Validation and Testing of Fast Healthcare Interoperability Resources Standards Compliance: Data Analysis

As indicated by the JASON report , the implications and benefits from a truly open digital health care architecture are wide ranging, from enabling individual patients to obtain, share, and authorize who can view their data, to population health analytics and research. Currently, data and exchange standards in health care do not adequately ensure out-of-the-box interoperability, chiefly due to the complexity and lack of identical interpretations of the published standards by health IT software developers. Rigorous testing and validation will help move the US health care system in the direction of open, accessible, patient-centric care.

The objective of this research was to examine whether or not the use of validation and test tools, specifically Crucible and Touchstone, had any impact on vendor compliance with the FHIR specification and, by extension, interoperability.

The full article can be downloaded below.  

Artificial intelligence (AI), and its sub-disciplines, machine learning (ML) and deep learning (DL), are beginning to play a significant role in healthcare. As AI moves out of research labs and into real-world applications, it is becoming a disruptive force in transforming patient care. These technologies, coupled with affordable data storage and computational power, enable healthcare organizations to analyze an immense volume and variety of data. Intelligence allows for progressively deeper insights which lead to proactive care, reduced future risk, and streamlined work processes. AI technologies are providing innovative solutions for precision medicine, organizational efficiency, and improved health outcomes.

Due to the significant volume of data created during patient care, the healthcare industry is well positioned to take advantage of the advancement and commoditization of computer algorithms and hardware. AI enables more automated decision-making on important data sets emerging from the Internet of Things (IoT), electronic health records (EHRs), and patient-generated health data. AI also gives machines the ability to mimic human behavior, an increasingly valuable feature in an industry that is experiencing high costs, high rates of physician burnout, and an increased focus on the patient experience.

On September 6, 2018, eHealth Initiative Foundation and Booz Allen Hamilton hosted a multi-stakeholder roundtable meeting to discuss expert opinions on the challenges and opportunities for AI and ML in healthcare. The meeting convened senior executives from provider, government, technology, pharmaceutical, clinical research, and professional organizations, representing radiology, pathology, cardiology, and other groups. This brief addresses the state of the field and includes examples of how AI and ML are being used within the industry; the challenges and barriers to the adoption of AI; current federal government initiatives; and where AI and ML may be headed in healthcare’s future.

Presentation slides by Jennifer Hall, Chief, Institute for Precision Cardiovascular Medicine, American Heart Association at the September 6, 2018 Artificial Intelligence and Machine Learning Executive Roundtable Meeting. The presentation reviewed initiatives at the AHA's Institute for Precision Cardiovascular Medicine, including their grant portfolio, One Brave Idea, Precision Medicine Platform, My Research Legacy, and Center for Accelerated Drug Discovery.

Implementing Blockchains for Efficient Healthcare: A Systematic Review

The scattered nature of sensitive health information can bring about situations where timely information is unavailable, worsening health outcomes. Furthermore, as patient involvement in healthcare increases, there is a growing need for patients to access and control their data. Blockchain is a secure decentralised online ledger that could be used to manage electronic health records efficiently, and so improve health outcomes by enabling interoperability.

The full article can be downloaded below.  

NIH programs shed light on gene variants and their connections to health and disease

Programs supported by the National Institutes of Health are establishing which genes and genomic variants play a role in human disease, enabling their use in genomic medicine and research. NIH’s Clinical Genome Resource (ClinGen(link is external)) and ClinVar programs address a major barrier to incorporating genomic medicine into healthcare, which is a lack of evidence about the relationship between gene variants and diseases. A special issue of Human Mutation(link is external), published on Oct. 12, highlights the broad array of advances made through these programs, which work in concert to advance knowledge connecting human genomic variation to human health.

The full news release can be viewed at this link.  

Slides from September 26, 2018 eHealth Initiative Prior Authorization Workshop by Jocelyn Keegan, Payer Practice Lead, Point of Care Partners.

Presentation reviews near term improvement opportunities and how value based care shifts the role of authorization.

U.S. National Health IT Week (NHIT Week) is a nationwide awareness week focused on catalyzing actionable change within the U.S. health system through the application of information and technology. Founded by HIMSS and the Institute for e-Policy in 2006, the week-long celebration is comprised of partner-driven activities and events led by the efforts of national health stakeholders. Participants range from the Administration, congressional, federal and state agencies, providers, non-profit organizations and more. Virtually, in Washington DC and beyond, National Health IT Week stakeholders collaborate towards actionable outcomes which demonstrate the power information and technology has to transform health in the U.S., and its wide-reaching global impact.

The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature

Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records’ use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012–10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.

The full article can be downloaded below.  

October 2018 report from the PEW Charitable Trusts.

This report lays out Pew’s research findings and recommendations, including steps that can be taken in the near term to improve patient matching and the infrastructure needed for more robust progress in the medium term and long term.