Effectiveness of an mHealth App That Uses Financial Incentives and Gamification to Promote Health Behavior Change in Adolescents and Caregivers: Protocol for a Clinic-Based Randomized Controlled Trial.

BACKGROUND: Adolescent and adult obesity continues to be a public health epidemic in the United States. Despite the popularity of mHealth apps with gamification among adolescents, there are insufficient studies to evaluate the efficacy of gamified mHealth apps and financial incentives to motivate sustained health behavior change in adolescents or their adult caregivers. OBJECTIVE: This study aims to evaluate the effectiveness of gamification techniques and financial incentives used in the novel "CommitFit" mHealth app to motivate health behavior change and improve various mental and physical health metrics in adolescents and their caregivers. METHODS: This study is a 3-month randomized controlled trial (RCT) with 30 adolescents (aged 13-15 years) and their adult caregivers (N=60). It evaluates "CommitFit," which uses gamification including points and leaderboards to motivate logging and achievement of self-selected health behavior goals (eg, more water, sleep, physical activity, fruits, or vegetables or fewer sugary beverages). The RCT had three arms, each with 10 dyads: (1) CommitFit-only users; (2) CommitFit$, where adolescents were paid US $0.05 for each point they earned; and (3) waitlist control. Intervention dyads used the app for 3 months and had the option to use it for the fourth month without prompts or extra financial incentives. User analytic software was used to evaluate the frequency of user logs and goal achievement. Monthly surveys evaluated self-reported change in the 5 CommitFit health behaviors. Changes in BMI and blood pressure were evaluated for all participants at 3 clinical visits. Mental health, gamification, and behavior economics surveys were completed during the clinical visits. RESULTS: Recruitment began in August 2023 and was completed in 10 weeks. The research team successfully recruited and enrolled 30 dyads. Researchers emailed and called 89 caregivers on a physician-approved adolescent patient list, a 33% recruitment rate. Data collection and analysis will be conducted in the spring and summer of 2024. The results of this study are anticipated to be published between late 2024 and early 2025. CONCLUSIONS: This RCT will expand knowledge of the effectiveness of gamification techniques, financial incentives, and mHealth apps to motivate sustained health behavior change among adolescents and caregivers. These results may offer new opportunities to caregivers, health insurers, health care systems, and clinicians to motivate health behavior change in adolescents and caregivers, with the ultimate goal of preventing or reducing obesity and obesity-related diseases. Additional gamification, mental health surveys, and app user analytics included in the study may provide further insight into the characteristics of adolescents or caregivers who would benefit the most from using a gamified mHealth app like CommitFit. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63505.

mHealth app features that facilitate adolescent use for lifestyle management, and are endorsed by caregivers and health care providers.

Background: Mobile health (mHealth) apps are becoming a promising tool to motivate sustainable lifestyle and behavior changes, including modifications to diet and exercise. However, most current mHealth apps do not have meaningful, and sustained user acceptance, particularly, among adolescents. They perceive mHealth apps designed for adults to be tedious and visually unexciting, which discourage adolescent usage. Researchers and adolescent mHealth app developers would benefit from a foundational understanding of which functions and features adolescents feel would most motivate app use. Capturing caregivers' and health care providers' inputs are also important as both groups play an integral role in adolescent health care decision-making. The purpose of the study is to explore and analyze mHealth app features identified by adolescents, caregivers, and health care providers that have the potential to inspire continued use, thereby resulting in sustained health behavior changes in adolescents. Methods: We used inductive thematic analysis of qualitative data obtained from semi-structured focus groups conducted via Zoom©. Important features of mHealth apps that encourage adoption and continued use were explored with 25 participants, including adolescents, their caregivers, and health care providers. Results: Common features facilitating continual usage of mHealth apps that were identified as significant by participating adolescents, their caregivers and health care providers were: look and feel of the app, customization, educational information/recommendations, and integration with electronic health record. Features such as gamification and social interaction that are usually lacking in current adolescent mHealth apps were well recognized as meaningful for motivational purposes. Conclusions: The findings suggest that adolescents and caregivers identify an app as valuable when it is user-friendly and intuitive and appreciate features that are motivating and can engage users in positive behaviors. Health care providers prefer mHealth apps that are user-friendly and can be effectively integrated into the cycle of care, thereby enabling delivery of efficient and value-based health care. Thus, mHealth app designs that are informed by health care providers' clinical experience and needs, in combination with app features that are desired and supported by both adolescents and their caregivers, have the potential to motivate widespread adoption and long-term use, which could result in improved health behaviors and outcomes among adolescents.

Study protocol: Collaboration Oriented Approach to Controlling High blood pressure (COACH) in adults - a randomised controlled trial.

INTRODUCTION: Hypertension, the clinical condition of persistent high blood pressure (BP), is preventable yet remains a significant contributor to poor cardiovascular outcomes. Digital self-management support tools can increase patient self-care behaviours to improve BP. We created a patient-facing and provider-facing clinical decision support (CDS) application, called the Collaboration Oriented Approach to Controlling High BP (COACH), to integrate home BP data, guideline recommendations and patient-centred goals with primary care workflows. We leverage social cognitive theory principles to support enhanced engagement, shared decision-making and self-management support. This study aims to measure the effectiveness of the COACH intervention and evaluate its adoption as part of BP management. METHODS AND ANALYSIS: The study design is a multisite, two-arm hybrid type III implementation randomised controlled trial set within primary care practices across three health systems. Randomised participants are adults with high BP for whom home BP monitoring is indicated. The intervention arm will receive COACH, a digital web-based intervention with effectively enhanced alerts and displays intended to drive engagement with BP lowering; the control arm will receive COACH without the alerts and a simple display. Outcome measures include BP lowering (primary) and self-efficacy (secondary). Implementation preplanning and postevaluation use the Consolidated Framework for Implementation Research and Reach-Effectiveness-Adoption-Implementation-Maintenance metrics with iterative cycles for qualitative integration into the trial and its quantitative evaluation. The trial analysis includes logistic regression and constrained longitudinal data analysis. ETHICS AND DISSEMINATION: The trial is approved under a single IRB through the University of Missouri-Columbia, #2091483. Dissemination of the intervention specifications and results will be through open-source mechanisms. TRIAL REGISTRATION NUMBER: NCT06124716.

Clinician Needs for Electronic Health Record Pediatric and Adolescent Weight Management Tools: A Mixed-Methods Study.

BACKGROUND: Clinicians play an important role in addressing pediatric and adolescent obesity, but their effectiveness is restricted by time constraints, competing clinical demands, and the lack of effective electronic health record (EHR) tools. EHR tools are rarely developed with provider input. OBJECTIVES: We conducted a mixed method study of clinicians who provide weight management care to children and adolescents to determine current barriers for effective care and explore the role of EHR weight management tools to overcome these barriers. METHODS: In this mixed-methods study, we conducted three 1-hour long virtual focus groups at one medium-sized academic health center in Missouri and analyzed the focus group scripts using thematic analysis. We sequentially conducted a descriptive statistical analysis of a survey emailed to pediatric and family medicine primary care clinicians (n = 52) at two private and two academic health centers in Missouri. RESULTS: Surveyed clinicians reported that they effectively provided health behavior lifestyle counseling at well-child visits (mean of 60 on a scale of 1-100) and child obesity visits (63); however, most felt the current health care system (27) and EHR tools (41) do not adequately support pediatric weight management. Major themes from the clinician focus groups were that EHR weight management tools should display data in a way that (1) improves clinical efficiency, (2) supports patient-centered communication, (3) improves patient continuity between visits, and (4) reduces documentation burdens. An additional theme was (5) clinicians trust patient data entered in real time over patient recalled data. CONCLUSION: Study participants report that the health care system status quo and currently available EHR tools do not sufficiently support clinicians working to manage pediatric or adolescent obesity and provide health behavior counseling. Clinician input in the development and testing of EHR weight management tools provides opportunities to address barriers, inform content, and improve efficiencies of EHR use.

Mixed-methods study of development and design needs for CommitFit, an adolescent mHealth App.

Background: Adolescent obesity remains a significant public health issue within the United States. Mobile application technology growth and popularity offer new opportunities for research and health improvement. The development of a consolidated mobile health application (mHealth app) for adolescents on these platforms has the potential to improve health outcomes. Thus, this study describes the co-development process working with adolescent users. The aims are as follows: (I) to explore the visual design and functional requirements when developing the CommitFit mHealth app, (II) to uncover the gamification techniques that incentivize adolescents to set and achieve healthy lifestyle goals, and (III) to identify adolescent expectations when using the CommitFit mHealth application. Methods: In this mixed method study, we used semi-structured interviews/task analysis and surveys of adolescents (aged 13 to 15 years) to understand their user requirements and design preferences during the development of the CommitFit mHealth app. Interviews were conducted online, via Zoom. The survey included the user design industry-standard System Usability Scale (SUS) paired with a supplemental questionnaire on the specific features and functionalities of the CommitFit mHealth app. Participants were recruited from the electronic health record from the University of Missouri Healthcare system. Results: Ten adolescents, aged 13 to 15 years (average of 13.6 years), were interviewed and surveyed to explore adolescent preferences with visual app design and functionality. Our inductive thematic analysis found that adolescents preferred colorful, user-friendly interfaces paired with gamification in the CommitFit mHealth app. Our analysis of SUS survey data validated our user-centered and human-system design and adolescents confirmed their design, feature, and functionality preferences. Overall, adolescent users were able to confirm their preference to have educational resources, goal recommendations, leaderboard, points, reminders, and an avatar in the app. Conclusions: Adolescent feedback is crucial in the successful development of our adolescent-targeted mHealth app, CommitFit. Adolescents preferred vibrant colors, easy-to-use interface, gamification, customizable and personalized, and mature graphics. Adolescents were especially motivated by gamification techniques to maintain their interest in the application and their health behavior goals. Additional research is now needed to explore the clinical effectiveness of the CommitFit mHealth app, as a health and lifestyle intervention.

Infrastructure Features Associated With Increased Department Research Capacity.

PURPOSE: Although researchers have identified factors associated with research capacity in academic medicine departments, less is known about how a department builds research capacity over time. The Association of Departments of Family Medicine's Research Capacity Scale (RCS) can be used by departments to self-categorize into five capacity levels. Our current study aimed to describe the distribution of infrastructure features and to evaluate how the addition of infrastructure features influences movement of a department along the RCS. METHOD: An online survey was sent to US family medicine department chairs in August 2021. Survey questions asked chairs to categorize their department's research capacity in 2018 and 2021 and also about the presence of infrastructure resources and changes in these features across 6 years. RESULTS: The response rate was 54.2%. Departments identified substantial variation in research capacity. Most departments classified into the middle three levels. Departments in higher levels were more likely than those at lower levels to have any of the infrastructure resources in 2021. Department size, as measured by full time faculty, was highly associated with department level. From 2018 and 2021, 43% of responding departments climbed at least one level. Of these, more than half added three or more infrastructure features. Adding a PhD researcher was the feature most associated with increasing research capacity (P<.001). CONCLUSIONS: Most departments that increased their research capacity added multiple additional infrastructure features. For chairs of departments without a PhD researcher, this additional resource may be the most impactful investment to increase research capacity.

Negotiating a new chair package: context and considerations.

Negotiating a resource package as a potential new department chair is common practice in academic medicine. The foundations for this negotiation include the historical presence of the department in relation to the broader institution, projections for future growth, accounting for mission/vision, resource needs (space, personnel, finances, etc), faculty and staff development, and external partnerships within and outside the institution. Despite similarities in this process across departments, many nuances influence the development of a specific new chair package, such as, department size; desires, perspectives and talents of the incoming chair, the department faculty, the medical school and dean; prevailing agendas and mission imperatives; and the overall priorities of the institution. With strategy and forethought, a new chair package can promote a successful chair tenure and departmental growth. Assembled through the Association of Departments of Family Medicine with input from several dozen department chairs and senior leaders, this is intended to serve as a practical guide to new chair packages for chair candidates.

Patient judgments about hypertension control: the role of patient numeracy and graph literacy.

OBJECTIVE: To assess the impact of patient health literacy, numeracy, and graph literacy on perceptions of hypertension control using different forms of data visualization. MATERIALS AND METHODS: Participants (Internet sample of 1079 patients with hypertension) reviewed 12 brief vignettes describing a fictitious patient; each vignette included a graph of the patient's blood pressure (BP) data. We examined how variations in mean systolic blood pressure, BP standard deviation, and form of visualization (eg, data table, graph with raw values or smoothed values only) affected judgments about hypertension control and need for medication change. We also measured patient's health literacy, subjective and objective numeracy, and graph literacy. RESULTS: Judgments about hypertension data presented as a smoothed graph were significantly more positive (ie, hypertension deemed to be better controlled) then judgments about the same data presented as either a data table or an unsmoothed graph. Hypertension data viewed in tabular form was perceived more positively than graphs of the raw data. Data visualization had the greatest impact on participants with high graph literacy. DISCUSSION: Data visualization can direct patients to attend to more clinically meaningful information, thereby improving their judgments of hypertension control. However, patients with lower graph literacy may still have difficulty accessing important information from data visualizations. CONCLUSION: Addressing uncertainty inherent in the variability between BP measurements is an important consideration in visualization design. Well-designed data visualization could help to alleviate clinical uncertainty, one of the key drivers of clinical inertia and uncontrolled hypertension.

Impact of Home Blood Pressure Data Visualization on Hypertension Medical Decision Making in Primary Care.

PURPOSE: Evidence shows the value of home blood pressure (BP) monitoring in hypertension management. Questions exist about how to effectively incorporate these readings into BP follow-up visits. We developed and implemented a tool that combines clinical and home BP readings into an electronic health record (EHR)-integrated visualization tool. We examined how this tool was used during primary care visits and its effect on physician-patient communication and decision making about hypertension management, comparing it with home BP readings on paper. METHODS: We video recorded the hypertension follow-up visits of 73 patients with 15 primary care physicians between July 2018 and April 2019. During visits, physicians reviewed home BP readings with patients, either directly from paper or as entered into the EHR visualization tool. We used conversation analysis to analyze the recordings. RESULTS: Home BP readings were viewed on paper for 26 patients and in the visualization tool for 47 patients. Access to home BP readings during hypertension management visits, regardless of viewing mode, positioned the physician and patient to assess BP management and make decisions about treatment modification, if needed. Length of BP discussion with the visualization tool was similar to or shorter than that with paper. Advantages of the visualization tool included ease of use, and enhanced and faster sense making and decision making. Successful use of the tool required patients' ability to obtain their BP readings and enter them into the EHR via a portal, and an examination room configuration that allowed for screen sharing. CONCLUSIONS: Reviewing home BP readings using a visualization tool is feasible and enhances sense making and patient engagement in decision making. Practices and their patients need appropriate infrastructure to realize these benefits.

A Longitudinal Effectiveness Study of a Child Obesity Electronic Health Record Tool.

BACKGROUND: Primary-care providers, clinic staff, and nurses play an important role in reducing child obesity; yet time restraints and clinical demands compete with effective pediatric weight management and prevention. METHODS: To investigate the potential impact of an electronic health record (EHR) enabled tool to assist primary care teams in addressing child obesity, we conducted a controlled effectiveness study of FitTastic compared with usual care on the BMI pattern of 291 children (2 to 17 years) up to 4 years later. RESULTS: Per χ2 analysis, a greater proportion of children with baseline overweight/obesity in the EHR tool group than the control group had a favorable BMI pattern (32% vs 13%, P = .03). In logistic regression, FitTastic children were more likely than control children to have a favorable BMI pattern at follow-up (OR 3.8, 95% CI 1.1 to 13.2), adjusted for age, gender, race, and parental education. CONCLUSION: Study findings suggest that EHR-enabled tools to assist primary care teams in managing child obesity may be useful for helping to address the weight in children with overweight/obesity, especially in younger children (2 to 5 years). Digital and EHR-enabled technologies may prove useful for partnering health care teams and families in the important tasks of setting positive, family-centered healthy lifestyle behavioral goals and managing child overweight and obesity.

Development and Pilot Analysis of the Nursing Home Health Information Technology Maturity Survey and Staging Model.

The current research includes a psychometric test of a nursing home (NH) health information technology (HIT) maturity survey and staging model. NHs were assembled based on HIT survey scores from a prior study representing NHs with low (20%), medium (60%), and high (20%) HIT scores. Inclusion criteria were NHs that completed at least two annual surveys over 4 years. NH administrators were excluded who participated in the Delphi panel responsible for instrument recommendations. Recruitment occurred from January to May 2019. Administrators from 121 of 429 facilities completed surveys. NHs were characteristically for-profit, medium bed size, and metropolitan. A covariance matrix demonstrated that all dimensions and domains were significantly correlated, except HIT capabilities and integration in administrative activities. Cronbach's alpha was very good (0.86). Principal component analysis revealed all items loaded intuitively onto four components, explaining 80% variance. The HIT maturity survey and staging model can be used to assess nine dimensions and domains, total HIT maturity, and stage, leading to reliable assumptions about NH HIT. [Research in Gerontological Nursing, 15(2), 93-99.].

Assessing Racial and Ethnic Discrimination in Children: A Scoping Review of Available Measures for Child Health Disparities Research.

Objectives: To characterize the availability, content, and psychometric properties of self-reported measures that assess race/ethnicity-related discrimination or psychosocial stress and have potential relevance to studies of health disparities in children and adolescents. Design: Using PRISMA extension guidelines for scoping reviews, we searched Ovid Medline, CINAHL, PsychInfo, and Scopus databases from 1946 to April 20, 2020, using the search terms "stress," "child," "adolescents," "discrimination," and "psychometrics." We limited the search to articles in English, with children and adolescents, in the United States. For each measure, we extracted information about the content, reliability, and construct validity. Results: The 12 measures that met inclusion criteria assessed discrimination or stress from racial discrimination in African American children and adolescents (n=8), acculturative stress in Hispanic/Latino children (n=1), or bicultural stress in Mexican American adolescents (n=2), and one measure assessed both discrimination-related and acculturative stress in Hispanic/Latino children. The majority (n=7) articles were published between 2001 and 2010. All discrimination measures evaluated individual experiences of discrimination and one also evaluated stressfulness of discrimination and coping. The acculturative stress measures assessed general stress and immigration-related discrimination, and the bicultural stress measures evaluated many different aspects of biculturalism. Conclusions: Despite the recent increased interest in the racial discrimination and stress as a contributor to racial or ethnic health disparities affecting U.S. children and adolescents, the small number of eligible measures identified and incomplete coverage of various types of racial and ethnic discrimination within and across population groups indicates a currently inadequate capacity to conduct child health disparity studies on this issue.

Home blood pressure data visualization for the management of hypertension: using human factors and design principles.

BACKGROUND: Home blood pressure measurements have equal or even greater predictive value than clinic blood pressure measurements regarding cardiovascular outcomes. With advances in home blood pressure monitors, we face an imminent flood of home measurements, but current electronic health record systems lack the functionality to allow us to use this data to its fullest. We designed a data visualization display for blood pressure measurements to be used for shared decision making around hypertension. METHODS: We used an iterative, rapid-prototyping, user-centred design approach to determine the most appropriate designs for this data display. We relied on visual cognition and human factors principles when designing our display. Feedback was provided by expert members of our multidisciplinary research team and through a series of end-user focus groups, comprised of either hypertensive patients or their healthcare providers required from eight academic, community-based practices in the Midwest of the United States. RESULTS: A total of 40 participants were recruited to participate in patient (N = 16) and provider (N = 24) focus groups. We describe the conceptualization and development of data display for shared decision making around hypertension. We designed and received feedback from both patients and healthcare providers on a number of design elements that were reported to be helpful in understanding blood pressure measurements. CONCLUSIONS: We developed a data display for substantial amounts of blood pressure measurements that is both simple to understand for patients, but powerful enough to inform clinical decision making. The display used a line graph format for ease of understanding, a LOWESS function for smoothing data to reduce the weight users placed on outlier measurements, colored goal range bands to allow users to quickly determine if measurements were in range, a medication timeline to help link recorded blood pressure measurements with the medications a patient was taking. A data display such as this, specifically designed to encourage shared decision making between hypertensive patients and their healthcare providers, could help us overcome the clinical inertia that often results in a lack of treatment intensification, leading to better care for the 35 million Americans with uncontrolled hypertension.

Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs.

BACKGROUND: Nearly half of US adults with diagnosed hypertension have uncontrolled blood pressure. Clinical inertia may contribute, including patient-physician uncertainty about how variability in blood pressures impacts overall control. Better information display may support clinician-patient hypertension decision making through reduced cognitive load and improved situational awareness. METHODS: A multidisciplinary team employed iterative user-centered design to create a blood pressure visualization EHR prototype that included patient-generated blood pressure data. An attitude and behavior survey and 10 focus groups with patients (N = 16) and physicians (N = 24) guided iterative design and confirmation phases. Thematic analysis of qualitative data yielded insights into patient and physician needs for hypertension management. RESULTS: Most patients indicated measuring home blood pressure, only half share data with physicians. When receiving home blood pressure data, 88% of physicians indicated entering gestalt averages as text into clinical notes. Qualitative findings suggest that including a data visualization that included home blood pressures brought this valued data into physician workflow and decision-making processes. Data visualization helps both patients and physicians to have a fuller understanding of the blood pressure 'story' and ultimately promotes the activated engaged patient and prepared proactive physician central to the Chronic Care Model. Both patients and physicians expressed concerns about workflow for entering and using home blood pressure data for clinical care. CONCLUSIONS: Our user-centered design process with physicians and patients produced a well-received blood pressure visualization prototype that includes home blood pressures and addresses patient-physician information needs. Next steps include evaluating a recent EHR visualization implementation, designing annotation functions aligned with users' needs, and addressing additional stakeholders' needs (nurses, care managers, caregivers). This significant innovation has potential to improve quality of care for hypertension through better patient-physician understanding of control and goals. It also has the potential to enable remote monitoring of patient blood pressure, a newly reimbursed activity, and is a strong addition to telehealth efforts.

Use of Enhanced Data Visualization to Improve Patient Judgments about Hypertension Control.

Objective. Uncontrolled hypertension is driven by clinical uncertainty around blood pressure data. This research sought to determine whether decision support-in the form of enhanced data visualization-could improve judgments about hypertension control. Methods. Participants (Internet sample of patients with hypertension) in 3 studies (N = 209) viewed graphs depicting blood pressure data for fictitious patients. For each graph, participants rated hypertension control, need for medication change, and perceived risk of heart attack and stroke. In study 3, participants also recalled the percentage of blood pressure measurements outside of the goal range. The graphs varied by systolic blood pressure mean and standard deviation, change in blood pressure values over time, and data visualization type. Results. In all 3 studies, data visualization type significantly affected judgments of hypertension control. In studies 1 and 2, perceived hypertension control was lower while perceived need for medication change and subjective perceptions of stroke and heart attack risk were higher for raw data displays compared with enhanced visualization that employed a smoothing function generated by the locally weighted smoothing algorithm. In general, perceptions of hypertension control were more closely aligned with clinical guidelines when data visualization included a smoothing function. However, conclusions were mixed when comparing tabular presentations of data to graphical presentations of data in study 3. Hypertension was perceived to be less well controlled when data were presented in a graph rather than a table, but recall was more accurate. Conclusion. Enhancing data visualization with the use of a smoothing function to minimize the variability present in raw blood pressure data significantly improved judgments about hypertension control. More research is needed to determine the contexts in which graphs are superior to data tables.

Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs.

OBJECTIVES: To identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning electronic health records (EHR) to address these needs. MATERIALS AND METHODS: In this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users' information needs, which were then used to produce EHR design principles. RESULTS: Analyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information. CONCLUSION: Developing EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.

Adoption of an Electronic Medical Record Tool for Childhood Obesity by Primary Care Providers.

BACKGROUND: Primary care providers are tasked with the increasingly difficult job of addressing childhood obesity during clinic visits. Electronic medical record (EMR)-enabled decision-support tools may aid providers in this task; however, information is needed regarding whether providers perceive such tools to be useful for addressing nutrition and physical activity lifestyle behaviors. OBJECTIVES: This study aimed to evaluate the usefulness and usability of FitTastic, an EMR-enabled tool to support prevention and management of childhood obesity in primary care. METHODS: In this mixed-method study, we implemented the FitTastic tool in two primary-care clinics, then surveyed and conducted focused interviews with providers. Validated Technology Acceptance Model perceived usefulness and National Aeronautics and Space Administration (NASA) perceived usability survey questions were e-mailed to 60 providers. In-depth provider interviews with family medicine and pediatric physicians (n = 12) were used to further probe adoption of FitTastic. RESULTS: Surveys were completed by 73% of providers (n = 44). The mean score for FitTastic's usefulness was 3.3 (standard deviation [SD] = 0.54, scale 1-5, where 5 is strongly agree) and usability, 4.8 (SD = 0.86, scale 1-7, where 7 is strongly agree). Usefulness and usability scores were associated with intention to use FitTastic (correlation for both, p < 0.05). Data from provider interviews indicated that useful features of FitTastic included: standardizing the approach to childhood obesity, and facilitating conversations about weight management, without increasing cognitive workload. However, use of FitTastic required more time from nurses to input lifestyle data. CONCLUSION: FitTastic is perceived as a useful and usable EMR-based lifestyle behavior tool that standardizes, facilitates, and streamlines healthy lifestyle conversations with families. Perceived usability and usefulness scores correlated with provider intention-to-use the technology. These data suggest that EMR-based child obesity prevention and management tools can be feasible to use in the clinic setting, with potential for scalability. Usefulness can be optimized by limiting amount of time needed by staff to input data.

Correction to: Forecasting Content and Stage in a Nursing Home Information Technology Maturity Instrument Using a Delphi Method.

The original article unfortunately contained a mistake.

Forecasting Content and Stage in a Nursing Home Information Technology Maturity Instrument Using a Delphi Method.

Health information technology capabilities in some healthcare sectors, such as nursing homes, are not well understood because measures for information technology uptake have not been fully developed, tested, validated, or measured consistently. The paper provides a report of the development and testing of a new instrument measuring nursing home information technology maturity and stage of maturity. Methods incorporated a four round Delphi panel composed of 31 nursing home experts from across the nation who reported the highest levels of information technology sophistication in a separate national survey. Experts recommended 183 content items for 27 different content areas specifying the measure of information technology maturity. Additionally, experts ranked each of the 183 content items using an IT maturity instrument containing seven stages (stages 0-6) of information technology maturity. The majority of content items (40% (n = 74)) were associated with information technology maturity stage 4, corresponding to facilities with external connectivity capability. Over 11% of the content items were at the highest maturity stage (Stage 5 and 6). Content areas with content items at the highest stage of maturity are reflected in nursing homes that have technology available for residents or their representatives and used extensively in resident care. An instrument to assess nursing home IT maturity and stage of maturity has important implications for understanding health service delivery systems, regulatory efforts, patient safety and quality of care.

Effect of Health Information Technologies on Cardiovascular Risk Factors among Patients with Diabetes.

PURPOSE OF REVIEW: To identify a common effect of health information technologies (HIT) on the management of cardiovascular disease (CVD) risk factors among people with type 2 diabetes (T2D) across randomized control trials (RCT). RECENT FINDINGS: CVD is the most frequent cause of morbidity and mortality among patients with diabetes. HIT are effective in reducing HbA1c; however, their effect on cardiovascular risk factor management for patients with T2D has not been evaluated. We identified 21 eligible studies (23 estimates) with measurement of SBP, 20 (22 estimates) of DBP, 14 (17 estimates) of HDL, 14 (17 estimates) of LDL, 15 (18 estimates) of triglycerides, and 10 (12 estimates) of weight across databases. We found significant reductions in SBP, DBP, LDL, and TG, and a significant improvement in HDL associated with HIT. As adjuvants to standard diabetic treatment, HIT can be effective tools for improving CVD risk factors among patients with T2D, especially in those whose CVD risk factors are not at goal.