Dr. Ashley Griffin is a medical informatics postdoctoral research fellow at the Center for Primary Care and Outcomes Research at Stanford and the VA Palo Alto Health Care System Center for Innovation to Implementation. Her research focuses on the use of digital health technologies and patient-generated health data to support patients with multimorbidities. Dr. Griffin's research develops methods and tools that can empower patients to take an active role in their health and inform decision-making for the care team.

All Publications

  • CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health. JAMIA open Aalami, O., Hittle, M., Ravi, V., Griffin, A., Schmiedmayer, P., Shenoy, V., Gutierrez, S., Venook, R. 2023; 6 (3): ooad044


    Smartphone devices capable of monitoring users' health, physiology, activity, and environment revolutionize care delivery, medical research, and remote patient monitoring. Such devices, laden with clinical-grade sensors and cloud connectivity, allow clinicians, researchers, and patients to monitor health longitudinally, passively, and persistently, shifting the paradigm of care and research from low-resolution, intermittent, and discrete to one of persistent, continuous, and high resolution. The collection, transmission, and storage of sensitive health data using mobile devices presents unique challenges that serve as significant barriers to entry for care providers and researchers alike. Compliance with standards like HIPAA and GDPR requires unique skills and practices. These requirements make off-the-shelf technologies insufficient for use in the digital health space. As a result, budget, timeline, talent, and resource constraints are the largest barriers to new digital technologies. The CardinalKit platform is an open-source project addressing these challenges by focusing on reducing these barriers and accelerating the innovation, adoption, and use of digital health technologies. CardinalKit provides a mobile template application and web dashboard to enable an interoperable foundation for developing digital health applications. We demonstrate the applicability of CardinalKit to a wide variety of digital health applications across 18 innovative digital health prototypes.

    View details for DOI 10.1093/jamiaopen/ooad044

    View details for PubMedID 37485467

    View details for PubMedCentralID PMC10356573

  • A chatbot for hypertension self-management support: user-centered design, development, and usability testing. JAMIA open Griffin, A. C., Khairat, S., Bailey, S. C., Chung, A. E. 2023; 6 (3): ooad073


    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."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.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.The text-based chatbot was viewed favorably for assisting with blood pressure and medication-related tasks and had good usability.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.

    View details for DOI 10.1093/jamiaopen/ooad073

    View details for PubMedID 37693367

    View details for PubMedCentralID PMC10491950

  • Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities. Journal of medical Internet research Pillai, M., Griffin, A. C., Kronk, C. A., McCall, T. 2023; 25: e48498


    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.

    View details for DOI 10.2196/48498

    View details for PubMedID 37540551

  • Clinical, technical, and implementation characteristics of real-world health applications using FHIR. JAMIA open Griffin, A. C., He, L., Sunjaya, A. P., King, A. J., Khan, Z., Nwadiugwu, M., Douthit, B., Subbian, V., Nguyen, V., Braunstein, M., Jaffe, C., Schleyer, T. 2022; 5 (4): ooac077


    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.We searched public repositories for potentially eligible FHIR apps and surveyed app implementers and other stakeholders.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.Though limited in scope, our results show FHIR apps encompass various domains and characteristics.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.

    View details for DOI 10.1093/jamiaopen/ooac077

    View details for PubMedID 36247086

    View details for PubMedCentralID PMC9555876

  • Tablet distribution to veterans: an opportunity to increase patient portal adoption and use. Journal of the American Medical Informatics Association : JAMIA Griffin, A. C., Troszak, L. K., Van Campen, J., Midboe, A. M., Zulman, D. M. 2022


    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.

    View details for DOI 10.1093/jamia/ocac195

    View details for PubMedID 36269168

  • A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs). Journal of the American Medical Informatics Association : JAMIA Hussein, R., Griffin, A. C., Pichon, A., Oldenburg, J. 2022


    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.

    View details for DOI 10.1093/jamia/ocac198

    View details for PubMedID 36259962

  • Health information technology to support cancer survivorship care planning: A systematic review. Journal of the American Medical Informatics Association : JAMIA Mikles, S. P., Griffin, A. C., Chung, A. E. 2021


    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.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.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).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.

    View details for DOI 10.1093/jamia/ocab134

    View details for PubMedID 34333588

  • Gender representation in U.S. biomedical informatics leadership and recognition. Journal of the American Medical Informatics Association : JAMIA Griffin, A. C., Leung, T. I., Tenenbaum, J. D., Chung, A. E. 2021; 28 (6): 1270-1274


    This study sought to describe gender representation in leadership and recognition within the U.S. biomedical informatics community.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.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.As in other STEM fields, leadership and recognition in biomedical informatics is lower for women.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.

    View details for DOI 10.1093/jamia/ocaa344

    View details for PubMedID 33555005

    View details for PubMedCentralID PMC8200259

  • Information needs and perceptions of chatbots for hypertension medication self-management: a mixed methods study. JAMIA open Griffin, A. C., Xing, Z., Mikles, S. P., Bailey, S., Khairat, S., Arguello, J., Wang, Y., Chung, A. E. 2021; 4 (2): ooab021


    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.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.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.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.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.

    View details for DOI 10.1093/jamiaopen/ooab021

    View details for PubMedID 33898936

    View details for PubMedCentralID PMC8054030

  • From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care. Yearbook of medical informatics Griffin, A. C., Topaloglu, U., Davis, S., Chung, A. E. 2020; 29 (1): 235-242


    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.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.Key developments and opportunities in cancer informatics research in the areas of digital health, machine learning, and precision oncology were summarized.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.

    View details for DOI 10.1055/s-0040-1701983

    View details for PubMedID 32823322

    View details for PubMedCentralID PMC7442514

  • Conversational Agents for Chronic Disease Self-Management: A Systematic Review. AMIA ... Annual Symposium proceedings. AMIA Symposium Griffin, A. C., Xing, Z., Khairat, S., Wang, Y., Bailey, S., Arguello, J., Chung, A. E. 2020; 2020: 504-513


    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.

    View details for PubMedID 33936424

    View details for PubMedCentralID PMC8075433

  • 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). Journal of the American Medical Informatics Association : JAMIA Chung, A. E., Shoenbill, K., Mitchell, S. A., Dueck, A. C., Schrag, D., Bruner, D. W., Minasian, L. M., St Germain, D., O'Mara, A. M., Baumgartner, P., Rogak, L. J., Abernethy, A. P., Griffin, A. C., Basch, E. M. 2019; 26 (4): 276-285


    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.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.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.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.Patient reporting of symptomatic AEs using a text box functionality with mapping to existing terminologies is both feasible and informative.

    View details for DOI 10.1093/jamia/ocy169

    View details for PubMedID 30840079

    View details for PubMedCentralID PMC6402312

  • Health Tracking and Information Sharing in the Patient-Centered Era: A Health Information National Trends Survey (HINTS) Study. AMIA ... Annual Symposium proceedings. AMIA Symposium Griffin, A. C., Chung, A. E. 2019; 2019: 1041-1050


    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.

    View details for PubMedID 32308901

    View details for PubMedCentralID PMC7153080

  • Health and Fitness Apps for Hands-Free Voice-Activated Assistants: Content Analysis. JMIR mHealth and uHealth Chung, A. E., Griffin, A. C., Selezneva, D., Gotz, D. 2018; 6 (9): e174


    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.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.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.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.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.

    View details for DOI 10.2196/mhealth.9705

    View details for PubMedID 30249581

    View details for PubMedCentralID PMC6231786

  • Patient Portals: Who uses them? What features do they use? And do they reduce hospital readmissions? Applied clinical informatics Griffin, A., Skinner, A., Thornhill, J., Weinberger, M. 2016; 7 (2): 489-501


    Patient portals have demonstrated numerous benefits including improved patient-provider communication, patient satisfaction with care, and patient engagement. Recent literature has begun to illustrate how patients use selected portal features and an association between portal usage and improved clinical outcomes.This study sought to: (1) identify patient characteristics associated with the use of a patient portal; (2) determine the frequency with which common patient portal features are used; and (3) examine whether the level of patient portal use (non-users, light users, active users) is associated with 30-day hospital readmission.My UNC Chart is the patient portal for the UNC Health Care System. We identified adults discharged from three UNC Health Care hospitals with acute myocardial infarction, congestive heart failure, or pneumonia and classified them as active, light, or non-users of My UNC Chart. Multivariable analyses were conducted to compare across user groups; logistic regression was used to predict whether patient portal use was associated with 30-day readmission.Of 2,975 eligible patients, 83.4% were non-users; 8.6% were light users; and 8.0% were active users of My UNC Chart. The messaging feature was used most often. For patients who were active users, the odds of being readmitted within 30 days was 66% greater than patients who were non-users (p<0.05). There was no difference in 30-day readmission between non-users and light users.The vast majority of patients who were given an access code for My UNC Chart did not use it within 30 days of discharge. Of those who used the portal, active users had a higher odds of being readmitted within 30 days. Health care systems should consider strategies to: (1) increase overall use of patient portals and (2) target patients with the highest comorbidity scores to reduce hospital readmissions.

    View details for DOI 10.4338/ACI-2016-01-RA-0003

    View details for PubMedID 27437056

    View details for PubMedCentralID PMC4941855