industry competencies align with the Health Information Management Reimaged perspectives. The results indicate that the workforce has not experienced deskilling, that a theory-practice gap does exist, and that Health Information Management Reimaged is aligned with industry needs.

A mid-South chronic disease registry and practice-based research network to address disparities.

OBJECTIVES: To describe an innovative health information technology (HIT) model for supporting community-wide health improvement through multiprovider collaboration in a regional population health registry and practice-based research network (PBRN). STUDY DESIGN: Case study. METHODS: We describe the HIT data structure and governance of the Diabetes Wellness and Prevention Coalition (DWPC) Registry and PBRN based in Memphis, Tennessee. The population served and their characteristics were assessed for all adult patients with at least 1 encounter in a participating health care delivery system from January 1, 2013, to March 31, 2019. Disparities in access and health care utilization were assessed by residential zip code. RESULTS: The DWPC Registry is a chronic disease and population health data warehouse designed to facilitate chronic disease surveillance and tracking of processes and outcomes of care in medically underserved areas of the mid-South. The Registry primarily focuses on obesity-associated chronic conditions such as diabetes, hypertension, hyperlipidemia, and chronic kidney disease. It combines patient data from 7 regional health systems, which include 6 adult hospitals and more than 50 outpatient practices, covering 462,223 adults with 2,032,425 clinic visits and 602,679 hospitalizations and/or emergency department visits from January 1, 2013, to March 31, 2019. The most prevalent chronic conditions include obesity (37.2%), hypertension (34.4%), overweight (26.4%), hyperlipidemia (18.0%), and type 2 diabetes (14.0%). The Registry provides quarterly practice improvement reports to participating clinics, facilitates surveillance of and outreach to patients with unmet health needs, and supports a pragmatic clinical trial and multiple cohort studies. CONCLUSIONS: Regional registries and PBRNs are powerful tools that can support real-world quality improvement and population health efforts to reduce disparities and improve equity in chronic disease care in medically underserved communities across the United States.

COVID-19 e Telemedicina: ferramenta de medição do nível de maturidade das instituições de saúde para implementar serviços de telemedicina / COVID-19 y Telemedicina: herramienta de medición del nivel de madurez de las instituciones de salud para implementar servicios de telemedicina / COVID-19 and Telemedicine: tool for assessing the maturity level of health institutions to implement telemedicine services / COVID-19 et Télémédecine: outil de mesure du niveau de maturité des établissements de santé pour la mise en œuvre des services de télémédecine

A elaboração desta ferramenta faz parte do apoio às operações de resposta à pandemia. Baseia-se nos modelos implementados por diferentes instituições de saúde em vários países do mundo, com diferentes graus de complexidade. Instituições e especialistas em telemedicina e no uso de tecnologia da informação na área da saúde pública da Região das Américas e da Espanha colaboraram em seu desenvolvimento. A ferramenta foi desenvolvida com o entendimento de que existe uma intenção institucional de implementar serviços de telemedicina imediatamente. Porém, também será útil para instituições que já contam com programas de telemedicina e desejam fazer uma autoavaliação para redefinir as suas prioridades diante da pandemia. A ferramenta traz uma série de perguntas organizadas nas seis categorias.

La elaboración de esta herramienta forma parte del apoyo a las operaciones de respuesta a la pandemia. Se basa en los modelos que distintas instituciones de salud con diferente grado de complejidad han implementado en varios países del mundo. En su desarrollo han colaborado instituciones y expertos de la Región de las Américas y de España especializados en telemedicina y en el uso de tecnologías de la información en la esfera de la salud pública. La herramienta se ha desarrollado en el entendido de que existe la intención institucional de implementar de forma inmediata servicios de telemedicina. Pero también resultará útil a las instituciones que ya cuenten con programas de telemedicina en funcionamiento y que deseen autoevaluarse para redefinir prioridades frente a la pandemia. La herramienta consta de una serie de preguntas organizadas en las seis categorías.

This tool forms part of the support for pandemic response operations. Its design is based on the models that have been implemented by different health institutions with different levels of complexity in several countries. The tool was developed collaboratively with institutions and experts specialized in telemedicine and in the use of information technology (IT) in public health, from the Region of the Americas and. The tool has been developed with the understanding that there is an institutional commitment to immediately implement telemedicine services. However, it will also be useful to institutions that already have telemedicine programs up and running, which want to perform a self-assessment to redefine their priorities in light of the pandemic. The tool comprises a series of questions, organized into the six categories.

La mise au point de cet outil s'inscrit dans le cadre du soutien aux opérations d'intervention en cas de pandémie. Il repose sur les modèles que différents établissements de santé avec des degrés de complexité variables ont mis en œuvre dans plusieurs pays à travers le monde. Des institutions et des experts de la Région des Amériques et d'Espagne spécialisés dans la télémédecine et l'utilisation des technologies de l'information dans le domaine de la santé publique ont collaboré au développement du présent outil (voir annexe). L'existence d'une intention institutionnelle de mettre immédiatement en œuvre des services de télémédecine est un préalable au développement de cet outil. Néanmoins, ce dernier sera également utile pour les institutions qui ont déjà mis en place des programmes de télémédecine et qui souhaitent réaliser une auto-évaluation de manière à redéfinir leurs priorités face à la pandémie. L'outil comprend une série de questions organisées selon les six catégories.

Health Information Technology Adoption and Clinical Performance in Federally Qualified Health Centers.

A national sample (N = 982) of federally qualified health centers (FQHCs) for the period 2011-2016 was examined regarding the relationship between the age and extent of health information technology (HIT) use and clinical performance. We found that each additional year of HIT use was associated with an approximate 4 percent increase in both process and outcome measures of clinical performance. Furthermore, FQHCs that fully adopted HIT had 7 percent higher clinical performance on hypertension control than those that did not adopt HIT. This study's findings can assist stakeholders to make informed decisions for improving care and sustaining a competitive advantage.

The French Health Data Hub and the German Medical Informatics Initiatives: Two National Projects to Promote Data Sharing in Healthcare.

OBJECTIVE: The diversity and volume of health data have been rapidly increasing in recent years. While such big data hold significant promise for accelerating discovery, data use entails many challenges including the need for adequate computational infrastructure and secure processes for data sharing and access. In Europe, two nationwide projects have been launched recently to support these objectives. This paper compares the French Health Data Hub initiative (HDH) to the German Medical Informatics Initiatives (MII). METHOD: We analysed the projects according to the following criteria: (i) Global approach and ambitions, (ii) Use cases, (iii) Governance and organization, (iv) Technical aspects and interoperability, and (v) Data privacy access/data governance. RESULTS: The French and German projects share the same objectives but are different in terms of methodologies. The HDH project is based on a top-down approach and focuses on a shared computational infrastructure, providing tools and services to speed projects between data producers and data users. The MII project is based on a bottom-up approach and relies on four consortia including academic hospitals, universities, and private partners. CONCLUSION: Both projects could benefit from each other. A Franco-German cooperation, extended to other countries of the European Union with similar initiatives, should allow sharing and strengthening efforts in a strategic area where competition from other countries has increased.

Envisioning health equity for American Indian/Alaska Natives: a unique HIT opportunity.

The Indian Health Service provides care to remote and under-resourced communities in the United States. American Indian/Alaska Native patients have some of the highest morbidity and mortality among any ethnic group in the United States. Starting in the 1980s, the IHS implemented the Resource and Patient Management System health information technology (HIT) platform to improve efficiency and quality to address these disparities. The IHS is currently assessing the Resource and Patient Management System to ensure that changing health information needs are met. HIT assessments have traditionally focused on cost, reimbursement opportunities, infrastructure, required or desired functionality, and the ability to meet provider needs. Little information exists on frameworks that assess HIT legacy systems to determine solutions for an integrated rural healthcare system whose end goal is health equity. This search for a next-generation HIT solution for a historically underserved population presents a unique opportunity to envision and redefine HIT that supports health equity as its core mission.

Do Neural Information Extraction Algorithms Generalize Across Institutions?

PURPOSE: Natural language processing (NLP) techniques have been adopted to reduce the curation costs of electronic health records. However, studies have questioned whether such techniques can be applied to data from previously unseen institutions. We investigated the performance of a common neural NLP algorithm on data from both known and heldout (ie, institutions whose data were withheld from the training set and only used for testing) hospitals. We also explored how diversity in the training data affects the system's generalization ability. METHODS: We collected 24,881 breast pathology reports from seven hospitals and manually annotated them with nine key attributes that describe types of atypia and cancer. We trained a convolutional neural network (CNN) on annotations from either only one (CNN1), only two (CNN2), or only four (CNN4) hospitals. The trained systems were tested on data from five organizations, including both known and heldout ones. For every setting, we provide the accuracy scores as well as the learning curves that show how much data are necessary to achieve good performance and generalizability. RESULTS: The system achieved a cross-institutional accuracy of 93.87% when trained on reports from only one hospital (CNN1). Performance improved to 95.7% and 96%, respectively, when the system was trained on reports from two (CNN2) and four (CNN4) hospitals. The introduction of diversity during training did not lead to improvements on the known institutions, but it boosted performance on the heldout institutions. When tested on reports from heldout hospitals, CNN4 outperformed CNN1 and CNN2 by 2.13% and 0.3%, respectively. CONCLUSION: Real-world scenarios require that neural NLP approaches scale to data from previously unseen institutions. We show that a common neural NLP algorithm for information extraction can achieve this goal, especially when diverse data are used during training.

The Best of Both Models: Key Components of a Successful Hybrid Project Management Office Model in a Health Care Organization.

Project management (PM) is considered an important competency for improving organizational efficiencies, and its practice is evolving in health care organizations. As a medium-sized health care organization, Ontario Shores Centre for Mental Health Sciences used a hybrid PM office model and created a PM network to connect the small, centralized PM office to the decentralized project leaders. The key components to create the PM network were (1) skilled leader, (2) organizational support, (3) infrastructure, and (4) session content. Membership grew from 12 to 45 members within the first year. The network continues to evolve to meet member and organizational needs.

[Determinants of time required by medical information technicians for quality control of hospital activity coding, in French medico-administrative system]. / Déterminants du temps nécessaire au contrôle qualité dans le cadre du programme de médicalisation des systèmes d'information (PMSI), dans le champ médecine, chirurgie et obstétrique (MCO) d'un centre hospitalier régional, par les techniciens d'information médicale.

BACKGROUND: Since 2008, in France, hospital funding is determined by the nature of activities provided (activity-based funding). Quality control of hospital activity coding is essential to optimize hospital remuneration. There is a need for reliable tools to allocate human resources wisely in order to improve these controls. METHODS: The main objective of this study was to identify the determinants of time needed by medical information technicians to control hospital activity coding in a Regional Hospital Center. From March 2016 to the beginning of January 2017, medical information technicians reported the time they spent on each quality control, and the time they needed when they had to code the entire stay. Multiple linear regressions were performed to identify the determinants of quality control or coding duration. A split sample validation was used: model was created on one half of the sample and validated on the remaining half. RESULTS: Among the controls, 5431 were included in the analysis of determinants of control duration (2715 kept aside for model validation). Seven determinants have been identified (stay duration, level of complexity, month of control, type of control, medical information technician, rank of classing information, and major diagnostic category). The correlation coefficient between predicted and real control duration was 0.71 (P<10-4); 808 stays were included in the analysis of determinants of coding duration (404 kept aside for model validation). Two determinants have been identified. The correlation coefficient, between predicted and real coding duration, was 0.47 (P<10-3). We performed the same multiple regression, on 2017 activity data, to estimate the weight of each hospital activity pole, regarding quality control of hospital activity coding. CONCLUSION: We succeeded in modeling time needed for quality control of hospital stays. These results helped to estimate human resources required for quality control of each hospital pole. Nevertheless, the second analysis did not give satisfactory results: we failed in modeling time needed to code hospital stays.

Patient disempowerment through the commercial access to digital health records.

In this article, I consider how patients are disempowered through the commercial access to their health data in the United States. I examine two healthcare information technology bills that ostensibly give patients access and control over their health records. However, I contend that, since these regulations were drafted, in part or in whole, by corporate interests represented by healthcare lobbyists, policymakers use the rhetorical device of patient empowerment to allow for the commercial access to patient data, which ultimately disempowers patients. This is because in both bills the asymmetrical relationship to patient data remains the same: patients do not have ownership or control over the data that they produce. Rather, policymakers legislatively cede control over patient data to commercial interests.

Technological Ecosystems in the Health Sector: a Mapping Study of European Research Projects.

The European Union has a substantial investment in research and development and demand side-measures in the health sector in order to promote new initiatives, prevent disease and foster healthy lifestyles. In particular, the European Commission and other European entities have funded research projects focused on the use of technology in the health sector. In this context, health research initiatives have evolved from user-centred monolithic solutions into collaborative partnerships of different stakeholders that gather around different technological platforms. In order to identify the lacks and opportunities in this area, a systematic mapping study was conducted with the aim of identifying and analysing the recent research projects developed in Europe related to technological ecosystems in the health sector. The study covered closed European research projects from 2003 to 2018. This paper aims to extend that systematic mapping study through ongoing research projects. The analysis of these research projects provides an overview of the current trends and identify the lacks and opportunities to define new advances in this research area. Moreover, the comparison between the first mapping study focused on closed projects, and the current study, allows getting an overview of the evolution of technological ecosystems in the health sector.

'Fit-for-purpose?' - challenges and opportunities for applications of blockchain technology in the future of healthcare.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Public health delivery in the information age: the role of informatics and technology.

AIM: Public health systems have embraced health informatics and information technology as a potential transformational tool to improve real-time surveillance systems, communication, and sharing of information among various agencies. Global pandemic outbreaks like Zika and Ebola were quickly controlled due to electronic surveillance systems enabling efficient information access and exchange. However, there is the need for a more robust technology to enhance adequate epidemic forecasting, data sharing, and effective communication. The purpose of this review was to examine the use of informatics and information technology tools and its impact on public health delivery. METHOD: Investigators searched six electronic databases. These were MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete, Cochrane Database of Systematic Reviews, COMPENDEX, Scopus, and Academic Search Premier from January 2000 to 31 March 2016. RESULTS: A total of 60 articles met the eligibility criteria for inclusion. These studies were organized into three areas as (1) definition of the term public health informatics; (2) type of public health surveillance systems and implications for public health; and (3) electronic surveillance systems functionality, capability, training, and challenges. Our analysis revealed that due to the growing expectations to provide real-time response and population-centered evidence-based public health in this information-driven age there has been a surge in informatics and information technology adoption. Education and training programs are now available to equip public health students and professionals with skills in public health informatics. However, obstacles including interoperability, data standardization, privacy, and technology transfer persist. CONCLUSION: Re-engineering the delivery of public health is necessary to meet the demands of the 21st century and beyond. To meet this expectation, public health must invest in workforce development and capacity through education and training in informatics.