The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).

PURPOSE: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making. METHODS: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives. RESULTS: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed. CONCLUSIONS: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.

Creativity in Health Communication to Promote Blood Lead Testing in Children.

Low rates of blood lead level screening among young children persist as a public health issue in the United States, including in Texas where levels remain below the national average. This article describes a multiyear, multipartner initiative aimed at increasing screening rates through a creative, community-informed social media campaign. Interviews with parents, providers, and state health department staff revealed a common perception that lead poisoning was a relic of the past. Using these insights, the team developed humorous social media messaging comparing extinct animals to lead poisoning to capture attention and change attitudes about lead's current relevance. The "#GetLeadCheckedTexas" campaign ran on state health department channels during National Lead Poisoning Prevention Week in October 2020. Colorful graphics depicted extinct creatures like dinosaurs along with their babies, playing on childhood enthusiasm for such animals while evoking protective feelings in parents. Messaging highlighted lead's dangers for young children and encouraged viewers to discuss testing with providers. Website analytics showed the campaign drove substantial increases in page views for lead screening resources, particularly among providers. While originally designed with a parent audience in mind, the campaign seemed to resonate more with providers, likely due to timing during an awareness week and use of official health department channels. The initiative demonstrates the value of creative communications approaches employed in traditional advertising to raise awareness and promote public health priorities. Audience research, thoughtful use of humor, and designing human-focused messaging helped cut through information clutter and drive engagement with an important childhood health issue.

Methods for development and application of data standards in an ontology-driven information model for measuring, managing, and computing social determinants of health for individuals, households, and communities evaluated through an example of asthma.

OBJECTIVE: To describe methods to approach application of data standards to integrate social determinants of health (SDoH) into EHRs through evaluation of a case of clinical decision support for pediatric asthma. MATERIALS AND METHODS: We identified a list of environmental factors important for managing pediatric asthma. We identified and integrated data from local outdoor air quality monitors with elements available from the clinic's EHR and self-reported indoor air quality questionnaire data. We assessed existing SDoH frameworks, assessment tools, and terminologies to identify representative data standards for these environmental SDoH measures. RESULTS: We found many-to-many relationships between the multiple framework domains, the environmental exposure measures collected, and existing standards. The majority of concepts did not accurately align with environmental exposure measurements. We propose an ontology-driven information framework methodology to apply standards for SDoH measurements to support measuring, managing, and computing SDoH data. DISCUSSION: To support methods of integrating SDoH data in the EHR via an ontology-driven information framework, a common SDoH ecosystem should be developed descriptively and prescriptively integrating framework domains, assessment tools, and standard ontologies to support future data sharing, aggregation, and interoperability. A hierarchical object-oriented information model should be adopted to manage SDoH to extend beyond patient-centered orientation of EHRs to orient to households and communities. CONCLUSION: SDoH data pose unique challenges and opportunities in collecting, measuring, and managing health information. Future work is needed to define data standards for implementing SDoH in a hierarchical, object-oriented information model representing multiple units of orientation including individuals, households, and communities.

Spatial Insights for Understanding Colorectal Cancer Screening in Disproportionately Affected Populations, Central Texas, 2019.

INTRODUCTION: Colorectal cancer (CRC) screening can reduce morbidity and mortality; however, important disparities exist in CRC uptake. Our study examines the associations of distance to care and frequency of using primary care and screening. METHODS: To examine the distribution of screening geographically and according to several demographic features, we used individual patient-level data, dated September 30, 2018, from a large urban safety-net health system in Central Texas. We used spatial cluster analysis and logistic regression adjusted for age, race, sex, socioeconomic status, and health insurance status. RESULTS: We obtained screening status data for 13,079 age-eligible patients from the health system's electronic medical records. Of those eligible, 55.1% were female, and 55.9% identified as Hispanic. Mean age was 58.1 years. Patients residing more than 20 miles from one of the system's primary care clinics was associated with lower screening rates (odds ratio [OR], 0.63; 95% CI, 0.43-0.93). Patients with higher screening rates included those who had a greater number of primary care-related (nonspecialty) visits within 1 year (OR, 6.90; 95% CI, 6.04-7.88) and those who were part of the county-level medical assistance program (OR, 1.61; 95% CI, 1.40-1.84). Spatial analysis identified an area where the level of CRC screening was particularly low. CONCLUSION: Distance to primary care and use of primary care were associated with screening. Priorities in targeted interventions should include identifying and inviting patients with limited care engagements.

Challenges encountered in comparing international policy responses to COVID-19 and their effects.

BACKGROUND: A variety of policies have been implemented around the world in response to the COVID-19 pandemic. This study originally aimed to identify and compare policy responses of different countries and their effects on the pandemic. It quickly evolved into an identification of the heterogeneity among existing policies and the challenges in making meaningful comparisons of the impact of these policies. METHODS: The process of collecting and comparing data from different sources was analysed through inductive thematic analysis to understand the obstacles that impede research designed to compare COVID-19 data and related policies. RESULTS: We identified the following obstacles: (1) no single reputable source of information and too much noise; (2) a lack of standards for how to measure and report data across countries; (3) variations in the content, implementation and enforcement of policies; and (4) politics, instead of science, leading the efforts in pandemic management. CONCLUSION: Heterogeneity in existing policies makes it challenging to compare the effects of various policies worldwide on the COVID-19 pandemic. Our findings call for an automatically updated informatics infrastructure across the globe for collecting and maintaining standardized data from multiple sources. There is a strong need for steadfast utilization of scientific and technical experts to inform and influence health policy. Increased investment in public health and emergency planning is essential to overcome the current pandemic, as well as future public health emergencies. Focused leadership and collaboration from world leaders in a unified mission to decrease the mortality and morbidity of the COVID-19 pandemic is imperative.

Local Health Departments' Engagement in Activities to Address Opioid Use and Abuse: The Influence of Surveillance Systems' Use.

AIMS: To examine the extent to which local health departments (LHDs) conduct activities to address opioid use and abuse. To test the hypothesis that (i) LHDs' access to data from an electronic syndromic surveillance system is associated with conducting activities to address opioid use and abuse, and (ii) among those LHDs with access to syndromic surveillance data, the use of syndromic and other surveillance data on opioid-related events is associated with LHDs' report of conducting activities to address opioid use and abuse. METHODS: Logistic regression was used to analyze data from the 2018 Forces of Change Survey of a statistically representative sample of 966 LHDs, of which 591 participated in the survey. RESULTS: The LHDs' access to a syndromic surveillance system was significantly associated with their report of conducting activities to address opioid use and abuse. Compared with LHDs that had no surveillance systems, odds of participating in activities to address the opioid use or abuse were higher for LHDs that managed their own surveillance systems (adjusted odds ratio, AOR = 3.022, P = .03) and those who had but did not manage their own surveillance systems (AOR = 1.920, P < .01). The LHDs' use of syndromic surveillance systems (AOR = 2.98, P = .01) or other surveillance systems (AOR = 2.21, P = .03) was also associated with higher odds to participate in activities to address the opioid use or abuse (vs no such use). CONCLUSION: The LHDs are strategically well positioned to play their role in addressing this multifaceted epidemic. Access to data or information from electronic syndromic surveillance systems that use hospital emergency department data might significantly improve LHDs' engagement in conducting activities to address opioid use and abuse within their communities while building their capacity to face the next epidemic.

Using Blockchain Technology to Mitigate Challenges in Service Access for the Homeless and Data Exchange Between Providers: Qualitative Study.

BACKGROUND: In the homeless population, barriers to housing and supportive services include a lack of control or access to data. Disparate data formats and storage across multiple organizations hinder up-to-date intersystem access to records and a unified view of an individual's health and documentation history. The utility of blockchain to solve interoperability in health care is supported in recent literature, but the technology has yet to be tested in real-life conditions encompassing the complex regulatory standards in the health sector. OBJECTIVE: This study aimed to test the feasibility and performance of a blockchain system in a homeless community to securely store and share data across a system of providers in the health care ecosystem. METHODS: We performed a series of platform demonstrations and open-ended qualitative feedback interviews to determine the key needs and barriers to user and stakeholder adoption. Account creation and data transactions promoting organizational efficiency and improved health outcomes in this population were tested with homeless users and service providers. RESULTS: Persons experiencing homelessness and care organizations could successfully create accounts, grant and revoke data sharing permissions, and transmit documents across a distributed network of providers. However, there were issues regarding the security of shared data, user experience and adoption, and organizational preparedness for service providers as end users. We tested a set of assumptions related to these problems within the project time frame and contractual obligations with an existing blockchain-based platform. CONCLUSIONS: Blockchain technology provides decentralized data sharing, validation, immutability, traceability, and integration. These core features enable a secure system for the management and distribution of sensitive information. This study presents a concrete evaluation of the effectiveness of blockchain through an existing platform while revealing limitations from the perspectives of user adoption, cost-effectiveness, scalability, and regulatory frameworks.

When Going Digital Becomes a Necessity: Ensuring Older Adults' Needs for Information, Services, and Social Inclusion During COVID-19.

Older adults are in triple jeopardy during COVID-19: compared with younger people, older adults are (1) more likely to develop serious conditions and experience higher mortality; (2) less likely to obtain high quality information or services online; and (3) more likely to experience social isolation and loneliness. Hybrid solutions, coupling online and offline strategies, are invaluable in ensuring the inclusion of vulnerable populations. Most of these solutions require no new inventions. Finding the financial resources for a rapid, well-coordinated implementation is the biggest challenge. Setting up the requisite support systems and digital infrastructure is important for the present and future pandemics.

Texting for Health: An Evaluation of a Population Approach to Type 2 Diabetes Risk Reduction With a Personalized Message.

txt4health is an innovative, 14-week, interactive, population-based mobile health program for individuals at risk of type 2 diabetes, developed under the Beacon Community Program in the Greater New Orleans, La., area. A comprehensive social marketing campaign sought to enroll hard-to-reach, at-risk populations using a combination of mass media and face-to-face engagement in faith-based and retail environments. Little is known about the effectiveness of social marketing for mobile technology application in the general population. A systematic evaluation of the campaign identified successes and barriers to implementing a population-based mobile health program. Face-to-face engagement helped increase program enrollment after the initial launch; otherwise, enrollment leveled off over time. Results show positive trends in reaching target populations and in the use of mobile phones to record personal health information and set goals for reducing the risk of type 2 diabetes. The lessons from the txt4health campaign can help inform the development and programmatic strategies to provide a person-level intervention using a population-level approach for individuals at risk for diabetes as well as aid in chronic disease management.

Harnessing Blockchain to Transform Healthcare Data Management: A Comprehensive Research Agenda.

Properly managing healthcare data is a complex endeavor that must balance the requirements and interests of many stakeholders. In this paper, we present the findings from a panel discussion with healthcare professionals and academics, who elaborate on the current situation in healthcare data management as well as the future role that blockchain could play in this sector. Based on the findings of this panel, we structure the research field of healthcare data management and provide numerous avenues for future research. The outcome is a framework that highlights the important role of healthcare data and puts them into context. From a patient's perspective, we specifically elaborate on trust and privacy as well as the expected benefits. Additionally, four important data aspects are identified: integrity, security, interoperability, and, finally, sharing and transfer. We also outline the importance of current problems and derive several relevant and timely research questions that build the foundation of a research agenda for blockchain-driven innovation in healthcare data management. In summary, the framework will inform practitioners of blockchain's potential in healthcare and structure the area for researchers, who are called upon to investigate the respective topics in greater detail.

Social and Health Information Platform: Piloting a Standards-Based, Digital Platform Linking Social Determinants of Health Data into Clinical Workflows for Community-Wide Use.

BACKGROUND: Social determinants of health (SDoH)a are increasingly recognized as a main contributor to clinical health outcomes, but the technologies and workflows within clinics make it difficult for health care providers to address SDoH needs during routine clinical visits. OBJECTIVES: Our objectives were to pilot a digital platform that matches, links, and visualizes patient-level information and community-level deidentified data from across sectors; establish a technical infrastructure that is scalable, generalizable, and interoperable with new datasets or technologies; employ user-centered codesign principles to refine the platform's visualizations, dashboards, and alerts with community health workers, clinicians, and clinic administrators. METHODS: We used privacy-preserving record linkage (PPRL) tools to ensure that all identifiable patient data were encrypted, only matched and displayed with consent, and never accessed or stored by the data intermediary. We used limited data sets (LDS) to share nonidentifiable patient data with the data intermediary through a health information exchange (HIE) to take advantage of existing partner agreements, technical infrastructure, and community clinical data. RESULTS: The platform was successfully piloted in two Federally Qualified Health Clinics by 26 clinic staff. SDoH and demographic data from findhelp were successfully linked, matched, and displayed with clinical and demographic data from the HIE, Connxus. Pilot users tested the platform using real-patient data, guiding the refinement of the social and health information platform's visualizations and alerts. Users emphasized the importance of visuals and alerts that gave quick insights into individual patient SDoH needs, survey responses, and clinic-level trends in SDoH service referrals. CONCLUSION: This pilot shows the importance of PPRL, LDS, and HIE-based data intermediaries in sharing data across sectors and service providers for scalable patient-level care coordination and community-level insights. Clinic staff are integral in designing, developing, and adopting health technologies that will enhance their ability to address SDoH needs within existing workflows without adding undue burdens or additional stress.

Expansion of the Community Engagement Studio Method: Deepening Community Participation in Health Care Innovation.

BACKGROUND: The Community Engagement Studio (CE Studio) method has emerged as a valuable model for community participation in health innovation research, and we advance the model by expanding the timing and number of CE Studio sessions, as well as facilitation. OBJECTIVES: The authors expanded the CE Studio method first to include five sessions corresponding to five phases of innovation: a) health experiences, b) community readiness,c) design features, d) adoption, and e) sustainability. Community experts were engaged throughout the duration of the research. Second, the authors positioned the CE Studio Team to be deeply embedded within the research team and the community of interest through community health workers. METHODS: The expanded CE Studio method was incorporated into a federally funded research project focused on a health technology platform. The CE Studio Team held five sessions with each of four community expert panels (total of 20 sessions) based on race/ethnicity and language: African American, Asian American, English-speaking Latinx, and Spanishspeaking Latinx. CONCLUSIONS: CE Studio sessions revealed community experts' shared and unique evolving and deepening perspectives that show promise for expanding the model.

MediLinker: a blockchain-based decentralized health information management platform for patient-centric healthcare.

Patients' control over how their health information is stored has been an ongoing issue in health informatics. Currently, most patients' health information is stored in centralized but siloed health information systems of healthcare institutions, rarely connected to or interoperable with other institutions outside of their specific health system. This centralized approach to the storage of health information is susceptible to breaches, though it can be mitigated using technology that allows for decentralized access. One promising technology that offers the possibility of decentralization, data protection, and interoperability is blockchain. In 2019, our interdisciplinary team from the University of Texas at Austin's Dell Medical School, School of Information, Department of Electrical and Computer Engineering, and Information Technology Services developed MediLinker-a blockchain-based decentralized health information management platform for patient-centric healthcare. This paper provides an overview of MediLinker and outlines its ongoing and future development and implementation. Overall, this paper contributes insights into the opportunities and challenges in developing and implementing blockchain-based technologies in healthcare.

Improving Transitions of Care: Designing a Blockchain Application for Patient Identity Management.

Background: The current healthcare ecosystem in the United States is plagued by inefficiencies in transitions of patient care between healthcare providers due in large part to a lack of interoperability among the many electronic medical record (EMR) systems that exist today. Both providers and patients experience significant frustration due to the negative effects of increased costs, unnecessary administrative burden, and duplication of services that occur because of data fragmentation in the system. Blockchain technology provides a potential solution to mitigate or eliminate these gaps by allowing for exchange of healthcare information that is distributed, auditable, immutable, and respectful of patient autonomy. Our multidisciplinary team identified key tasks required for a transition of care to design and develop a blockchain application, MediLinker, which served as a patient-centric identity management system to address issues of data fragmentation ultimately aiding in the delivery of high-value care services. Methods: The MediLinker application was evaluated for its ability to accomplish various key tasks needed for a successful transition of patient care in an outpatient setting. Our team created 20 unique patient use cases covering a diversity of medical needs and social circumstances that were played out by participants who were asked to perform various tasks as they received case across a simulated healthcare ecosystem composed of four clinics, a research institution, and other ancillary public services. Tasks included, but were not limited to, clinic enrollment, verification of identity, medication reconciliation, sharing insurance and billing information, and updating demographic information. With this iteration of MediLinker, we specifically focused on the functionality of digital guardianship and patient revocation of healthcare information. In addition, throughout the simulation, we surveyed participant perceptions regarding the use of MediLinker and blockchain technology to better ascertain comfortability and usability of the application. Results: Quantitative evaluation of simulation results revealed that MediLinker was able to successfully accomplish all seven clinical scenarios tested across the 20 patient use cases. MediLinker successfully achieved its goal of patient-centered interoperability as participants transitioned their simulated healthcare data, including COVID-19 vaccination status and current medications, across the four clinic sites and research institution. In addition to completing all key tasks designated, all eligible participants were able to enroll with and subsequently revoke data access with our simulated research site. MediLinker had a low data-entry error rate, with most errors occurring due to work-flow vulnerabilities. Our qualitative analysis of user perceptions indicated that comfortability and trust with blockchain technology, such as MediLinker, grew with increased education and exposure to such technology. Conclusions: The ubiquitous problem of data fragmentation in our current healthcare ecosystem has placed considerable strain on providers and patients alike. Blockchain applications for health identity management, such as MediLinker, provide a viable solution to stem the inefficiencies that exist today. The interoperability that MediLinker provided across our simulated healthcare system has the potential to improve transitions of care by sharing key aspects of healthcare information in a timely, secure, and patent-centric fashion allowing for the delivery of consistent and personalized high value care. Blockchain technologies appear to face similar challenges to widespread adoption as other novel interventions, namely recognition, trust, and usability. Further development and scaling are required for such technology to realize its full potential in the real world and transform the practice of modern health care.

Clinical, Organizational and Regulatory, and Ethical and Social (CORES) Issues and Recommendations on Blockchain Deployment for Healthcare: Evidence from Experts.

Objective: While existing research by our team has demonstrated the feasibility of building a decentralized identity management application ("MediLinker") for health information, there are implementation issues related to testing such blockchain-based health applications in real-world clinical settings. In this study, we identified clinical, organizational and regulatory, and ethical and social (CORES) issues, including recommendations, associated with deploying MediLinker, and blockchain in general, for clinical testing. Methods: CORES issues and recommendations were identified through a focus group with 11 academic, industry, and government experts on March 26, 2021. They were grouped according to their expertise: clinical care (n = 4), organizational and regulatory concerns (n = 4), and ethical and social issues (n = 3). The focus group was conducted via Zoom in which experts were briefed about the study aims, formed into breakout groups to identify key issues based on their group's expertise, and reconvened to share identified issues with other groups and to discuss potential recommendations to address such issues. The focus group was video recorded and transcribed. The resulting transcriptions and meeting notes were imported to MAXQDA 2018 for thematic analysis. Results: Clinical experts identified issues that concern the clinical system, clinical administrators, clinicians, and patients. Organizational and regulatory experts emphasized issues on accountability, compliance, and legal safeguards. Ethics and social-context experts raised issues on trust, transparency, digital divide, and health-related digital autonomy. Accordingly, experts proposed six recommendations that could address most of the identified issues: (1) design interfaces based on patient preferences, (2) ensure testing with diverse populations, (3) ensure compliance with existing policies, (4) present potential positive outcomes to top management, (5) maintain clinical workflow, and (6) increase the public's awareness of blockchain. Conclusions: This study identified a myriad of CORES issues associated with deploying MediLinker in clinical settings. Moreover, the study also uncovered several recommendations that could address such issues. The findings raise awareness on CORES issues that should be considered when designing, developing, and deploying blockchain for healthcare. Further, the findings provide additional insights into the development of MediLinker from a prototype to a minimum viable product for clinical testing. Future studies can use CORES as a socio-technical model to identify issues and recommendations associated with deploying health information technologies in clinical settings.

Technical Design and Development of A Self-Sovereign Identity Management Platform for Patient-Centric Health Care Using Blockchain Technology.

Objective: Clinical data in the United States are highly fragmented, stored in numerous different databases, and are defined by service providers or clinical specialties rather than by individuals or their families. As a result, linking or aggregating a complete record for a patient is a major technological, legal, and operational challenge. One of the factors that has made clinical data integration so difficult to achieve is the lack of a universal ID for everyone. This leads to other related problems of having to prove identity at each interaction with the health system and repeatedly providing basic information on demographics, insurance, payment, and medical conditions. Traditional solutions that require complex governance, expensive technology, and risks to privacy and security of the data have failed adequately to solve this interoperability problem. We describe the technical design decisions of a patient-centric decentralized health identity management system using the blockchain technology, called MediLinker, to address some of these challenges. Design: Our multidisciplinary research group developed and implemented an identity wallet, which uses the blockchain technology to manage verifiable credentials issued by healthcare clinics, banks, and insurance companies. To manage patient's self-sovereign identity, we leveraged the Hyperledger Indy blockchain framework to store patient's decentralized identifiers (DIDs) and the schemas or format for each credential type. In contrast, the credentials containing patient data are stored 'off-ledger' in each person's wallet and accessible via a computer or smartphone. We used Hyperledger Aries as a middleware layer (API: Application Programming Interface) to connect Hyperledger Indy with the front-end, which was developed using a JavaScript framework, ReactJS (Web Application) and React Native (iOS Application). Results: MediLinker allows users to store their personal data on digital wallets, which they control. It uses a decentralized trusted identity using Hyperledger Indy and Hyperledger Aries. Patients use MediLinker to register and share their information securely and in a trusted system with healthcare and other service providers. Each MediLinker wallet can have six credential types: health ID with patient demographics, insurance, medication list including COVID-19 vaccination status, credit card, medical power of attorney (MPOA) for guardians of pediatric or geriatric patients, and research consent. The system allows for in-person and remote granting and revoking of such permissions for care, research, or other purposes without repeatedly requiring physical identity documents or enrollment information. Conclusion: We successfully developed and tested a blockchain-based technical architecture, described in this article, as an identity management system that may be operationalized and scaled for future implementation to improve patient experience and control over their personal information.

Perceptions of Life Support and Advance Care Planning During the COVID-19 Pandemic: A Global Study of Twitter Users.

BACKGROUND: The COVID-19 pandemic has presented new challenges surrounding end-of-life planning and has been associated with increased online discussion about life support. RESEARCH QUESTION: How has online communication about advance care planning (ACP) and specific life-sustaining interventions (LSIs) changed during the pandemic? STUDY DESIGN AND METHODS: Conversations on Twitter containing references to LSIs (eg, "ECMO") or ACP (eg, "DNR/DNI") were collected between January 2019 and May 2021. User account metadata were used to predict user demographic information and to classify users as organizations, individuals, clinicians, or influencers. The number of impressions was compared across these user categories and the content of tweets analyzed by using natural language processing models to identify topics of discussion and associated emotional sentiment. RESULTS: There were 202,585 unique tweets about LSIs and 67,162 unique tweets about ACP. Users who were younger, male, or influencers were more likely to discuss LSIs online. Tweets about LSIs were associated with more positive emotional sentiment scores than tweets about ACP (LSIs, 0.3; ACP, -0.2; P < .001). Among tweets about ACP, most contained personal experiences related to the death of loved ones (27%) or discussed discrimination through do-not-resuscitate orders directed at the elderly and disabled (19%). Personal experiences had the greatest retweet-to-tweet-ratio (4.7), indicating high levels of user engagement. Tweets about discrimination contained the most negative net sentiment score (-0.5). INTERPRETATION: The observed increase in tweets regarding LSIs and ACP suggests that Twitter was consistently used to discuss treatment modalities and preferences related to intensive care during the pandemic. Future interventions to increase online engagement with ACP may consider leveraging influencers and personal stories. Finally, we identified do-not-resuscitate-related discrimination as a commonly held public fear, which should be further explored as a barrier to ACP completion and can be proactively addressed by clinicians during bedside goals-of-care discussions.

Assessment of structured data elements for social risk factors.

OBJECTIVES: Computable social risk factor phenotypes derived from routinely collected structured electronic health record (EHR) or health information exchange (HIE) data may represent a feasible and robust approach to measuring social factors. This study convened an expert panel to identify and assess the quality of individual EHR and HIE structured data elements that could be used as components in future computable social risk factor phenotypes. STUDY DESIGN: Technical expert panel. METHODS: A 2-round Delphi technique included 17 experts with an in-depth knowledge of available EHR and/or HIE data. The first-round identification sessions followed a nominal group approach to generate candidate data elements that may relate to socioeconomics, cultural context, social relationships, and community context. In the second-round survey, panelists rated each data element according to overall data quality and likelihood of systematic differences in quality across populations (ie, bias). RESULTS: Panelists identified a total of 89 structured data elements. About half of the data elements (n = 45) were related to socioeconomic characteristics. The panelists identified a diverse set of data elements. Elements used in reimbursement-related processes were generally rated as higher quality. Panelists noted that several data elements may be subject to implicit bias or reflect biased systems of care, which may limit their utility in measuring social factors. CONCLUSIONS: Routinely collected structured data within EHR and HIE systems may reflect patient social risk factors. Identifying and assessing available data elements serves as a foundational step toward developing future computable social factor phenotypes.

The case for establishing a blockchain research and development program at an academic medical center.

Objective: To develop a research and development program to study factors that will support research, education and innovation using blockchain technology for health in an effective and sustainable manner. We proposed to conduct qualitative research to generate insights for developing a market strategy to build a research lab for the promotion of blockchain technologies in health in academic environments. The team aimed to identify the key barriers and opportunities for developing a sustainable research lab that generates research, education, and application of blockchain in healthcare at an academic medical institution and test those strategies in a real-world scenario. Methods: The research team identified potential customers and stakeholders through interviews and snowball sampling. The team conducted semi-structured interviews with 4 faculty researchers, 10 industry leaders, and 6 students from a variety of disciplines and organizations. The findings of these research activities informed our understanding of the needs of stratified customers and helped identify key assets and activities the lab will have to offer to meet those needs. Results: The research insights from data analysis were used to build the business model for establishing a blockchain in health impact lab. This systematic study of areas where blockchain technology can impact health will guide the future development of research agenda for the researchers on campus. Conclusion: Based on our learnings, we hope to design a Blockchain in Health Impact Lab to serve as a platform for students and faculty to come together with industry partners and explore current challenges of blockchain in healthcare. The academic medical center's partnership with other healthcare providers will help create real-world opportunities to demonstrate and implement new technologies.