Review
Health Care Sciences & Services
Umar Ruhi, Ritesh Chugh
Summary: This paper provides an integrative review of the extant literature on personal health records (PHRs), offering a high-level functional utility model of PHR features and functions, conceptualizing a consumer value framework of PHRs, and summarizing the benefits of PHRs for various healthcare constituents.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Review
Health Care Sciences & Services
Timothy Charles Kariotis, Megan Prictor, Shanton Chang, Kathleen Gray
Summary: This paper conducted a scoping review to explore the impact of electronic health records (EHRs) on information practices in mental health contexts, as well as how sensitive information, data standardization, and therapeutic relationships are managed when using EHRs. The review included 40 articles and found that EHRs improved the documentation of information compared to paper, but mental health-related information was often missing, especially sensitive information. EHRs introduced standardized documentation practices that raised issues in the mental health context. EHRs also disrupted information workflows and had usability issues. The management of sensitive information in EHRs was problematic. The study highlighted the need for EHRs to better reflect the complexity and sensitivity of information practices and workflows in mental health contexts.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Review
Computer Science, Artificial Intelligence
Adrian Caruana, Madhushi Bandara, Katarzyna Musial, Daniel Catchpoole, Paul J. Kennedy
Summary: This paper systematically reviews AHR-based research, analysing the application of machine learning techniques and health informatics applications on AHRs. The study finds that while AHR-based studies are disconnected from each other, the use of AHRs in health informatics research is substantial and accelerating.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Review
Computer Science, Information Systems
Amir Kamel Rahimi, Oliver J. Canfell, Wilkin Chan, Benjamin Sly, Jason D. Pole, Clair Sullivan, Sally Shrapnel
Summary: This study systematically reviewed the literature on the development and validation of machine learning (ML) models using electronic medical records (EMR) for improving the care of hospitalized adult patients with diabetes. The study found a limited number of ML models developed for inpatient management of diabetes, but none of these models have been implemented in real hospital settings.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2022)
Review
Health Care Sciences & Services
Charlene Weir
Summary: This article highlights the shortcomings of electronic health records in representing the human context, emphasizing the importance of narrative communication and the deficiencies in EHR support for such communication functions.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Health Care Sciences & Services
Xiao Luo, Haoran Ding, Andrea Broyles, Stuart J. Warden, Ranjani N. Moorthi, Erik A. Imel
Summary: The study aimed to improve the detection of sarcopenia using structured data from electronic health records (EHR) through machine learning models. The results showed that sarcopenia can be predicted from EHR, which can facilitate large-scale early detection and intervention in clinical populations.
Article
Geriatrics & Gerontology
Claire M. Campbell, Daniel R. Murphy, George E. Taffet, Anita B. Major, Christine S. Ritchie, Bruce Leff, Aanand D. Naik
Summary: The paper discusses a conceptual model for EHR implementation of quality measures, successfully implemented a depression screening quality measure in a home-based medical care setting. Additional components of early leadership, clinician buy-in, strong IT relationships, and simplified implementation processes were necessary for success.
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY
(2021)
Review
Health Care Sciences & Services
Debby J. Damen, Guus G. Schoonman, Barbara Maat, Mirela Habibovic, Emiel Krahmer, Steffen Pauws
Summary: This study explores the barriers and facilitators patients face when deciding to review, enter, update, or modify their personal and medical data in their PEHR. The findings indicate that patients tend to use their PEHR passively rather than actively and refrain from generating and managing data due to concerns about data validity, applicability, and confidentiality. Patient-generated and-managed health data ensures the completeness and up-to-dateness of medical records, and is positively associated with patient engagement and satisfaction.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Review
Computer Science, Information Systems
Siyue Yang, Paul Varghese, Ellen Stephenson, Karen Tu, Jessica Gronsbell
Summary: This study evaluates the application of machine learning-based phenotyping in terms of data sources, phenotypes considered, methods applied, and reporting and evaluation methods. The results show that most studies used data from a single institution, including information from clinical notes. While most studies focused on binary phenotypes such as chronic conditions, machine learning also enabled the characterization of nuanced phenotypes. The study discusses the application of supervised deep learning, semi-supervised learning, and unsupervised learning methods. Machine learning approaches did not uniformly outperform rule-based algorithms, but deep learning offered a marginal improvement over traditional machine learning methods for many conditions.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Review
Computer Science, Information Systems
Irene Li, Jessica Pan, Jeremy Goldwasser, Neha Verma, Wai Pan Wong, Muhammed Yavuz Nuzumlali, Benjamin Rosand, Yixin Li, Matthew Zhang, David Chang, R. Andrew Taylor, Harlan M. Krumholz, Dragomir Radev
Summary: Electronic health records (EHRs) are digital collections of patient healthcare events and observations that play a critical role in healthcare delivery, operations, and research. However, a significant portion of the information stored in EHRs is unstructured text, making it challenging to process automatically. Recent advances in neural network and deep learning methods for Natural Language Processing have shown promise in unlocking the potential of this unstructured text in EHRs.
COMPUTER SCIENCE REVIEW
(2022)
Review
Ethics
Jan Piasecki, Ewa Walkiewicz-Zarek, Justyna Figas-Skrzypulec, Anna Kordecka, Vilius Dranseika
Summary: The digitization of health records has changed their accessibility, as electronic health records can now be accessed by multiple authorized users. A systematic review on the ethical issues of research using EHRs revealed the complexity and depth of problems, with a central ethical question being how to manage access to EHRs. Various interconnected issues such as streamlining access, minimizing risk, engaging and educating patients, and ensuring trustworthy governance of EHR data were identified as key ethical considerations in EHR-based research.
MEDICINE HEALTH CARE AND PHILOSOPHY
(2021)
Review
Health Care Sciences & Services
Hao Sen Andrew Fang, Teng Hwee Tan, Yan Fang Cheryl Tan, Chun Jin Marcus Tan
Summary: Blockchain technology in the healthcare sector has matured over the past 5 years, with a growing trend towards publications describing prototypes and implementations. Most articles on blockchain PHRs are found in engineering or computer science publications, with common design choices being permissioned blockchains and off-chain storage. Although interest in blockchain PHRs is increasing, the technology is largely in the conceptual stage.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Review
Computer Science, Information Systems
Safa ElKefi, Onur Asan
Summary: This literature review explores the impact of health information technologies on doctor-patient communication in oncology settings. It identifies that effective use of technology can improve access to care, increase patient satisfaction, enhance social support, and strengthen the therapeutic alliance between clinicians and patients. Future studies should focus on comparing outpatient and inpatient settings in terms of effort required and impacts from both perspectives.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2021)
Review
Medical Informatics
Shikha Modi, Sue S. Feldman
Summary: This literature review focuses on the value of electronic health records (EHRs) in relation to financial and clinical outcomes. It investigates how EHRs contribute to these outcomes and identifies both positive and negative impacts.
JMIR MEDICAL INFORMATICS
(2022)
Review
Health Care Sciences & Services
Christophe A. T. Stevens, Alexander R. M. Lyons, Kanika Dharmayat, Alireza Mahani, Kausik K. Ray, Antonio J. Vallejo-Vaz, Mansour T. A. Sharabiani
Summary: Electronic health records provide opportunities for machine learning techniques to identify undiagnosed individuals with diseases and improve medical screening and case finding. Ensemble machine learning models, especially those with complex combination strategies and heterogeneous classifiers, often outperform other models in this context. However, there is a lack of comprehensive reporting on the methodologies used in clinical research involving machine learning.
Article
Medicine, Research & Experimental
Amir H. Pakpour, Sara Fazeli, Isa Mohammadi Zeidi, Zainab Alimoradi, Mattias Georgsson, Anders Brostrom, Marc N. Potenza
Summary: This study aims to determine the effectiveness of an app-based intervention for treating Internet Gaming Disorder (IGD) among adolescents, utilizing a transtheoretical model and cognitive-behavioral therapy. By delivering eight consecutive sessions over two months, the study seeks to change adolescents' behaviors and assess the outcomes through measures such as scales and questionnaires.
Article
Infectious Diseases
Elvira de Lara-Tuprio, Carlo Delfin S. Estadilla, Jay Michael R. Macalalag, Timothy Robin Teng, Joshua Uyheng, Kennedy E. Espina, Christian E. Pulmano, Maria Regina Justina E. Estuar, Raymond Francis R. Sarmiento
Summary: This paper documents the role of mathematical modeling in guiding pandemic policies in the Philippines, showing how the FASSSTER model accurately predicted the outcomes of interventions and helped in gradually reopening economic activities while limiting the spread of COVID-19.
Article
Health Care Sciences & Services
Youmin Cho, Rumei Yang, Yang Gong, Yun Jiang
Summary: This nationally representative survey analysis explores disparities in cancer survivors' use of electronic communication with clinicians and highlights the potential impact of the COVID-19 pandemic on e-communication usage. Additional support is needed to promote optimal and high-quality cancer care through e-communication, particularly for older individuals, nonwhite populations, those living in rural areas, and those without regular healthcare providers.
TELEMEDICINE AND E-HEALTH
(2023)
Review
Public, Environmental & Occupational Health
Tao H. Wei, Yun Jiang
Summary: The purpose of this review study was to explore the extent and quality of research on the health needs of women with same-sex attraction (WSSA) in mainland China. The study reviewed published articles and gray reports from 1990 to 2022, and identified unmet health needs in mental health and substance abuse, sexual and reproductive health, and domestic violence among Chinese WSSA. The study also highlighted the barriers to healthcare for Chinese WSSA, including heteronormative assumptions of healthcare providers and concealment of minority sexuality.
Article
Health Care Sciences & Services
Stephanie Ruth Young, Emily Gardiner Lattie, Andrew B. L. Berry, Lynn Bui, Greg Joseph Byrne, Julia Noelani Yoshino Benavente, Michael Bass, Richard C. Gershon, Michael S. Wolf, Cindy J. Nowinski
Summary: This study described the design and proposed implementation of a remote cognitive screening app called MyCog Mobile, which aims to facilitate cognitive screening before annual wellness visits in primary care settings. The findings suggest that primary care clinicians and clinic administrators are motivated to adopt a remote cognitive screening process if it saves time, and older adult patients are interested in completing screeners on a smartphone, with potential benefits such as time-saving and privacy.
JMIR FORMATIVE RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Tavleen Singh, Kirk Roberts, Trevor Cohen, Nathan Cobb, Amy Franklin, Sahiti Myneni
Summary: This study developed a method called PRISM to analyze peer interactions in an online health community, revealing the interplay of multilevel characteristics of online communication and their association with individual health behaviors. The analysis showed that social support and behavioral progress were common communication themes, feedback and monitoring and comparison of behavior were the most used behavior change techniques, and expressive and emotional speech acts were commonly used to express intentions. Social network analysis also revealed associations between users' engagement or abstinence status with various categories of behavior change techniques and speech acts.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Health Care Sciences & Services
Weijiao Zhou, Youmin Cho, Shaomei Shang, Yun Jiang
Summary: This study examined the trends and factors associated with digital health technology use among older adults with cancer. The findings revealed that digital health technology use has increased gradually, especially during the COVID-19 pandemic. However, socioeconomic and racial disparities still exist in older cancer survivors, and they may have unique features influencing their digital health technology use.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Computer Science, Information Systems
Sarvesh Soni, Surabhi Datta, Kirk Roberts
Summary: This article proposes a system called quEHRy, which retrieves precise and interpretable answers to natural language questions from structured data in electronic health records (EHRs). The performance of quEHRy is evaluated on 2 clinical question answering (QA) datasets, and the results show high precision and accuracy. However, errors in medical concept extraction affect the downstream generation of correct logical structures, indicating the need for QA-specific clinical concept normalizers.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Article
Surgery
Egide Abahuje, Carmen M. Diaz, Katherine A. Lin, Kaithlyn Tesorero, Omar Bushara, Sohae Yang, Andrew B. L. Berry, Miriam R. Rafferty, Julie K. Johnson, Anne M. Stey
Summary: This study explored the relationship between team characteristics and leadership and information sharing. It found that team leaders used different leadership techniques to involve team members in discussions related to patient care, predefined tasks for team members allowed them to prepare for effective information sharing during rounds, and a psychologically safe environment allowed team members to participate in discussions related to patient care.
Article
Medical Informatics
Raina Langevin, Andrew B. L. Berry, Jinyang Zhang, Callan E. Fockele, Layla Anderson, Dennis Hsieh, Andrea Hartzler, Herbert C. Duber, Gary Hsieh
Summary: This study investigates patients' perceptions of a chatbot as a tool for social needs screening and uses three implementation outcome measures to evaluate its acceptability, feasibility, and appropriateness. The findings suggest that patients perceive the chatbot as an acceptable, feasible, and appropriate modality for social needs screening.
APPLIED CLINICAL INFORMATICS
(2023)
Article
Health Care Sciences & Services
Surabhi Datta, Kirk Roberts
Summary: The objective of this study is to improve clinical natural language processing by utilizing weak supervision methods that leverage domain resources and expertise. The authors proposed a weak supervision approach based on data programming to extract spatial information from radiology reports. Their weakly supervised BERT model achieved satisfactory results in extracting spatial relations without the need for manual annotations, and outperformed state-of-the-art models when annotated data was available.
Editorial Material
Geriatrics & Gerontology
Yun Jiang, Jinjiao Wang
Summary: JMIR Aging is dedicated to supporting the community of patients and families, clinicians, and scientists in improving the efficiency, equity, and effectiveness of older adult care through the dissemination of cutting-edge evidence in this new digital era, where novel devices and emerging technologies, including artificial intelligence, are playing an incredible role with significant impact on health and health care delivery.
Article
Health Care Sciences & Services
Andrew Wen, Huan He, Sunyang Fu, Sijia Liu, Kurt Miller, Liwei Wang, Kirk E. Roberts, Steven D. Bedrick, William R. Hersh, Hongfang Liu
Summary: Clinical phenotyping is essential for developing digital health applications, but the traditional manual abstraction method is time-consuming and costly. Therefore, there is significant interest in using in-silico methods to accomplish this task. However, current in-silico phenotyping development lacks reusable tools for cross-task generalization and is inaccessible for many potential users. This article highlights the barriers to using in-silico phenotyping and proposes a framework with potential solutions. An example implementation of this framework is introduced as a software application, focusing on ease of adoption, cross-task reusability, and facilitating clinical phenotyping algorithm development.
NPJ DIGITAL MEDICINE
(2023)
Article
Psychology, Clinical
Jonah Meyerhoff, Rachel Kornfield, Emily G. Lattie, Ashley A. Knapp, Kaylee P. Kruzan, Maia Jacobs, Caitlin A. Stamatis, Bayley J. Taple, Miranda L. Beltzer, Andrew B. L. Berry, Madhu Reddy, David C. Mohr, Andrea K. Graham
Summary: This article utilizes five case studies to illustrate pragmatic approaches to the development of digital mental health interventions and provides a series of questions for researchers to navigate key decision points in the development process.
INTERNET INTERVENTIONS-THE APPLICATION OF INFORMATION TECHNOLOGY IN MENTAL AND BEHAVIOURAL HEALTH
(2023)
Proceedings Paper
Computer Science, Information Systems
Hyeyoung Ryu, Andrew B. L. Berry, Catherine Y. Lim, Andrea L. Hartzler, Tad Hirsch, Juanita I. Trejo, Zoe A. Bermet, Brandi Crawford-Gallagher, Vi Tran, Dawn Ferguson, David J. Cronkite, Brooks Tiffany, John Weeks, James D. Ralston
Summary: Individuals with multiple chronic health conditions can benefit from using an interactive visualization system, called Conversation Canvas, to develop and share connections between personal values and self-management tasks. This study showed that this guided process and visualization can help individuals understand their health priorities, share them with healthcare providers, and support value-aligned changes.
PROCEEDINGS OF THE 2023 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2023
(2023)