Population Health/Analytics

Unlock your data by normalizing your clinical or claims based data into standard terminologies and ensuring consistent representations of clinical concepts.

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Meaningful Use

Improve Problems and Diagnoses Search and Documentation within your EHR to increase clinician satisfaction and ease the transition to ICD-10.

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Use sophisticated claims analytics and mapping capabilities to drive informed business decisions, streamline systems remediation efforts, and gaining post transition insights.

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  • Avoiding One of the Most Common Analytics Pitfalls By Christy Green and Cheryl Mason

    Summary: Today’s hospital and health system executives cannot help but hear the clamor to advance data-driven care delivery models focused on proactive management of populations. Pressed by a sense of urgency to position for the future of risk-based reimbursement arrangements, executives can often overlook a cornerstone element to success with analytics: data normalization. In fact, it is not uncommon for a health system to invest millions of dollars in an analytics solution, only to realize later that the reports being produced are inaccurate or meaningless due to missing or poor quality data.

    Date: 3/22/2016

  • National Efforts Take Aim at Reaching Semantic Interoperability By Greg Slabodkin Health Data Management

    Summary: As the healthcare industry grapples with the daunting challenges of achieving interoperability, stakeholders are focused on solving the fundamental problem of ensuring that all parties “speak the same language,” through the use of common data models and vocabularies. Semantic interoperability, the ability of two or more healthcare systems to share clinical information and use it meaningfully, is a critical requirement for enabling population health management and the rapidly approaching transition from fee-for-service to value-based care models.

    However, the lack of a universal terminology standard is a major barrier to communication between different electronic health record systems and the ability to derive clinical meaning from EHR data imported or queried from elsewhere.

    Date: 3/3/2016

  • Beyond Words: Terminology’s Role in Meaningful Use By Jason Wolfson For The Record

    Summary: As a focal point of national quality initiatives, meaningful  use (MU) is unfolding across the industry as a strategic effort to increase the  momentum of health information exchange (HIE). The initiative accomplishes this  goal by progressively laying a foundation of attestation requirements for the  collection, exchange, and reporting of data using certified EHR technology  (CEHRT).

    As the MU timeline matures, the stakes for meeting  attestation requirements become increasingly high. More rigorous requirements  related to HIT terminology standards are introduced with each stage as critical  steps to positioning the industry for accurate and consistent exchange of  patient information. The adoption of such industry-respected clinical  vocabularies as RxNorm, SNOMED CT, and LOINC provide the needed infrastructures  for improving communication between disparate IT systems, enabling better  sharing of critical patient data and ultimately leading to better  decision-making and outcomes.

    While the burden for designing infrastructures that meet  CEHRT requirements rests with the vendor community, it’s important to note that  solely adopting a certified EHR does not qualify a provider to receive  incentive payments. Providers must successfully attest to MU of the certified  EHR. The interoperability challenges for attestation go much deeper than what  is provided by the CEHRT. For example, the burden of integrating structured  data from systems outside of the CEHRT rests with the provider.

    Going forward, providers will need to implement enterprise  terminology management strategies to comply with MU terminology standards and  to advance interoperability. It’s a complex undertaking for the average  resource-strapped IT department. For this reason, many facilities are turning  to advanced technology and automation to lay a foundation that supports  semantic interoperability and MU compliance.

    Date: 11/2015

  • Health IT News: Data Normalization: A foundational step to achieving Triple Aim goals

    Summary:  Actionable data is critical to advancing healthcare’s Triple Aim: improving patient experience, population health and costs. Data accuracy for analytics and information sharing must exist to accomplish these goals.

    Interoperability is a focal point of national efforts to advance information sharing and data analytics, but lack of a common clinical vocabulary is currently a primary roadblock to forward momentum. Until a foundation for semantic interoperability is laid that standardizes clinical terminology across disparate systems, success with such care delivery models as population health management, health information exchange and accountable care organizations will be limited.

    Industry standards such as SNOMED CT, LOINC and RxNORM are important steps towards achieving this goal, but there is currently no existing standard that addresses all clinical terminology. Patient data shared between health information systems must be “cleaned” before data warehousing and analytics strategies can be realized.

    Simply put, data must be normalized to remove semantic ambiguity.

    Date:  October 8, 2015

  • Health Payer News: The Quest for a Single Source of Terminology Truth

    Summary: As federal regulatory initiatives up the ante on information sharing capabilities inside and outside a healthcare organization, the C-Suite is increasingly finding that a comprehensive terminology management strategy is critical.

    Lack of a common clinical vocabulary across disparate systems is a primary roadblock to greater collaboration between payers and providers and the greater goals of health information exchange and accountable care.

    Like many health systems, Wisconsin-based Dean Health Plan faced the challenge of managing code sets across numerous departments and disparate IT systems, each with their own inherent language and clinical terminology infrastructure. Largely governed by error-prone manual processes and workflows, the organization faced inevitable conflicts regarding terminology intake, management and distribution and lacked a formal process for governance and accountability.

    Date: April 17th, 2015

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