The Impacts of the Perceived Transparency of Privacy Policies and Trust in Providers for Building Trust in Health Information Exchange: Empirical Study

Innovative approaches in discussions of diabetes among healthcare sector actors in Germany

The dramatic growth in the rate of diabetes prompts serious debates about awareness, early diagnosis, and care interventions. This Viewpoint aims to explore, from the perspectives of healthcare sector representatives, what challenges and difficulties they face in dealing with diabetes and how these can be overcome. We applied the World Café method for group discussions, which enabled us to bring together 50 stakeholders. They identified challenges at institutional and structural levels under the concepts of awareness, digitalisation, and new forms of care and shared their suggestions for feasible solutions. We learned there is a need for a diabetes map of Germany to identify risk groups and that hybrid solutions should be implemented for treatment, care, prevention, and early diagnosis, considering digital infrastructure. Also, the demand for digital innovation in the healthcare system raised concerns about information transparency and data management.

Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review

BACKGROUND

International advances in information communication, eHealth, and other digital health technologies have led to significant expansions in the collection and analysis of personal health data. However, following a series of high-profile data sharing scandals and the emergence of COVID-19, critical exploration of public willingness to share personal health data remains limited, particularly for third-party or secondary uses.

OBJECTIVE

This systematic review aims to explore factors that affect public willingness to share personal health data for third-party or secondary uses.

METHODS

A systematic search of 6 databases (MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and SocINDEX) was conducted with review findings analyzed using inductive-thematic analysis and synthesized using a narrative approach.

RESULTS

Of the 13,949 papers identified, 135 were included. Factors most commonly identified as a barrier to data sharing from a public perspective included data privacy, security, and management concerns. Other factors found to influence willingness to share personal health data included the type of data being collected (ie, perceived sensitivity); the type of user requesting their data to be shared, including their perceived motivation, profit prioritization, and ability to directly impact patient care; trust in the data user, as well as in associated processes, often established through individual choice and control over what data are shared with whom, when, and for how long, supported by appropriate models of dynamic consent; the presence of a feedback loop; and clearly articulated benefits or issue relevance including valued incentivization and compensation at both an individual and collective or societal level.

CONCLUSIONS

There is general, yet conditional public support for sharing personal health data for third-party or secondary use. Clarity, transparency, and individual control over who has access to what data, when, and for how long are widely regarded as essential prerequisites for public data sharing support. Individual levels of control and choice need to operate within the auspices of assured data privacy and security processes, underpinned by dynamic and responsive models of consent that prioritize individual or collective benefits over and above commercial gain. Failure to understand, design, and refine data sharing approaches in response to changeable patient preferences will only jeopardize the tangible benefits of data sharing practices being fully realized.

Promoting TEFCA with Blockchain Technology: A Decentralized Approach to Patient-centered Healthcare Data Management

The Trusted Exchange Framework and Common Agreement (TEFCA) is a framework consisting of seven principles designed to create a secure and seamless health information exchange system across various healthcare settings. The ultimate goal of TEFCA is to facilitate public health surveillance, increase interoperability, promote data sharing, and ensure patient-centered healthcare data management. While the implementation of these principles is challenging, blockchain technology, with its unique features such as transparency, auditability, immutability, and anonymity, can provide a promising solution to the development of TEFCA. This article delves into the potential of blockchain technology to promote TEFCA design. By providing an immutable and transparent ledger, blockchain ensures data integrity, openness, and patient privacy. Overall, the use of blockchain technology can help address the challenges of implementing TEFCA principles and promote patient empowerment and control over their health data, improve data interoperability, and enhance healthcare quality.

Medical service quality evaluation based on LDA and sentiment analysis: Examples of seven chronic diseases

Objective

In this article, we investigate how chronic noncommunicable disease (CND) patients evaluate the medical service, and what obstacles exist in this process, which is useful for hospitals to improve efficiency and enhance patient satisfaction.

Methods

Based on the total number of CND patients in China, 7 CNDs were selected as the evaluation objects, and then selected the Haodaifu website as the data source, crawled 15,682 medical service reviews, then the 9 themes were analyzed by the LDA theme model. The evaluation index system of six indicators was constructed based on quality management theory. The binary long short-term memory model was used to analyze the sentiment, and the entropy-valued, TOPSIS and gray correlation model was implemented for medical service quality evaluation; the barrier model was used to find out the key factors limiting medical services.

Results

(a) Hypertension was rated at a good level in the degree of gray correlation closeness, bronchitis was rated at a low level and the rest were at an intermediate level. (b) The first two overall barriers were the hospitalization process and registration services which occupy about 30%, respectively. This implies that hospitals should focus on providing registration services and inpatient settings in the future.

Conclusion

To promote hospitals to provide better services for patients with CNDs and improve patient satisfaction with medical care. And it is necessary to optimize medical services fundamentally by optimizing the inpatient process and improving the registration process to improve efficiency.

Successes and Barriers of Health Information Exchange Participation Across Hospitals in South Carolina From 2014 to 2020: Longitudinal Observational Study

BACKGROUND

The 2009 Health Information Technology for Economic and Clinical Health Act sets three stages of Meaningful Use requirements for the electronic health records incentive program. Health information exchange (HIE) technologies are critical in the meaningful use of electronic health records to support patient care coordination. However, HIE use trends and barriers remain unclear across hospitals in South Carolina (SC), a state with the earliest HIE implementation.

OBJECTIVE

This study aims to explore changes in the proportion of HIE participation and factors associated with HIE participation, and barriers to exchange and interoperability across SC hospitals.

METHODS

This study derived data from a longitudinal data set of the 2014-2020 American Hospital Association Information Technology Supplement for 69 SC hospitals. The primary outcome was whether a hospital participated in HIE in a year. A cross-sectional multivariable logistic regression model, clustered at the hospital level and weighted by bed size, was used to identify factors associated with HIE participation. The second outcome was barriers to sending, receiving, or finding patient health information to or from other organizations or hospital systems. The frequency of hospitals reporting each barrier related to exchange and interoperability were then calculated.

RESULTS

Hospitals in SC have been increasingly participating in HIE, improving from 43% (24/56) in 2014 to 82% (54/66) in 2020. After controlling for other hospital factors, teaching hospitals (adjusted odds ratio [AOR] 3.7, 95% CI 1.0-13.3), system-affiliated hospitals (AOR 6.6, 95% CI 3.2-13.7), and rural referral hospitals (AOR 8.0, 95% CI 1.2-53.4) had higher odds to participate in HIE than their counterparts, whereas critical access hospitals (AOR 0.1, 95% CI 0.02-0.6) were less likely to participate in HIE than their counterparts reimbursed by the prospective payment system. Hospitals with greater ratios of Medicare or Medicaid inpatient days to total inpatient days also reported higher odds of HIE participation. Despite the majority of hospitals reporting HIE participation in 2020, barriers to exchange and interoperability remained, including lack of provider contacts (27/40, 68%), difficulty in finding patient health information (27/40, 68%), adapting different vendor platforms (26/40, 65%), difficulty matching or identifying same patients between systems (23/40, 58%), and providers that do not typically exchange patient data (23/40, 58%).

CONCLUSIONS

HIE participation has been widely adopted in SC hospitals. Our findings highlight the need to incentivize optimization of HIE and seamless information exchange by facilitating and implementing standardization of health information across various HIE systems and by addressing other technical issues, including providing providers' addresses and training HIE stakeholders to find relevant information. Policies and efforts should include more collaboration with vendors to reduce platform compatibility issues and more user engagement and technical training and support to facilitate effective, accurate, and efficient exchange of provider contacts and patient health information.

Trust and Health Information Exchanges: Qualitative Analysis of the Intent to Share Personal Health Information

BACKGROUND

Digital health has the potential to improve the quality of care, reduce health care costs, and increase patient satisfaction. Patient acceptance and consent are a prerequisite for effective sharing of personal health information (PHI) through health information exchanges (HIEs). Patients need to form and retain trust in the system(s) they use to leverage the full potential of digital health. Germany is at the forefront of approving digital treatment options with cost coverage through statutory health insurance. However, the German population has a high level of technology skepticism and a low level of trust, providing a good basis to illuminate various facets of eHealth trust formation.

OBJECTIVE

In a German setting, we aimed to answer the question, How does an individual form a behavioral intent to share PHI with an HIE platform? We discussed trust and informed consent through (1) synthesizing the main influence factor models into a complex model of trust in HIE, (2) providing initial validation of influence factors based on a qualitative study with patient interviews, and (3) developing a model of trust formation for digital health apps.

METHODS

We developed a complex model of the formation of trust and the intent to share PHI. We provided initial validation of the influence factors through 20 qualitative, semistructured interviews in the German health care setting and used a deductive coding approach to analyze the data.

RESULTS

We found that German patients show a positive intent to share their PHI with HIEs under certain conditions. These include (perceived) information security and a noncommercial organization as the recipient of the PHI. Technology experience, age, policy and regulation, and a disposition to trust play an important role in an individual's privacy concern, which, combined with social influence, affects trust formation on a cognitive and emotional level. We found a high level of cognitive trust in health care and noncommercial research institutions but distrust in commercial entities. We further found that in-person interactions with physicians increase trust in digital health apps and PHI sharing. Patients' emotional trust depends on disposition and social influences. To form their intent to share, patients undergo a privacy calculus. Hereby, the individual's benefit (eg, convenience), benefits for the individual's own health, and the benefits for public welfare often outweigh the perceived risks of sharing PHI.

CONCLUSIONS

With the higher demand for timely PHI, HIE providers will need to clearly communicate the benefits of their solutions and their information security measures to health care providers (physicians, nursing and administrative staff) and patients and include them as key partners to increase trust. Offering easy access and educational measures as well as the option for specific consent may increase patients' trust and their intention to share PHI.

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 (β=.803, P<.001), perceived benefit (β=.123, P=.04), and perceived effectiveness of government regulation (β=.110, P=.001) had a significantly positive association with sharing willingness, while perceived risk (β=-.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.

Returning study results to research participants: Data access, format, and sharing preferences

INTRODUCTION

Research participants have a growing expectation for transparency with their collected information; however, there is little guidance on participant preferences for receiving health information and how researchers should return this information to participants.

METHODS

We conducted a cross-sectional online survey with a representative sample of 502 participants in the United States. Participants were asked about their preferences for receiving, sharing, and the formatting of health information collected for research purposes.

RESULTS

Most participants wanted their health information returned (84 %) to use it for their own knowledge and to manage their own health. Email was the most preferred format for receiving health data (67 %), followed by online website (44 %), and/or paper copy (32 %). Data format preferences varied by age, education, financial resources, subjective numeracy, and health literacy. Around one third of Generation Z (25 %), Millennials (30 %), and Generation X (29 %) participants preferred to receive their health information with a mobile app. In contrast, very few Baby Boomers (12 %) and none from the Silent Generation preferred the mobile app format. Having a paper copy of the data was preferred by 38 % of participants without a college degree compared to those with a college degree. Preferences were highest for sharing all health information with doctors and nurses (77 %), and some information with friends and family (66 %).

CONCLUSION

Study findings support returning research information to participants in multiple formats, including email, online websites, and paper copy. Preferences for whom to share information with varied by stakeholders and by sociodemographic characteristics. Researchers should offer multiple formats to participants and tailor data sharing options to participants' preferences. Future research should further explore combinations of individual characteristics that may further influence data sharing and format preferences.

Read and accepted? Scoping the cognitive accessibility of privacy policies of health apps and websites in three European countries

Objective

Trust and accessibility are vital to adoption of health and wellness apps. This research scoped three elements of cognitive accessibility of health app privacy policies: availability, ease of navigation, and readability.

Methods

For this cross-sectional study, quantitative data collected in the Netherlands, Sweden, and the United Kingdom included: whether privacy information was in a country's official language (availability); number of distracting visual elements (ease of navigation); word count and Common European Framework of Reference (CEFR) reading level (readability). Health app privacy policies were compared to policies from a purposively selected sample of websites, and to benchmarks, including CEFR reading level B1.

Results

Health app privacy policies were less often available in countries' official languages compared to sampled websites (Chi-Square [1, 180]  =  57.470, p < 0.001) but contained fewer distracting visual elements. More UK privacy policies were in the country's official language, whereas Swedish privacy policies contained fewest words and fewest potentially distracting design elements. Only one privacy policy met the CEFR reading level benchmark.

Conclusions

Lack of privacy information in non-Anglophone app-users' native languages and high reading levels may be major barriers to cognitive accessibility. Web and app developers should consider recommendations arising from this study, to stimulate trust in and adoption of health and wellness apps.

Sharing intention of electronic health records in online health communities: Patients' behavioral decisions in the context of privacy protection measures

Online health communities (OHCs) have become more important to people's daily lives on the foundation of the voluntary sharing of electronic health records (EHRs). However, no in-depth investigation has been conducted concerning the influence of the perceptions of privacy protection among patients on their willingness to share EHRs. To fill the knowledge gap, by combining and modifying the theory of planned behavior (TPB) and the health belief model in the context of the privacy protection models implemented by OHCs, an empirical research method using a questionnaire approach is conducted to validate the hypotheses. The results indicate that the more positive a patient's attitude toward medical information sharing behavior is, the higher that patient's level of perceived behavioral control; in addition, the greater the social rewards obtained from this process, the more willing the patient is to share his or her EHRs after privacy protection measures are implemented by OHCs. Meanwhile, the effects of past positive experiences and disease severity have also been tested. The findings of this study can be used to promote patients' full participation in OHCs from a privacy perspective and offer theoretical and practical suggestions to promote the development of OHCs.

Factors influencing patients' opt-in intention of exchanging health information

Introduction

Health information exchange (HIE) exhibits tremendous benefits in improving the quality of healthcare and reducing healthcare costs. However, it also poses challenges related to data security, data privacy, patient engagement, etc.

Objective

This study aimed to explore the factors affecting patients' opt-in intention to HIE by using an empirical study based on the theory of planned behavior.

Methods

A Web-based survey was conducted involving 501 valid participants in China (69% validity rate).

Results

Information sensitivity and perceived HIE transparency affected the patients' opt-in intention to HIE through the mediation of perceived behavior control and trust in HIE. Information sensitivity negatively influenced perceived behavior control (-0.551, P < 0.001) and trust in HIE (-0.489, P < 0.001). Perceived transparency of HIE positively influenced perceived behavior control (0.396, P < 0.001) and trust in HIE (0.471, P < 0.001). Moreover, patients' opt-in intention to HIE can be positively affected by perceived HIE transparency (0.195, P < 0.001) and trust in HIE (0.294, P < 0.001). In addition, the moderating effect of health status was positive and significant between trust in HIE and opt-in intention to HIE but not between the perceived behavior control and opt-in intention to HIE.

Conclusion

This study contributes to the theory of planned behavior and enriches the literature on HIE efforts. HIE administrators should design personalized health services on the basis of these different health statuses to successfully achieve patients' opt-in intention to HIE.

Online Patient Recommender Systems for Preventive Care: Propositions to Advance Research (Preprint)

BACKGROUND

Preventive care helps patients identify and address medical issues early when they are easy to treat. The internet offers vast information about preventive measures, but the sheer volume of data can be overwhelming for individuals to process. To help individuals navigate this information, recommender systems filter and recommend relevant information to specific users. Despite their popularity in other fields, such as e-commerce, recommender systems have yet to be extensively studied as tools to support the implementation of prevention strategies in health care. This underexplored area presents an opportunity for recommender systems to serve as a complementary tool for medical professionals to enhance patient-centered decision-making and for patients to access health information. Thus, these systems can potentially improve the delivery of preventive care.

OBJECTIVE

This study proposes practical, evidence-based propositions. It aims to identify the key factors influencing patients' use of recommender systems and outlines a study design, methods for creating a survey, and techniques for conducting an analysis.

METHODS

This study proposes a 6-stage approach to examine user perceptions of the factors that may influence the use of recommender systems for preventive care. First, we formulate 6 research propositions that can be developed later into hypotheses for empirical testing. Second, we will create a survey instrument by collecting items from extant literature and then verify their relevance using expert analysis. This stage will continue with content and face validity testing to ensure the robustness of the selected items. Using Qualtrics (Qualtrics), the survey can be customized and prepared for deployment on Amazon Mechanical Turk. Third, we will obtain institutional review board approval because this is a human subject study. In the fourth stage, we propose using the survey to collect data from approximately 600 participants on Amazon Mechanical Turk and then using R to analyze the research model. This platform will serve as a recruitment tool and the method of obtaining informed consent. In our fifth stage, we will perform principal component analysis, Harman Single Factor test, exploratory factor analysis, and correlational analysis; examine the reliability and convergent validity of individual items; test if multicollinearity exists; and complete a confirmatory factor analysis.

RESULTS

Data collection and analysis will begin after institutional review board approval is obtained.

CONCLUSIONS

In pursuit of better health outcomes, low costs, and improved patient and provider experiences, the integration of recommender systems with health care services can extend the reach and scale of preventive care. Examining recommender systems for preventive care can be vital in achieving the quadruple aims by advancing the steps toward precision medicine and applying best practices.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/43316.

Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities

Privacy disclosure is one of the most common user information behaviors in online health communities. Under the premise of implementing privacy protection strategies in online health communities, promoting user privacy disclosure behavior can result in a “win–win” scenario for users and online health communities. Combining the real situation and evolutionary game theory, in this study, we first constructed an evolutionary game model of privacy disclosure behavior with users and online health communities as the main participants. Then, we solved the replication dynamic equations for both parties and analyzed the evolutionary stable strategies (ESSs) in different scenarios. Finally, we adopted MATLAB for numerical simulations to verify the accuracy of the model. Studies show that: (1) factors such as medical service support and community rewards that users receive after disclosing their private personal information affect user game strategy; and (2) the additional costs of the online health communities implementing the “positive protection” strategy and the expected loss related to the privacy leakage risk affect the online health communities’ game strategy. In this regard, this paper puts forward the following suggestions in order to optimize the benefits of both sets of participants: the explicit benefits of users should be improved, the internal environment of the communities should be optimized, the additional costs of the “positive protection” strategy should be reduced, and penalties for privacy leakages should be increased.

Building trust in research through information and intent transparency with health information: representative cross-sectional survey of 502 US adults

OBJECTIVE

Participation in healthcare research shapes health policy and practice; however, low trust is a barrier to participation. We evaluated whether returning health information (information transparency) and disclosing intent of data use (intent transparency) impacts trust in research.

MATERIALS AND METHODS

We conducted an online survey with a representative sample of 502 US adults. We assessed baseline trust and change in trust using 6 use cases representing the Social-Ecological Model. We assessed descriptive statistics and associations between trust and sociodemographic variables using logistic and multinomial regression.

RESULTS

Most participants (84%) want their health research information returned. Black/African American participants were more likely to increase trust in research with individual information transparency (odds ratio (OR) 2.06 [95% confidence interval (CI): 1.06-4.34]) and with intent transparency when sharing with chosen friends and family (3.66 [1.98-6.77]), doctors and nurses (1.96 [1.10-3.65]), or health tech companies (1.87 [1.02-3.40]). Asian, Native American or Alaska Native, Native Hawaiian or Pacific Islander, Multirace, and individuals with a race not listed, were more likely to increase trust when sharing with health policy makers (1.88 [1.09-3.30]). Women were less likely to increase trust when sharing with friends and family (0.55 [0.35-0.87]) or health tech companies (0.46 [0.31-0.70]).

DISCUSSION

Participants wanted their health information returned and would increase their trust in research with transparency when sharing health information.

CONCLUSION

Trust in research is influenced by interrelated factors. Future research should recruit diverse samples with lower baseline trust levels to explore changes in trust, with variation on the type of information shared.

Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 2): Focus Group Study

BACKGROUND

Patient-directed selection and sharing of health information "granules" is known as granular information sharing. In a previous study, patients with behavioral health conditions categorized their own health information into sensitive categories (eg, mental health) and chose the health professionals (eg, pharmacists) who should have access to those records. Little is known about behavioral health professionals' perspectives of patient-controlled granular information sharing (PC-GIS).

OBJECTIVE

This study aimed to assess behavioral health professionals' (1) understanding of and opinions about PC-GIS; (2) accuracy in assessing redacted medical information; (3) reactions to patient rationale for health data categorization, assignment of sensitivity, and sharing choices; and (4) recommendations to improve PC-GIS.

METHODS

Four 2-hour focus groups and pre- and postsurveys were conducted at 2 facilities. During the focus groups, outcomes from a previous study on patients' choices for medical record sharing were discussed. Thematic analysis was applied to focus group transcripts to address study objectives.

RESULTS

A total of 28 health professionals were recruited. Over half (14/25, 56%) were unaware or provided incorrect definitions of granular information sharing. After PC-GIS was explained, all professionals demonstrated understanding of the terminology and process. Most (26/32 codes, 81%) recognized that key medical data had been redacted from the study case. A majority (41/62 codes, 66%) found the patient rationale for categorization and data sharing choices to be unclear. Finally, education and other approaches to inform and engage patients in granular information sharing were recommended.

CONCLUSIONS

This study provides detailed insights from behavioral health professionals on granular information sharing. Outcomes will inform the development, deployment, and evaluation of an electronic consent tool for granular health data sharing.

Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 1): Focus Group Study

BACKGROUND

Patient-controlled granular information sharing (PC-GIS) allows a patient to select specific health information "granules," such as diagnoses and medications; choose with whom the information is shared; and decide how the information can be used. Previous studies suggest that health professionals have mixed or concerned opinions about the process and impact of PC-GIS for care and research. Further understanding of behavioral health professionals' views on PC-GIS are needed for successful implementation and use of this technology.

OBJECTIVE

The aim of this study was to evaluate changes in health professionals' opinions on PC-GIS before and after a demonstrative case study.

METHODS

Four focus groups were conducted at two integrated health care facilities: one serious mental illness facility and one general behavioral health facility. A total of 28 participants were given access to outcomes of a previous study where patients had control over medical record sharing. Participants were surveyed before and after focus groups on their views about PC-GIS. Thematic analysis of focus group output was paired with descriptive statistics and exploratory factor analysis of surveys.

RESULTS

Behavioral health professionals showed a significant opinion shift toward concern after the focus group intervention, specifically on the topics of patient understanding (P=.001), authorized electronic health record access (P=.03), patient-professional relationship (P=.006), patient control acceptance (P<.001), and patient rights (P=.02). Qualitative methodology supported these results. The themes of professional considerations (2234/4025, 55.5% of codes) and necessity of health information (260/766, 33.9%) identified key aspects of PC-GIS concerns.

CONCLUSIONS

Behavioral health professionals agreed that a trusting patient-professional relationship is integral to the optimal implementation of PC-GIS, but were concerned about the potential negative impacts of PC-GIS on patient safety and quality of care.

Privacy and Trust in eHealth: A Fuzzy Linguistic Solution for Calculating the Merit of Service

The use of eHealth and healthcare services are becoming increasingly common across networks and ecosystems. Identifying the quality and health impact of these services is a big problem that in many cases it is difficult determine. Health ecosystems are seldom designed with privacy and trust in mind, and the service user has almost no way of knowing how much trust to place in the service provider and other stakeholders using his or her personal health information (PHI). In addition, the service user cannot rely on privacy laws, and the ecosystem is not a trustworthy system. This demonstrates that, in real life, the user does not have significant privacy. Therefore, before starting to use eHealth services and subsequently disclosing personal health information (PHI), the user would benefit from tools to measure the level of privacy and trust the ecosystem can offer. For this purpose, the authors developed a solution that enables the service user to calculate a Merit of Service (Fuzzy attractiveness rating (FAR)) for the service provider and for the network where PHI is processed. A conceptual model for an eHealth ecosystem was developed. With the help of heuristic methods and system and literature analysis, a novel proposal to identify trust and privacy attributes focused on eHealth was developed. The FAR value is a combination of the service network’s privacy and trust features, and the expected health impact of the service. The computational Fuzzy linguistic method was used to calculate the FAR. For user friendliness, the Fuzzy value of Merit was transformed into a linguistic Fuzzy label. Finally, an illustrative example of FAR calculation is presented.

Trust and digital privacy in healthcare: a cross-sectional descriptive study of trust and attitudes towards uses of electronic health data among the general public in Sweden

Background

The ability of healthcare to protect sensitive personal data in medical records and registers might influence public trust, which in turn might influence willingness to allow healthcare to use such data. The aim of this study was to examine how the general public’s trust relates to their attitudes towards uses of health data.

Methods

A stratified sample from the general Swedish population received a questionnaire about their willingness to share health data. Respondents were also asked about their trust in the management and protection of electronic health data.

Results

A large majority (81.9%) of respondents revealed high levels of trust in the ability of healthcare to protect electronic patient data. Good health was associated with significantly higher levels of trust compared to bad health. Respondents with low levels of trust were significantly less willing to allow personal data to be used for different purposes and were more inclined to insist on being asked for permission beforehand. Those with low levels of trust also perceived risks of unauthorized access to personal data to be higher and the likely damage of such unauthorized access worse, compared to those with high levels of trust.

Conclusions

Trust in the ability of healthcare to protect electronic health is generally high in Sweden. Those with higher levels of trust are more willing to let their data be used, including without informed consent. It thus seems crucial to promote trust in order to be able to reap the benefits that digitalization makes possible through increased access and use of data in healthcare.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12910-022-00758-z.

Users' Willingness to Share Health Information in a Social Question-and-Answer Community: Cross-sectional Survey in China

BACKGROUND

Social question-and-answer communities play an increasingly important role in the dissemination of health information. It is important to identify influencing factors of user willingness to share health information to improve public health literacy.

OBJECTIVE

This study explored influencing factors of social question-and-answer community users who share health information to provide reference for the construction of a high-quality health information sharing community.

METHODS

A cross-sectional study was conducted through snowball sampling of 185 participants who are Zhihu users in China. A structural equation analysis was used to verify the interaction and influence of the strength between variables in the model. Hierarchical regression was also used to test the mediating effect in the model.

RESULTS

Altruism (β=.264, P<.001), intrinsic reward (β=.260, P=.03), self-efficacy (β=.468, P<.001), and community influence (β=.277, P=.003) had a positive effect on users' willingness to share health information (WSHI). By contrast, extrinsic reward (β=-0.351, P<.001) had a negative effect. Self-efficacy also had a mediating effect (β=.147, 29.15%, 0.147/0.505) between community influence and WSHI.

CONCLUSIONS

The findings suggest that users' WSHI is influenced by many factors including altruism, self-efficacy, community influence, and intrinsic reward. Improving the social atmosphere of the platform is an effective method of encouraging users to share health information.

A systematic literature review of health consumer attitudes towards secondary use and sharing of health administrative and clinical trial data: a focus on privacy, trust, and transparency

We aimed to synthesise data on issues related to stakeholder perceptions of privacy, trust, and transparency in use of secondary data. A systematic literature review of healthcare consumer attitudes towards the secondary use and sharing of health administrative and clinical trial data was conducted. EMBASE/MEDLINE, Cochrane Library, PubMed, CINAHL, Informit Health Collection, PROSPERO Database of Systematic Reviews, PsycINFO, and ProQuest databases were searched. Eligible articles included those reporting qualitative or quantitative original research and published in English. No restrictions were placed on publication dates, study design or disease setting. One author screened articles for eligibility, and two authors were involved in the full text review process. Data was extracted using a pre-piloted data extraction template by one author and checked by another. Conflicts were resolved by consensus. Quality and bias were assessed using the QualSyst criteria for qualitative and quantitative studies. This paper focuses on a subset of 35 articles identified from the wider search which focus on issues of privacy, trust, and transparency. Studies included a total of 56,365 respondents. Results of this systematic literature review indicate that while respondents identified advantages in sharing health data, concerns relating to trust, transparency, and privacy remain. Organisations collecting health data and those who seek to share data or undertake secondary data analysis should continue to develop trust, transparency, and privacy with healthcare consumers through open dialogue and education. Consideration should be given to these issues at all stages of data collection including the conception, design, and implementation phases. While individuals understand the benefits of health data sharing for research purposes, ensuring a balance between public benefit and individual privacy is essential. Researchers and those undertaking secondary data analysis need to be cognisant of these key issues at all stages of their research. Systematic review registration: PROSPERO registration number CRD42018110559 (update June 2020).

Privacy Protection in Online Health Communities: Natural Experimental Empirical Study

Background

An online health community (OHC) is a novel sharing channel through which doctors share professional health care knowledge with patients. While doctors have the authority to protect their patients’ privacy in OHCs, we have limited information on how doctors’ privacy protection choices affect their professional health care knowledge sharing with patients.

Objective

We examined the relationship between privacy protection and professional health care knowledge sharing in OHCs. Specifically, we examined the effects of privacy protection settings in an OHC on doctors’ interactive professional health care knowledge sharing and searching professional health care knowledge sharing (two dimensions of professional health care knowledge sharing). Moreover, we explored how such effects differ across different levels of disease stigma.

Methods

We collected the monthly panel data of 19,456 doctors from Good Doctor, one of the largest OHCs in China, from January 2008 to April 2016. A natural experimental empirical study with difference-in-difference analysis was conducted to test our hypotheses. The time fixed effect and the individual fixed effect were both considered to better identify the effects of a privacy protection setting on professional health care knowledge sharing. Additionally, a cross-sectional analysis was performed for a robust check.

Results

The results indicate that the privacy protection setting has a significant positive effect on interactive professional health care knowledge sharing (β=.123, P<.001). However, the privacy protection setting has a significant negative effect on searching professional health care knowledge sharing (β=–.225, P=.05). Moreover, we found that high disease stigma positively impacts the effect of privacy protection on interactive professional health care knowledge sharing (coefficients are in the same valence) and negatively impacts the effects of privacy protection on searching professional health care knowledge sharing (coefficients are in the reverse valence).

Conclusions

Privacy protection has a bilateral effect on professional health care knowledge sharing (ie, a positive effect on interactive professional health care knowledge sharing and a negative effect on searching professional health care knowledge sharing). Such bilateral switches of professional health care knowledge sharing call for a balanced state in conjunction with practical implications. This research also identifies a moderate effect of disease stigma on privacy protection settings and professional health care knowledge sharing.