hData - A Simple XML Framework for Health Data Exchange

Health data interoperability issues limit the expected benefits of Electronic Health Record (EHR) systems. Ideally, the medical history of a patient is recorded in a set of digital continuity of care documents which are securely available to the patient and their care providers on demand. The history of electronic health data standards includes multiple standards organizations, differing goals, and ongoing efforts to reconcile the various specifications. Existing standards define a format that is too complex for exchanging health data effectively. We propose hData, a simple XML-based framework to describe health information. hData addresses the complexities of the current HL7 Clinical Document Architecture (CDA). hData is an XML design that can be completely validated by modern XML editors and is explicitly designed for extensibility to address future health information exchange needs. hData applies established best practices for XML document architectures to the health domain, thereby facilitating interoperability, increasing software developer productivity, and thus reducing the cost for creating and maintaining EHR technologies.

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Health Information Exchange in Practice

Essentials of Clinical Informatics ◽

10.1093/med/9780190855574.003.0025 ◽

2019 ◽

pp. 264-280

Author(s):

Mark E. Frisse ◽

Karl E. Misulis

Keyword(s):

Health Information ◽

Information Exchange ◽

Data Exchange ◽

Health Information Exchange ◽

Healthcare Delivery ◽

Health Record ◽

Healthcare Data ◽

Electronic Health ◽

Alternative Settings ◽

Collaborative Efforts

Even when restricting the focus of care to hospitals and ambulatory clinics, most individuals seek care from many practitioners operating in different locations and often employing different electronic health records. Early efforts at creating interoperable data exchange among these systems have often disappointed users and administrators. Effective collaboration is a prerequisite for effective healthcare delivery. Even if using different EHRs, every clinician and caregiver should share a common clinical record set and means of communicating to other providers. Recent collaborative efforts among major electronic health record vendors are simplifying exchange of information among hospitals and large clinics, but they have not yet sufficiently addressed the necessary broader exchange of healthcare data among the caregivers in alternative settings and in the home.

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Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality

PLoS ONE ◽

10.1371/journal.pone.0247235 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0247235

Author(s):

Guillermo A. Tortolero ◽

Michael R. Brown ◽

Shreela V. Sharma ◽

Marcia C. de Oliveira Otto ◽

Jose-Miguel Yamal ◽

...

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Health Information ◽

Tobacco Use ◽

Information Exchange ◽

Health Information Exchange ◽

Smoking History ◽

History Of ◽

Race Ethnicity ◽

Electronic Health

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic’s onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient’s encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.

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What Do People Affected by Cancer Think About Electronic Health Information Exchange? Results From the 2010 LIVESTRONG Electronic Health Information Exchange Survey and the 2008 Health Information National Trends Survey

Journal of Oncology Practice ◽

10.1200/jop.2011.000324 ◽

2011 ◽

Vol 7 (4) ◽

pp. 237-241 ◽

Cited By ~ 23

Author(s):

Ellen B. Beckjord ◽

Ruth Rechis ◽

Stephanie Nutt ◽

Lawrence Shulman ◽

Bradford W. Hesse

Keyword(s):

Health Information ◽

Health Care Providers ◽

Information Exchange ◽

Health Information Exchange ◽

Security And Privacy ◽

Care Providers ◽

Electronic Information ◽

Electronic Health ◽

National Trends ◽

Electronic Health Information

Responses to a 2010 survey by LIVESTRONG showed that, compared with the general population, persons affected by cancer had greater enthusiasm for electronic information exchange between patients and health care providers. Especially valued were security and privacy of communication.

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Maturity assessment of Kenya’s health information system interoperability readiness

BMJ Health & Care Informatics ◽

10.1136/bmjhci-2020-100241 ◽

2021 ◽

Vol 28 (1) ◽

pp. e100241

Author(s):

Job Nyangena ◽

Rohini Rajgopal ◽

Elizabeth Adhiambo Ombech ◽

Enock Oloo ◽

Humphrey Luchetu ◽

...

Keyword(s):

Health Information ◽

Information Exchange ◽

Working Group ◽

Data Exchange ◽

Enterprise Architecture ◽

Health Information Exchange ◽

Digital Health ◽

Health Information System ◽

Maturity Level ◽

Technical Standards

BackgroundThe use of digital technology in healthcare promises to improve quality of care and reduce costs over time. This promise will be difficult to attain without interoperability: facilitating seamless health information exchange between the deployed digital health information systems (HIS).ObjectiveTo determine the maturity readiness of the interoperability capacity of Kenya’s HIS.MethodsWe used the HIS Interoperability Maturity Toolkit, developed by MEASURE Evaluation and the Health Data Collaborative’s Digital Health and Interoperability Working Group. The assessment was undertaken by eHealth stakeholder representatives primarily from the Ministry of Health’s Digital Health Technical Working Group. The toolkit focused on three major domains: leadership and governance, human resources and technology.ResultsMost domains are at the lowest two levels of maturity: nascent or emerging. At the nascent level, HIS activities happen by chance or represent isolated, ad hoc efforts. An emerging maturity level characterises a system with defined HIS processes and structures. However, such processes are not systematically documented and lack ongoing monitoring mechanisms.ConclusionNone of the domains had a maturity level greater than level 2 (emerging). The subdomains of governance structures for HIS, defined national enterprise architecture for HIS, defined technical standards for data exchange, nationwide communication network infrastructure, and capacity for operations and maintenance of hardware attained higher maturity levels. These findings are similar to those from interoperability maturity assessments done in Ghana and Uganda.

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