Using generative artificial intelligence in bibliometric analysis: 10 years of research trends from the European Resuscitation Congresses.

Aims: The aim of this study is to use generative artificial intelligence to perform bibliometric analysis on abstracts published at European Resuscitation Council (ERC) annual scientific congress and define trends in ERC guidelines topics over the last decade. Methods: In this bibliometric analysis, the WebHarvy software (SysNucleus, India) was used to download data from the Resuscitation journal's website through the technique of web scraping. Next, the Chat Generative Pre-trained Transformer 4 (ChatGPT-4) application programming interface (Open AI, USA) was used to implement the multinomial classification of abstract titles following the ERC 2021 guidelines topics. Results: From 2012 to 2022 a total of 2491 abstracts have been published at ERC congresses. Published abstracts ranged from 88 (in 2020) to 368 (in 2015). On average, the most common ERC guidelines topics were Adult basic life support (50.1%), followed by Adult advanced life support (41.5%), while Newborn resuscitation and support of transition of infants at birth (2.1%) was the least common topic. The findings also highlight that the Basic Life Support and Adult Advanced Life Support ERC guidelines topics have the strongest co-occurrence to all ERC guidelines topics, where the Newborn resuscitation and support of transition of infants at birth (2.1%; 52/2491) ERC guidelines topic has the weakest co-occurrence. Conclusion: This study demonstrates the capabilities of generative artificial intelligence in the bibliometric analysis of abstract titles using the example of resuscitation medicine research over the last decade at ERC conferences using large language models.

Limited English Proficiency in Older Adults Referred to the Cardiovascular Team.

Limited English proficiency (LEP) is defined as individuals in whom English is not the primary language and who have limited ability to read, speak, write, or understand the English language. Cardiovascular (CV) team members routinely encounter language barriers in their practice. These barriers have a significant impact on the quality of CV care that patients with LEP receive. Despite evidence demonstrating the negative association between language barriers and health disparities, the impact on CV care is insufficiently known. In addition, older adults with CV disease and LEP are facing increasing risk of adverse events when complex medical information is not optimally delivered. Overcoming language barriers in CV care will need a thoughtful approach. Although well recognized, the initial step will be to continue to highlight the importance of language needs identification and appropriate use of professional interpreter services. In parallel, a health system-level approach is essential that describes initiatives and key policies to ensure a high-level quality of care for a growing LEP population. This review aims to present the topic of LEP during the CV care of older adults, for continued awareness along with practical considerations for clinical use and directions for future research.

A RE-AIM Evaluation of a Visualization-Based Electronic Patient-Reported Outcome System.

OBJECTIVES: Health care systems are primarily collecting patient-reported outcomes (PROs) for research and clinical care using proprietary, institution- and disease-specific tools for remote assessment. The purpose of this study was to conduct a Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) evaluation of a scalable electronic PRO (ePRO) reporting and visualization system in a single-arm study. METHODS: The "mi.symptoms" ePRO system was designed using gerontechnological design principles to ensure high usability among older adults. The system enables longitudinal reporting of disease-agnostic ePROs and includes patient-facing PRO visualizations. We conducted an evaluation of the implementation of the system guided by the RE-AIM framework. Quantitative data were analyzed using basic descriptive statistics, and qualitative data were analyzed using directed content analysis. RESULTS: Reach-the total reach of the study was 70 participants (median age: 69, 31% female, 17% Black or African American, 27% reported not having enough financial resources). Effectiveness-half (51%) of participants completed the 2-week follow-up survey and 36% completed all follow-up surveys. Adoption-the desire for increased self-knowledge, the value of tracking symptoms, and altruism motivated participants to adopt the tool. Implementation-the predisposing factor was access to, and comfort with, computers. Three enabling factors were incorporation into routines, multimodal nudges, and ease of use. Maintenance-reinforcing factors were perceived usefulness of viewing symptom reports with the tool and understanding the value of sustained symptom tracking in general. CONCLUSION: Challenges in ePRO reporting, particularly sustained patient engagement, remain. Nonetheless, freely available, scalable, disease-agnostic systems may pave the road toward inclusion of a more diverse range of health systems and patients in ePRO collection and use.

Community Health Recommendations Driven by mHealth Population Surveillance Data Amongst Burmese Displaced People in Eastern India: A Pilot Usability Assessment of a Mobile Health Application for Data Collection.

With recent increases in armed conflict and forced migration, refugee health has become a growing priority amongst those who work in global health. Refugees and forced migrants, also known as displaced persons, face barriers to accessing health services and are often at an increased risk for adverse health outcomes, such as sexual violence, infectious diseases, poor maternal outcomes, and mental health concerns. Mobile health (mHealth) applications have been shown to increase access and improve health outcomes among refugee populations. Our study aims to evaluate the feasibility of using a novel mHealth application to conduct population health surveillance data collection amongst a population of Myanmar citizens who have been forced to relocate to eastern India. The data collected in a low-resource setting through the mHealth application will be used to identify priority areas for intervention which will assist in the development of a tailored intervention plan that best suits our population.

Risk factor management of atrial fibrillation using mHealth: The Atrial Fibrillation - Helping Address Care with Remote Technology (AF-HEART) Pilot Study.

Background: Personalized treatment of atrial fibrillation (AF) risk factors using mHealth and telehealth may improve patient outcomes. Objective: The purpose of this study was to assess the feasibility of the Atrial Fibrillation Helping Address Care with Remote Technology (AF-HEART) intervention on the following patient outcomes: (1) heart rhythm tracking; (2) weight, alcohol, blood pressure (BP), and sleep apnea reduction; (3) AF symptom reduction; and (4) quality-of-life (QOL) improvement. Methods: A total of 20 patients with AF undergoing antiarrhythmic therapy, cardioversion, and/or catheter ablation were enrolled and followed for 6 months. The AF-HEART intervention included remote heart rhythm, weight, and BP tracking; televisits with a dietician focusing on AF risk factors; and referrals for sleep apnea and hypertension treatment. Results: Patients transmitted a median of 181 rhythm recordings during the 6-month follow-up period. Patients lost an average of 3.5 kilograms at 6 months (P = .005). Patients had improved SF-12 scores (P = .01), AFSS score (P = .01), EQ-5D score (P = .006), and AFEQT Global Score (P = .03). There was significant correlation between weight loss and decrease in symptom severity (r = -0.45, P = .05), and between % weight loss and decrease in symptom severity (r = -0.49, P = .03). Conclusion: This study described the feasibility of the AF-HEART intervention for (1) consistent remote tracking of heart rhythm, weight, and BP; (2) achievement of weight loss; (3) reduction of symptoms; and (4) improvement in QOL. Expansion to a larger randomized study is planned.

A Structured Review of Commercially Available Cardiac Rehabilitation mHealth Applications Using the Mobile Application Rating Scale.

PURPOSE: This study systematically evaluated the quality and functionalities of patient-facing, commercially available mobile health (mHealth) apps for cardiac rehabilitation (CR). METHODS: We performed our search in two of the most widely used commercial mobile app stores: Apple iTunes Appstore and Google Play Store (Android apps). Six search terms were used to query relevant CR apps: "cardiac rehabilitation," "heart disease and remote therapy," "heart failure exercise," "heart therapy and cardiac recovery," "cardiac recovery," and "heart therapy." App quality was evaluated using the Mobile Application Rating Scale (MARS). App functionality was evaluated using the IQVIA functionality scale, and app content was evaluated against the American Heart Association guidelines for CR. Apps meeting our inclusion criteria were downloaded and evaluated by two to three reviewers, and interclass correlations between reviewers were calculated. RESULTS: We reviewed 3121 apps and nine apps met our inclusion criteria. On average, the apps scored a 3.0 on the MARS (5-point Likert scale) for overall quality. The two top-ranking mHealth apps for CR for all three quality, functionality, and consistency with evidence-based guidelines were My Cardiac Coach and Love My Heart for Women, both of which scored ≥4.0 for behavior change. CONCLUSION: Overall, the quality and functionality of free apps for mobile CR was high, with two apps performing the best across all three quality categories. High-quality CR apps are available that can expand access to CR for patients with cardiovascular disease.

Effect of coronary artery bypass grafting on quality of life: a meta-analysis of randomized trials.

AIMS: We conducted a systematic review and meta-analysis to evaluate temporal trends in quality of life (QoL) after coronary artery bypass grafting (CABG) surgery in randomized clinical trials, and a quantitative comparison from before surgery to up to 5 years after surgery. METHODS AND RESULTS: We searched MEDLINE, CINAHL, EMBASE, Cochrane Library, and PsycINFO from 2010 to 2020 to identify studies that included the measurement of QoL in patients undergoing CABG. The primary outcome was the Seattle Angina Questionnaire (SAQ), and secondary outcomes were the 36-item Short Form Health Survey (SF-36) and EuroQol Questionnaire (EQ-5D). We pooled the means and the weighted mean differences over the follow-up period. In the meta-analysis, 2586 studies were screened and 18 full-text studies were included. There was a significant trend towards higher QoL scores from before surgery to 1 year post-operatively for the SAQ angina frequency (AF), SAQ QoL, SF-36 physical component (PC), and EQ-5D, whereas the SF-36 mental component (MC) did not improve significantly. The weighted mean differences from before surgery to 1 year after was 24 [95% confidence interval (CI): 21.6-26.4] for the SAQ AF, 31 (95% CI: 27.5-34.6) for the SAQ QoL, 9.8 (95% CI: 7.1-12.8) for the SF-36 PC, 7.1 (95% CI: 4.2-10.0) for the SF-36 MC, and 0.1 (95% CI: 0.06-0.14) for the EQ-5D. There was no evidence of publication bias or small-study effect. CONCLUSION: CABG had both short- and long-term improvements in disease-specific QoL and generic QoL, with the largest improvement in angina frequency.

Phenotypes of engagement with mobile health technology for heart rhythm monitoring.

OBJECTIVES: Guided by the concept of digital phenotypes, the objective of this study was to identify engagement phenotypes among individuals with atrial fibrillation (AF) using mobile health (mHealth) technology for 6 months. MATERIALS AND METHODS: We conducted a secondary analysis of mHealth data, surveys, and clinical records collected by participants using mHealth in a clinical trial. Patterns of participants' weekly use over 6 months were analyzed to identify engagement phenotypes via latent growth mixture model (LGMM). Multinomial logistic regression models were fitted to compute the effects of predictors on LGMM classes. RESULTS: One hundred twenty-eight participants (mean age 61.9 years, 75.8% male) were included in the analysis. Application of LGMM identified 4 distinct engagement phenotypes: "High-High," "Moderate-Moderate," "High-Low," and "Moderate-Low." In multinomial models, older age, less frequent afternoon mHealth use, shorter intervals between mHealth use, more AF episodes measured directly with mHealth, and lower left ventricular ejection fraction were more strongly associated with the High-High phenotype compared to the Moderate-Low phenotype (reference). Older age, more palpitations, and a history of stroke or transient ischemic attack were more strongly associated with the Moderate-Moderate phenotype compared to the reference. DISCUSSION: Engagement phenotypes provide a nuanced characterization of how individuals engage with mHealth over time, and which individuals are more likely to be highly engaged users. CONCLUSION: This study demonstrates that engagement phenotypes are valuable in understanding and possibly intervening upon engagement within a population, and also suggests that engagement is an important variable to be considered in digital phenotyping work more broadly.

Sexual Identity and Racial/Ethnic Differences in Awareness of Heart Attack and Stroke Symptoms: Findings From the National Health Interview Survey.

PURPOSE: Investigate sexual identity and racial/ethnic differences in awareness of heart attack and stroke symptoms. DESIGN: Cross-sectional. SETTING: 2014 and 2017 National Health Interview Survey. SAMPLE: 54 326 participants. MEASURES: Exposure measures were sexual identity (heterosexual, gay/lesbian, bisexual, "something else") and race/ethnicity. Awareness of heart attack and stroke symptoms was assessed. ANALYSIS: Sex-stratified logistic regression analyses to examine sexual identity and racial/ethnic differences in awareness of heart attack and stroke symptoms. RESULTS: Gay men were more likely than heterosexual men to identify calling 911 as the correct action if someone is having a heart attack (adjusted odds ratio [AOR] = 2.16, 95% CI: 1.18-3.96). The majority of racial/ethnic minority heterosexuals reported lower rates of awareness of heart attack and stroke symptoms than White heterosexuals. Hispanic sexual minority women had lower awareness of heart attack symptoms than White heterosexual women (AOR = 0.43, 95% CI: 0.25-0.74), whereas Asian sexual minority women reported lower awareness of stroke symptoms (AOR = 0.25, 95% CI: 0.08-0.80). Hispanic (AOR = 0.52, 95% CI: 0.33-0.84) and Asian (AOR = 0.35, 95% CI: 0.14-0.84) sexual minority men reported lower awareness of stroke symptoms than White heterosexual men. CONCLUSION: Hispanic and Asian sexual minorities had lower rates of awareness of heart attack and stroke symptoms. Health information technology may be a platform for delivering health education and targeted health promotion for sexual minorities of color.

Correlates of Mental Health Symptoms Among US Adults During COVID-19, March-April 2020.

OBJECTIVES: An understanding of mental health symptoms during the coronavirus disease 2019 (COVID-19) pandemic is critical to ensure that health policies adequately address the mental health needs of people in the United States. The objective of this study was to examine mental health symptoms among US adults in an early stage of the COVID-19 pandemic. METHODS: We conducted a cross-sectional study in late March 2020 with a national sample of 963 US adults using an online research platform. Participants self-reported state of residence, psychosocial characteristics, and levels of anxiety, depression, anger, cognitive function, and fatigue in the context of COVID-19 using validated patient-reported outcomes scales in the Patient-Reported Outcome Measurement Information System measures. We used analysis of variance and multivariate linear regression to evaluate correlates of mental health symptoms. RESULTS: Overall, participants reported high levels of anxiety (mean [SD], 57.2 [9.3]) and depression (mean [SD], 54.2 [9.5]). Levels of anger, anxiety, cognitive function, depression, and fatigue were significantly higher among the Millennial Generation and Generation X (vs Baby Boomers), those with not enough or enough (vs more than enough) financial resources, females vs males), those with self-reported disability (vs no self-reported disability), and those with inadequate (vs adequate) health literacy. In adjusted models, being in Generation X and the Millennial Generation (vs Baby Boomer), having not enough or enough vs more than enough) financial resources, and having inadequate (vs adequate) health literacy were most strongly correlated with worse mental health symptoms. CONCLUSIONS: Results suggest that mental health symptoms during the early stages of the COVID-19 pandemic were prevalent nationally, regardless of state of residence and especially among young, psychosocially vulnerable groups.

Exploring Depressive Symptoms and Anxiety Among Patients With Atrial Fibrillation and/or Flutter at the Time of Cardioversion or Ablation.

BACKGROUND: Depression and anxiety in patients with atrial fibrillation (AF) and/or atrial flutter may influence the effectiveness of cardioversion and ablation. There is a lack of knowledge related to depressive symptoms and anxiety at the time of these procedures. OBJECTIVE: We aimed to describe the prevalence and explore potential covariates of depressive symptoms and anxiety in patients with AF at the time of cardioversion or ablation. We further explored the influence of depressive symptoms and anxiety on quality of life at the time of procedure and 6-month AF recurrence. METHODS: Depressive symptoms, anxiety, and quality of life were collected at the time of cardioversion or ablation using the Patient Health Questionnaire-9, State-Trait Anxiety Inventory, and Atrial Fibrillation Effect on Quality of Life questionnaire. Presence of AF recurrence within 6 months post procedure was evaluated. RESULTS: Participants (N = 171) had a mean (SD) age of 61.20 (11.23) years and were primarily male (80.1%) and white, non-Hispanic (81.4%). Moderate to severe depressive symptoms (17.2%) and clinically significant state (30.2%) and trait (23.6%) anxiety were reported. Mood/anxiety disorder diagnosis was associated with all 3 symptoms. Atrial fibrillation symptom severity was associated with both depressive symptoms and trait anxiety. Heart failure diagnosis and digoxin use were also associated with depressive symptoms. Trends toward significance between state and trait anxiety and participant race/ethnicity as well as depressive symptoms and body mass index were observed. Study findings support associations between symptoms and quality of life, but not 6-month AF recurrence. CONCLUSION: Depressive symptoms and anxiety are common in patients with AF. Healthcare providers should monitor patients with AF for depressive symptoms and anxiety at the time of procedures and intervene when indicated. Additional investigations on assessment, prediction, treatment, and outcome of depressive symptoms and anxiety in patients with AF are warranted.

Performance of Electronic Health Record Diagnosis Codes for Ambulatory Heart Failure Encounters.

BACKGROUND: There is interest in leveraging the electronic medical records (EMRs) to improve knowledge and understanding of patients' characteristics and outcomes of patients with ambulatory heart failure (HF). However, the diagnostic performance of International Classification of Diseases (ICD) -10 diagnosis codes from the EMRs for patients with HF and with reduced or preserved ejection fraction (HFrEF or HFpEF) in the ambulatory setting are unknown. METHODS: We examined a cohort of patients aged ≥ 18 with at least 1 outpatient encounter for HF between January 2016 and June 2018 and an echocardiogram conducted within 180 days of the outpatient encounter for HF. We defined HFrEF encounters as those with ICD-10 codes of I50.2x (systolic heart failure); and we defined HFpEF encounters as those with ICD-10 codes of I50.3x (diastolic heart failure). The referent definitions of HFrEF and HFpEF were based on echocardiograms conducted within 180 days of the ambulatory encounter for HF RESULTS: We examined 68,952 encounters of 14,796 unique patients with HF. The diagnostic performance parameters for HFrEF (based on ICD-10 I50.2x only) depended on LVEF cutoff, with a sensitivity ranging from 68%-72%, specificity 63%-68%, positive predictive value 47%-63%, and negative predictive value 73%-84%. The diagnostic performance parameters for HFpEF depended on left ventricular ejection fraction cut-off, with sensitivity ranging from 34%-39%, specificity 92%-94%, positive predictive value 86%-93%, and negative predictive value 39%-54%. CONCLUSIONS: ICD-10 coding abstracted from the EMR for HFrEF vs HFpEF in the ambulatory setting had suboptimal diagnostic performance and, thus, should not be used alone to examine HFrEF and HFpEF in the ambulatory setting.

Review of mobile applications for the detection and management of atrial fibrillation.

BACKGROUND: Free mobile applications (apps) that use photoplethysmography (PPG) waveforms may extend atrial fibrillation (AF) detection to underserved populations, but they have not been rigorously evaluated. OBJECTIVE: The purpose of this study was to systematically review and evaluate the quality, functionality, and adherence to self-management behaviors of existing mobile apps for AF. METHODS: We systematically searched 3 app stores for apps that were free, available in English, and intended for use by patients to detect and manage AF. A minimum of 2 reviewers evaluated (1) app quality, using the Mobile Application Rating Scale (MARS); (2) functionality using published criteria; and (3) features that support 4 self-management behaviors (including PPG waveform monitoring) identified using evidence-based guidelines. Interrater reliability between the reviewers was calculated. RESULTS: Of 12 included apps, 5 (42%) scored above average for quality (MARS score ≥3.0). App quality was highest for their ease of use, navigation, layout, and visual appeal (eg, functionality and aesthetics) and lowest for their behavioral change support and subjective impressions of quality. The most common app functionalities were capturing and graphically displaying user-entered data (n = 9 [75%]). Nearly all apps (n = 11 [92%]) supported PPG waveform monitoring, but only 2 (17%) supported all 4 self-management behaviors. Interrater reliability was high (0.75-0.83). CONCLUSION: The reviewed apps had wide variability in quality, functionality, and adherence to self-management behaviors. Given the accessibility of these apps to underserved populations and the tremendous potential they hold for improving AF detection and management, high priority should be given to improving app quality and functionality.

On Board: Interdisciplinary Team Member Perspectives of How Patients With Heart Failure and Their Families Navigate Hospice Care.

Hospice agencies serve an expanding population of patients with varying disease conditions and sociodemographic characteristics. Patients with heart failure represent a growing share of hospice deaths in the United States. However, limited research has explored the perspectives of hospice interdisciplinary team members regarding how patients with heart failure and their families navigate hospice care. We sought to address this research gap by conducting qualitative interviews with hospice interdisciplinary team members at a large, not-for-profit hospice agency in New York City (N = 32). Five overarching themes from these interviews were identified regarding components that members of the hospice interdisciplinary team perceived as helping patients with heart failure and their families navigate hospice care. These themes included (1) "looking out: caregiving support in hospice care," (2) "what it really means: patient knowledge and understanding of hospice," (3) "on board: acceptance of death and alignment with hospice goals," (4) "on the same page: communication with the hospice team," and (5) "like a good student: symptom management and risk reduction practices." Interdisciplinary team members delineated several components that influence how patients with heart failure and their families navigate hospice services and communicate with care providers. Hospice agencies should consider policies for augmenting services among patients with heart failure to improve their understanding of hospice, supplement available caregiving supports for patients without them, and remove communication barriers.

The Effects of Gamification and Oral Self-Care on Oral Hygiene in Children: Systematic Search in App Stores and Evaluation of Apps.

BACKGROUND: Poor oral hygiene is a great public health problem worldwide. Oral health care education is a public health priority as the maintenance of oral hygiene is integral to overall health. Maintaining optimal oral hygiene among children is challenging and can be supported by using relevant motivational approaches. OBJECTIVE: The primary aim of this study was to identify mobile smartphone apps that include gamification features focused on motivating children to learn, perform, and maintain optimal oral hygiene. METHODS: We searched six online app stores using four search terms ("oral hygiene game," "oral hygiene gamification," "oral hygiene brush game," and "oral hygiene brush gamification"). We identified gamification features, identified whether apps were consistent with evidence-based dentistry, performed a quality appraisal with the Mobile App Rating Scale user version (uMARS), and quantified behavior scores (Behavior Change score, uMARS score, and Coventry, Aberdeen, and London-Refined [CALO-RE] score) using three different instruments that measure behavior change. RESULTS: Of 612 potentially relevant apps included in the analysis, 17 met the inclusion criteria. On average, apps included 6.87 (SD 4.18) out of 31 possible gamification features. The most frequently used gamification features were time pressure (16/17, 94%), virtual characters (14/17, 82%), and fantasy (13/17, 76%). The most common oral hygiene evidence-based recommendation was brushing time (2-3 minutes), which was identified in 94% (16/17) of apps. The overall mean uMARS score for app quality was high (4.30, SD 0.36), with good mean subjective quality (3.79, SD 0.71) and perceived impact (3.58, SD 0.44). Sufficient behavior change techniques based on three taxonomies were detected in each app. CONCLUSIONS: The majority of the analyzed oral hygiene apps included gamification features and behavior change techniques to perform and maintain oral hygiene in children. Overall, the apps contained some educational content consistent with evidence-based dentistry and high-quality background for oral self-care in children; however, there is scope for improvement.

Evaluating Commercially Available Mobile Apps for Depression Self-Management.

Clinical depression affects 17.3 million adults in the U.S. However, 37% of these adults receive no treatment, and many symptoms remain unmanaged. Mobile health apps may complement in-person treatment and address barriers to treatment, yet their quality has not been systematically appraised. We conducted a systematic review of apps for depression by searching in three major app stores. Apps were selected using specific inclusion and exclusion criteria. The final apps were downloaded and independently evaluated using the Mobile Application Rating Scale (MARS), IMS Institute for Healthcare Informatics functionality score, and six features specific to depression self-management. Mobile health apps for depression self-management exhibit a wide range of quality, but more than half (74%) of the apps had acceptable quality, with 32% having MARS scores ≥ 4.0 out of 5.0. These high scoring apps indicate that mobile apps have the potential to improve patient self-management, treatment engagement, and mental health outcomes.

A Systematic Review of Patient-Facing Visualizations of Personal Health Data.

OBJECTIVES: As personal health data are being returned to patients with increasing frequency and volume, visualizations are garnering excitement for their potential to facilitate patient interpretation. Evaluating these visualizations is important to ensure that patients are able to understand and, when appropriate, act upon health data in a safe and effective manner. The objective of this systematic review was to review and evaluate the state of the science of patient-facing visualizations of personal health data. METHODS: We searched five scholarly databases (PubMed, Embase, Scopus, ACM Digital Library [Association for Computing Machinery Digital Library], and IEEE Computational Index [Institute of Electrical and Electronics Engineers Computational Index]) through December 1, 2018 for relevant articles. We included English-language articles that developed or tested one or more patient-facing visualizations for personal health data. Three reviewers independently assessed quality of included articles using the Mixed methods Appraisal Tool. Characteristics of included articles and visualizations were extracted and synthesized. RESULTS: In 39 articles included in the review, there was heterogeneity in the sample sizes and methods for evaluation but not sample demographics. Few articles measured health literacy, numeracy, or graph literacy. Line graphs were the most common visualization, especially for longitudinal data, but number lines were used more frequently in included articles over past 5 years. Article findings suggested more patients understand the number lines and bar graphs compared with line graphs, and that color is effective at communicating risk, improving comprehension, and increasing confidence in interpretation. CONCLUSION: In this review, we summarize types and components of patient-facing visualizations and methodologies for development and evaluation in the reviewed articles. We also identify recommendations for future work relating to collecting and reporting data, examining clinically actionable boundaries for diverse data types, and leveraging data science. This work will be critically important as patient access of their personal health data through portals and mobile devices continues to rise.