Relationship Between Patient Portal Tool Use and Medication Adherence and Viral Load Among Patients Living with HIV.

BACKGROUND: Patient portals play an increasingly critical role in engaging patients in their health care. They have the potential to significantly impact the health of those living with chronic diseases, such as HIV, for whom consistent care engagement is both critical and complex. OBJECTIVE: The primary aim was to examine the longitudinal relationships between individual portal tool use and health-related outcomes in patients living with HIV. DESIGN: Retrospective cohort study using electronic health record data to examine the relationship between patient portal tool use and key HIV-specific, health-related outcomes in patients engaged in care in the Veterans Health Administration (VA) through the application of marginal structural models. PARTICIPANTS: A national sample of patients living with HIV (PLWH) active in VA care who were registered to use the VA's patient portal, My HealtheVet (MHV; n = 18,390) between 10/1/2012 and 4/1/2017. MAIN MEASURES: The MHV tools examined were prescription refill (including prescription refill of an antiretroviral (ART) medication and any medication), secure messaging, view appointments, and view labs. Primary outcomes were viral load test receipt, viral load suppression, and ART medication adherence (measured as proportion of days covered). KEY RESULTS: The use of prescription refill for any medication or for ART was positively associated with ART adherence. Secure messaging was positively associated with ART adherence but not with viral load test receipt or viral load suppression. The use of view appointments was positively associated with ART adherence and viral load test receipt but not viral load suppression. The use of view labs was positively associated with viral load suppression but not ART adherence or viral load test receipt. CONCLUSIONS: These findings highlight the valuable role patient portals may play in improving health-related outcomes among PLWH and have implications for patients living with other types of chronic disease.

A Tool to Identify and Engage Patients on Risky Opioid Regimens.

BACKGROUND: Concerns around opioid safety for patients living with chronic pain have led to a growing number of collaborative and multimodal pain care initiatives. A major challenge in these efforts has been identifying and engaging patients on high-risk opioid regimens in a timely manner. OBJECTIVES: In this clinical informatics case report, we describe the development and implementation of a web-based tool to support providers as they implement an integrated pain support clinical initiative at primary care clinics across three health care systems. METHODS: The tool identifies patients on risky opioid medication regimens and generates autopopulated patient outreach letters. It contains three core functions that: (1) identify patients prescribed high-dose opioids or coprescribed opioids and benzodiazepines, (2) generate automated letters for patients with an upcoming primary care appointment, and (3) allow clinic staff to write back to a database to track outreach and referrals. Qualitative stakeholder feedback was gathered through interviews and user testing to assess perceived usefulness and ease of use of the tool. RESULTS: Over a 24-month period, the tool identified 1,125 patients prescribed risky medication regimens and generated 1,315 total letters as some patients became reeligible. Stakeholder feedback revealed that the tool was useful to quickly find patients on risky medication regimens and efficient in generating prepopulated letters that could be mailed in large batches. Additional feedback led to iterative refinements and improved system capabilities that varied across clinics. CONCLUSION: Deploying clinical informatics tools that prioritize, engage, and track high-risk patient populations supports reduction of risky medication regimens. Such tools can reduce workload burden on busy primary care staff, particularly during implementation studies, and enhance patient-centered care through the use of direct-to-consumer outreach.

A chatbot for hypertension self-management support: user-centered design, development, and usability testing.

Objectives: Health-related chatbots have demonstrated early promise for improving self-management behaviors but have seldomly been utilized for hypertension. This research focused on the design, development, and usability evaluation of a chatbot for hypertension self-management, called "Medicagent." Materials and Methods: A user-centered design process was used to iteratively design and develop a text-based chatbot using Google Cloud's Dialogflow natural language understanding platform. Then, usability testing sessions were conducted among patients with hypertension. Each session was comprised of: (1) background questionnaires, (2) 10 representative tasks within Medicagent, (3) System Usability Scale (SUS) questionnaire, and (4) a brief semi-structured interview. Sessions were video and audio recorded using Zoom. Qualitative and quantitative analyses were used to assess effectiveness, efficiency, and satisfaction of the chatbot. Results: Participants (n = 10) completed nearly all tasks (98%, 98/100) and spent an average of 18 min (SD = 10 min) interacting with Medicagent. Only 11 (8.6%) utterances were not successfully mapped to an intent. Medicagent achieved a mean SUS score of 78.8/100, which demonstrated acceptable usability. Several participants had difficulties navigating the conversational interface without menu and back buttons, felt additional information would be useful for redirection when utterances were not recognized, and desired a health professional persona within the chatbot. Discussion: The text-based chatbot was viewed favorably for assisting with blood pressure and medication-related tasks and had good usability. Conclusion: Flexibility of interaction styles, handling unrecognized utterances gracefully, and having a credible persona were highlighted as design components that may further enrich the user experience of chatbots for hypertension self-management.

Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities.

Rapid development and adoption of natural language processing (NLP) techniques has led to a multitude of exciting and innovative societal and health care applications. These advancements have also generated concerns around perpetuation of historical injustices and that these tools lack cultural considerations. While traditional health care NLP techniques typically include clinical subject matter experts to extract health information or aid in interpretation, few NLP tools involve community stakeholders with lived experiences. In this perspective paper, we draw upon the field of community-based participatory research, which gathers input from community members for development of public health interventions, to identify and examine ways to equitably involve communities in developing health care NLP tools. To realize the potential of community-based NLP (CBNLP), research and development teams must thoughtfully consider mechanisms and resources needed to effectively collaborate with community members for maximal societal and ethical impact of NLP-based tools.

A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs).

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation.

Tablet distribution to veterans: an opportunity to increase patient portal adoption and use.

OBJECTIVE: Examine whether distribution of tablets to patients with access barriers influences their adoption and use of patient portals. MATERIALS AND METHODS: This retrospective cohort study included Veterans Affairs (VA) patients (n = 28 659) who received a VA-issued tablet between November 1, 2020 and April 30, 2021. Tablets included an app for VA's My HealtheVet (MHV) portal. Veterans were grouped into 3 MHV baseline user types (non-users, inactive users, and active users) based on MHV registration status and feature use pre-tablet receipt. Three multivariable models were estimated to examine the factors predicting (1) MHV registration among non-users, (2) any MHV feature use among inactive users, and (3) more MHV use among active users post-tablet receipt. Differences in feature use during the 6 months pre-/post-tablet were examined with McNemar chi-squared tests of proportions. RESULTS: In the 6 months post-tablet, 1298 (8%) non-users registered for MHV, 525 (24%) inactive users used at least one MHV feature, and 4234 (46%) active users increased feature use. Across veteran characteristics, there were differences in registration and feature use post-tablet, particularly among older adults and those without prior use of video visits (P < .01). Among active users, use of all features increased during the 6 months post-tablet, with the greatest differences in viewing prescription refills and scheduling appointments (P < .01). CONCLUSION: Providing patients who experience barriers to in-person care with a portal-enabled device supports engagement in health information and management tasks. Additional strategies are needed to promote registration and digital inclusion among inactive and non-users of portals.

Clinical, technical, and implementation characteristics of real-world health applications using FHIR.

Objective: Understanding the current state of real-world Fast Healthcare Interoperability Resources (FHIR) applications (apps) will benefit biomedical research and clinical care and facilitate advancement of the standard. This study aimed to provide a preliminary assessment of these apps' clinical, technical, and implementation characteristics. Materials and Methods: We searched public repositories for potentially eligible FHIR apps and surveyed app implementers and other stakeholders. Results: Of the 112 apps surveyed, most focused on clinical care (74) or research (45); were implemented across multiple sites (56); and used SMART-on-FHIR (55) and FHIR version R4 (69). Apps were primarily stand-alone web-based (67) or electronic health record (EHR)-embedded (51), although 49 were not listed in an EHR app gallery. Discussion: Though limited in scope, our results show FHIR apps encompass various domains and characteristics. Conclusion: As FHIR use expands, this study-one of the first to characterize FHIR apps at large-highlights the need for systematic, comprehensive methods to assess their characteristics.

Health information technology to support cancer survivorship care planning: A systematic review.

OBJECTIVE: The study sought to conduct a systematic review to explore the functions utilized by electronic cancer survivorship care planning interventions and assess their effects on patient and provider outcomes. MATERIALS AND METHODS: Based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, studies published from January 2000 to January 2020 were identified in PubMed, CINAHL, EMBASE, PsychINFO, Scopus, Web of Science, and the ACM Digital Library . The search combined terms for cancer, survivorship, care planning, and health information technology (HIT). Eligible studies evaluated the effects of a HIT intervention on usability, knowledge, process, or health-related outcomes. A total of 578 abstracts were reviewed, resulting in 60 manuscripts describing 40 studies. Thematic analyses were used to define meta-themes of system functions, and Fisher's exact tests were used to examine associations between functions and outcomes. RESULTS: Patients were the target end users for 18 interventions, while 12 targeted providers and 10 targeted both groups. Interventions used patient-reported outcomes collection (60%), automated content generation (58%), electronic sharing (40%), persistent engagement (28%), and communication features (20%). Overall, interventions decreased the time to create survivorship care plans (SCPs) and supported care planning knowledge and abilities, but results were mixed for effects on healthcare utilization, SCP sharing, and provoking anxiety. Persistent engagement features were associated with improvements in health or quality-of-life outcomes (17 studies, P = .003). CONCLUSIONS: Features that engaged users persistently over time were associated with better health and quality-of-life outcomes. Most systems have not capitalized on the potential of HIT to share SCPs across a care team and support care coordination.

Information needs and perceptions of chatbots for hypertension medication self-management: a mixed methods study.

OBJECTIVE: Chatbots have potential to deliver interactive self-management interventions but have rarely been studied in the context of hypertension or medication adherence. The objective of this study was to better understand patient information needs and perceptions of chatbots to support hypertension medication self-management. MATERIALS AND METHODS: Mixed methods were used to assess self-management needs and preferences for using chatbots. We purposively sampled adults with hypertension who were prescribed at least one medication. Participants completed questionnaires on sociodemographics, health literacy, self-efficacy, and technology use. Semi-structured interviews were conducted, audio-recorded, and transcribed verbatim. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using applied thematic analysis. RESULTS: Thematic saturation was met after interviewing 15 participants. Analysis revealed curiosity toward chatbots, and most perceived them as humanlike. The majority were interested in using a chatbot to help manage medications, refills, communicate with care teams, and for accountability toward self-care tasks. Despite general enthusiasm, there were concerns with chatbots providing too much information, making demands for lifestyle changes, invading privacy, and usability issues with deployment on smartphones. Those with overall positive perceptions toward chatbots were younger and taking fewer medications. DISCUSSION: Chatbot-related informational needs were consistent with existing self-management research, and many felt chatbots would be valuable if customizable and compatible with patient portals, pharmacies, or health apps. CONCLUSION: Although most were not familiar with chatbots, patients were interested in interacting with them, but this varied. This research informs future design and functionalities of conversational interfaces to support hypertension self-management.

Gender representation in U.S. biomedical informatics leadership and recognition.

OBJECTIVE: This study sought to describe gender representation in leadership and recognition within the U.S. biomedical informatics community. MATERIALS AND METHODS: Data were collected from public websites or provided by American Medical Informatics Association (AMIA) personnel from 2017 to 2019, including gender of membership, directors of academic informatics programs, clinical informatics subspecialty fellowships, AMIA leadership (2014-2019), and AMIA awardees (1993-2019). Differences in gender proportions were calculated using chi-square tests. RESULTS: Men were more often in leadership positions and award recipients (P < .01). Men led 74.7% (n = 71 of 95) of academic informatics programs and 83.3% (n = 35 of 42) of clinical informatics fellowships. Within AMIA, men held 56.8% (n = 1086 of 1913) of leadership roles and received 64.1% (n = 59 of 92) of awards. DISCUSSION: As in other STEM fields, leadership and recognition in biomedical informatics is lower for women. CONCLUSIONS: Quantifying gender inequity should inform data-driven strategies to foster diversity and inclusion. Standardized collection and surveillance of demographic data within biomedical informatics is necessary.

From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care.

OBJECTIVES: Conduct a survey of the literature for advancements in cancer informatics over the last three years in three specific areas where there has been unprecedented growth: 1) digital health; 2) machine learning; and 3) precision oncology. We also highlight the ethical implications and future opportunities within each area. METHODS: A search was conducted over a three-year period in two electronic databases (PubMed, Google Scholar) to identify peer-reviewed articles and conference proceedings. Search terms included variations of the following: neoplasms[MeSH], informatics[MeSH], cancer, oncology, clinical cancer informatics, medical cancer informatics. The search returned too many articles for practical review (23,994 from PubMed and 23,100 from Google Scholar). Thus, we conducted searches of key PubMed-indexed informatics journals and proceedings. We further limited our search to manuscripts that demonstrated a clear focus on clinical or translational cancer informatics. Manuscripts were then selected based on their methodological rigor, scientific impact, innovation, and contribution towards cancer informatics as a field or on their impact on cancer care and research. RESULTS: Key developments and opportunities in cancer informatics research in the areas of digital health, machine learning, and precision oncology were summarized. CONCLUSION: While there are numerous innovations in the field of cancer informatics to advance prevention and clinical care, considerable challenges remain related to data sharing and privacy, digital accessibility, and algorithm biases and interpretation. The implementation and application of these findings in cancer care necessitates further consideration and research.

Conversational Agents for Chronic Disease Self-Management: A Systematic Review.

We conducted a systematic literature review to assess how conversational agents have been used to facilitate chronic disease self-management. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used. Literature was searched across five databases, and we included full-text articles that contained primary research findings for text-based conversational agents focused on self-management for chronic diseases in adults. 1,606 studies were identified, and 12 met inclusion criteria. Outcomes were largely focused on usability of conversational agents, and participants mostly reported positive attitudes with some concerns related to privacy and shallow content. In several studies, there were improvements on the Patient Health Questionnaire (p<0.05), Generalized Anxiety Disorder Scale (p=0.004), Perceived Stress Scale (p=0.048), Flourishing Scale (p=0.032), and Overall Anxiety Severity and Impairment Scale (p<0.05). There is early evidence that suggests conversational agents are acceptable, usable, and may be effective in supporting self-management, particularly for mental health.

Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).

OBJECTIVE: The study sought to describe patient-entered supplemental information on symptomatic adverse events (AEs) in cancer clinical research reported via a National Cancer Institute software system and examine the feasibility of mapping these entries to established terminologies. MATERIALS AND METHODS: Patients in 3 multicenter trials electronically completed surveys during cancer treatment. Each survey included a prespecified subset of items from the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Upon completion of the survey items, patients could add supplemental symptomatic AE information in a free text box. As patients typed into the box, structured dropdown terms could be selected from the PRO-CTCAE item library or Medical Dictionary for Regulatory Activities (MedDRA), or patients could type unstructured free text for submission. RESULTS: Data were pooled from 1760 participants (48% women; 78% White) who completed 8892 surveys, of which 2387 (26.8%) included supplemental symptomatic AE information. Overall, 1024 (58%) patients entered supplemental information at least once, with an average of 2.3 per patient per study. This encompassed 1474 of 8892 (16.6%) dropdowns and 913 of 8892 (10.3%) unstructured free text entries. One-third of the unstructured free text entries (32%) could be mapped post hoc to a PRO-CTCAE term and 68% to a MedDRA term. DISCUSSION: Participants frequently added supplemental information beyond study-specific survey items. Almost half selected a structured dropdown term, although many opted to submit unstructured free text entries. Most free text entries could be mapped post hoc to PRO-CTCAE or MedDRA terms, suggesting opportunities to enhance the system to perform real-time mapping for AE reporting. CONCLUSIONS: Patient reporting of symptomatic AEs using a text box functionality with mapping to existing terminologies is both feasible and informative.

Health Tracking and Information Sharing in the Patient-Centered Era: A Health Information National Trends Survey (HINTS) Study.

We examined the current state of digital health tracking and information sharing with health professionals among patients with chronic conditions using data from the National Cancer Institute's 2018 Health Information National Trends Survey (HINTS). Descriptive statistics were used to examine the characteristics of health tracking and information sharing, Chi-squared tests were used to compare across groups, and multivariate logistic regression models were used to control for covariates. Between 17.4-37.6% of respondents reported sharing information with a health professional through either e-mail, monitoring device, text message, or online medical record message. There were sociodemographic differences across health tracking and information sharing modalities, and patients with chronic conditions disproportionately lacked Internet access, a basic cell phone, smartphone, or tablet compared to those without chronic conditions (p<0.05). This suggests there are sociodemographic and technology-based disparities for health tracking and information sharing for patients with chronic conditions.

Health and Fitness Apps for Hands-Free Voice-Activated Assistants: Content Analysis.

BACKGROUND: Hands-free voice-activated assistants and their associated devices have recently gained popularity with the release of commercial products, including Amazon Alexa and Google Assistant. Voice-activated assistants have many potential use cases in healthcare including education, health tracking and monitoring, and assistance with locating health providers. However, little is known about the types of health and fitness apps available for voice-activated assistants as it is an emerging market. OBJECTIVE: This review aimed to examine the characteristics of health and fitness apps for commercially available, hands-free voice-activated assistants, including Amazon Alexa and Google Assistant. METHODS: Amazon Alexa Skills Store and Google Assistant app were searched to find voice-activated assistant apps designated by vendors as health and fitness apps. Information was extracted for each app including name, description, vendor, vendor rating, user reviews and ratings, cost, developer and security policies, and the ability to pair with a smartphone app and website and device. Using a codebook, two reviewers independently coded each app using the vendor's descriptions and the app name into one or more health and fitness, intended age group, and target audience categories. A third reviewer adjudicated coding disagreements until consensus was reached. Descriptive statistics were used to summarize app characteristics. RESULTS: Overall, 309 apps were reviewed; health education apps (87) were the most commonly occurring, followed by fitness and training (72), nutrition (33), brain training and games (31), and health monitoring (25). Diet and calorie tracking apps were infrequent. Apps were mostly targeted towards adults and general audiences with few specifically geared towards patients, caregivers, or medical professionals. Most apps were free to enable or use and 18.1% (56/309) could be paired with a smartphone app and website and device; 30.7% (95/309) of vendors provided privacy policies; and 22.3% (69/309) provided terms of use. The majority (36/42, 85.7%) of Amazon Alexa apps were rated by the vendor as mature or guidance suggested, which were geared towards adults only. When there was a user rating available, apps had a wide range of ratings from 1 to 5 stars with a mean of 2.97. Google Assistant apps did not have user reviews available, whereas most of Amazon Alexa apps had at least 1-9 reviews available. CONCLUSIONS: The emerging market of health and fitness apps for voice-activated assistants is still nascent and mainly focused on health education and fitness. Voice-activated assistant apps had a wide range of content areas but many published in the health and fitness categories did not actually have a clear health or fitness focus. This may, in part, be due to Amazon and Google policies, which place restrictions on the delivery of care or direct recording of health data. As in the mobile app market, the content and functionalities may evolve to meet growing demands for self-monitoring and disease management.