Personal Health Records Research Articles

Impact of encounters on patient app use: results of a tethered mobile personal health record usage pattern analysis

Impact of encounters on patient app use: results of a tethered mobile personal health record usage pattern analysis

The outcomes of electronic personal health records in patients with heart failure or coronary artery disease.

There are limited data on the efficacy of smartphone-based personal health records (PHRs) in patients with cardiovascular disease. This study aimed to examine the processes, outcomes and challenges associated with the implementation of integrated PHRs in patients with heart failure (HF) or coronary artery disease (CAD). This prospective single-group study evaluated the effects of a PHR system with the capability to capture electronic health records and vital signs in patients with HF or CAD. The outcomes measured were the 6-month changes in blood pressure (BP), body weight (BW), brain natriuretic peptide (BNP) levels, lipid profiles and haemoglobin (Hb) A1c levels. Between June 2021 and March 2022, we enrolled 111 patients (median age: 61years and 47% women) with CAD and/or HF. Over 6months, the PHR review count distribution was skewed: median 749 times (lowest 2, highest 5724)/180days, suggesting both low and excessive PHR users. After 3days, 23% of the patients discontinued inputting their vital signs and medication status. At 6months, compared with patients who discontinued, those who continued to input their vital signs (N=86) showed a significant decrease in their systolic BP and LDL-C levels but not in the diastolic BP, BW, BNP, HDL-C, triglyceride or HbA1c levels. The implementation of smartphone-based PHRs in daily practice is challenging for patients with HF or CAD. However, we observed positive indications of the benefits of PHR in these patients. UMIN000044369.

Systematic review of ethics and legislation of a Global Patient co-Owned Cloud (GPOC)

Background The use of cloud-based storage for personal health records (PHRs) has significantly increased globally over the past thirty years. The four recently published GPOC Series articles introduced the concept of a Global Patient co-Owned Cloud (GPOC) for personal health records. The series includes a systematic review and meta-analysis, a summit, a sandbox, and a survey, with 100% participation from UN member states and key international health organisations. GPOC aims to establish patient co-ownership of PHRs, addressing integration and access challenges. Methods This study is built upon the published GPOC systematic review and meta-analysis that focused on examining cloud-based personal health records and elements such as data security, efficiency, performance, privacy and cost-based factors. However, this study selectively reviews the ethical, legislative and potential human rights dimensions of GPOC. Thus, it includes ethical aspects of co-ownership, rights, privacy, policies, and AI integration. The original study was PROSPERO registered with CRD42022342597, which serves as the foundation for the current study. Results This study offers a comprehensive global overview of ethics, legislation and initiatives by states and organisations. We analyse AI integration and future challenges for GPOC implementation. We present principles from ‘Ethics by Design’ and the ‘Principles of Biomedical Ethics’ by Beauchamp and Childress alongside the European General Data Protection Regulation (GDPR). The study presents a global overview of the relevant global latticework of legislation. Conclusions This study suggests that GPOC could potentially establish a new human right to patient co-ownership of personal health information. GPOC aims to facilitate global AI integration in healthcare and address existing challenges in PHR integration. A decentralised GPOC, supported by blockchain consensus, may offer benefits such as enhanced data security, interoperability, and equitable access to healthcare information globally. Thus, GPOC may have a positive impact on global health.

Automated anonymization of radiology reports: comparison of publicly available natural language processing and large language models.

Medical reports, governed by HIPAA regulations, contain personal health information (PHI), restricting secondary data use. Utilizing natural language processing (NLP) and large language models (LLM), we sought to employ publicly available methods to automatically anonymize PHI in free-text radiology reports. We compared two publicly available rule-based NLP models (spaCy; NLPac, accuracy-optimized; NLPsp, speed-optimized; iteratively improved on 400 free-text CT-reports (test set)) and one offline LLM approach (LLM-model, LLaMa-2, Meta-AI) for PHI-anonymization. The three models were tested on 100 randomly selected chest CT reports. Two investigators assessed the anonymization of occurring PHI entities and whether clinical information was removed. Subsequently, precision, recall, and F1 scores were calculated. NLPac and NLPsp successfully removed all instances of dates (n = 333), medical record numbers (MRN) (n = 6), and accession numbers (ACC) (n = 92). The LLM model removed all MRNs, 96% of ACCs, and 32% of dates. NLPac was most consistent with a perfect F1-score of 1.00, followed by NLPsp with lower precision (0.86) and F1-score (0.92) for dates. The LLM model had perfect precision for MRNs, ACCs, and dates but the lowest recall for ACC (0.96) and dates (0.52), corresponding F1 scores of 0.98 and 0.68, respectively. Names were removed completely or majorly (i.e., one first or family name non-anonymized) in 100% (NLPac), 72% (NLPsp), and 90% (LLM-model). Importantly, NLPac and NLPsp did not remove medical information, while the LLM model did in 10% (n = 10). Pre-trained NLP models can effectively anonymize free-text radiology reports, while anonymization with the LLM model is more prone to deleting medical information. Question This study compares NLP and locally hosted LLM techniques to ensure PHI anonymization without losing clinical information. Findings Pre-trained NLP models effectively anonymized radiology reports without removing clinical data, while a locally hosted LLM was less reliable, risking the loss of important information. Clinical relevance Fast, reliable, automated anonymization of PHI from radiology reports enables HIPAA-compliant secondary use, facilitating advanced applications like LLM-driven radiology analysis while ensuring ethical handling of sensitive patient data.

DocBot AI as Your Personal Health Assistant: Bridging the Gap in Consultations Revolutionizing Healthcare Using Natural Language Processing and Artificial Intelligence

The DocBot Chat Bot/AI system is a novel solution to the challenge of acquiring accurate and personalized health information. By utilizing cutting-edge artificial intelligence (AI) algorithms and natural language processing (NLP) methods, the DocBot system creates an engaging and intuitive interface that lets people convey their health concerns and get personalized advice. This study provides an in-depth assessment of the DocBot system, stressing its key features, AI algorithms, advantages, difficulties, and potential applications. To improve healthcare communication and encourage well-informed decision-making, it is important to highlight DocBot's transformative potential in providing users with accurate and trustworthy health knowledge.

A Personal Health Record for patients with multiple sclerosis: A 2-year evaluation study

Abstract Background Multiple sclerosis (MS) is a chronic disease impacting the central nervous system, affecting 2.8 million people worldwide. Effective self-management is crucial for treating chronic diseases, including MS. Personal health records (PHRs) show promise in supporting self-management, potentially empowering patients and enhancing their engagement in treatment and health. However, implementation challenges persist. Objectives This study aimed to) assess the feasibility and usability of the PHR according to patients and healthcare professionals (HCPs), and 2) evaluate implementation determinants, and exploring preliminary effects on a range of outcomes related to the quality, efficiency, and costs of care, as well as health-related outcomes. Methods A mixed-methods study was conducted in a Dutch hospital. Quantitative data from 80 patients and 12 HCPs were collected via questionnaires at baseline (T0), after one (T1) and 2 years (T2). Focus group interview were conducted at T2 with 7 patients and 4 HCPs. Results Most patients never logged in during the first year and logged in a couple of times during the second year, with 15 minutes per log-in session. The HCPs mainly logged in a couple of times per year, averaging six minutes per session. Patients’ and HCPs’ usability and satisfaction scores were below average and moderate respectively. Various facilitators and barriers were identified, including knowledge gaps, staff capacity issues, and ICT obstacles. No significant differences were found in preliminary effects. Qualitative data highlighted benefits in terms of gaining insight into health data but revealed challenges with log-in issues and information retrieval. Conclusions Implementation challenges hindered PHR adoption. The evolving nature of PHRs requires ongoing evaluation and adaptation to optimize their potential benefits. Utilizing a participatory design approach and a dedicated implementation team could enhance adoption and maximize benefits. Key messages • A personal health record (PHR) for patients with MS was evaluated within the care setting of a Dutch hospital, demonstrating limited usability and moderate satisfaction. • Diverse obstacles impeded the adoption and uptake of the PHR, but potential solutions lie in continuous development with a participatory design approach and dedicated implementation team.

Minimum Dataset of Lung Cancer Patients: An Initial Step Towards Developing a Web-Based Personal Health Record

Background: Personal Health Records (PHR), which utilize advanced health information technology tools, play a crucial role in patient self-management and improving the control of chronic diseases such as lung cancer. To optimize the design of these systems, it is essential to determine the necessary data elements. Objectives: This study aims to identify the minimum dataset required for designing a web-based PHR for lung cancer patients. Methods: This descriptive, cross-sectional research was conducted in 2023. Initially, a lung cancer dataset was extracted through text analysis. In the next phase, a proposed minimum lung cancer dataset was formulated into a questionnaire containing 18 data groups, including 126 data elements. The dataset underwent expert validation in two phases using the Delphi technique. Data analysis was performed using SPSS version 26, with descriptive statistics employed. Results: The minimum web-based PHR dataset for lung cancer patients, consisting of 18 data groups (112 data elements), includes demographics, insurance information, emergency contact details, patient symptoms, tumor-related data, physician details, treatment information, patient-reported measurements, personal medical history, history of procedures and surgeries, visits, allergies, family history, medication information, test results, imaging data, dietary information, and educational materials. Conclusions: Based on the study findings, it is recommended that lung cancer data management encompass not only routine information but also additional dimensions such as allergies, tumor-related information, and dietary details. Collecting comprehensive and complete data can significantly enhance the treatment process and post-treatment follow-up.

Integrating an AI-powered symptom assessment application (SAA) in a hospital network in Portugal

Abstract Introduction Patients often struggle to understand medical information and healthcare worker shortage strains health systems. Integrating SAAs that guide patients and provide diagnostic decision support (DDS) to doctors can help. This study evaluates the impact of the SAA ‘Ada’, a class IIa medical device, after its integration into the patient portal of a Portuguese hospital network, CUF, on clinical workflow and patient health. Methods This on-going post-market quality improvement study, started in Nov 2023 and has enrolled 664 participants. Participating doctors complete a baseline survey. Consenting patients conduct symptom assessments and answer survey questions within the app. The patient’s symptom report is shared with their physician, who then completes a post-consultation survey. Results After using Ada, 86% of patients could enter all their symptoms, 79% felt more prepared for their consultation, and 39% felt less health anxiety (N = 664). In the baseline survey, most doctors utilize online resources (96%) in the absence of a symptom checker, followed by discussions with colleagues (65%) for challenging cases (N = 26). In the post-consultation survey, 95% of doctors found Ada’s condition suggestions reasonable, with only 10% disagreeing with its triage classification. Doctors reported time saving and increased consultation efficiency (64%), and 59% felt more confidence in their diagnosis. A majority said that Ada provided them with additional information about patients (77%). Ada also improved consultation efficiency (74%), preparation (78%), patient engagement (82%), and health knowledge (77%; N = 22). Conclusions By providing personalized health information, Ada prepares patients for their consultation, resulting in improved patient engagement and facilitation of clinical conversation. Incorporating a SAA into routine patient care enhances quality of consultation, reduces consultation time, increases efficiency, and provides DDS to doctors. Key messages • Digital health enhances patient engagement, clinical efficiency, and diagnostic decision support for doctors in healthcare settings. • Ada’s personalized health information empowers patients, improves consultations, and reduces health-related anxiety.

Exploring Electronic Personal Health Record usage in Northern Italy: a cross-sectional study

Abstract Background The Electronic Personal Health Record (EPHR) is a patient-centered tool that enables citizens to manage their health information. The EPHR has been implemented worldwide, including in Italy, and holds immense potential, but it has shown a generalized underutilisation. Therefore, this paper aims to identify its fulfillment and the reasons behind its poor use, potentially uncovering the key to unlocking its benefits. Methods A survey was distributed on social media and in the waiting rooms of vaccination facilities in a Region of Italy. Multivariable regression models were conducted to detect a connection between the general population’s usage of the EPHR and specific independent variables. Results Of the 1634 respondents, 710 activated the EPHR, especially women, Italians, highly educated, unemployed, with good health but affected with chronic diseases. Amongst those who activated the EPHR, the multivariate analysis showed that the number of accesses to the platform was significantly associated with lower age (adjusted Odds Ratio (adjOR) 0.96 p = 0.015), higher level of education (adjOR 2.17 p = 0.029), unemployment (adjOR 5.61 p = 0.008) and considering the information on the EPHR complete (adjOR 3.83 p = 0.001). As age increases, the perceived ease of access to the EPHR decreases (adjOR=0.98 p = 0.049). Having a higher level of education (adjOR=0.41 p = 0.042), autonomy in reading health materials (adjOR=0.32 p = 0.043), and less self-confidence in filling out medical forms (adjOR=0.61 p = 0.033) were linked to a decrease in perceived ease of access. Conclusions The study showed that the EPHR is more utilised by specific categories of citizens, especially the young and those with higher education. More efforts should be made to increase access to the EPHR for the whole community by making it more intuitive and user-friendly. The present study provides valuable foundations to foster the implementation of a platform for sharing health data at a European level. Key messages • The Electronic Personal Health Record (EPHR) is underutilised despite its potential; it’s mainly accessed by young and highly educated individuals. • Efforts to increase EPHR usage must focus on improving accessibility and ease of access, as well as enhancing user confidence and autonomy in managing health information.

Advancing immunisation information systems: a proposal for the “unvaccinated registry”

Abstract Through a systematic review of 253 studies, we identified significant advancements in IIS functionalities including real-time data access, interoperability, and life-course vaccination records, crucial for robust public health responses. Our review reveals that vaccinations are vital for public health and societal welfare; however, vaccine hesitancy is a significant barrier, driven by complex factors. Most IIS implementations predominantly utilise web-based platforms focused on children’s vaccinations with features that enhance data interoperability and public health surveillance. Despite these advancements, gaps in vaccine coverage and hesitancy mapping persist due to suboptimal data integration and system interoperability. Parallelly, we propose a comprehensive registry that includes unvaccinated individuals, aiming to address vaccine hesitancy by integrating demographic and socio-economic data. This initiative promises to enhance health equity by providing actionable insights into vaccination gaps and facilitating targeted interventions. Ethical considerations, particularly data privacy, are paramount, as well as adhering to regulations such as GDPR to ensure the protection of personal health information. The integration of IIS with a registry that includes unvaccinated populations represents a transformative approach to public health, potentially increasing vaccine coverage and effectively informing policy decisions. This dual strategy leverages not only technological advancements but also incorporates essential behavioural insights, offering a path forward in the ongoing battle against vaccine-preventable diseases. This model aligns with the Italian National Vaccination Prevention Plan and underscores proactive, evidence-based strategies to enhance vaccination uptake, serving as a cornerstone for broader application in other national contexts.

Caregiver and Youth Characteristics That Influence Trust in Digital Health Platforms in Pediatric Care: Mixed Methods Study.

Combining patient-generated health data and digital health platforms may improve patient experience and population health, mitigate rising health care costs, reduce clinician burnout, and enable health equity. However, lack of trust may be a notable barrier to the data-sharing required by such platforms. Understanding sociodemographic, health, and personal characteristics will enable developers and implementers of such technologies to consider these in their technical design requirements. This study aims to understand relationships between sociodemographic characteristics of caregivers of children or adolescents and trust in and willingness to use digital platforms to store and share personal health information for clinical care and research. This study used a mixed methods approach, including surveys of caregivers of youth aged <18 years living in Canada or the United States and youth aged 16 to 17 years living in Canada, as well as web-based bulletin board discussions to further explore topics of trust in data sharing. Sociodemographic and survey data were tabulated and explored using proportional odds ordinal regression models. Comments from web-based group discussions were analyzed thematically using a coding approach to identify issues important to the participants. Survey data from 1128 caregivers (female participants: n=549, 48.7%; 36-50 years old: n=660, 58.5%; Canadian: n=603, 53.5%; urban population: n=494, 43.8%) were collected, of which 685 (60.7%) completed all questions. Data from 173 youth (female participants: n=73, 42.2%; urban population: n=94, 54.3%) were collected, of which 129 (74.6%) completed all questions, and data were available for analysis. Furthermore, among 40 participants, 23 (58%) caregivers contributed to the web-based discussion boards. Related to trust, living in a rural area (vs urban; odds ratio [OR] 0.66, 95% CI 0.46-0.95) resulted in lower concern for data privacy and security, while having an undergraduate (OR 1.82, 95% CI 1.30-2.55) or graduate degree (vs secondary or trade school; OR 2.50, 95% CI 1.68-3.73) resulted in higher levels of concern. Living with a chronic disease (OR 1.81, 95% CI 1.35-2.44) increased levels of concern regarding data privacy and security. Interestingly, those with chronic disease were more willing to use digital platforms for clinical care and share personal health information for not-for-profit research. Caregivers were most concerned about data breaches involving data from their children but also highlighted that digital platforms would allow for better coordination of care for their children. Our research confirms the willingness of caregivers and youth to use digital platforms for both clinical care delivery and research and suggests that the value of a digital platform may outweigh the risks of its use. Engagement of end users in co-designing such platforms has the potential to enhance digital trust. However, digital trust varies across sociodemographic groups; therefore, diverse end user engagement is necessary when designing digital applications.

Sociodemographic Factors Associated with the Utilization of Digital Health Technologies Among Informal Caregivers: A Nationwide Study in the USA, 2022.

Informal caregivers can leverage digital health technologies to support their own health while also assisting patients, particularly those with mental or physical challenges. This study investigated the sociodemographic factors associated with the use of digital health technology among informal caregivers. Data from the 2022 Health Information National Trends Survey (HINTS) were examined for this cross-sectional study. The survey identified key outcomes related to the use of online medical records, health apps, digital wearable health devices, and the digital sharing of health information with professionals, on social media, or with others facing similar health issues. Sociodemographic factors (gender, race/ethnicity, feelings of one's household income, education, and census division) were also analyzed. Weighted multivariable logistic regression models were employed. A total of 831 individuals were included, representing about 36,960,385 national informal caregivers in 2022. Caregivers with a high school education or less (vs. those with at least some college education) and non-Hispanic Black caregivers (vs. non-Hispanic White caregivers) were significantly less likely to be offered access to online medical records by their healthcare providers. Additionally, online medical record usage was lower among caregivers with high school education or less, but higher among caregivers aged 50-64 (vs. those aged 35-49). Caregivers with a high school education or less were less likely to use health apps and digital wearable health devices, but more likely to share personal health information on social media. Men caregivers, those aged 50-64 and over 65 (vs. the 35-49 age group), and caregivers who were dissatisfied with their income were less likely to use digital wearable health devices. The findings underscore disparities in the utilization of caregivers' digital health technology, particularly in digital wearable health devices. Recognizing and addressing these disparities are crucial for tailoring interventions to enhance equitable access to digital health technology among diverse informal caregiver populations.

The Evolution of Health Information Technology for Enhanced Patient-Centric Care in the United States: Data-Driven Descriptive Study.

Health information technology (health IT) has revolutionized health care in the United States through interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and electronic patient access to health information. This study aims to examine progress in health IT adoption and its alignment with the Office of the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT (ASTP's) mission to enhance health care through data access and exchange. This study leverages data on end users of health IT to capture trends in engagement in interoperable clinical care data exchange (ability to find, send, receive, and integrate information from outside organizations), e-prescribing, electronic public health reporting, and capabilities to enable patient access to electronic health information. Data were primarily sourced from the American Hospital Association Annual Survey IT Supplement (2008 to 2023), Surescripts e-prescribing use data (2008 to 2023), the National Cancer Institute's Health Information National Trends Survey (2014 to 2022), and the National Center for Health Statistics' National Electronic Health Records Survey (2009 to 2023). Since 2009, there has been a 10-fold increase in electronic health record (EHR) use among hospitals and a 5-fold increase among physicians. This enabled the interoperable exchange of electronic health information, e- prescribing, electronic public health data exchange, and the means for patients and their caregivers to access crucial personal health information digitally. As of 2023, 70% of hospitals are interoperable, with many providers integrated within EHR systems. Nearly all pharmacies and 92% of prescribers possess e-prescribing capabilities, an 85%-point increase since 2008. In 2013, 40% of hospitals and one-third of physicians allowed patients to view their online medical records. Patient access has improved, with 97% of hospitals and 65% of physicians possessing EHRs that enable patients to access their online medical records. As of 2022, three-fourths of individuals report being offered access to patient portals, and over half (57%) report engaging with their health information through their patient portal. Electronic public health reporting has also seen an increase, with most hospitals and physicians actively engaged in key reporting types. Federal incentives have contributed to the widespread adoption of EHRs and broad digitization in health care, while efforts to promote interoperability have encouraged collaboration across health care entities. As a result, interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and patient access to health information have grown substantially over the past quarter century and have been shown to improve health care outcomes. However, interoperability hurdles, usability issues, data security concerns, and inequitable patient access persist. Addressing these issues will require collaborative efforts among stakeholders to promote data standardization, implement governance structures, and establish robust health information exchange networks.

Does telemedicine hold the key for reproductive health care? A quantitative examination of women's intentions toward use and accurate information disclosure.

To investigate women's perceptions of telemedicine for reproductive health care services, focusing on how perceived benefits and privacy risks influence their intentions to adopt telemedicine and their willingness to disclose personal health information. A cross-sectional survey was conducted. The study applied the privacy calculus theory to the context of telemedicine for reproductive health, using adapted, validated variables to develop the survey. Outcome variables included intentions to adopt telemedicine and willingness to disclose accurate personal health information. Data were collected in May and June 2023 using Qualtrics online panel services, targeting women across the United States who had not used telemedicine for reproductive health. The sample comprised 847 women aged 18 and older. Structural equation modeling was employed using AMOS v28.0 to test the hypothesized relationships between perceived benefits, perceived risks, and adoption intentions. The analysis controlled for age, household income, political affiliation, religious views, and prior births. Perceived benefits were positively related to intention to adopt telemedicine for reproductive care (β: 0.600, p < 0.001), and willingness to disclose accurate personal health information (β: 0.453, p < 0.001). Unexpectedly, perceived privacy risks were positively related to adoption intentions (β: 0.128, p < 0.001), but negatively related to willingness to disclose (β: -0.282, p < 0.001). Intentions to adopt were positively associated with willingness to disclose (β: 0.089, p < 0.05). Lastly, older women and women located in states with abortion restrictions expressed lower intentions to adopt. The model explained 40.2% of variance in intention to adopt and 38.3% of variance in willingness to disclose. The study demonstrates the importance of perceived benefits and privacy risks in driving telemedicine adoption and disclosure intentions among women in the reproductive health context. These findings suggest the need for targeted strategies to address privacy concerns and support telemedicine adoption, particularly in restrictive regulatory environments.

Sensitive personal health information, public trust, and biases in algorithmic decision-making: public health concerns in digital wellness.

Sensitive personal health information, public trust, and biases in algorithmic decision-making: public health concerns in digital wellness.

Cybersecurity Transformation: Cyber-Resilient IT Project Management Framework

In response to the escalating threats of cybersecurity attacks and breaches, ensuring the development and deployment of secure IT products has become paramount for organizations in their cybersecurity transformation. This work emphasizes the critical need for a comprehensive and secure IT project management life cycle that safeguards products from their initial development stages through decommissioning. The primary objective is to seamlessly integrate security considerations into every facet of IT project management life cycles. This work embraces a cyber-resilient IT project management framework and advocates the inclusion of cybersecurity measures in IT projects and their strategic, organized, continuous, and systematic integration throughout the entire product life cycle. It introduces a pioneering framework that harmonizes the cybersecurity risk management process with the IT project management life cycle. This framework delineates a methodical sequence of steps, each encompassing a distinct set of activities. The effectiveness and practical applicability of the proposed framework were validated through a comprehensive case study focused on the Personal Health Record (PHR) system. The PHR case study served as a real-world scenario to assess the framework’s ability to address cybersecurity challenges in a specific domain. The results of the experiment demonstrated the framework’s efficacy in enhancing the security posture of IT projects, showcasing its adaptability and scalability across diverse applications.

Cyber-Threat Landscape in Healthcare Industry and Legal Framework Governing Personal Health Information in India

Cyber-Threat Landscape in Healthcare Industry and Legal Framework Governing Personal Health Information in India

Decoding privacy concerns: the role of perceived risk and benefits in personal health data disclosure

BackgroundPersonal health data is crucial for effective medical care, personalized treatment, and health monitoring. It enables accurate diagnosis, efficient treatment plans, and informed healthcare decisions. Personal health data should be protected to ensure patient privacy, prevent misuse or unauthorized access, and maintain trust in healthcare systems, thereby safeguarding individuals’ sensitive information from potential harm or exploitation. Therefore, this study aimed to investigate whether perceived risk and perceived benefits have mediating roles in the relationships among individuals’ personal health information disclosure behaviour, perceived control, and privacy concerns.MethodThe population of the study consisted of individuals living in the provinces of Izmir, Konya and Adana. The sample of the study consisted of individuals who were reached through a convenience sampling method. The scales for privacy concerns, perceived control, perceived risk, perceived benefits and information disclosure behaviour were used in the study. Cronbach’s alpha and the AVE were calculated, and a confirmatory factor analysis was performed. A path analysis was performed using the structural equation model to test the hypotheses.ResultsThe analysis revealed a significant negative relationship between individuals’ personal health data disclosure behaviour and their privacy concerns. However, perceived risk and perceived benefit did not mediate this relationship. Additionally, a significant positive relationship was found between individuals’ behaviour of disclosing their perceived control and personal health data, with perceived risk and benefits playing a mediating role in this relationship.ConclusionThe study concluded that as individuals’ concerns about sharing personal health data increase, they are less likely to share these data. It was also found that perceived risk and perceived benefit mediate this relationship. Additionally, higher perceived risk intensifies privacy concerns, further discouraging data sharing, while perceived benefits can mitigate these concerns, promoting greater willingness to disclose health information.

Enhancing the Functionalities of Personal Health Record Systems: Empirical Study Based on the HL7 Personal Health Record System Functional Model Release 1.

The increasing demand for personal health record (PHR) systems is driven by individuals' desire to actively manage their health care. However, the limited functionality of current PHR systems has affected users' willingness to adopt them, leading to lower-than-expected usage rates. The HL7 (Health Level Seven) PHR System Functional Model (PHR-S FM) was proposed to address this issue, outlining all possible functionalities in PHR systems. Although the PHR-S FM provides a comprehensive theoretical framework, its practical effectiveness and applicability have not been fully explored. This study aimed to design and develop a tethered PHR prototype in accordance with the guidelines of the PHR-S FM. It sought to explore the feasibility of applying the PHR-S FM in PHR systems by comparing the prototype with the results of previous research. The PHR-S FM profile was defined to meet broad clinical data management requirements based on previous research. We designed and developed a PHR prototype as a web application using the Fast Healthcare Interoperability Resources R4 (FHIR) and Logical Observation Identifiers Names and Codes (LOINC) coding system for interoperability and data consistency. We validated the prototype using the Synthea dataset, which provided realistic synthetic medical records. In addition, we compared the results produced by the prototype with those of previous studies to evaluate the feasibility and implementation of the PHR-S FM framework. The PHR prototype was developed based on the PHR-S FM profile. We verified its functionality by demonstrating its ability to synchronize data with the FHIR server, effectively managing and displaying various health data types. Validation using the Synthea dataset confirmed the prototype's accuracy, achieving 100% coverage across 1157 data items. A comparison with the findings of previous studies indicated the feasibility of implementing the PHR-S FM and highlighted areas for future research and improvements. The results of this study offer valuable insights into the potential for practical application and broad adoption of the PHR-S FM in real-world health care settings.

Development of a minimum data set for a blockchain-based personal health records (PHRs), for patient/physician interaction in family medicine

BACKGROUND: The primary requirement for a capable patient health record (PHR) that can interact appropriately with the family medicine system and collect and share qualified data is a minimum data set (MDS) aligned with family medicine’s functions and goals. The aim of this research was to determine the MDS for a blockchain-based PHR system that can effectively interact with family medicine providers and collect and share qualified data. This MDS is intended to be applicable to all members of the community covered by family medicine. MATERIALS AND METHODS: This applied study was conducted in 2022 in a cross-sectional and descriptive approach in three phases. In the first phase, a content analysis related to the research objectives was conducted in scientific databases, search engines, and websites of the centers and scientific research organizations with publications and policy-making in this field. Consequently, 11 studies were selected for use in the second and third phases. In the second phase, to determine information needs, a researcher-developed questionnaire including 17 classes was given to 50 people under the cover of the family medicine plan in Shiraz city. By choosing one of the two options “Yes” or “No” by them, the necessary data classes were determined. In the third phase, the second researcher-developed questionnaire was designed and administered to 100 family physicians in Shiraz city. This questionnaire included the data elements corresponding to the data classes approved in the previous phase. The family physicians were asked to rate the importance of each data element using a Likert scale with five options, ranging from “very unimportant” to “very important.” The necessary data elements were determined based on these scores. RESULTS: In the first questionnaire, 16 of the 17 data classes received approval from individuals covered by the family medicine plan. Consequently, a questionnaire comprising 16 classes and 105 data elements was administered to the family physicians. Ultimately, the MDS was determined to include 16 classes and 72 data elements. CONCLUSIONS: Determining essential data elements, especially for patient/physician interaction in family medicine, should be such that they can be managed by the person while being comprehensive and providing sufficient help to the physician during the treatment process. This MDS can be used to interact with and refer PHRs to other physicians and specialists, as well as help interoperability between the PHR and other health systems, such as hospital information systems (HIS) and electronic health records (EHRs).