Public preference on sharing health data to inform research, health policy and clinical practice in Australia: A stated preference experiment.

OBJECTIVE: To investigate public willingness to share sensitive health information for research, health policy and clinical practice. METHODS: A total of 1,003 Australian respondents answered an online, attribute-driven, survey in which participants were asked to accept or reject hypothetical choice sets based on a willingness to share their health data for research and frontline-medical support as part of an integrated health system. The survey consisted of 5 attributes: Stakeholder access for analysis (Analysing group); Type of information collected; Purpose of data collection; Information governance; and Anticipated benefit; the results of which were analysed using logistic regression. RESULTS: When asked about their preference for sharing their health data, respondents had no preference between data collection for the purposes of clinical practice, health policy or research, with a slight preference for having government organisations manage, govern and curate the integrated datasets from which the analysis was being conducted. The least preferred option was for personal health records to be integrated with insurance records or for their data collected by privately owned corporate organisations. Individuals preferred their data to be analysed by a public healthcare provider or government staff and expressed a dislike for any private company involvement. CONCLUSIONS: The findings from this study suggest that Australian consumers prefer to share their health data when there is government oversight, and have concerns about sharing their anonymised health data for clinical practice, health policy or research purposes unless clarity is provided pertaining to its intended purpose, limitations of use and restrictions to access. Similar findings have been observed in the limited set of existing international studies utilising a stated preference approach. Evident from this study, and supported by national and international research, is that the establishment and preservation of a social license for data linkage in health research will require routine public engagement as a result of continuously evolving technological advancements and fluctuating risk tolerance. Without more work to understand and address stakeholder concerns, consumers risk being reluctant to participate in data-sharing and linkage programmes.

Factors Influencing the Sharing of Personal Health Data Based on the Integrated Theory of Privacy Calculus and Theory of Planned Behaviors Framework: Results of a Cross-Sectional Study of Chinese Patients in the Yangtze River Delta.

BACKGROUND: The health care system in China is fragmented, and the distribution of high-quality resources remains uneven and irrational. Information sharing is essential to the development of an integrated health care system and maximizing its benefits. Nevertheless, data sharing raises concerns regarding the privacy and confidentiality of personal health information, which affect the willingness of patients to share information. OBJECTIVE: This study aims to investigate patients' willingness to share personal health data at different levels of maternal and child specialized hospitals in China, to propose and test a conceptual model to identify key influencing factors, and to provide countermeasures and suggestions to improve the level of data sharing. METHODS: A research framework based on the Theory of Privacy Calculus and the Theory of Planned Behavior was developed and empirically tested through a cross-sectional field survey from September 2022 to October 2022 in the Yangtze River Delta region, China. A 33-item measurement instrument was developed. Descriptive statistics, chi-square tests, and logistic regression analyses were conducted to characterize the willingness of sharing personal health data and differences by sociodemographic factors. Structural equation modeling was used to assess the reliability and validity of the measurement as well as to test the research hypotheses. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for cross-sectional studies was applied for reporting results. RESULTS: The empirical framework had a good fit with the chi-square/degree of freedom (χ2/df)=2.637, root-mean-square residual=0.032, root-mean-square error of approximation=0.048, goodness-of-fit index=0.950, and normed fit index=0.955. A total of 2060 completed questionnaires were received (response rate: 2060/2400, 85.83%). Moral motive (ß=.803, P<.001), perceived benefit (ß=.123, P=.04), and perceived effectiveness of government regulation (ß=.110, P=.001) had a significantly positive association with sharing willingness, while perceived risk (ß=-.143, P<.001) had a significant negative impact, with moral motive having the greatest impact. The estimated model explained 90.5% of the variance in sharing willingness. CONCLUSIONS: This study contributes to the literature on personal health data sharing by integrating the Theory of Privacy Calculus and the Theory of Planned Behavior. Most Chinese patients are willing to share their personal health data, which is primarily motivated by moral concerns to improve public health and assist in the diagnosis and treatment of illnesses. Patients with no prior experience with personal information disclosure and those who have tertiary hospital visits were more likely to share their health data. Practical guidelines are provided to health policy makers and health care practitioners to encourage patients to share their personal health information.

A Digital Opportunity for Patients to Manage Their Health: Turkey National Personal Health Record System (The e-Nabiz)

Background: Health records changed over time in the countries, and also Türkiye passed from paper versions to personal health records (PHR) and put patients at the center of the system by allowing them to become the master of their health data. Aims: Presenting the current state of the e-Nabiz application nationwide in Turkey, and to evaluate the benefits of patients' online access to electronic health records and the system's interoperability. Study Design: A descriptive observational study. Methods: In the Turkish PHR system (e-Nabiz), services to patients to manage their health are categorized and analyzed within the scope of national digital health services. In addition, the data validation in the e-Nabiz within itself has been systematically expressed. Results: The Turkish PHR system allows users to use 30 different services for treatment, prevention, health promotion, and health-related and interrelated areas. Moreover, some statistics regarding the categories specified in the e-Nabiz system are included. Today, data is flowing from 28,608 system-integrated health facilities and 39 e-Nabiz integrated public institutions. In addition, 4.5 billion transactions are done by people by 2023 and 220 million users are queried by physicians to reach patients' labs and results. Plus, the e-Nabiz is adopted by 82% of the Türkiye population. Conclusion: There is no universal model for the content of the PHR. Given its importance to the patient, the content evolved and will continue to grow over the years. With the advent of coronavirus disease 2019, the system is equipped with three new services. The importance of these services over time and in the future has been demonstrated with increasing momentum.

A Description of Personal Health Information Management Work With a Spotlight on the Practices of Older Adults: Qualitative e-Delphi Study With Professional Organizers.

BACKGROUND: Personal health information (PHI) is created on behalf of and by health care consumers to support their care and wellness. Available tools designed to support PHI management (PHIM) remain insufficient. A comprehensive understanding of PHIM work is required, particularly for older adults, to offer more effective PHIM tools and support. OBJECTIVE: The primary objective of this study was to use the Patient Work System model to provide a holistic description of PHIM work from the perspective of professional organizers with experience assisting health care consumers, including older adults, in managing their PHI. A secondary objective was to examine how factors associated with 4 Patient Work System components (person, tasks, tools and technologies, and context) interact to support or compromise PHIM work performance. METHODS: A modified e-Delphi methodology was used to complete 3 web-based rounds of open-ended questions and obtain consensus among a panel of 16 experts in professional organizing. Data were collected between April and December 2017. The Patient Work System model was used as a coding schema and guided the interpretation of findings during the analysis. RESULTS: The PHIM work of adults who sought assistance focused on the tasks of acquiring, organizing, and storing 3 classifications of PHI (medical, financial, and reference) and then processing, reconciling, and storing the medical and financial classifications to tend to their health, health care, and health finances. We also found that the complexities of PHI and PHIM-related work often exceeded the abilities and willingness of those who sought assistance. A total of 6 factors contributed to the complexity of PHIM work. The misalignment of these factors was found to increase the PHIM workload, particularly for older adults. The life changes that often accompanied aging, coupled with obscure and fragmented health care provider- and insurer-generated PHI, created the need for much PHIM work. Acquiring and integrating obscure and fragmented PHI, detecting and reconciling PHI discrepancies, and protecting PHI held by health care consumers were among the most burdensome tasks, especially for older adults. Consequently, personal stakeholders (paid and unpaid) were called upon or voluntarily stepped in to assist with PHIM work. CONCLUSIONS: Streamlining and automating 2 of the most common and burdensome PHIM undertakings could drastically reduce health care consumers' PHIM workload: developing and maintaining accurate current and past health summaries and tracking medical bills and insurance claims to reconcile discrepancies. Other improvements that hold promise are the simplification and standardization of commonly used financial and medical PHI; standardization and automation of commonly used PHI acquisition interfaces; and provision of secure, Health Insurance Portability and Accountability Act (HIPAA)-certified PHI tools and technologies that control multiperson access for PHI stored by health care consumers in electronic and paper formats.

Privacy and Trust in pHealth - Past, Present and Future.

From beginning to today, pHealth has been a data driven service that collects and uses personal health information (PHI) for personal health services and personalized healthcare. As a result, pHealth services use intensively ICT technology, sensors, computers and mathematical algorithms. In past, pHealth applications were focused to certain health or sickness related problem, but in today they use mobile devices, wireless networks, Web-technology and Cloud platforms. In future, pHealth uses information systems that are highly distributed, dynamic, increasingly autonomous, multi-stakeholder data driven eco-system having ability to monitor anywhere person's regular life, movements and health related behaviours. Because privacy and trust are pre-requirements for successful pHealth, this development raises huge privacy and trust challenges to be solved. Researchers have shown that current privacy approaches and solutions used in pHealth do not offer acceptable level of privacy, and trust is only an illusion. This indicates, that today's privacy models and technology shall not be moved to the future pHealth. The authors have analysed interesting new privacy and trust ideas published in journals, and found that they seem to be effective but offer only a partial solution. To solve this weakness, the authors used a holistic system view to aspects impacting privacy and trust in pHealth, and created a template that can be used in planning and development future pHealth services. The authors also propose a tentative solution for future trustworthy pHealth. It combines privacy as personal property and trust as legal binding fiducial duty approaches, and uses a Blockchain-based smart contract solution to store person's privacy and trust requirements and service providers' promises.

Digital Health Literacy as a Predictor of Awareness, Engagement, and Use of a National Web-Based Personal Health Record: Population-Based Survey Study.

BACKGROUND: Web-based personal health records (PHRs) have the potential to improve the quality, accuracy, and timeliness of health care. However, the international uptake of web-based PHRs has been slow. Populations experiencing disadvantages are less likely to use web-based PHRs, potentially widening health inequities within and among countries. OBJECTIVE: With limited understanding of the predictors of community uptake and use of web-based PHR, the aim of this study was to identify the predictors of awareness, engagement, and use of the Australian national web-based PHR, My Health Record (MyHR). METHODS: A population-based survey of adult participants residing in regional Victoria, Australia, was conducted in 2018 using telephone interviews. Logistic regression, adjusted for age, was used to assess the relationship among digital health literacy, health literacy, and demographic characteristics, and the 3 dependent variables of MyHR: awareness, engagement, and use. Digital health literacy and health literacy were measured using multidimensional tools, using all 7 scales of the eHealth Literacy Questionnaire and 4 out of the 9 scales of the Health Literacy Questionnaire. RESULTS: A total of 998 responses were analyzed. Many elements of digital health literacy were strongly associated with MyHR awareness, engagement, and use. A 1-unit increase in each of the 7 eHealth Literacy Questionnaire scales was associated with a 2- to 4-fold increase in the odds of using MyHR: using technology to process health information (odds ratio [OR] 4.14, 95% CI 2.34-7.31), understanding of health concepts and language (OR 2.25, 95% CI 1.08-4.69), ability to actively engage with digital services (OR 4.44, 95% CI 2.55-7.75), feel safe and in control (OR 2.36, 95% CI 1.43-3.88), motivated to engage with digital services (OR 4.24, 95% CI 2.36-7.61), access to digital services that work (OR 2.49, 95% CI 1.32-4.69), and digital services that suit individual needs (OR 3.48, 95% CI 1.97-6.15). The Health Literacy Questionnaire scales of health care support, actively managing health, and social support were also associated with a 1- to 2-fold increase in the odds of using MyHR. Using the internet to search for health information was another strong predictor; however, older people and those with less education were less likely to use MyHR. CONCLUSIONS: This study revealed strong and consistent patterns of association between digital health literacy and the use of a web-based PHR. The results indicate potential actions for promoting PHR uptake, including improving digital technology and skill experiences that may improve digital health literacy and willingness to engage in web-based PHR. Uptake may also be improved through more responsive digital services, strengthened health care, and better social support. A holistic approach, including targeted solutions, is needed to ensure that web-based PHR can realize its full potential to help reduce health inequities.

Privacy Protection and Secondary Use of Health Data: Strategies and Methods.

Health big data has already been the most important big data for its serious privacy disclosure concerns and huge potential value of secondary use. Measurements must be taken to balance and compromise both the two serious challenges. One holistic solution or strategy is regarded as the preferred direction, by which the risk of reidentification from records should be kept as low as possible and data be shared with the principle of minimum necessary. In this article, we present a comprehensive review about privacy protection of health data from four aspects: health data, related regulations, three strategies for data sharing, and three types of methods with progressive levels. Finally, we summarize this review and identify future research directions.

Can a Chatbot Increase the Motivation to Provide Personal Health Information?

In healthcare settings, questionnaires are used to collect information from a patient. A standard method for this are paper-based questionnaires, but they are often complex to understand or long and frustrating to fill. To increase motivation, we developed a chatbot-based system Ana that asks questions that are normally asked using paper forms or in face-to-face encounters. Ana has been developed for the specific use case of collecting the music biography in the context of music therapy. In this paper, we compare user motivation, relevance of answers and time needed to answer the questions depending on the data entry method (i.e. app Ana versus paper-based questionnaire). A randomised trial was performed with 26 students of music therapy. The results show that the chatbot is more motivating and answers are given faster than on paper. No differences in answer relevance could be determined between the two means. We conclude that a chatbot could become an additional data entry method for collecting personal health information.

Barriers to patient, provider, and caregiver adoption and use of electronic personal health records in chronic care: a systematic review.

BACKGROUND: Electronic personal health records (ePHRs) are defined as electronic applications through which individuals can access, manage, and share health information in a private, secure, and confidential environment. Existing evidence shows their benefits in improving outcomes, especially for chronic disease patients. However, their use has not been as widespread as expected partly due to barriers faced in their adoption and use. We aimed to identify the types of barriers to a patient, provider, and caregiver adoption/use of ePHRs and to analyze their extent in chronic disease care. METHODS: A systematic search in Medline, PubMed, Science Direct, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, and the Institute of Electrical and Electronics Engineers (IEEE) database was performed to find original studies assessing barriers to ePHR adoption/use in chronic care until the end of 2018. Two researchers independently screened and extracted data. We used the PHR adoption model and the Unified Theory of Acceptance and Use of Technology to analyze the results. The Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of evidence in the included studies. RESULTS: Sixty publications met our inclusion criteria. Issues found hindering ePHR adoption/use in chronic disease care were associated with demographic factors (e.g., patient age and gender) along with key variables related to health status, computer literacy, preferences for direct communication, and patient's strategy for coping with a chronic condition; as well as factors related to medical practice/environment (e.g., providers' lack of interest or resistance to adopting ePHRs due to workload, lack of reimbursement, and lack of user training); technological (e.g., concerns over privacy and security, interoperability with electronic health record systems, and lack of customized features for chronic conditions); and chronic disease characteristics (e.g., multiplicities of co-morbid conditions, settings, and providers involved in chronic care). CONCLUSIONS: ePHRs can be meaningfully used in chronic disease care if they are implemented as a component of comprehensive care models specifically developed for this care. Our results provide insight into hurdles and barriers mitigating ePHR adoption/use in chronic disease care. A deeper understating of the interplay between these barriers will provide opportunities that can lead to an enhanced ePHR adoption/use.

Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study.

BACKGROUND: As a counter-cluster measure to prevent the spread of the infectious novel coronavirus disease (COVID-19), an efficient system for health observation outside the hospital is urgently required. Personal health records (PHRs) are suitable for the daily management of physical conditions. Importantly, there are no major differences between the items collected by daily health observation via PHR and the observation of items related to COVID-19. Until now, observations related to COVID-19 have been performed exclusively based on disease-specific items. Therefore, we hypothesize that PHRs would be suitable as a symptom-tracking tool for COVID-19. To this end, we integrated health observation items specific to COVID-19 with an existing PHR-based app. OBJECTIVE: This study is conducted as a proof-of-concept study in a real-world setting to develop a PHR-based COVID-19 symptom-tracking app and to demonstrate the practical use of health observations for COVID-19 using a smartphone or tablet app integrated with PHRs. METHODS: We applied the PHR-based health observation app within an active epidemiological investigation conducted by Wakayama City Public Health Center. At the public health center, a list is made of individuals who have been in close contact with known infected cases (health observers). Email addresses are used by the app when a health observer sends data to the public health center. Each health observer downloads the app and installs it on their smartphone. Self-observed health data are entered daily into the app. These data are then sent via the app by email at a designated time. Localized epidemiological officers can visualize the collected data using a spreadsheet macro and, thus, monitor the health condition of all health observers. RESULTS: We used the app as part of an active epidemiological investigation executed at a public health center. During the investigation, 72 close contacts were discovered. Among them, 57 had adopted the use of the health observation app. Before the introduction of the app, all health observers would have been interviewed by telephone, a slow process that took four epidemiological officers more than 2 hours. After the introduction of the app, a single epidemiological officer can carry out health observations. The app was distributed for free beginning in early March, and by mid-May, it had been used by more than 20,280 users and 400 facilities and organizations across Japan. Currently, health observation of COVID-19 is socially recognized and has become one of the requirements for resuming social activities. CONCLUSIONS: Health observation by PHRs for the purpose of improving health management can also be effectively applied as a measure against large-scale infectious diseases. Individual habits of improving awareness of personal health and the use of PHRs for daily health management are powerful armaments against the rapid spread of infectious diseases. Ultimately, similar actions may help to prevent the spread of COVID-19.

Evaluating the implementation of a personal health record for chronic primary and secondary care: a mixed methods approach.

BACKGROUND: Personal health records (PHRs) provide the opportunity for self-management support, enhancing communication between patients and caregivers, and maintaining and/or improving the quality of chronic disease management. Their implementation is a multi-level and complex process, requiring a holistic approach that takes into account the technology, its users and the context of implementation. The aim of this research is to evaluate the fidelity of a PHR in chronic care (the degree to which it was implemented as intended) in order to explain the found effects. METHODS: A convergent parallel mixed methods design was used, where qualitative and quantitative data were collected in parallel, analyzed separately, and finally merged. Log data of 536 users were used to gain insight into the actual long-term use of the PHR (the dose). Focus group meetings among caregivers (n = 13) were conducted to assess program differentiation (or intended use). Interviews with caregivers (n = 28) and usability tests with potential end-users (n = 13) of the PHR were used to understand the responsiveness and the differences and similarities between the intended and actual use of the PHR. RESULTS: The results of the focus groups showed that services for coaching are strongly associated with monitoring health values and education. However, the PHR was not used that way during the study period. In the interviews, caregivers indicated that they were ignorant on how to deploy the PHR in current working routines. Therefore, they find it difficult to motivate their patients in using the PHR. Participants in the usability study indicate that they would value a PHR in the future, given that the usability will be improved and that the caregivers will use it in daily practice as well. CONCLUSIONS: In this study, actual use of the PHRs by patients was influenced by the responsiveness of caregivers. This responsiveness is likely to be strongly influenced by the perceived support when defining the differentiation and delivery of the PHR. A mixed-methods approach to understand intervention fidelity was of added value in providing explanations for the found effects that could not be revealed by solely focusing on the effectiveness of the technology in an experimental trial.

Development of a techno-humanist model for e-health adoption of innovative technology.

BACKGROUND AND PURPOSE: After investing billions of dollars in an integrated Electronic Medical Records (physicians) and Personal Health Records (patients) system to allow both parties to manage and communicate through e-health innovative technologies, Canada is still making slow adoption progress. In an attempt to bridge the human and technological perspectives by developing and testing a holistic model, this study purports to predict patients' behavioral intentions to use e-health applications. METHODS: An interdisciplinary approach labelled as a techno-humanism model (THM) is testing twelve constructs identified from the technological, sociological, psychological, and organizational research literature and deemed to have a significant effect upon and positive relationship with patients' e-health applications adoption. Subjects were Canadians recruited in a mall-intercept mode from a region representing a demographically diverse population, including rural and urban residents. The SmartPLS measurement tool was used to evaluate the reliability and validity of study constructs. The twelve constructs were separately tested with quantitative data such as factor analysis, single, multiple, and hierarchical multiple regression. RESULTS: The hierarchical multiple regression analysis process led us to formulate four models, each hinged on a combination of interdisciplinary variables. Model 1 consisted of the technological predictors and explained 62.3% (p < .001) of variance in the behavioral intention to use e-health. Model 2 added the sociological predictors to the equation and explained 72.3% (p < .001) of variance. Model 3 added the psychological predictors to Model 2 and explained 72.8% (p < .001). Finally, Model 4 included all twelve predictors and explained 73% (p < .001) of variance in the behavioral intention to use e-health applications. CONCLUSIONS: One of the greatest barriers to applying e-health records in Canada resides in the lack of coordination among stakeholders. The present study implies that healthcare policy makers must consider the twelve variables with their findings and implications as a whole. The techno-humanist model (THM) we are proposing is a more holistic and continuous approach. It pushes back to a breakdown of the various technological, sociological, psychological, and managerial factors and stakeholders that are at the root cause of behavioral intentions to use e-health, as opposed to merely observing behavioral outcomes at the end of the "assembly line". Active participation and coordination of all stakeholders is a key feature.

Making it work for me: beliefs about making a personal health record relevant and useable.

BACKGROUND: A Personal Health Record (PHR) is an electronic record that individuals use to manage and share their health information, e.g. data from their medical records and data collected by apps. However, engagement with their record can be low if people do not find it beneficial to their health, wellbeing or interactions with health and other services. We have explored the beliefs potential users have about a PHR, how it could be made personally relevant, and barriers to its use. METHODS: A qualitative design comprising eight focus groups, each with 6-8 participants. Groups included adults with long-term health conditions, young people, physically active adults, data experts, and members of the voluntary sector. Each group lasted 60-90 min, was audio recorded and transcribed verbatim. We analysed the data using thematic analysis to address the question "What are people's beliefs about making a Personal Health Record have relevance and impact?" RESULTS: We found four themes. Making it work for me is about how to encourage individuals to actively engage with their PHR. I control my information is about individuals deciding what to share and who to share it with. My concerns is about individuals' concerns about information security and if and how their information will be acted upon. Potential impact shows the potential benefits of a PHR such as increasing self-efficacy, uptake of health-protective behaviours, and professionals taking a more holistic approach to providing care and facilitating behaviour change. CONCLUSIONS: Our research shows the functionality that a PHR requires in order for people to engage with it. Interactive functions and integration with lifestyle and health apps are particularly important. A PHR could increase the effectiveness of behaviour change apps by specifying evidence-based behaviour change techniques that apps should incorporate. A PHR has the potential to increase health-protective behaviours and facilitate a more person-driven health and social care system. It could support patients to take responsibility for self-managing their health and treatment regimens, as well as helping patients to play a more active role when care transfers across boundaries of responsibility.

Cost savings through implementation of an integrated home-based record: a case study in Vietnam.

OBJECTIVES: In Vietnam, there are three major home-based records (HBRs) for maternal and child health (MCH) that have been already nationally scaled up, i.e., Maternal and Child Health Handbook (MCH Handbook), Child Vaccination Handbook, and Child Growth Monitoring Chart. The MCH Handbook covers all the essential recording items that are included in the other two. This overlapping of recording items between the HBRs is likely to result in inefficient use of both financial and human resources. This study is aimed at estimating the magnitude of cost savings that are expected to be realized through implementing exclusively the MCH Handbook by terminating the other two. STUDY DESIGN: Secondary data collection and analyses on HBR production and distribution costs and health workers' opportunity costs. METHODS: Through multiplying the unit costs by their respective quantity multipliers, recurrent costs of operations of three HBRs were estimated. Moreover, magnitude of cost savings likely to be realized was estimated, by calculating recurrent costs overlapping between the three HBRs. RESULTS: It was estimated that implementing exclusively the MCH Handbook would lead to cost savings of United States dollar 3.01 million per annum. The amount estimated is minimum cost savings because only recurrent cost elements (HBR production and distribution costs and health workers' opportunity costs) were incorporated into the estimation. Further indirect cost savings could be expected through reductions in health expenditures, as the use of the MCH Handbook would contribute to prevention of maternal and child illnesses by increasing antenatal care visits and breastfeeding practices. CONCLUSION: To avoid wasting financial and human resources, the MCH Handbook should be exclusively implemented by abolishing the other two HBRs. This study is globally an initial attempt to estimate cost savings to be realized through avoiding overlapping operations between multiple HBRs for MCH.

Bridging the digital divide: mobile access to personal health records among patients with diabetes.

OBJECTIVES: Some patients lack regular computer access and experience a digital divide that causes them to miss internet-based health innovations. The diffusion of smartphones has increased internet access across the socioeconomic spectrum, and increasing the channels through which patients can access their personal health records (PHRs) could help bridge the divide in PHR use. We examined PHR use through a computer-based Web browser or mobile device. STUDY DESIGN: Cross-sectional historical cohort analysis. METHODS: Among adult patients in the diabetes registry of an integrated healthcare delivery system, we studied the devices used to access their PHR during 2016. RESULTS: Among 267,208 patients with diabetes, 68.1% used the PHR in 2016; 60.6% of all log-ins were via computer and 39.4% were via mobile device. Overall, 63.9% used it from both a computer and mobile device, 29.6% used only a computer, and 6.5% used only a mobile device. After adjustment, patients who were black, Hispanic, or Asian; lived in lower socioeconomic status (SES) neighborhoods; or had lower engagement were all significantly more likely to use the PHR only from a mobile device (P <.05). Patients using the PHR only via mobile device used it less frequently. CONCLUSIONS: Mobile-ready PHRs may increase access among patients facing a digital divide in computer use, disproportionately reaching racial/ethnic minorities and lower SES patients. Nonetheless, even with a mobile-optimized and app-accessible PHR, differences in PHR use by race/ethnicity and SES remain. Continued efforts are needed to increase equitable access to PHRs among patients with chronic conditions.

Understanding Older Adult Use of Data Visualizations as a Resource for Maintaining Health and Wellness.

To better understand how older adults use health visualizations and the potential barriers that impact utility, we conducted semistructured interviews with 21 older adults. Within these sessions, we presented participants with two interactive visualizations for exploration. Through an affinity mapping exercise, we extracted five key themes associated with how older adults utilize health visualizations and provide corresponding recommendations as points of consideration for designers developing older adult focused health visualizations. By examining how older adults perceive the utility of health visualizations, we lay the groundwork for design choices that impact eventual use and adoption of systems that generate data for such visualizations.

Understanding views on everyday use of personal health information: Insights from community dwelling older adults.

BACKGROUND: Older adults apply various strategies to pursue healthy aging, but we know little about their views and use of personal health information to accomplish those ends. METHODS: As a first step in formulating the role of personal health information management (PHIM) in healthy aging, we explored the perspectives of older adults on health and health information used in their everyday lives through four focus groups with 25 community-dwelling adults aged 60 and over. RESULTS: We found that the concept of wellness-the holistic and multidimensional nature of health and wellbeing-plays prominently in how older adults think about health and health information. Participants expressed wellness from a position of personal strength, rather than health-related deficits, by focusing on wellness activities for staying healthy through: (1) personal health practices, (2) social network support, and (3) residential community engagement. CONCLUSION: Although these themes involve personal health information, existing PHIM systems that focus on disease management are generally not designed to support wellness activities. Substantial opportunity exists to fill this wellness support gap with innovative health information technology designed for older adults. Findings carry implications for the design of PHIM tools that support healthy aging and methods for engaging older adults as co-producers of this critical support.

Use of a child health surveillance instrument focusing on growth. A cross-sectional study

ABSTRACT BACKGROUND: Proper use of a child health handbook is an important indicator of the quality of care provided to children at healthcare services. This study aimed to evaluate the use of child health surveillance tool (by health professionals?), especially focusing on growth. DESIGN AND SETTING: Cross-sectional study carried out in the context of the Family Health Strategy in two municipalities in Paraíba, Brazil. METHODS: Three hundred and twenty-one children under five years of age from areas covered by health workers were included in the study. Mothers answered a questionnaire asking for information on sociodemographic characteristics. Growth charts, records of iron and vitamin A supplementation and notes on immunization schedules registered in the instrument were analyzed. In the case of children for whom the third version of the child health handbook was used, the association between completion of this handbook and sociodemographic characteristics was analyzed. RESULTS: All the parameters studied showed high frequencies of inadequate data entry, ranging from 41.1% for the weight-versus- age chart to 95.3% for the body mass index-versus-age chart. Higher frequency of inadequate data entry was found among children aged 25 months and over and among those living in areas of these municipalities with minimal numbers of professionals in the healthcare teams. CONCLUSIONS: The use of a child health handbook to monitor children's growth in the municipalities studied appeared to be faulty. Data entry to this instrument was better at locations with larger healthcare teams.

Use of a child health surveillance instrument focusing on growth. A cross-sectional study.

BACKGROUND: Proper use of a child health handbook is an important indicator of the quality of care provided to children at healthcare services. This study aimed to evaluate the use of child health surveillance tool (by health professionals?), especially focusing on growth. DESIGN AND SETTING: Cross-sectional study carried out in the context of the Family Health Strategy in two municipalities in Paraíba, Brazil. METHODS: Three hundred and twenty-one children under five years of age from areas covered by health workers were included in the study. Mothers answered a questionnaire asking for information on sociodemographic characteristics. Growth charts, records of iron and vitamin A supplementation and notes on immunization schedules registered in the instrument were analyzed. In the case of children for whom the third version of the child health handbook was used, the association between completion of this handbook and sociodemographic characteristics was analyzed. RESULTS: All the parameters studied showed high frequencies of inadequate data entry, ranging from 41.1% for the weight-versus- age chart to 95.3% for the body mass index-versus-age chart. Higher frequency of inadequate data entry was found among children aged 25 months and over and among those living in areas of these municipalities with minimal numbers of professionals in the healthcare teams. CONCLUSIONS: The use of a child health handbook to monitor children's growth in the municipalities studied appeared to be faulty. Data entry to this instrument was better at locations with larger healthcare teams.

Longitudinal Study-Based Dementia Prediction for Public Health.

The issue of public health in Korea has attracted significant attention given the aging of the country's population, which has created many types of social problems. The approach proposed in this article aims to address dementia, one of the most significant symptoms of aging and a public health care issue in Korea. The Korean National Health Insurance Service Senior Cohort Database contains personal medical data of every citizen in Korea. There are many different medical history patterns between individuals with dementia and normal controls. The approach used in this study involved examination of personal medical history features from personal disease history, sociodemographic data, and personal health examinations to develop a prediction model. The prediction model used a support-vector machine learning technique to perform a 10-fold cross-validation analysis. The experimental results demonstrated promising performance (80.9% F-measure). The proposed approach supported the significant influence of personal medical history features during an optimal observation period. It is anticipated that a biomedical "big data"-based disease prediction model may assist the diagnosis of any disease more correctly.