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.

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.

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.

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.

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.

FHIRedApp: a LEAP in health information technology for promoting patient access to their medical information.

OBJECTIVE: Our aim is to develop a patient engagement technology that makes it easy for patients to access their own medical information and share it with others. MATERIALS AND METHODS: This paper describes our design through an adapted Community Engagement Studio methodology to identify the needs and preferences of a diverse group of Latinx, African-American, and Asian-American individuals in the community. We use Human-Centered Design to interpret these needs and preferences to build a digital app platform, using national data standards, clinical data aggregators, and privacy-preserving solutions while maintaining the security and confidentiality of patients. RESULTS: We designed and developed FHIRedApp, an app platform, that allows patients to access their data and to share that access as HL7® FHIR® application programming interfaces with third-party app developers. We accomplished 2 major tasks: first, to demonstrate the use of interoperability and authentication standards, such as HL7® FHIR and OAuth2, to help develop patient engagement technologies, and second, to co-develop and co-design FHIRedApp with active involvement of African-American, Latinx, and Asian-American community members. Usability results show high satisfaction rates for FHIRedApp. CONCLUSION: The development of FHIRedApp demonstrates how technology innovations using national interoperability standards can be informed through a methodology of community engagement and human-centered design that involves local racial and ethnic groups.

Developing a real-time EHR-integrated SDoH clinical tool.

We describe an implementation of a pilot integration to embed SDoH-based data visualizations into the EHR in real time for clinical staff treating children with asthma.

Contributions of activity ergonomics to the design of an electronic health record to support collaborative mental care of children and youth: Preliminary results.

BACKGROUND: The use of electronic health records (EHR) is related to the improvement of service quality and care coordination. The design of this platform generally focuses on the individual use of the system and does not integrate the specific needs of workers to provide support for collaborative activities. OBJECTIVE: The study investigated how activity ergonomics (AE) contributed to improve the design of an EHR that supports the collaborative mental health care of children and youth. METHODS: This qualitative study, based on the theoretical framework of AE, used individual and group interviews and document analysis as research procedures. The data collection occurred between March and September 2017 in Rio de Janeiro, Brazil. RESULTS: The study highlighted the following points: the characteristics that marked the different perceptions of workers regarding the use of a communication tool for collaborative care; the problems related to spreadsheet usability; and the desirable attributes that should be considered in the conception of a new EHR. CONCLUSIONS: The research indicated that AE favors improving the design of an EHR by incorporating the work dimension into the project.

Evolving Research Data Sharing Networks to Clinical App Sharing Networks.

Research networks for data sharing are growing into a large platform for pragmatic clinical trials to generate quality evidence for shared medical decision-making. Institutions partnering in the networks have made large investments in developing the infrastructure for sharing data. We investigate whether institutions partnering on Patient-Centered Outcomes Research Institute's (PCORI) network can share clinical apps. At two different sites, we imported patient data in PCORI's clinical data model (CDM) format into i2b2 repositories, and adapted the SMART-on-FHIR cell to perform CDM-to-FHIR translation, serving demographics, laboratory results and diagnoses. We performed manual validations and tested the platform using four apps from the SMART app gallery. Our study demonstrates an approach to extend the research infrastructure to allow the partnering institutions to run shared clinical apps, and highlights the involved challenges. Our results, tooling and publically accessible data service can potentially transform research networks into clinical app sharing networks and pave the way towards a learning health system.