Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions.

Background: Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality. Methods: We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions. Results: We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes. Discussion: Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Human Factors and Organizational Issues: Contributions from 2022.

OBJECTIVES: To review publications in the field of Human Factors and Organisational Issues (HF&OI) in the year 2022 and to assess major contributions to the subject. METHOD: A bibliographic search was conducted following refinement of standardized queries used in previous years. Sources used were PubMed, Web of Science, and referral via references from other papers. The search was carried out in January 2023, and (using the PubMed article type inclusion functionality) included clinical trials, meta-analyses, randomized controlled trials, reviews, case reports, classical articles, clinical studies, observational studies (including veterinary), comparative studies, and pragmatic clinical trials. RESULTS: Among the 520 returned papers published in 2022 in the various areas of HF&OI, the full review process selected two best papers from among 10 finalists. As in previous years, topics showed development including increased use of Artificial Intelligence (AI) and digital health tools, advancement of methodological frameworks for implementation and evaluation as well as design, and trials of specific digital tools. CONCLUSIONS: Recent literature in HF&OI continues to focus on both theoretical advances and practical deployment, with focus on areas of patient-facing digital health, methods for design and evaluation, and attention to implementation barriers.

Navigating Infection Control Processes in a COVID-19 Only Safety-Net Hospital at the Height of the Pandemic.

Hospitals faced extraordinary challenges during the pandemic. Some of these were directly related to patient care-expanding capacities, adjusting services, and using new knowledge to save lives in a dynamically changing situation. Other challenges were regulatory. The COVID-19 pandemic significantly disrupted routine hospital infection control practices. We report the results of an interview study with 13 individuals associated with infection control in a small independent hospital. We employed the Systems Engineering Initiative for Patient Safety (SEIPS) model as a theoretical framework and as a basis to analyze data. The findings revealed how routine practices and protocols were displaced in notable ways. Due to COVID-19, clinical activities were modified, and the increased demands of regulatory reporting became laborious, and punitive if reports were late. Strategies are needed to mitigate increases in healthcare-associated infections. Our examination of the information flows, transformation, and needs shows areas in which digital tool creation and the use of a trained informatics workforce could ameliorate and automate many processes.

Modelling Information Needs and Sources in a COVID-19 Designated Hospital.

COVID-19 remains an important focus of study in the field of public health informatics. COVID-19 designated hospitals have played an important role in the management of patients affected by the disease. In this paper we describe our modelling of the needs and sources of information for infectious disease practitioners and hospital administrators used to manage a COVID-19 outbreak. Infectious disease practitioner and hospital administrator stakeholders were interviewed to learn about their information needs and where they obtained their information. Stakeholder interview data were transcribed and coded to extract use case information. The findings indicate that participants used many and varied sources of information in the management of COVID-19. The use of multiple, differing sources of data led to considerable effort. In modelling participants' activities, we identified potential subsystems that could be used as a basis for developing an information system specific to the public health needs of hospitals providing care to COVID-19 patients.

Comparing Responses to COVID-19 Across Institutions: Conceptualization of an Emergency Response Maturity Model.

The impact of Covid-19 on hospitals was profound, with many lower-resourced hospitals' information technology resources inadequate to efficiently meet the new needs. We interviewed 52 personnel at all levels in two New York City hospitals to understand their issues in emergency response. The large differences in IT resources show the need for a schema to classify hospital IT readiness for emergency response. Here we propose a set of concepts and model, inspired by the Health Information Management Systems Society (HIMSS) maturity model. The schema is designed to permit evaluation of hospital IT emergency readiness, permitting remediation of IT resources where necessary.

Using Clinical Data Visualizations in Electronic Health Record User Interfaces to Enhance Medical Student Diagnostic Reasoning: Randomized Experiment.

BACKGROUND: In medicine, the clinical decision-making process can be described using the dual-process theory consisting of the fast, intuitive "System 1," commonly seen in seasoned physicians, and the slow, deliberative "System 2," associated with medical students. System-1-type diagnostic reasoning is thought to be less cognitively burdensome, thereby reducing physician error. To date, limited literature exists on inducing System-1-type diagnosis in medical students through cognitive heuristics, particularly while using modern electronic health record (EHR) interfaces. OBJECTIVE: In this experimental pilot study, we aimed to (1) attempt to induce System-1-type diagnostic reasoning in inexperienced medical students through the acquisition of cognitive user interface heuristics and (2) understand the impact of clinical patient data visualizations on students' cognitive load and medical education. METHODS: The participants were third- and fourth-year medical students recruited from the University of Pittsburgh School of Medicine who had completed 1+ clinical rotations. The students were presented 8 patient cases on a novel EHR, featuring a prominent data visualization designed to foster at-a-glance rapid case assessment, and asked to diagnose the patient. Half of the participants were shown 4 of the 8 cases repeatedly, up to 4 times with 30 seconds per case (Group A), and the other half of the participants were shown cases twice with 2 minutes per case (Group B). All participants were then asked to provide full diagnoses of all 8 cases. Finally, the participants were asked to evaluate and elaborate on their experience with the system; content analysis was subsequently performed on these user experience interviews. RESULTS: A total of 15 students participated. The participants in Group A scored slightly higher on average than those in Group B, with a mean percentage correct of 76% (95% CI 0.68-0.84) versus 69% (95% CI 0.58-0.80), and spent on average 50% less time per question than Group B diagnosing patients (13.98 seconds vs 19.13 seconds, P=.03, respectively). When comparing the novel EHR design to previously used EHRs, 73% (n=11) of participants rated the new version on par or higher (3+/5). Ease of use and intuitiveness of this new system rated similarly high (mean score 3.73/5 and 4.2/5, respectively). In qualitative thematic analysis of poststudy interviews, most participants (n=11, 73%) spoke to "pattern-recognition" cognitive heuristic strategies consistent with System 1 decision-making. CONCLUSIONS: These results support the possibility of inducing type-1 diagnostics in learners and the potential for data visualization and user design heuristics to reduce cognitive burden in clinical settings. Clinical data presentation in the diagnostic reasoning process is ripe for innovation, and further research is needed to explore the benefit of using such visualizations in medical education.

Best Papers in Human Factors and Sociotechnical Development.

OBJECTIVES: To select the best papers that made original and high impact contributions in human factors and organizational issues in biomedical informatics in 2021. METHODS: A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2021 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 3,206 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 and mobile health. This year three papers were clearly outstanding and help advance in the field. They provide examples of examining novel and important topics such as the nature of human-machine interaction behavior and norms, use of social-media based design for an electronic health record, and emerging topics such as brain-computer interfaces. thematic development of electronic health records and usability techniques, and condition-focused patient facing tools. 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.

Testing Medical Student Diagnostic Reasoning Using Clinical Data Visualizations.

This experiment aimed to (1) induce System-1-type diagnostic reasoning in medical students through the acquisition of cognitive user interface (UI) heuristics and (2) understand qualitatively how clinical data visualizations could enhance medical education. Third- and fourth-year medical students were presented patient cases through a novel electronic health record (EHR) design then asked to diagnose patients after being shown the cases either briefly and repeatedly (Group A) or twice over a longer period (Group B). Group A had higher accuracy than Group B. Findings support the possibility of inducing System-1 reasoning via UI heuristics and potential of integrating data visualizations in medical education.

Defining Telehealth for Research, Implementation, and Equity.

When the COVID-19 pandemic spurred a disruption in health care delivery, the role of telehealth shifted from an option to a near necessity to maintain access when in-person care was deemed too risky. Each state and many organizations developed temporary telehealth policies for the COVID-19 emergency, each policy with its own definitions, coverage, government cases, and regulations. As pandemic-era policies are now being replaced with more permanent guidelines, we are presented with an opportunity to reevaluate how telehealth is integrated into routine health care delivery. We believe that the timing and nature of the sequential steps for redefining telehealth are critical and that it is important to develop a clear and agreed-on definition of telehealth and its components at this time. We further suggest a necessary preliminary step is to support clear communication and interoperability throughout the development of this definition. Precise and standardized definitions could create an unambiguous environment for clinical care for both patients and providers while enabling researchers to have more precise control over their investigations of telehealth. A consensus when defining telehealth and its derivatives at this critical stage could create a consistent expectation of care for all patients and those who set the standards of care, as it has for other clinical scenarios with clear guidelines.

A Comparative Evaluation of Measurement-Based Psychiatric Care Delivered via Specialized Telemental Health Platform Versus Treatment As Usual: A Retrospective Analysis.

Background and objective A significant proportion of the adult population in the United States (US) live with some form of mental illness. The more prevalent conditions of depression and anxiety are typically managed in primary care settings rather than specialty care. The aim of this study was to determine the efficacy of a novel, measurement-driven psychiatric treatment platform delivered via an online telemental health platform as compared to treatment as usual (TAU). Methods The TAU dataset and the telemental health platform (Brightside) dataset were constructed based on the total populations of adult patients receiving care for depression from January 2018 through December 2020 (November 2018 through March 2021 for the Brightside group). Patients in both groups had a primary mental health diagnosis of depression and the presence of a positive screen for depression as measured by the Patient Health Questionnaire-9 (PHQ-9) upon initiation of treatment. HITLAB, an independent digital health verification and testing lab, conducted comparative analyses of the two groups using the Chi-square test of independence. Results Close to 80% of telemental health platform patients experienced a reduction of 5 or more points from their baseline PHQ-9 score as compared to 52% of TAU patients. The mean reduction in PHQ-9 score was slightly higher in the Brightside group (-11.5) versus the TAU group (-10.1). Chi-square tests of independence [x2 (1, n=6281) = 256.75, p≤0.001] for meaningful reduction and for remission [x2 (1, n=6281) = 105.50 p≤0.001] were highly significant. Conclusion The telemental health platform patients performed significantly better than those under psychiatric TAU in terms of reduction in symptoms of depression in adults.

Application of Natural Language Processing to Learn Insights on the Clinician's Lived Experience of Electronic Health Records.

We interviewed six clinicians to learn about their lived experience using electronic health records (EHR, Allscripts users) using a semi-structured interview guide in an academic medical center in New York City from October to November 2016. Each participant interview lasted approximately one to two hours. We applied a clustering algorithm to the interview transcript to detect topics, applying natural language processing (NLP). We visualized eight themes using network diagrams (Louvain modularity 0.70). Novel findings include the need for a concise and organized display and data entry page, the user controlling functions for orders, medications, radiology reports, and missing signals of indentation or filtering functions in the order page and lab results. Application of topic modeling to qualitative interview data provides far-reaching research insights into the clinicians' lived experience of EHR and future optimal EHR design to address human-computer interaction issues in an acute care setting.

Making the case for workforce diversity in biomedical informatics to help achieve equity-centered care: a look at the AMIA First Look Program.

Developing a diverse informatics workforce broadens the research agenda and ensures the growth of innovative solutions that enable equity-centered care. The American Medical Informatics Association (AMIA) established the AMIA First Look Program in 2017 to address workforce disparities among women, including those from marginalized communities. The program exposes women to informatics, furnishes mentors, and provides career resources. In 4 years, the program has introduced 87 undergraduate women, 41% members of marginalized communities, to informatics. Participants from the 2019 and 2020 cohorts reported interest in pursuing a career in informatics increased from 57% to 86% after participation, and 86% of both years' attendees responded that they would recommend the program to others. A June 2021 LinkedIn profile review found 50% of participants working in computer science or informatics, 4% pursuing informatics graduate degrees, and 32% having completed informatics internships, suggesting AMIA First Look has the potential to increase informatics diversity.

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.

Enhancing Safety During a Pandemic Using Virtual Care Remote Monitoring Technologies and UML Modeling.

OBJECTIVES: This paper describes a methodology for gathering requirements and early design of remote monitoring technology (RMT) for enhancing patient safety during pandemics using virtual care technologies. As pandemics such as COrona VIrus Disease (COVID-19) progress there is an increasing need for effective virtual care and RMT to support patient care while they are at home. METHODS: The authors describe their work in conducting literature reviews by searching PubMed.gov and the grey literature for articles, and government websites with guidelines describing the signs and symptoms of COVID-19, as well as the progression of the disease. The reviews focused on identifying gaps where RMT could be applied in novel ways and formed the basis for the subsequent modelling of use cases for applying RMT described in this paper. RESULTS: The work was conducted in the context of a new Home of the Future laboratory which has been set up at the University of Victoria. The literature review led to the development of a number of object-oriented models for deploying RMT. This modeling is being used for a number of purposes, including for education of students in health infomatics as well as testing of new use cases for RMT with industrial collaborators and projects within the smart home of the future laboratory. CONCLUSIONS: Object-oriented modeling, based on analysis of gaps in the literature, was found to be a useful approach for describing, communicating and teaching about potential new uses of RMT.

Ethics and informatics in the age of COVID-19: challenges and recommendations for public health organization and public policy.

The COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we critically analyze informatics-related ethical issues in light of the pandemic across 3 themes: (1) public health reporting and data sharing, (2) contact tracing and tracking, and (3) clinical scoring tools for critical care. We provide context and rationale for ethical considerations and recommendations that are actionable during the pandemic and conclude with recommendations calling for longer-term, broader change (beyond the pandemic) for public health organization and policy reform.

Characterizing and Visualizing Display and Task Fragmentation in the Electronic Health Record: Mixed Methods Design.

BACKGROUND: The complexity of health care data and workflow presents challenges to the study of usability in electronic health records (EHRs). Display fragmentation refers to the distribution of relevant data across different screens or otherwise far apart, requiring complex navigation for the user's workflow. Task and information fragmentation also contribute to cognitive burden. OBJECTIVE: This study aims to define and analyze some of the main sources of fragmentation in EHR user interfaces (UIs); discuss relevant theoretical, historical, and practical considerations; and use granular microanalytic methods and visualization techniques to help us understand the nature of fragmentation and opportunities for EHR optimization or redesign. METHODS: Sunburst visualizations capture the EHR navigation structure, showing levels and sublevels of the navigation tree, allowing calculation of a new measure, the Display Fragmentation Index. Time belt visualizations present the sequences of subtasks and allow calculation of proportion per instance, a measure that quantifies task fragmentation. These measures can be used separately or in conjunction to compare EHRs as well as tasks and subtasks in workflows and identify opportunities for reductions in steps and fragmentation. We present an example use of the methods for comparison of 2 different EHR interfaces (commercial and composable) in which subjects apprehend the same patient case. RESULTS: Screen transitions were substantially reduced for the composable interface (from 43 to 14), whereas clicks (including scrolling) remained similar. CONCLUSIONS: These methods can aid in our understanding of UI needs under complex conditions and tasks to optimize EHR workflows and redesign.

Human Factors and Organizational Issues.

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 2019. METHODS: A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2019 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two editors led to a total of 30 papers. These papers were discussed for a selection of 15 finalist papers, which were then reviewed by the two editors and by three external reviewers from internationally renowned research teams. RESULTS: The query process resulted in 626 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 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. 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 "Advancing People of Color in Clinical Trials Now!": Web-Based Randomized Controlled Trial Protocol.

BACKGROUND: Participation in clinical trials among people of color remains low, compared with white subjects. This protocol describes the development of "Advancing People of Color in Clinical Trials Now!" (ACT Now!), a culturally tailored website designed to influence clinical trial decision making among people of color. OBJECTIVE: This cluster randomized study aims to test the efficacy of a culturally tailored website to increase literacy, self-efficacy, and willingness to enroll in clinical trials among people of color. METHODS: ACT Now! is a randomized trial including 2 groups: (1) intervention group (n=50) with access to the culturally tailored website and (2) control group (n=50) exposed to a standard clinical recruitment website. Clinical trial literacy and willingness to enroll in a clinical trial will be measured before and after exposure to the website corresponding to their assigned group (intervention or control). Surveys will be conducted at baseline and during the 1-month postintervention and 3-month follow-up. Website architecture and wireframing will be informed by the literature and experts in the field. Statistical analysis will be conducted using a two-tailed t test, with 80% power, at .05 alpha level, to increase clinical trial literacy, self-efficacy, and willingness to enroll in clinical trials 3 months post intervention. RESULTS: We will design a culturally tailored website that will provide leverage for community stakeholders to influence clinical trial literacy, self-efficacy, and willingness to enroll in clinical trials among racial and ethnic groups. ACT Now! applies a community-based participatory research approach through the use of a community steering committee (CSC). The CSC provides input during the research study conception, development, implementation, and enrollment. CSC relationships help foster trust among communities of color. ACT Now! has the potential to fill a gap in clinical trial enrollment among people of color through an accessible web-based website. This study was funded in July 2017 and obtained institutional review board approval in spring 2017. As of December 2019, we had enrolled 100 participants. Data analyses are expected to be completed by June 2020, and expected results are to be published in fall 2020. CONCLUSIONS: ACT Now! has the potential to fill an important gap in clinical trial enrollment among people of color through an accessible web-based website. TRIAL REGISTRATION: ClinicalTrials.gov NCT03243071; https://clinicaltrials.gov/ct2/show/NCT00102401. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17589.

Use of Eye-Tracking in Studies of EHR Usability - The Current State: A Scoping Review.

Eye-tracking has long been used to assess usability for the public web. Recently, it is used to assess user behavior with electronic health records (EHRs). We conducted a scoping review of studies involving eye-tracking for usability of EHRs to determine the current state. Three main themes emerged: studies of usual use of systems, development of new methods, and studies of new features. Detailed user behaviors revealed by eye-tracking can contribute valuable information to redesign efforts.

Human Factors and Sociotechnical Issues.

OBJECTIVE: To summarize significant research contributions on human factors (HF) and organizational issues in medical informatics published in 2018. METHODS: An extensive search using PubMed/Medline and Web of Science® was conducted to identify the scientific contributions published in 2018 that address human factors and organizational issues in medical informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of four best papers was conducted by the editorial board of the Yearbook. RESULTS: The four selected best papers are excellent contributions to the HF literature: they show the added value of HF studies by providing nice illustrated and rigorous interventions. CONCLUSION: HF interventions are known to have great potential to contribute to efficient HIT design, but the interventions still face challenges in successfully demonstrating their value to the main stakeholders of the healthcare domain. There is a need to strengthen the demand for high-quality HF studies by increasing awareness among powerful stakeholders of the value of high-quality HF studies.