Health Language Blog

3 Ways to Ease the Transition to ICD-10

Posted on 04/08/15 | Comments

Ready or not, the ICD-10 deadline will be arriving shortly.


Topics: ease the transition to icd-10

Are You Ready for the ICD-10 Conversion?

Posted on 04/03/15 | Comments

How many times has your ICD-10 leadership team asked themselves the dreaded question: Are we ready for ICD-10 conversion? With the senate scheduled to vote on a permanent fix of the reimbursement formula for Medicare physicians in a couple of weeks (this was the legislation that delivered the ICD-10 delay last year), October 1, 2015 looks to be the deadline the industry is racing towards.


Topics: ICD-10

An Overview of How to Get Started with a Data Normalization Solution

Posted on 03/18/15 | Comments

A harsh reality of today’s healthcare environment is that providers and payers use a multitude of systems -- each with their own way of representing data. 

A health system may be integrating a hospital bringing a new electronic health record (EHR) system into the network, while maintaining legacy EHR applications. Health systems often grapple with how to accommodate practices using a mix of EHRs.  A health plan, meanwhile, may employ multiple claims systems. In the past, those systems often operated in isolation, using conflicting terminologies to represent clinical data.


Topics: data normalization

How to Increase Clinician Satisfaction By Mapping Clinical Terms to Standards

Posted on 03/12/15 | Comments

Clinicians aren’t coders – or at least they aren’t trained to be. But that doesn’t mean they don’t function as coders in practice. In fact, clinicians typically play the primary role in establishing diagnosis codes, even when they’re backed up by professional coders (in the inpatient setting), and particularly when they don’t (in the ambulatory setting).


Topics: clinical terminology management

3 Benefits of an Enterprise Terminology Management Platform

Posted on 03/03/15 | Comments

Fragmentation is a defining characteristic of today’s healthcare ecosystem.

A health delivery organization may manage 40 or more separate IT systems, each of which has its own clinical terminology content and infrastructure. Those terminology silos make it difficult for organizations to leverage isolated clinical data, which impacts downstream activities such as data analytics. The problem intensifies when a health system seeks to share data with other healthcare partners. In that scenario, the relevant data resides in numerous isolated systems scattered across multiple healthcare organizations.


Topics: enterprise terminology management

Can Value Sets be Used Beyond CQMs?

Posted on 02/27/15 | Comments

Value sets, also called code groups, are essentially bags of codes that represent clinical concepts.

Those sets consist of terms and their associated numerical codes, which are derived from various terminologies such as ICD-10, SNOMED CT®, RxNorm and LOINC®. Each bag, or grouping, of codes could represent a population of patients with a particular disease (myocardial infarction) or a particular class of drug (aspirin).


Topics: CQM

How Enterprise Terminology Management Can Be Used for Clinical Alignment

Posted on 02/12/15 | Comments

Healthcare organizations have deployed myriad healthcare IT systems in recent years, hoping to improve patient outcomes and improve operational efficiencies.

Unfortunately, most of the systems scattered across the healthcare community today are not semantically interoperable. That is, even with EHR certification under “meaningful use”, health IT systems still often use different terminologies to say the same things. The resulting fragmentation hinders communication among systems and makes it difficult for healthcare organizations to create a comprehensive view of clinical data.


Topics: enterprise terminology management

How Caradigm is Leveraging Data Normalization to Enable Population Health

Posted on 02/04/15 | Comments

Population health management seeks to identify at-risk populations, tailor interventions for individuals and measure the clinical impact.

It’s a complex task that relies on the ability to collect and aggregate patient data and use that data to measure the quality of care. The job also calls for health systems to generate reports on those quality measures for internal use and external regulators.


Topics: data normalization

How SNOMED CT Compliance Will Benefit Your Patients

Posted on 01/28/15 | Comments

Historically, a doctor recorded a patient’s medical issues on a problem list included as part of the patient’s paper chart.

Chronic illnesses and major medical issues were included on the list. Such paper records faced severe limitations, however. The chart was housed in one physical location, restricting accessibility. Each healthcare provider organization working with the patient would maintain its own records -- including problem lists -- leading to a highly fragmented view of the patient. Caregivers moving towards a more collaborative care delivery model would soon find paper records an undesirable and insecure way to share patient data. In addition, these paper-based problem lists were not always consistently maintained.  



How to Use Code Groups for Cohort Rules Management

Posted on 01/22/15 | Comments

Code groups have a number of uses and one of the more prevalent examples is the creation of cohort identification rules.

Those code groups, bags of codes that represent clinical concepts, are often associated with clinical quality measures (CQMs). But cohort identification ranks among the top uses outside of CQMs.  Healthcare delivery systems must create cohort identification rules within IT systems so that their care management programs can properly identify at-risk patients. This is important for both big data analytics and population health management.


Topics: cohort rules management