Collaborating for COVID-19: Hospital Health Information Exchange and Public Health Partnership.

Background: The coronavirus disease (COVID-19) pandemic highlighted the need for effective communication and information sharing among health care organizations and public health systems (PHSs). Health information exchange (HIE) plays a vital role in improving quality control and efficiency in hospital settings, particularly in underserved areas. Objective: This study aimed to investigate the variation of HIE availability among hospitals based on their collaboration with the PHS and affiliation with Accountable Care Organizations (ACOs) in 2020, as well as variation by community social determinants of health. Methods: The primary data set used for this study comprised the linked data set of the 2020 American Hospital Association (AHA) Annual Survey and the AHA Information Technology Supplement. The measures used included the hospital's participation in HIE networks, availability of data exchange, and HIE measures during the COVID-19 pandemic, including whether hospitals effectively received electronically transmitted information from outside providers for COVID-19 treatment. Results: The sample size of hospitals ranged from 1,316 to 1,436, depending on different outcomes related to HIE questions. Of the hospitals surveyed, ∼67% reported public health collaboration and ACO affiliation, while 7% reported neither. Hospitals without public health collaboration or ACO affiliation were more likely to be located in underserved areas. Compared with hospitals without public health collaboration or ACO affiliation, hospitals with both were 9% more likely to report the availability of electronically transmitted clinical information from outside providers and to participate in local and national HIE networks. Furthermore, these hospitals were 30% (marginal effect [ME] = 0.30, p < 0.001) more likely to report effective receipt of information from outside providers for COVID-19 treatment and 12% (ME = 0.12, p = 0.02) more likely to always/often receive clinical information for COVID-19 treatment electronically. Conclusions: Hospital collaboration with the PHS and ACO affiliation are associated with greater availability of electronic health data, particularly during the COVID-19 pandemic.

Health worker registries: managing the health care workforce

Registries play an instrumental role in facilitating the transfer, aggregation, and analysis of standardized data in health information exchange (HIE). One such example is a health worker registry (HWR), a central, authoritative registry that maintains the unique identities of health workers according to a defined, minimum data set. Currently, data comprising workers' information—such as education, licensure, and place of employment—are collected through disparate methods and maintained in a variety of information systems. Harmonization of these data via an HWR can support interoperability and comparability of worker information across systems, thereby facilitating efficient workforce enumeration, planning, regulation and deployment, verification of training and education, identification of workforce shortages, and rapid communication and coordination of emergency response. In fact, HWR technologies played a role in coordinating response to both Ebola in West Africa in 2014 and more recently in response to COVID-19, making a HWR integral to nations' infrastructure upgrades postpandemic. This chapter identifies who is considered a "health worker” and why a registry of these individuals is a useful component of an HIE, especially in the wake of the COVID-19 pandemic. It also provides guidance on selection of data elements and standards to include in the development of an HWR. © 2023 Elsevier Inc. All rights reserved.

Facility registries: metadata for where care is delivered

Comprehensively identifying and monitoring health facilities where care is delivered is critical to care coordination as well as public health. This became poignantly clear during the COVID-19 pandemic. Currently, few sources exist which can provide canonical identification of healthcare facilities. Furthermore, quantifying facility-specific services and infrastructure in a standard manner ranges from insufficient to nonexistent. A health facility registry provides a central authority to store, manage, and share health facility identification, services, and resources data with a wide range of stakeholders. Such universal collection and standardization of these data may support care coordination, public health responsiveness, quality improvement, health services research, health service planning, and health policy development. This chapter introduces the concept of a facility registry and provides scenarios in which stakeholders would benefit from facility data. The chapter further discusses unique identifiers, data collection, and the metadata necessary for establishing and maintaining a facility registry. © 2023 Elsevier Inc. All rights reserved.

Introduction to health information exchange

To support health care and public health in managing the array of information available about patients and populations, health systems have adopted a variety of information and communications technologies (ICT). Examples include electronic health record systems that document patient symptoms, diseases, and medications as well as health care processes. Yet, many ICT systems operate as islands unto themselves, unable to connect or share information with other ICT systems. Such fragmentation of data and information is an impediment to achieving the goal of efficient, coordinated health care delivery. It was further a major challenge during the COVID-19 pandemic when information was rapidly needed yet challenging to access. Health information exchange (HIE) seeks to address the challenges of connecting disparate ICT systems, enabling information to be available when and where it is needed by clinicians, administrators, and public health authorities. This chapter robustly defines HIE, including its core components and various forms. This chapter further discusses the role of HIE in supporting care delivery and public health. © 2023 Elsevier Inc. All rights reserved.

Future directions for health information exchange

Health information exchange (HIE) now exists in diverse forms within and across countries. However, our HIE infrastructure is fragmented, which impedes the ability to meet the needs of varied data sharing use cases—particularly public health data needs that became evident during the COVID-19 pandemic. In response, several efforts—some within the United States and some outside the United States—have started to undertake work to help tie existing HIE approaches together into a more seamless whole. While the societal benefits of doing so are clear, there are substantial cost and complexity involved, leaving it an open question as to how successful they will be. This chapter describes three major efforts underway to advance HIE infrastructure at scale—the Trusted Exchange Framework and Common Agreement (a US policy strategy), the Joint Action Towards the European Health Data Space (an EU initiative), and the emerging concept of health data utility models as more comprehensive repositories of health data with strong government requirements for participation. For each, we describe the effort as well as discuss potential challenges to implementation and success in achieving the intended outcomes. We also discuss a complementary issue related to health data integration and usability of exchanged health information that will become more acute as efforts to advance data sharing at scale are pursued. © 2023 Elsevier Inc. All rights reserved.

Leveraging PEPFAR-Supported Health Information Systems for COVID-19 Pandemic Response.

Since 2003, the US President's Emergency Plan for AIDS Relief (PEPFAR) has supported implementation and maintenance of health information systems for HIV/AIDS and related diseases, such as tuberculosis, in numerous countries. As the COVID-19 pandemic emerged, several countries conducted rapid assessments and enhanced existing PEPFAR-funded HIV and national health information systems to support COVID-19 surveillance data collection, analysis, visualization, and reporting needs. We describe efforts at the US Centers for Disease Control and Prevention (CDC) headquarters in Atlanta, Georgia, USA, and CDC country offices that enhanced existing health information systems in support COVID-19 pandemic response. We describe CDC activities in Haiti as an illustration of efforts in PEPFAR countries. We also describe how investments used to establish and maintain standards-based health information systems in resource-constrained settings can have positive effects on health systems beyond their original scope.

The value of community-integrated health information exchanges: three recent examples from El Paso, Texas.

The foundational role of health information exchanges (HIEs) is to facilitate communication between clinical partners in real time. Once this infrastructure for the secure and immediate flow of patient information is built, however, HIEs can benefit community public health and clinical care in myriad other ways that are in line with their mission, goals, patient privacy, and funding structures. We encourage the development of community-integrated HIEs and list specific steps that can be taken toward community integration. We give three examples of those steps in action from a community HIE in El Paso, TX. Each local partnership, in combination with technology innovation, resulted in the development of informatics tools to address community health needs and generated long-term benefits, especially for the most vulnerable patients. Two examples relate to different aspects of the COVID-19 pandemic and a third to the Afghan refugee evacuation.

The Role of Telehealth and Clinical Informatics in Data Driven Primary Care Redesign.

Clinical informatics linked inpatient and emergency department use to clinical data to evaluate utilization for population segments. Trend analysis demonstrates how remote registered nurse care management and the COVID-79 pandemic reduced emergency department utilization in adult populations with high social needs.

Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR).

BACKGROUND: Referral linkages are crucial for efficient functioning of primary health care (PHC) systems. Fast Healthcare Interoperability Resource (FHIR) is an open global standard that facilitates structuring of health information for coordinated exchange among stakeholders. OBJECTIVE: The objective of this study is to design FHIR profiles and present methodology and the profiled FHIR resource for Maternal and Child Health referral use cases in Ebonyi state, Nigeria-a typical low- and middle-income country (LMIC) setting. METHODS: Practicing doctors, midwives, and nurses were purposefully sampled and surveyed. Different referral forms were reviewed. The union of data sets from surveys and forms was aggregated and mapped to base patient FHIR resource elements, and extensions were created for data sets not in the core FHIR specification. This study also introduced FHIR and its relation to the World Health Organization's (WHO's) International Classification of Diseases. RESULTS: We found many different data elements from the referral forms and survey responses even in urban settings. The resulting FHIR standard profile is published on GitHub for adaptation or adoption as necessary to aid alignment with WHO recommendations. Understanding data sets used in health care and clinical practice for information sharing is crucial in properly standardizing information sharing, particularly during the management of COVID-19 and other infectious diseases. Development organizations and governments can use this methodology and profile to fast-track FHIR standards adoption for paper and electronic information sharing at PHC systems in LMICs. CONCLUSIONS: We presented our methodology for profiling the referral resource crucial for the standardized exchange of new and expectant moms' information. Using data from frontline providers and mapping to the FHIR profile helped contextualize the standardized profile.

Daily Visualization of Statewide COVID-19 Healthcare Data

To manage a localized outbreak or global pandemic like COVID-19, Public Health agencies (PH) and health systems utilize a variety of information systems. Although existing PH information systems enable capture of data on laboratory-confirmed cases of COVID-19, the current pandemic has illuminated several deficits in the existing U.S. information infrastructure, including gaps in access to and visualization of near-real-time (daily) impacts to the healthcare system. To address these gaps, we leveraged our state-wide health information exchange-derived dataset that represents nearly all healthcare facilities in Indiana. The resultant dashboard has evolved to present data on hospitalization, emergency department utilization, and other metrics of interest to PH and a broader constituency across the state.

Using FHIR to Support COVID-19 Vaccine Safety Electronic Case Reports in America.

During the COVID-19 pandemic, the Pan American Health Organization (PAHO) promoted several activities to strengthen the countries' emergency response. Vaccines represented a breakthrough in the pandemic evolution, even though they have not been equitably distributed. As most vaccines have received emergency authorizations for their timely delivery, vaccine safety surveillance has been highlighted for detecting early signals of potential adverse events following immunization (AEFI, also known as ESAVI). The objective of this article is to share the different steps, methodologies, and preliminary results of a regional policy to strengthen the ESAVI surveillance system in the Americas, including the adoption of HL7 FHIR for health information exchange between countries and PAHO.

Improvement of the Japanese healthcare data system for the effective management of patients with COVID-19: A national survey.

OBJECTIVE: The burden of data entry in public platforms used for reporting patients with novel coronavirus disease 2019 (COVID-19) is a challenge in the healthcare setting. The key to mitigating the burden of data entry is system integration and elimination of double data entry. In addition, the linkage between public platforms and electronic medical records (EMRs) involves external networks, which are an important target for security management. The purpose of this study was to elucidate the status and challenges of infrastructure for continuous data reporting from hospitals in Japan. MATERIALS AND METHODS: An online survey of Japanese care delivery institutions was conducted from January 25 to February 22, 2021, to obtain data on the admission of patients with COVID-19, use of information infrastructures, and status of network connections with external organizations. The survey request was distributed to each care delivery institution by Japanese health authorities. RESULTS: Of the care delivery institutions that responded to the survey, 53.9% treated patients with COVID-19. Of these institutions, 73.3% used EMRs. 57.8% of the EMRs were connected to an external network. The purpose of connecting to the external network was to contribute to regional health information-sharing with other hospitals (22.0%), report online medical insurance claims (27.5%), and conduct intrahospital system maintenance (61.5%). A frequent concern about connecting an EMR to an external network was data leakage. DISCUSSION: In cases where the frequency of reporting patients with COVID-19 is high, health authorities should provide information regarding anti-data-leakage measures and coordinate frameworks for efficient, sustainable data collection. CONCLUSIONS: We obtained information on existing infrastructures for patient data sharing among care delivery institutions and public health authorities. Our findings may be referenced by the government to make informed decisions about investments.

Reopen Offline Business during a Pandemic? Characterization of Health Certificate Exchange for Human Movement Management

The COVID-19 pandemic has significantly restricted the regular offline business activities. Nevertheless, as certain offline business activities are still indispensable, to conduct offline business under pandemic control becomes a valuable research question. This paper addressed this problem by studying business movement management based on health certificate exchange. We first observed three patterns of health certificate exchange multiplicity that serve as a basis for business movement management. Then, we reviewed published literature along two orthogonal directions, health certificates and exchange systems. We studied different health certificates published during the COVID-19 pandemic to identify the categories of health certificates and their characteristics. Meanwhile, we further studied different design paradigms and characteristics of health certificate exchange systems. Last, we mapped our findings on health certificate exchange into the four challenges of movement management systems in a pandemic, namely flexible controllability, scalable accessibility, adaptive reusability, and spatiotemporal traceability, and conceptualized how such the requirements should be achieved and a complete system should operate. © 2021 IEEE.

The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform.

OBJECTIVE: Learning healthcare systems use routinely collected data to generate new evidence that informs future practice. While implementing an electronic health record (EHR) system can facilitate this goal for individual institutions, meaningfully aggregating data from multiple institutions can be more empowering. Cosmos is a cross-institution, single EHR vendor-facilitated data aggregation tool. This work aims to describe the initiative and illustrate its potential utility through several use cases. METHODS: Cosmos is designed to scale rapidly by leveraging preexisting agreements, clinical health information exchange networks, and data standards. Data are stored centrally as a limited dataset, but the customer facing query tool limits results to prevent patient reidentification. RESULTS: In 2 years, Cosmos grew to contain EHR data of more than 60 million patients. We present practical examples illustrating how Cosmos could further efforts in chronic disease surveillance (asthma and obesity), syndromic surveillance (seasonal influenza and the 2019 novel coronavirus), immunization adherence and adverse event reporting (human papilloma virus and measles, mumps, rubella, and varicella vaccination), and health services research (antibiotic usage for upper respiratory infection). DISCUSSION: A low barrier of entry for Cosmos allows for the rapid accumulation of multi-institutional and mostly de-duplicated EHR data to power research and quality improvement queries characteristic of learning healthcare systems. Limitations are being vendor-specific, an "all or none" contribution model, and the lack of control over queries run on an institution's healthcare data. CONCLUSION: Cosmos provides a model for within-vendor data standardization and aggregation and a steppingstone for broader intervendor interoperability.

Complementary Blockchain-Based Privacy Protection for Covid-19 Contact Tracing

Fighting any pandemic outbreak begins with health authorities already behind time. They are required to locate, isolate and treat infected individuals while tracking possibly infected ones. In the case of Covid-19, the high reproductive number of the virus necessitates that all contacts of an infected individual be found within the shortest possible time to slow the rate of spreading. This presents multiple challenges because of the highly invasive nature of tracing activities which demand the mobility history of patients. Patients may be unwilling to cooperate or may be unable to communicate if the infection has advanced to the point where critical care is necessary. To speedily locate contacts of an infected individual, we propose using communications data logs from telecommunications operators. We employ a modified directed graph to determine which other individuals have been in close proximity to an infected individual in a specific frame of time. We then generate a contact graph and place it in a secure offline storage platform. We employ Smart Contracts to control access to the data while the blockchain keeps records of the provenance of all data and transactions. We find this method of conducting the contact tracing and protecting the resulting data more secure and pliant to the privacy laws that regulate the handling of sensitive personal data. © 2021 IEEE.

The Social Data Foundation model: Facilitating health and social care transformation through datatrust services

Turning the wealth of health and social data into insights to promote better public health, while enabling more effective personalized care, is critically important for society. In particular, social determinants of health have a significant impact on individual health, well-being, and inequalities in health. However, concerns around accessing and processing such sensitive data, and linking different datasets, involve significant challenges, not least to demonstrate trustworthiness to all stakeholders. Emerging datatrust services provide an opportunity to address key barriers to health and social care data linkage schemes, specifically a loss of control experienced by data providers, including the difficulty to maintain a remote reidentification risk over time, and the challenge of establishing and maintaining a social license. Datatrust services are a sociotechnical evolution that advances databases and data management systems, and brings together stakeholder-sensitive data governance mechanisms with data services to create a trusted research environment. In this article, we explore the requirements for datatrust services, a proposed implementation—the Social Data Foundation, and an illustrative test case. Moving forward, such an approach would help incentivize, accelerate, and join up the sharing of regulated data, and the use of generated outputs safely amongst stakeholders, including healthcare providers, social care providers, researchers, public health authorities, and citizens.

Notifiable diseases interoperable framework toward improving Iran public health surveillance system: Lessons learned from COVID-19 pandemic.

BACKGROUND: Direct transmission of notifiable disease information in a real-time and reliable way to public health decision-makers is imperative for early identification of epidemiological trends as well as proper response to potential pandemic like ongoing coronavirus disease 2019 crisis. Thus, this research aimed to develop of semantic-sharing and collaborative-modeling to meet the information exchange requirements of Iran's notifiable diseases surveillance system. MATERIALS AND METHODS: First, the Iran's Notifiable diseases Minimum Data Set (INMDS) was determined according to a literature review coupled with agreements of experts. Then the INMDS was mapped to international terminologies and classification systems, and the Health Level seven-Clinical Document Architecture (HL7-CDA) standard was leveraged to define the exchangeable and machine-readable data formats. RESULTS: A core dataset consisting of 15 classes and 96 data fields was defined. Data elements and response values were mapped to Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) reference terminology. Then HL7-CDA standard for interoperable data exchange were defined. CONCLUSION: The notifiable disease surveillance requires an integrative participation of multidisciplinary team. In this field, data interoperability is more essential due to the heterogeneous nature of health information systems. Developing of INMDS based on HL7-CDA along with SNOMED-CT codes offers an inclusive and interoperable dataset that can help make notifiable diseases data more comparable and reportable across studies and organizations. The proposed data model will be further modifications in the future according probable changes in Iran's notifiable diseases list.

Letter to Editor (Response from author): Toward a universal electronic health record system.

Health information exchange (HIE) has mostly emerged as centralized data hubs that can pass data requests from one subscribing healthcare institution to another. Using traditional health information systems (HISs) with different technologies in hospitals leads to usability and incompatibility issues because of islands of information. This paper discusses shifting from HIE into an integrated universal health information infrastructure. Migration to such integrated universal electronic health records architecture could support real-time HIE and advanced modern big data analytics. However, there are various standards and technologies to facilitate HIS integration, a significant amount of efforts is still needed.

Utilizing a health information exchange to facilitate COVID-19 VA primary care follow-up for Veterans diagnosed in the community.

The use of alerts from the Bronx RHIO, a health information exchange (HIE) to identify James J. Peters VAMC patients diagnosed with COVID-19 in the community was described to facilitate COVID-19 VA primary care follow-up. COVID-19 hospitalization and testing alerts were delivered on a Bronx RHIO facility report. VA COVID-19 follow-up care by telephone and video was guided by local COVID-19 clinical pathways, electronic health record (EHR) templates, and tracking through a database. VA received 180 RHIO alerts for 111 unique patients, and 88 had positive non-VA testing from March to June 2020. 41% of the 88 had non-VA admissions and 23% died. 63% received VA primary care follow-up of COVID-19 symptoms documented by custom EHR templates. The HIE identified 11% of the facility COVID-19 patients. HIE alerts can be used to identify facility COVID-19 patients diagnosed in the community and facilitate follow-up by their VA primary care teams.

Association of COVID-19 With Race and Socioeconomic Factors in Family Medicine.

INTRODUCTION: Recent data demonstrated that socioeconomic, environmental, demographic, and health factors can contribute to vulnerability for coronavirus 2019 (COVID-19). The goal of this study was to assess association between severe acute respiratory syndrome coronavirus (SARS CoV-2) infection and demographic and socioeconomic factors in patients from a large academic family medicine practice to support practice operations. METHODS: Patients referred for SARS CoV-2 testing by practice providers were identified using shared patient lists in the electronic health records (Epic). The Health Information Exchange (CRISP) was used to identify additional practice-attributed patients receiving testing elsewhere. RESULTS: Compared with white non-Hispanic patients, the odds of COVID-19 detection were higher in black non-Hispanic (odds ratio [OR] = 1.75; 95% CI, 1.18-2.59, P = .0052) and Hispanic patients (OR = 5.40; 95% CI, 3.11-9.38, P < .0001). The latent class analysis revealed additional patterns in health disparities. Patients living in the areas with Area Deprivation Index 8-10 who were predominantly black had higher risk for SARS CoV-2 infection compared with patients living in less socioeconomically deprived areas who were predominantly white (OR = 1.68; 95% CI, 1.25-2.28; P = .0007). CONCLUSION: Our data provide insight into the association of COVID-19 with race/ethnic minority patients residing in highly socioeconomically deprived areas. These data could impact outreach and management of ambulatory COVID-19 in the future.