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On the Internet, people share personal experiences as well as facts and objective information. This also holds true for the exchange of health-related information in a variety of Internet forums. In online discussions about health topics, both fact-oriented and strongly personal contributions occur on a regular basis. In this field experiment, we examined in what way the particular type of contribution (ie, factual information vs personal experiences) has an impact on the subsequent communication in health-related Internet forums. For this purpose, we posted parallelized queries to 28 comparable Internet forums; queries were identical with regard to the information contained but included either fact-oriented descriptions or personal experiences related to measles vaccination. In the factual information condition, we posted queries to the forums that contained the neutral summary of a scientific article. In the personal experiences condition, we posted queries to the forums that contained the same information as in the first condition, but were framed as personal experiences We found no evidence that personal experiences evoked more responses (mean 3.79, SD 3.91) from other members of the Internet forums than fact-oriented contributions (mean 2.14, SD 2.93, t26=0.126, P=.219). But personal experiences elicited emotional replies (mean 3.17, SD 1.29) from other users to a greater extent than fact-oriented contributions (mean 2.13, SD 1.29, t81=3.659, P<.001). We suggest that personal experiences elicited more emotional replies due to the process of emotional anchoring of people's own style of communication. We recommend future studies should aim at testing the hypotheses with more general and with less emotionally charged topics, constructing different fact-oriented posts, and examining additional potential factors of influence such as personality factors or particular communication situations.

Nowadays, a number of mechanisms and tools are being used by health care organizations and physicians to electronically exchange the personal health information of patients. The main objectives of different methods of health information exchange (HIE) are to reduce health care costs, minimize medical errors, and improve the coordination of interorganizational information exchange across health care entities. The main challenges associated with the common HIE systems are privacy concerns, security risks, low visibility of system transparency, and lack of patient control. Blockchain technology is likely to disrupt the current information exchange models utilized in the health care industry. Little is known about patients' perceptions and attitudes toward the implementation of blockchain-enabled HIE networks, and it is still not clear if patients (as one of the main HIE stakeholders) are likely to opt in to the applications of this technology in HIE initiatives. Thus, this study aimed at exploring the core value of blockchain technology in the health care industry from health care consumers' views. To recognize the potential applications of blockchain technology in health care practices, we designed 16 information exchange scenarios for controlled Web-based experiments. Overall, 2013 respondents participated in 16 Web-based experiments. Each experiment described an information exchange condition characterized by 4 exchange mechanisms (ie, direct, lookup, patient-centered, and blockchain), 2 types of health information (ie, sensitive vs nonsensitive), and 2 types of privacy policy (weak vs strong). The findings show that there are significant differences in patients' perceptions of various exchange mechanisms with regard to patient privacy concern, trust in competency and integrity, opt-in intention, and willingness to share information. Interestingly, participants hold a favorable attitude toward the implementation of blockchain-based exchange mechanisms for privacy protection, coordination, and information exchange purposes. This study proposed the potentials and limitations of a blockchain-based attempt in the HIE context. The results of this research should be of interest to both academics and practitioners. The findings propose potential limitations of a blockchain-based HIE that should be addressed by health care organizations to exchange personal health information in a secure and private manner. This study can contribute to the research in the blockchain area and enrich the literature on the use of blockchain in HIE efforts. Practitioners can also identify how to leverage the benefit of blockchain to promote HIE initiatives nationwide.

Traditionally, guidance and support to new parents have come from family, friends, and health care providers. However, the internet and social media are growing sources of guidance and support for parents. Little is known about how the internet and social media are used by parents of young infants and specifically about parental perceptions of the internet and social media as sources of parenting and infant health information. The aim of this study was to explore, using qualitative methods, parental perceptions of the advantages and disadvantages of the internet and social media as sources of parenting and health information regarding their infant. A total of 28 mothers participated in focus groups or individual interviews. Probing questions concerning parenting and health information sources were asked. Themes were developed in an iterative manner from coded data. The central themes were (1) reasons that mothers turn to the internet for parenting and health information, (2) cautionary advice about the internet, and (3) reasons that mothers turn to social media for parenting and health information. Mothers appreciated the ability to gather unlimited information and multiple opinions quickly and anonymously, but recognized the need to use reputable sources of information. Mothers also appreciated the immediacy of affirmation, support, and tailored information available through social media. The internet and social media are rapidly becoming important and trusted sources of parenting and health information that mothers turn to when making infant care decisions.

Objective To identify the source (press releases or news) of distortions, exaggerations, or changes to the main conclusions drawn from research that could potentially influence a reader’s health related behaviour. Design Retrospective quantitative content analysis. Setting Journal articles, press releases, and related news, with accompanying simulations. Sample Press releases (n=462) on biomedical and health related science issued by 20 leading UK universities in 2011, alongside their associated peer reviewed research papers and news stories (n=668). Main outcome measures Advice to readers to change behaviour, causal statements drawn from correlational research, and inference to humans from animal research that went beyond those in the associated peer reviewed papers. Results 40% (95% confidence interval 33% to 46%) of the press releases contained exaggerated advice, 33% (26% to 40%) contained exaggerated causal claims, and 36% (28% to 46%) contained exaggerated inference to humans from animal research. When press releases contained such exaggeration, 58% (95% confidence interval 48% to 68%), 81% (70% to 93%), and 86% (77% to 95%) of news stories, respectively, contained similar exaggeration, compared with exaggeration rates of 17% (10% to 24%), 18% (9% to 27%), and 10% (0% to 19%) in news when the press releases were not exaggerated. Odds ratios for each category of analysis were 6.5 (95% confidence interval 3.5 to 12), 20 (7.6 to 51), and 56 (15 to 211). At the same time, there was little evidence that exaggeration in press releases increased the uptake of news. Conclusions Exaggeration in news is strongly associated with exaggeration in press releases. Improving the accuracy of academic press releases could represent a key opportunity for reducing misleading health related news.

A blockchain is a list of records that uses cryptography to make stored data immutable; their use has recently been proposed for electronic medical record (EMR) systems. This paper details a systematic review of trade-offs in blockchain technologies that are relevant to EMRs. Trade-offs are defined as \"a compromise between two desirable but incompatible features.\" This review's primary research question was: \"What are the trade-offs involved in different blockchain designs that are relevant to the creation of blockchain-based electronic medical records systems?\" Seven databases were systematically searched for relevant articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Papers published from January 1, 2017 to June 15, 2018 were selected. Quality assessments of papers were performed using the Risk Of Bias In Non-randomized Studies-of Interventions (ROBINS-I) tool and the Critical Assessment Skills Programme (CASP) tool. Database searches identified 2885 articles, of which 15 were ultimately included for analysis. A total of 17 trade-offs were identified impacting the design, development, and implementation of blockchain systems; these trade-offs are organized into themes, including business, application, data, and technology architecture. The key findings concluded the following: (1) multiple trade-offs can be managed adaptively to improve EMR utility; (2) multiple trade-offs involve improving the security of blockchain systems at the cost of other features, meaning EMR efficacy highly depends on data protection standards; and (3) multiple trade-offs result in improved blockchain scalability. Consideration of these trade-offs will be important to the specific environment in which electronic medical records are being developed. This review also uses its findings to suggest useful design choices for a hypothetical National Health Service blockchain. RR2-10.2196/10994.

Hospital-based health promotion resources to assist pregnant women in adopting a healthy lifestyle and optimizing gestational weight gain are important, but with limited effects. Increasingly, women are using mobile apps to access health information during the antenatal period. The aims of the study were to investigate app-usage by Chinese women during pregnancy and to gain a better understanding of their views and attitudes toward apps containing health information. A mixed methods study design was applied. Study participants were recruited from 2 maternity hospitals in Shanghai, China, between March and July 2018. A self-administered Web-based survey was conducted with 535 pregnant Chinese women on their sources of health information and reasons for using apps during pregnancy. A total of 4 semistructured focus groups were also conducted with the pregnant women (n=28). The use of pregnancy-related apps and the internet was common among the respondents. Almost half of the women had used pregnancy-related apps. Specifically, the use of apps for health information declined as pregnancy progressed from 70% (35/50) in the first trimester to 41.3% (143/346) in the third trimester. The main reason for using an app was to monitor fetal development (436/535, 81.5%), followed by learning about nutrition and recording diet in pregnancy (140/535, 26.2%). The women found that the apps were useful and convenient and can support lifestyle modifications during pregnancy. However, some apps also contained misinformation or incorrect information that could cause anxiety as reported by the participants. Many women expressed the need for developing an app containing evidence-based, well-informed, and tailored health information to support them during pregnancy. The study suggests that apps were widely used by many Chinese women during pregnancy to monitor fetal development, to obtain diet and physical activity information, and to track their body changes. The women highly appreciated the evidence-based information, expert opinions, and tailored advice available on apps. Smartphone apps have the potential to deliver health information for pregnant women.

The diffusion of health information technologies (HITs) within the health care sector continues to grow. However, there is no theory explaining how success of HITs influences patient care outcomes. With the increase in data breaches, HITs' success now hinges on the effectiveness of data protection solutions. Still, empirical research has only addressed privacy concerns, with little regard for other factors of information assurance. The objective of this study was to study the effectiveness of HITs using the DeLone and McLean Information Systems Success Model (DMISSM). We examined the role of information assurance constructs (ie, the role of information security beliefs, privacy concerns, and trust in health information) as measures of HIT effectiveness. We also investigated the relationships between information assurance and three aspects of system success: attitude toward health information exchange (HIE), patient access to health records, and perceived patient care quality. Using structural equation modeling, we analyzed the data from a sample of 3677 cancer patients from a public dataset. We used R software (R Project for Statistical Computing) and the Lavaan package to test the hypothesized relationships. Our extension of the DMISSM to health care was supported. We found that increased privacy concerns reduce the frequency of patient access to health records use, positive attitudes toward HIE, and perceptions of patient care quality. Also, belief in the effectiveness of information security increases the frequency of patient access to health records and positive attitude toward HIE. Trust in health information had a positive association with attitudes toward HIE and perceived patient care quality. Trust in health information had no direct effect on patient access to health records; however, it had an indirect relationship through privacy concerns. Trust in health information and belief in the effectiveness of information security safeguards increases perceptions of patient care quality. Privacy concerns reduce patients' frequency of accessing health records, patients' positive attitudes toward HIE exchange, and overall perceived patient care quality. Health care organizations are encouraged to implement security safeguards to increase trust, the frequency of health record use, and reduce privacy concerns, consequently increasing patient care quality.

Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced language models, such as large language models (LLMs), may help overcome current challenges in information exchange. This study aims to evaluate the capability of LLMs in transforming and transferring health care data to support interoperability. Using data from the Medical Information Mart for Intensive Care III and UK Biobank, the study conducted 3 experiments. Experiment 1 assessed the accuracy of transforming structured laboratory results into unstructured format. Experiment 2 explored the conversion of diagnostic codes between the coding frameworks of the ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), and Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) using a traditional mapping table and a text-based approach facilitated by the LLM ChatGPT. Experiment 3 focused on extracting targeted information from unstructured records that included comprehensive clinical information (discharge notes). The text-based approach showed a high conversion accuracy in transforming laboratory results (experiment 1) and an enhanced consistency in diagnostic code conversion, particularly for frequently used diagnostic names, compared with the traditional mapping approach (experiment 2). In experiment 3, the LLM showed a positive predictive value of 87.2% in extracting generic drug names. This study highlighted the potential role of LLMs in significantly improving health care data interoperability, demonstrated by their high accuracy and efficiency in data transformation and exchange. The LLMs hold vast potential for enhancing medical data exchange without complex standardization for medical terms and data structure.

Data coordination across multiple health care facilities has become increasingly important for many emerging health care applications. Distrust has been recognized as a key barrier to the success of such applications. Leveraging blockchain technology could provide potential solutions tobuild trust between data providers and receivers by taking advantage of blockchain properties such as security, immutability, anonymity, decentralization, and smart contracts. Many health technologies have empirically proven that blockchain designs fit well with the needs of health care applications with certain degrees of success. However, there is a lack of robust architecture to provide a practical framework for developers to implement applications and test the performance of stability, efficiency, and scalability using standard blockchain designs. A generalized blockchain model is needed for the health care community to adopt blockchain technology and develop applications in a timely fashion. This study aimed at building a generalized blockchain architecture that provides data coordination functions, including data requests, permission granting, data exchange, and usage tracking, for a wide spectrum of health care application developments. An augmented, 3-layered blockchain architecture was built on a private blockchain network. The 3 layers, from bottom to top, are as follows: (1) incorporation of fundamental blockchain settings and smart contract design for data collection; (2) interactions between the blockchain and health care application development environment using Node.js and web3.js; and (3) a flexible development platform that supports web technologies such as HTML, https, and various programing languages. Two example applications, health information exchange (HIE) and clinical trial recruitment, were developed in our design to demonstrate the feasibility of the layered architecture. Case studies were conducted to test the performance in terms of stability, efficiency, and scalability of the blockchain system. A total of 331,142 simulated HIE requests from accounts of 40,000 patients were successfully validated through this layered blockchain architecture with an average exchange time of 11.271 (SD 2.208) seconds. We also simulated a clinical trial recruitment scenario with the same set of patients and various recruitment criteria to match potential subjects using the same architecture. Potential subjects successfully received the clinical trial recruitment information and granted permission to the trial sponsors to access their health records with an average time of 3.07 seconds. This study proposes a generalized layered blockchain architecture that offers health technology community blockchain features for application development without requiring developers to have extensive experience with blockchain technology. The case studies tested the performance of our design and empirically proved the feasibility of the architecture in 2 relevant health application domains.

Context: The United States has invested billions of dollars to encourage the adoption of and implement the information technologies necessary for health information exchange (HIE), enabling providers to efficiently and effectively share patient information with other providers. Health care providers now have multiple options for obtaining and sharing patient information. Community HIEs facilitate information sharing for a broad group of providers within a region. Enterprise HIEs are operated by health systems and share information among affiliated hospitals and providers. We sought to identify why hospitals and health systems choose either to participate in community HIEs or to establish enterprise HIEs. Methods: We conducted semistructured interviews with 40 policymakers, community and enterprise HIE leaders, and health care executives from 19 different organizations. Our qualitative analysis used a general inductive and comparative approach to identify factors influencing participation in, and the success of, each approach to HIE. Findings: Enterprise HIEs support health systems' strategic goals through the control of an information technology network consisting of desired trading partners. Community HIEs support obtaining patient information from the broadest set of providers, but with more dispersed benefits to all participants, the community, and patients. Although not an either/or decision, community and enterprise HIEs compete for finite organizational resources like time, skilled staff, and money. Both approaches face challenges due to vendor costs and lessthan-interoperable technology. Conclusions: Both community and enterprise HIEs support aggregating clinical data and following patients across settings. Although they can be complementary, community and enterprise HIEs nonetheless compete for providers' attention and organizational resources. Health policymakers might try to encourage the type of widespread information exchange pursued by community HIEs, but the business case for enterprise HIEs clearly is stronger. The sustainability of a community HIE, potentially a public good, may necessitate ongoing public funding and supportive regulation.