info@ehidc.org

 202-624-3270

Member News

Healthix is Working to Turn Data into Information

Healthix accumulates data from across the region from a diverse range of facility types. Many of these facilities have in the past used local codes in their EHR for labs, diagnosis, and other key data elements. With efforts at the federal level, statewide initiatives and growing value based care models, aligning the data into standardized codes (eg. LOINC, SNOMED, ICD10) is now essential. Standardized codes allows data to be understood across all facilities.

Bradley Merrill Thompson Quoted in “Use This App and Call Me in the Morning: The Promise of Prescription Digital Therapeutics”

Bradley Merrill Thompson, Member of the Firm in the Health Care & Life Sciences practice, in the firm’s Washington, DC, office, was quoted in Seeking Alpha, in “Use This App and Call Me in the Morning: The Promise of Prescription Digital Therapeutics.

EHNAC Updates Interoperability Criteria, Health IT Standards

EHNAC, a health IT data standards accreditation organization, has released updated criteria for its programs to support new interoperability regulations. EHNAC's newly enhanced accreditation programs are designed to ensure compliance, mitigate risk, and address contingency planning as organizations address the ever-changing best practices and legislative and regulatory revisions.

Accenture and Microsoft to Assist Mount Sinai Health System on Five-Year Transformation Journey to Cloud

Accenture will collaborate with New York City’s largest academic medical system to help devise and securely execute its strategic cloud migration of clinical applications, including its Epic electronic health records system. In addition, Accenture will provide hybrid cloud managed services post-migration. The managed services will include around-the-clock server management and support for migrated workloads; storage and backup operations; database support; and automation and analytics.

Identity Resolution as a Top Strategic Imperative to Improve Siloed, Inaccurate Patient Data

A new report published by Verato and Sage Growth Partners sheds light on healthcare executives’ top concerns and strategic priorities in 2022. Most shockingly, 72% of respondents note that they are “concerned” or “extremely concerned” that siloed, inaccurate patient data negatively impacts care quality and the bottom line.

Value Specialty Pharmacy Selects the Inovalon ONE Platform’s Leading SaaS Capabilities

Inovalon, a leading provider of cloud-based platforms empowering data-driven healthcare, announced a multi-year agreement with Value Specialty Pharmacy, an innovative leader in the pharmaceutical industry, providing a continuum of care and specialty medications across 50 states for thousands of patients. This engagement will provide cloud-based capabilities delivered through the Inovalon ONE® Platform and will support Value Specialty’s data-driven strategy to improve clinical and quality outcomes and economics for its patients.

The What’s, When’s and How’s of Home Blood Pressure Monitoring

In this episode, Drs. George Stergiou and Florian Rader discuss the use of home blood pressure monitoring in the diagnosis, management, and treatment of hypertension. This panel will specifically focus on the differences between home and ambulatory blood pressure monitoring, the clinical situations in which these should be utilized, and the interpretation of this data by clinicians. Further, these experts will review how to discuss home blood pressure monitoring with patients and how to address common questions that arise.

A Leap Forward for AI Development

Creating an artificial intelligence (AI) model for a healthcare application which works well at multiple institutions typically requires a large collection of training data acquired from varied sources. Obtaining such large and varied healthcare training datasets can be difficult given the sensitive nature of medical data. Beginning in early 2022, AI-LAB users will be able to participate in federated learning (FL) through AI-LAB to help mitigate these issues. FL enables data from multiple institutions to be used for AI model training without data leaving institutional firewalls.