Pharmacists' role in detection and evaluation of adverse drug reactions: Developing proactive systems for pharmacosurveillance.

PURPOSE: To identify current challenges in detection of medication-related symptoms, and review technology-based opportunities to increase the patient-centeredness of postmarketing pharmacosurveillance to promote more accountable, safer, patient-friendly, and equitable medication prescribing. SUMMARY: Pharmacists have an important role to play in detection and evaluation of adverse drug reactions (ADRs). The pharmacist's role in medication management should extend beyond simply dispensing drugs, and this article delineates the rationale and proactive approaches for pharmacist detection and assessment of ADRs. We describe a stepwise approach for assessment, best practices, and lessons learned from a pharmacist-led randomized trial, the CEDAR (Calling for Detection of Adverse Drug Reactions) project. CONCLUSION: Health systems need to be redesigned to more fully utilize health information technologies and pharmacists in detecting and responding to ADRs.

Characterizing Responses to COVID-19 Vaccine Promotion on TikTok.

PURPOSE: The Alabama Department of Public Health (ADPH) sponsored a TikTok contest to improve vaccination rates among young people. This analysis sought to advance understanding of COVID-19 vaccine perceptions among ADPH contestants and TikTok commenters. APPROACH: This exploratory content analysis characterized sentiment and imagery in the TikTok videos and comments. Videos were coded by two reviewers and engagement metrics were collected for each video. SETTING: Publicly available TikTok videos entered into ADPH's contest with the hashtags #getvaccinatedAL and #ADPH between July 16 - August 6, 2021. PARTICIPANTS: ADPH contestants (n = 44) and TikTok comments (n = 502). METHOD: A content analysis was conducted; videos were coded by two reviewers and engagement metrics was collected for each video (e.g., reason for vaccination, content, type of vaccination received). Video comments were analyzed using VADER, a lexicon and rule-based sentiment analysis tool). RESULTS: Of 44 videos tagged with #getvaccinatedAL and #ADPH, 37 were related to the contest. Of the 37 videos, most cited family/friends and civic duty as their reason to get the COVID-19 vaccine. Videos were shared an average of 9 times and viewed 977 times. 70% of videos had comments, ranging from 0-61 (mean 44). Words used most in positively coded comments included, "beautiful," "smiling face emoji with 3 hearts," "masks," and "good.;" whereas words used most in negatively coded comments included "baby," "me," "chips," and "cold." CONCLUSION: Understanding COVID-19 vaccine sentiment expressed on social media platforms like TikTok can be a powerful tool and resource for public health messaging.

Patient Experience and Satisfaction in Online Reviews of Obstetric Care: Observational Study.

BACKGROUND: The quality of care in labor and delivery is traditionally measured through the Hospital Consumer Assessment of Healthcare Providers and Systems but less is known about the experiences of care reported by patients and caregivers on online sites that are more easily accessed by the public. OBJECTIVE: The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp. METHODS: We identified all Yelp reviews of US hospitals posted online from May 2005 to March 2017. We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson r to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. RESULTS: A total of 1569 hospitals listed in the American Hospital Association directory had at least one Yelp posting, contributing a total of 41,095 Yelp reviews. Among those hospitals, 919 (59%) had at least one Yelp rating for labor and delivery services (median of 9 reviews), contributing a total of 6523 labor and delivery reviews. Reviews concentrated among 5-star (n=2643, 41%) and 1-star reviews (n=1934, 30%). Themes strongly associated with favorable ratings included the following: top-notch care (r=0.45, P<.001), describing staff as comforting (r=0.52, P<.001), the delivery experience (r=0.46, P<.001), modern and clean facilities (r=0.44, P<.001), and hospital food (r=0.38, P<.001). Themes strongly correlated with 1-star labor and delivery reviews included complaints to management (r=0.30, P<.001), a lack of agency among patients (r=0.47, P<.001), and issues with discharging from the hospital (r=0.32, P<.001). CONCLUSIONS: Online review content about labor and delivery can provide meaningful information about patient satisfaction and experiences. Narratives from these reviews that are not otherwise captured in traditional surveys can direct efforts to improve the experience of obstetrical care.

Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study.

BACKGROUND: The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. OBJECTIVE: Using an SMS text message-based system, we sought to build and test a remote model to explore community needs, connect individuals to curated resources, and facilitate community health worker intervention when needed during the pandemic. The primary aims of this pilot study were to establish the feasibility (ie, engagement with the text line) and acceptability (ie, participant ratings of resources and service) of delivering automated well-being resources via smartphone technology. METHODS: Eligible patients (aged 18 years or older, having a cell phone with SMS text messaging capability, and recently visited the emergency department) were identified using the electronic health record. The patients were consented to enroll and begin receiving COVID-19-related information and links to community resources. We collected open-ended and close-ended resource and mood ratings. We calculated the frequencies and conducted a thematic review of the open-ended responses. RESULTS: In 7 weeks, 356 participants were enrolled; 13,917 messages were exchanged including 333 resource ratings (mean 4) and 673 well-being scores (mean 6.8). We received and coded 386 open-ended responses, most of which elaborated upon their self-reported mood score (29%). Overall, 77% (n=274) of our participants rated the platform as a service they would highly recommend to a family member or friend. CONCLUSIONS: This approach is designed to broaden the reach of health systems, tailor to community needs in real time, and connect at-risk individuals with robust community health support.

Effect of Posting on Social Media on Systolic Blood Pressure and Management of Hypertension: A Randomized Controlled Trial.

Background Online platforms are used to manage aspects of our lives including health outside clinical settings. Little is known about the effectiveness of using online platforms to manage hypertension. We assessed effects of tweeting/retweeting cardiovascular health content by individuals with poorly controlled hypertension on systolic blood pressure (SBP) and patient activation. Methods and Results We conducted this 2-arm randomized controlled trial. Eligibility included diagnosis of hypertension; SBP >140 mm Hg; and an existing Twitter account or willingness to create one to follow study Twitter account. Intervention arm was asked to tweet/retweet health content 2×/week using a specific hashtag for study duration (6 months). The main measures include primary outcome change in SBP; secondary outcome point change in Patient Activation Measure (PAM). We remotely recruited and enrolled 611 participants, mean age 52 (SD, 11.7). Mean baseline SBP for the intervention group was 155.8 and for control was 155.6. At 6 months, mean SBP for intervention group was 137.6 and for control was 135.7. Mean change in SBP from baseline to 6 months for the intervention group was -18.5 and for control was -19.8 (P=0.48). Mean PAM at baseline for the intervention group was 70.3 for control was 72.7. At 6 months, mean PAM scores were 71.1 (intervention) and 75.6 (control). Mean change in PAM score for the intervention group was 0.0 and for control was 3.3 (P=0.12). Conclusions Recruiting and engaging patients and collecting outcome measures remotely are feasible using Twitter. Encouraging patients with poorly controlled hypertension to tweet or retweet health content on Twitter did not improve SBP or PAM score at 6 months. Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT02622256.

Characterizing COVID-19 Content Posted to TikTok: Public Sentiment and Response During the First Phase of the COVID-19 Pandemic.

PURPOSE: The purpose of this study was to characterize COVID-19 content posted by users and disseminated via TikTok, a social media platform that has become known largely as an entertainment platform for viral video-sharing. We sought to capture how TikTok videos posted during the initial months of the COVID pandemic changed over time as cases accelerated. METHODS: This study is an observational analysis of sequential TikTok videos with #coronavirus from January to March 2020. Videos were independently coded to assess content (e.g., health relatedness, humor, fear, empathy), misinformation, and public sentiment. To assess engagement, we also codified how often videos were shared relative to their content. RESULTS: We coded 750 videos and approximately one in four videos tagged with #coronavirus featured health-related content such as featuring objects such as face masks, hand sanitizer, and other cleaning products. Most videos evoked "humor/parody," whereas 15% and 6% evoked "fear" and "empathy", respectively. TikTok videos posted in March 2020 had the largest number of shares and comments compared with January and February 2020. The proportion of shares and comments for "misleading and incorrect information" featured in videos was lower in March than in January and February 2020. There was no statistical difference between the share and comment counts of videos coded as "incorrect/incomplete" and "correct" over the entire time period. CONCLUSIONS: Analyzing readily available social media platforms, such as TikTok provides real-time insights into public views, frequency and types of misinformation, and norms toward COVID-19. Analyzing TikTok videos has the potential to be used to inform public health messaging and public health mitigation strategies.

The role of digital health technologies in COVID-19 surveillance and recovery: a specific case of long haulers.

Digital health and technologies are essential to curbing the novel coronavirus 2019 (COVID-19) pandemic especially with shelter-in-place and social distancing orders. Epidemiologists and public health officials are tapping into frequently used technologies like wearables, digital devices, digital and social media data to detect and validate COVID-19 symptoms throughout the pandemic, especially during early stages when symptoms were evolving. In this article, we review how digital technologies and social media platforms can identify and inform our understanding of COVID-19 pandemic surveillance and recovery efforts. We analyze Reddit narrative posts and comments on r/covidlonghaulers to demonstrate how social media can be used to better understand COVID-19 pandemic. Using Reddit data, we highlight long haulers' patient journeys and shed light on potential consequences of their condition. We identified 21 themes, of which the following were significantly associated with valence: COVID-19 Symptoms (r = -0.037), medical advice (r = -0.030), medical system (r = -0.029), bodily processes (r = -0.020), questions (r = 0.024), physical activity (r = 0.033), self-differentials and negations (r = 0.040) and supplements (r = 0.025). Our brief literature review and analysis of r/covidlonghaulers narrative posts demonstrate the value of digital technologies and social media platforms as they act as modern avenues for public health, safety, and well-being.

Social media language of healthcare super-utilizers.

An understanding of healthcare super-utilizers' online behaviors could better identify experiences to inform interventions. In this retrospective case-control study, we analyzed patients' social media posts to better understand their day-to-day behaviors and emotions expressed online. Patients included those receiving care in an urban academic emergency department who consented to share access to their historical Facebook posts and electronic health records. Super-utilizers were defined as patients with more than six visits to the Emergency Department (ED) in a year. We compared posts by super-utilizers with a matched group using propensity scoring based on age, gender and Charlson comorbidity index. Super-utilizers were more likely to post about confusion and negativity (D = .65, 95% CI-[.38, .95]), self-reflection (D = .63 [.35, .91]), avoidance (D = .62 [.34, .90]), swearing (D = .52 [.24, .79]), sleep (D = .60 [.32, .88]), seeking help and attention (D = .61 [.33, .89]), psychosomatic symptoms, (D = .49 [.22, .77]), self-agency (D = .56 [.29, .85]), anger (D = .51, [.24, .79]), stress (D = .46, [.19, .73]), and lonely expressions (D = .44, [.17, .71]). Insights from this study can potentially supplement offline community care services with online social support interventions considering the high engagement of super-utilizers on social media.

Improving Mood Through Community Connection and Resources Using an Interactive Digital Platform: Development and Usability Study.

BACKGROUND: COVID-19 continues to disrupt global health and well-being. In April-May 2020, we generated a digital, remote interactive tool to provide health and well-being resources and foster connectivity among community members through a text messaging platform. OBJECTIVE: This study aimed to prospectively investigate the ability of a health system-based digital, remote, interactive tool to provide health and well-being resources to local community participants and to foster connectivity among them during the early phases of COVID-19. METHODS: We performed descriptive and nonparametric longitudinal statistical analyses to describe and compare the participants' mood ratings over time and thematic analysis of their responses to text messages to further assess mood. RESULTS: From among 393 individuals seeking care in an urban emergency department in an academic setting, engaged in a two-way text messaging platform, we recorded 287 mood ratings and 368 qualitative responses. We observed no difference in the initial mood rating by week of enrollment [Kruskal-Wallis chi-square H(5)=1.34; P=.93], and the average mood rating did not change for participants taken together [Friedman chi-square Q(3)=0.32; P=.96]. However, of participants providing mood ratings at baseline, mood improved significantly among participants who reported a low mood rating at baseline [n=25, 14.97%; Q(3)=20.68; P<.001] but remained stable among those who reported a high mood rating at baseline [n=142, 85.03%; Q(3)=2.84; P=.42]. Positive mood elaborations most frequently included words related to sentiments of thankfulness and gratitude, mostly for a sense of connection and communication; in contrast, negative mood elaborations most frequently included words related to anxiety. CONCLUSIONS: Our findings suggest the feasibility of engaging individuals in a digital community with an emergency department facilitation. Specifically, for those who opt to engage in a text messaging platform during COVID-19, it is feasible to assess and respond to mood-related queries with vetted health and well-being resources.

Studying social media language changes associated with pregnancy status, trimester, and parity from medical records.

We sought to evaluate whether there was variability in language used on social media across different time points of pregnancy (before, during, and after pregnancy, as well as by trimester and parity). Consenting patients shared access to their individual Facebook posts and electronic medical records. Random forest models trained on Facebook posts could differentiate first trimester of pregnancy from 3 months before pregnancy (F1 score = .63) and from a random 3-month time period (F1 score = .64). Posts during pregnancy were more likely to include themes about family (ß = .22), food craving (ß = .14), and date/times (ß = .13), while posts 3 months prior to pregnancy included themes about social life (ß = .30), sleep (ß = .31), and curse words (ß = .27), and 3 months post-pregnancy included themes of gratitude (ß = .17), health appointments (ß = .21), and religiosity (ß = .18). Users who were pregnant for the first time were more likely to post about lack of sleep (ß = .15), activities of daily living (ß = .09), and communication (ß = .08) compared with those who were pregnant after having a child who posted about others' birthdays (ß = .16) and life events (.12). A better understanding about social media timelines can provide insight into lifestyle choices that are specific to pregnancy.

Patients' willingness to share digital health and non-health data for research: a cross-sectional study.

BACKGROUND: Patients generate large amounts of digital data through devices, social media applications, and other online activities. Little is known about patients' perception of the data they generate online and its relatedness to health, their willingness to share data for research, and their preferences regarding data use. METHODS: Patients at an academic urban emergency department were asked if they would donate any of 19 different types of data to health researchers and were asked about their views on data types' health relatedness. Factor analysis was used to identify the structure in patients' perceptions of willingness to share different digital data, and their health relatedness. RESULTS: Of 595 patients approached 206 agreed to participate, of whom 104 agreed to share at least one types of digital data immediately, and 78% agreed to donate at least one data type after death. EMR, wearable, and Google search histories (80%) had the highest percentage of reported health relatedness. 72% participants wanted to know the results of any analysis of their shared data, and half wanted their healthcare provider to know. CONCLUSION: Patients in this study were willing to share a considerable amount of personal digital data with health researchers. They also recognize that digital data from many sources reveal information about their health. This study opens up a discussion around reconsidering US privacy protections for health information to reflect current opinions and to include their relatedness to health.

Google search histories of patients presenting to an emergency department: an observational study.

OBJECTIVE: To test patients' willingness to share and link their prior Google search histories with data from their electronic medical record (EMR), and to explore associations between search histories and clinical conditions. DESIGN: Cross-sectional study of emergency department (ED) patients from 2016 to 2017. SETTING: Academic medical centre ED. PARTICIPANTS: A total of 703 patients were approached; 334 of a volunteer sample of 411 (81%) reported having a Google account; 165 of those (49%) consented to share their Google search histories and EMR data; 119 (72%) were able to do so. 16 (13%) of those 119 patients had no data and were not included in the final count. Patients under the age of 18 or with a triage level of 1 were considered ineligible and were not approached. MAIN OUTCOME MEASURES: Health relatedness of searches in the remote past and within 7 days of the ED visit, and associations between patients' clinical and demographic characteristics and their internet search volume and search content. RESULTS: The 103 participants yielded 591 421 unique search queries; 37 469 (6%) were health related. In the 7 days prior to an ED visit, the percentage of health-related searches was 15%. During that time, 56% of patients searched for symptoms, 53% for information about a hospital and 23% about the treatment or management of a disease. 53% of participants who used Google in the week leading up to their ED visit searched for content directly related to their chief complaint. CONCLUSIONS: Patients were willing to allow researchers simultaneous access to their Google search histories and their EMR data. The change in volume and content of search activity prior to an ED visit suggests opportunities to anticipate and improve health care utilisation in advance of ED visits.

Online Ratings of the Patient Experience: Emergency Departments Versus Urgent Care Centers.

STUDY OBJECTIVE: Individuals increasingly use online rating platforms to rate and review hospitals. We seek to describe and compare publicly available online review content and ratings of emergency departments (EDs) and urgent care centers. METHODS: We analyzed Yelp reviews of EDs and urgent care centers to identify topics most correlated with 1- and 5-star ratings. Latent Dirichlet Allocation, a method of identifying groups of co-occurring words in narrative text, was used to identify and label 25 topics across 1- and 5-star reviews of urgent care centers and EDs. Differential Language Analysis was then used to measure the correlation of these topics with 1- and 5-star reviews for urgent care centers and EDs. RESULTS: We analyzed 100,949 Yelp reviews, 16,447 from 1,566 EDs and 84,502 from 5,601 urgent care centers. There were significantly more 5-star urgent care center reviews (n=43,487; 51%) than 5-star ED reviews (n=4,437; 27%). Themes associated with 5-star reviews among EDs and urgent care centers were similar for comfort, professionalism, facilities, pediatric care, and staff interactions. Themes associated with 1-star reviews among EDs and urgent care centers were similar for communication, telephone experience, waiting, billing, pain management, and diagnostic testing. Themes unique to 5-star ED reviews included bedside manner, care for family members, and access. Themes unique to 5-star urgent care center reviews were based on recommendation and prescription refills. Themes unique to 1-star ED reviews were service and speed of care. Themes unique to 1-star urgent care center reviews were lack of confidence and reception experience. CONCLUSION: Understanding drivers for high and low online ratings and what patients value in their ED and urgent care center experiences offers insights for health systems and providers to improve acute care delivery. Patients' perspectives may become increasingly important as they seek care in the expanding urgent care markets.

Screening for Adverse Drug Events: a Randomized Trial of Automated Calls Coupled with Phone-Based Pharmacist Counseling.

BACKGROUND: Medication adverse events are important and common yet are often not identified by clinicians. We evaluated an automated telephone surveillance system coupled with transfer to a live pharmacist to screen potentially drug-related symptoms after newly starting medications for four common primary care conditions: hypertension, diabetes, depression, and insomnia. METHODS: Cluster randomized trial with automated calls to eligible patients at 1 and 4 months after starting target drugs from intervention primary care clinics compared to propensity-matched patients from control clinics. Primary and secondary outcomes were physician documentation of any adverse effects associated with newly prescribed target medication, and whether the medication was discontinued and, if yes, whether the reason for stopping was an adverse effect. RESULTS: Of 4876 eligible intervention clinic patients who were contacted using automated calls, 776 (15.1%) responded and participated in the automated call. Based on positive symptom responses or request to speak to a pharmacist, 320 patients were transferred to the pharmacist and discussed 1021 potentially drug-related symptoms. Of these, 188 (18.5%) were assessed as probably and 479 (47.1%) as possibly related to the medication. Compared to a propensity-matched cohort of control clinic patients, intervention patients were significantly more likely to have adverse effects documented in the medical record by a physician (277 vs. 164 adverse effects, p < 0.0001, and 177 vs. 122 patients discontinued with documented adverse effects, p < 0.0001). DISCUSSION: Systematic automated telephone outreach monitoring coupled with real-time phone referral to a pharmacist identified a substantial number of previously unidentified potentially drug-related symptoms, many of which were validated as probably or possibly related to the drug by the pharmacist or their physicians. Multiple challenges were encountered using the interactive voice response (IVR) automated calling system, suggesting that other approaches may need to be considered and evaluated. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02087293.

Patient narratives in Yelp reviews offer insight into opioid experiences and the challenges of pain management.

AIM: To characterize Yelp reviews about pain management and opioids. METHODS: We manually coded and applied natural language processing to 836 Yelp reviews of US hospitals mentioning an opioid medication. RESULTS: Yelp reviews by patients and caregivers describing experiences with pain management and opioids had lower ratings compared with other reviews. Negative descriptions of pain management and opioid-related experiences were more commonly described than positive experiences, and the number of themes they reflected was more diverse. CONCLUSION: Yelp reviews offer insights into pain management and opioid use that are not assessed by traditional surveys. As a free, highly utilized source of unstructured narratives, Yelp may allow ongoing assessment of policies related to pain management and opioid use.

Accuracy of self-perceived risk for common conditions.

BACKGROUND: Accurate awareness of common disease risk is necessary to promote healthy lifestyles and to prevent unnecessary anxiety and evaluation. Our objective is to identify characteristics of patients who do not accurately perceive their risk of developing coronary heart disease (CHD), diabetes (DM), breast cancer (BC) and colorectal cancer (CRC). METHODS: Using personalized disease risk reports and risk perception surveys, subjects (n = 4703) were classified as high or low/average risk and high or low/average perceived risk for each condition. Models were used to examine factors associated with risk under-estimation by high risk patients and risk over-estimation by low/average risk patients. RESULTS: Patients at high risk for DM, BC and CRC often (60%-75% of the time) under-estimated their risk, while low/average risk patients overestimated their risk 13%-40% of the time. For CHD, under-estimation by high risk individuals approximated over-estimation by low/average individuals. Compared to normal weight patients at high risk for cancer, obese patients were more likely to under-estimate their risk for BC (OR 3.1, CI 1.9-5.0) and CRC (2.6, 1.5-4.5) as were overweight patients. Overweight and obese patients at low/average risk of DM or CHD were more likely than normal weight patients to over-estimate their risk. Low/average risk women were more likely than men to over-estimate their risk of DM (1.3, 1.1-1.5) and CHD (1.8, 1.5-2.1). CONCLUSIONS: Our data show that body mass index is the factor most consistently associated with incorrect risk perceptions for several common conditions.

Cost-Effectiveness of a Health System-Based Smoking Cessation Program.

INTRODUCTION: Project CLIQ (Community Link to Quit) was a proactive population-outreach strategy using an electronic health records-based smoker registry and interactive voice recognition technology to connect low- to moderate-income smokers with cessation counseling, medications, and social services. A randomized trial demonstrated that the program increased cessation. We evaluated the cost-effectiveness of CLIQ from a provider organization's perspective if implemented outside the trial framework. METHODS: We calculated the cost, cost per smoker, incremental cost per additional quit, and, secondarily, incremental cost per additional life year saved of the CLIQ system compared to usual care using data from a 2011-2013 randomized trial assessing the effectiveness of the CLIQ system. Sensitivity analyses considered economies of scale and initial versus ongoing costs. RESULTS: Over a 20-month period (the duration of the trial) the program cost US $283 027 (95% confidence interval [CI] $209 824-$389 072) more than usual care in a population of 8544 registry-identified smokers, 707 of whom participated in the program. The cost per smoker was $33 (95% CI 28-40), incremental cost per additional quit was $4137 (95% CI $2671-$8460), and incremental cost per additional life year saved was $7301 (95% CI $4545-$15 400). One-time costs constituted 28% of costs over 20 months. Ongoing costs were dominated by personnel costs (71% of ongoing costs). Sensitivity analyses showed sharp gains in cost-effectiveness as the number of identified smokers increased because of the large initial costs. CONCLUSIONS: The CLIQ system has favorable cost-effectiveness compared to other smoking cessation interventions. Cost-effectiveness will be greatest for health systems with high numbers of smokers and with the high smoker participation rates. IMPLICATIONS: Health information systems capable of establishing registries of patients who are smokers are becoming more prevalent. This economic analysis illustrates the cost implications for health care systems adopting a proactive tobacco treatment outreach strategy for low- and middle-income smokers. We find that under many circumstances, the CLIQ system has a favorable cost-per-quit compared to other population-based tobacco treatment strategies. The strategy could be widely disseminable if health systems leverage economies of scale.

A Cluster Randomized Trial of a Personalized Multi-Condition Risk Assessment in Primary Care.

INTRODUCTION: Personal risk for multiple conditions should be assessed in primary care. This study evaluated whether collection of risk factors to generate electronic health record (EHR)-linked health risk appraisal (HRA) for coronary heart disease, diabetes, breast cancer, and colorectal cancer was associated with improved patient-provider communication, risk assessment, and plans for breast cancer screening. METHODS: This pragmatic trial recruited adults with upcoming visits to 11 primary care practices during 2013-2014 (N=3,703). Pre-visit, intervention patients completed a risk factor and perception assessment and received an HRA; coded risk factor data were sent to the EHR. Post-visit, intervention patients reported risk perception. Pre-visit, control patients only completed the risk perception assessment; post-visit they also completed the risk factor assessment and received the HRA. No data were sent to the EHR for controls. Accuracy/improvement of self-perceived risk was assessed by comparing self-perceived to calculated risk. RESULTS: The intervention was associated with improvement of patient-provider communication of changes to improve health (78.5% vs 74.1%, AOR=1.67, 99% CI=1.07, 2.60). There was a similar trend for discussion of risk (54.1% vs 45.5%, AOR=1.34, 95% CI=0.97, 1.85). The intervention was associated with greater improvement in accuracy of self-perceived risk for diabetes (16.0% vs 12.6%, p=0.006) and colorectal cancer (27.9% vs 17.2%, p<0.001) with a similar trend for coronary heart disease and breast cancer. There were no changes in plans for breast cancer screening. CONCLUSIONS: Patient-reported risk factors and EHR-linked multi-condition HRAs in primary care can modestly improve communication and promote accuracy of self-perceived risk.

Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review.

BACKGROUND: Self-management is essential to caring for high-need, high-cost (HNHC) populations. Advances in mobile phone technology coupled with increased availability and adoption of health-focused mobile apps have made self-management more achievable, but the extent and quality of the literature supporting their use is not well defined. OBJECTIVE: The purpose of this review was to assess the breadth, quality, bias, and types of outcomes measured in the literature supporting the use of apps targeting HNHC populations. METHODS: Data sources included articles in PubMed and MEDLINE (National Center for Biotechnology Information), EMBASE (Elsevier), the Cochrane Central Register of Controlled Trials (EBSCO), Web of Science (Thomson Reuters), and the NTIS (National Technical Information Service) Bibliographic Database (EBSCO) published since 2008. We selected studies involving use of patient-facing iOS or Android mobile health apps. Extraction was performed by 1 reviewer; 40 randomly selected articles were evaluated by 2 reviewers to assess agreement. RESULTS: Our final analysis included 175 studies. The populations most commonly targeted by apps included patients with obesity, physical handicaps, diabetes, older age, and dementia. Only 30.3% (53/175) of the apps studied in the reviewed literature were identifiable and available to the public through app stores. Many of the studies were cross-sectional analyses (42.9%, 75/175), small (median number of participants=31, interquartile range 11.0-207.2, maximum 11,690), or performed by an app's developers (61.1%, 107/175). Of the 175 studies, only 36 (20.6%, 36/175) studies evaluated a clinical outcome. CONCLUSIONS: Most apps described in the literature could not be located on the iOS or Android app stores, and existing research does not robustly evaluate the potential of mobile apps. Whereas apps may be useful in patients with chronic conditions, data do not support this yet. Although we had 2-3 reviewers to screen and assess abstract eligibility, only 1 reviewer abstracted the data. This is one limitation of our study. With respect to the 40 articles (22.9%, 40/175) that were assigned to 2 reviewers (of which 3 articles were excluded), inter-rater agreement was significant on the majority of items (17 of 30) but fair-to-moderate on others.

Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain.

With rising smartphone ownership, mobile health applications (mHealth apps) have the potential to support high-need, high-cost populations in managing their health. While the number of available mHealth apps has grown substantially, no clear strategy has emerged on how providers should evaluate and recommend such apps to patients. Key stakeholders, including medical professional societies, insurers, and policy makers, have largely avoided formally recommending apps, which forces patients to obtain recommendations from other sources. To help stakeholders overcome barriers to reviewing and recommending apps, we evaluated 137 patient-facing mHealth apps-those intended for use by patients to manage their health-that were highly rated by consumers and recommended by experts and that targeted high-need, high-cost populations. We found that there is a wide variety of apps in the marketplace but that few apps address the needs of the patients who could benefit the most. We also found that consumers' ratings were poor indications of apps' clinical utility or usability and that most apps did not respond appropriately when a user entered potentially dangerous health information. Going forward, data privacy and security will continue to be major concerns in the dissemination of mHealth apps.