Health Language Blog

Keeping Up With COVID-19

Posted on 03/25/20 | Comments

New COVID-19 Related Codes Now Available

With the outbreak of the COVID-19 virus, the world is hyper-focused, as it should be, on the caregivers and the population of patients contracting the virus.  However, we must also keep in mind the need for clear and concise documentation regarding the diagnosis, testing, and tracking of the spread of the virus.

There are hundreds of medical terminologies that document every step of the health care process through admission, testing, treatment, discharge, and billing.  So when there is a large health event or worldwide pandemic, like COVID-19, it requires quick changes and updates to those terminology sets.  This is required to ensure that health care providers have the ability to accurately document, track, and treat their patients in a timely fashion. 

For the benefit of healthcare organizations looking to understand what’s changed and how to manage this pandemic, I’ve taken the opportunity to summarize changes to the billing and coding sets, their effective dates, provided links to the various standards bodies, and summarized how these codes will benefit clinicians who are tasked with documenting the COVID-19 condition at the point-of-care.

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Topics: ICD-10, Standard terminologies, LOINC, SNOMED CT, standards, COVID-19, Coronavirus

Webinar Recap: Applying AI in Healthcare: Practical Applications of Clinical NLP to Drive Value in Your Organization

Posted on 03/11/20 | Comments

AI in Healthcare:  Practical Applications of Clinical NLP

While there’s been a lot of buzz about the promise of artificial intelligence (AI) in healthcare, health leaders are recognizing that AI holds the potential to diagnose and treat disease, improve processes, and better manage underlying operational, financial, and patient health data through which they can innovate and maximize value.

Specifically, within healthcare, Natural Language Processing (NLP), a specific branch of AI, has quickly proven value by enabling healthcare organizations the ability to efficiently leverage unstructured data, which represents nearly 80% of all healthcare data.

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Topics: NLP, Natural Language Processing, unstructured text, quality measure reporting, clinical natural language processing, cnlp, sepsis detection, risk adjustment

The Strategic Role of Health Plans and Providers in the Opioid Battle

Posted on 01/29/20 | Comments

Is your organization equipped with the right code sets?

The opioid crisis remains a critical public health issue. Every day more than 130 die from overdosing on opioids, and current industry estimates suggest that the total economic burden related to misuse alone in the United States is $78.5 billion a year, including the costs of healthcare, lost productivity, addiction treatment, and criminal justice involvement.

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Topics: value sets, MIPS, CMS, quality measure reporting, HEDIS, opioid epidemic, opioid crisis, PQA Quality Measures

From Data to Intelligence: The Path to Improving Plans’ Performance

Posted on 01/08/20 | Comments

The Value of AI in Healthcare 

There’s been a lot of buzz about the promise of artificial intelligence (AI) in healthcare. We’re moving rapidly from hype to real-world use cases in which health leaders recognize that AI holds the potential to diagnose and treat disease, improve processes, and better manage underlying operational, financial, and patient health data through which they can innovate and maximize value. 

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Topics: Health Plans, NLP, unstructured text, quality measure reporting, clinical natural language processing, patient risk, cnlp, Medicare Advantage, HEDIS, Star Ratings, member health

Is Your Organization Protecting Sensitive Patient Information?

Posted on 12/04/19 | Comments

Technology is a critical enabler of efforts to mobilize data and promote greater stakeholder collaboration. As healthcare organizations deploy frameworks to support meaningful data sharing and greater care coordination across the continuum, one area that must not be overlooked is the compliant protection of sensitive health information.

Federal regulations outlined in 42 CFR Part 2 (Confidentiality of Substance Use Disorder Patient Records) limit the use and disclosure of sensitive health information and identifying information. This means healthcare organizations must identify and filter data related to substance abuse to comply, but other regulations also add the need to include mental health, family planning, genetic testing, HIV, and other sexually transmitted diseases (STDs) to protect patient and member confidentiality. 

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Topics: Sensitivity Codes, 42 CFR Part 2, Mental Health, sensitive health information

Social Determinants of Health (SDoH) … or maybe, Socially Dominating Our Health Information!

Posted on 11/14/19 | Comments

Since 2002, researchers have attempted to assess the impact of social factors on health outcomes. Recent studies estimate that traditional medical care accounts for only 10-20% of an individual’s health, while the remaining 80-90% is due to SDoH.(1)

Regardless of where you sit on the political spectrum, I think we can all agree on some fundamental facts like the rising costs of healthcare and cost of living, economic disparities, mental health concerns, food insecurity, and shortage of housing, just to name a few. These concerns all fall into a category called social determinants of health (SDoH). Given the power this category has on healthcare costs and outcomes, everyone in healthcare is trying to figure out how to address these "social determinants."

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Topics: SDOH, Social Determinants of Health

Webinar Recap: Investing for the Future:  The ONC and CMS Proposed Rules on Interoperability

Posted on 10/21/19 | Comments

The proposed rules on interoperability released earlier this year by the Office of the National Coordinator (ONC) and Centers for Medicare & Medicaid Services (CMS) have generated a lot of industry chatter. More than 1,000 organizations submitted comments addressing the draft rules, which many believe are very ambitious in scope. While the two regulatory bodies have much to consider, one thing is certain: the final rules will create a new paradigm for health data management and governance in today’s healthcare organizations that is intended to improve interoperability and empower patients.

A recent webinar hosted by Health Data ManagementInvesting for the Future: The ONC & CMS Proposed Rules on Interoperability—explored the critical elements in the proposed rule and how they could impact payers, providers, and health IT vendors. Mark Fuchs, director of market research for Wolters Kluwer Health Language Solutions and Bob Hussey, founder and principal of RGH Health Consulting, LLC, reflected on the industry’s goals in advancing access to data and interoperability and the steps payers and providers can take to prepare and invest in their data today.

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Topics: medical data, semantic interoperability, interoperability, CMS, government, ONC, quality measure reporting, data blocking, proposed rules

Your Data is the Problem

Posted on 09/25/19 | Comments

Welcome to the final installment of our four-part blog series dedicated to the importance of data mapping.  If you are just now tuning in, be sure to check out the last three blogs discussing the importance of lab, medication, and allergy mapping. 

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Topics: data normalization, interoperability, mapping, clinical decision support, value-based care, enabling interoperability

The Crack Down on Silos of Patient Data: CMS and ONC Interoperability Rules Hit Health Plans

Posted on 08/30/19 | Comments

Earlier in the year, the Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) proposed rules on interoperability, data blocking, and other activities as part of implementing the 21st Century Cures Act. The proposed separate but related rules would require that patients have easy access to their health data. As described by ONC, the rule would “support seamless and secure access, exchange, and use of electronic health information.”

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Topics: medical data, interoperability, government, ONC, data blocking

Are You Allergic to Messy Data?

Posted on 08/21/19 | Comments

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Topics: semantic interoperability, data normalization, interoperability, mapping, quality reporting, Natural Language Processing, Machine learning, clinical decision support, quality measure reporting, value-based care, enabling interoperability