Health Language Blog

Webinar Recap: How Quality Data is Key to Delivering Value

Posted on 06/13/19 | Comments

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Topics: data normalization, interoperability, mapping, quality reporting, NLP, Natural Language Processing, Reference Data Management, artificial intelligence, Machine learning, clinical decision support, quality measure reporting, value-based care, clinical and claims data, enabling interoperability

Webinar Recap: Quality Data: Three Steps to Simplify Data Governance, Enable Semantic Interoperability, and Enhance Your Reporting and Analytics

Posted on 05/30/19 | Comments

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Topics: data normalization, interoperability, mapping, quality reporting, NLP, Natural Language Processing, Reference Data Management, artificial intelligence, Machine learning, clinical decision support, quality measure reporting, value-based care, clinical and claims data, enabling interoperability

Webinar Recap: Applying AI in healthcare: Challenges, opportunities, and emerging applications

Posted on 11/19/18 | Comments

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Topics: NLP, Natural Language Processing, Reference Data Management, artificial intelligence, Machine learning

Breaking Down the Data Silos: How reference data is the cornerstone of an overall data management strategy

Posted on 05/09/18 | Comments

Providers and payers face growing pressure to control costs, increase profitability, and succeed with value-based care. Healthcare executives must turn to data as their strongest ally to inform decision-making and drive performance improvement. Yet many organizations fail to extract the full value of their data assets due to fragmented operations, ineffective data governance, and IT structural limitations that create data silos across an enterprise.

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Topics: Reference Data Management

Financial Stability in a Fluid Market

Posted on 11/01/17 | Comments

Four Ways to Address Data Management Challenges and Strengthen Your Revenue Cycle

Revenue cycle management can leverage systems and workflows that close gaps, tie up loose ends, and ensure submission of a clean claim. Reference data—representing the coded and uncoded data used across a health system—plays an all-important role in strategies that optimize revenue cycle processes and ensure compliance with industry licensing requirements.

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Topics: revenue cycle management

Three Reasons DSM-5 Mapping Strategies Matter

Posted on 09/07/17 | Comments

The introduction of industry standards such as SNOMED CT, ICD-10, LOINC, and RxNorm is an important step toward achieving the goals of interoperability and information sharing. Yet healthcare organizations still face notable challenges to laying the best frameworks for normalizing data to these standards. Since there is no one standard that addresses all healthcare information, clinical and financial data must be “cleaned” and appropriately mapped to a single source of truth to remove semantic ambiguity.

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Topics: Standard terminologies, Analytics, mapping, DSM-5

Are Your Reports Showing Pregnant Men and Smoking Babies?

Posted on 08/16/17 | Comments

Four Reasons Dirty Data Destroys Healthcare Analytics

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Topics: Analytics, data quality

NLP: Unlocking the potential of unstructured text in healthcare

Posted on 05/30/17 | Comments

Hospitals and health systems are sitting on a wealth of patient information that has potential to transform care delivery. Yet analytics infrastructures designed to fuel performance improvement have traditionally overlooked much of that data because it resides in health IT systems as unstructured free text.

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Topics: NLP, Natural Language Processing, unstructured text

Provider Friendly Terminology: A Better Problem List Strategy

Posted on 05/17/17 | Comments

How to get ahead with access to primary and secondary terms.

Problem lists are not new to healthcare, yet the industry has historically struggled to accurately capture this critical snapshot of patient problems and visit diagnoses. While EHRs now provide an efficient way to gather problem list data, they don’t address the underlying challenge of clean data capture due to the wide variance in terminologies used across the industry.

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Topics: provider friendly terminology, visit diagnosis, problem lists, primary terms, secondary terms

Health Language and MediMobile Partner to Improve the Hospital Revenue Cycle

Posted on 04/27/17 | Comments

It’s no secret that reimbursement is increasingly complex for today’s hospitals and health systems. In truth, a fair amount of billing inaccuracies and missed charge capture has always been part of the bottom-line challenge. But today’s providers simply cannot afford to let any money slip through the cracks as they navigate new value-based care models and take on more risk.

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Topics: revenue cycle management, provider friendly terminology, MediMobile, billing accuracy