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Unspecified Diagnosis Codes Can Have Significant Financial Impacts

Clinicians have on average over five hundred common diagnoses on their picklist and use an average of nine hundred diagnosis codes every day. Find out how you can help manage the vast number of codes, improve your clinical diagnosis process, decrease queries and maximize your reimbursement.

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

In order for healthcare to be safe, effective, patient centered, timely, efficient, and equitable,the adoption of information technology is critical.Only when you can merge clinical, claims, and patient-collected data can you generate a holistic view of the patient and his or her care over time.

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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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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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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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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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Understanding the Health Language SNOMED CT® to ICD-10 Maps

THE PROBLEM: SNOMED CT® / ICD-10-CM MAPS.  As specified by Meaningful Use Stage 2, the 2014 edition of EHR certification will require problem list entries to have SNOMED CT® encoding. Further, on October 1, 2014, diagnoses must be encoded in ICD-10-CM for billing. After that time personnel and systems will need to convert problem list […]

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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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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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Achieving SNOMED CT® Compliance for Better Care Delivery

The healthcare industry faces a critical question of semantics. As meaningful use (MU) converges with ICD-10 and the evolving performance-based revenue landscape, one important issue for health IT vendors and providers alike is the need for a common clinical vocabulary.

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