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How to Use Standardized Healthcare Terminologies to Meet Your Quality Care Goals

This white paper is intended to help HIM professionals better understand the standard terminologies needed to meet the increasing need for semantic interoperability to cross the quality chasm. We discuss the common standard code sets used in the clinical setting, and the history, governing bodies, and maintenance of those standards as well as when you […]

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Addressing the Documentation Challenge for Clinicians: Provider Friendly Terminology

To support Meaningful Use, clinicians will need to create SNOMED CT®-encoded problem lists and ensure accurate ICD-9-CM and ICD- 10-CM diagnosis codes. The proper encoding of these problem lists would become a cumbersome endeavor if clinicians had to know the underlying complexity of SNOMED and ICD. Clinicians should consider deploying a Provider Friendly Terminology solution that ensures problems, procedures, and diagnoses […]

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Terminology Requirements for Meaningful Use, Stages 1 through 3

This chart outlines electronic health record (EHR) requirements in the Meaningful Use program that necessitate consideration for healthcare terminologies. Although the Meaningful Use program is near its end, the Centers for Medicare & Medicaid Services (CMS) will continue to strengthen requirements for documenting, standardizing and sharing data within, and amongst, EHRs through other programs such […]

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Data Normalization: Common Use Cases and Terminology Domain Challenges

The rapid evolution of health IT systems has resulted in significant interoperability problems, which stem from the presence of numerous local and standardized clinical terminologies. A key ingredient for a data normalization solution should include mapping algorithms for labs, drugs, and problems and diagnoses that can translate disparate data to support the needs of data […]

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Managing Value Sets: The Building Blocks for Your Analytics Initiatives

Ensuring that patient information is accurately codified is critical to making informed decisions regarding care and utilization management, minimizing re-admissions, and ensuring medical adherence to treatment plans. Code groups, also called value sets, are defined sets of codes that represent clinical concepts derived from one or more standard terminologies such as SNOMED CT®, LOINC®, ICD-10, ICD-9, and RxNorm. For […]

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Merging Claims and Clinical Data: CPT to LOINC Maps

Increasingly, payers are relying on laboratory data to support quality and reporting initiatives, analytics, and population health strategies. Maps between lab orders and lab results can assist health plans to identify and close gaps between claims from providers and lab results received from a variety of sources including hospitals, national lab providers, and HL7 messages. […]

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Ensuring Clinical Accuracy During ICD-10 Medical Policy Remediation

95% of policies we have reviewed contained a key medical concept that was lost or assumed in translation from ICD-9 to ICD-10 using GEMs. Because of this, the medical intent is lost. With real-world examples and analyses, you’ll see how to avoid claim rejections and payment losses when remediating your medical policies.

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Achieving Advanced Interoperability and Analytics: The Importance of Data Quality and Governance

As federal regulatory initiatives continue to encourage information-sharing capabilities inside and outside a healthcare organization, the C-level is increasingly finding that an Enterprise Terminology Management strategy is critical to success.

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Meaningful Use Stage 2 Certification: A Guide for EHR Product Managers

The federal government’s Meaningful Use program aims to boost the adoption of electronic health records, providing financial incentives to healthcare providers who adhere to the program’s standards. To qualify for those payments, healthcare providers must deploy “certified” EHR technology, yet the task of creating such a product is complex.

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Data Normalization: The Foundation of Forward-Thinking Initiatives

Terminology is core to everything in healthcare. Unfortunately, the explosive growth in healthcare IT has resulted in patient data being scattered across an array of rapidly proliferating IT systems—each with their own way of representing clinical terms, creating an environment of data locked in silos. This terminology barrier must be overcome if we are to recognize the national […]

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