Readers Write: Diagnostically Connected Data – The Key to EHR Clinical Usability

Diagnostically Connected Data: The Key to EHR Clinical Usability
By Dave Lareau

Dave Lareau is CEO of Medicomp Systems of Chantilly, VA.

Clinicians are among the most highly trained knowledge workers in any industry, yet the systems they use to care for patients often actually hinder their ability to deliver care. We hear anecdotes from patients about clinicians spending inordinate amounts of time trying to find information in their EHRs – only to often give up rather than search through other sections of the chart to find a lab result, view past encounter notes, or try to correlate medications with problems or the course of a condition.

EHRs require users to spend too much time searching for clinically relevant information for the patient they are treating and, once that information is located, to go through a series of disconnected processes to complete their work.

This situation will only get worse once the floodgates of healthcare data interoperability are opened. Then, it will be even more challenging for clinical users to find what they need.

Consider the bright side of this data-driven conundrum: The effects of the 21^st Century Cures Act and TEFCA will make it easier for HIT systems to send and receive information. Plus, emerging terminology standards and the use of common codes such as ICD-10, SNOMED, LOINC, RxNorm, CPT, DSM5, CTCAE, UNII, CVX, and others will provide a basis for what is often called “semantic interoperability.” And today, the performance of natural language processing is getting more consistent and reliable, providing a means to convert free-text notes that use those same terminologies and codes.

So, does that mean that more coded data is a good thing?

Not necessarily – that is, unless clinicians can readily locate the information they need to assess, evaluate, treat, and manage a given patient and their clinical problems. With the widespread adoption of risk-based reimbursement through Medicare Advantage and similar programs sharpening the focus on chronic condition management, it will be increasingly crucial for clinicians to see a diagnostically focused view for each patient along with their medical problems. They need instant access to this view, without searching through disparate sections of the EHR.

Semantic interoperability facilitated by standard terminologies and code sets is a great start – and is necessary for sharing clinical information between systems. It will also drive better analytics and population health insights. But it will not make it easier for clinicians to find the data they need for the patient at the point of care (whether that patient is in-office or on a screen.)

Most existing EHRs, and the terminologies and codes for semantic interoperability, are structured in distinct “domains.” In an EHR, this typically shows up as separate sections or tabs – problem list, medication list, laboratory orders and results, procedures, encounter notes, discharge summaries, etc. Problems, meanwhile, have ICD-10 and SNOMED codes, labs have CPT and LOINC codes, medications have RxNorm or NDC codes, and other domains use other code sets. These codes were designed for their specific domain. They were not designed to work together for the clinical user.

The key to usability is to link these to the problem list, so that the user can click on a problem and immediately view the related medications, labs, procedures, therapies, co-morbidities, and findings from encounter notes that all are related to the problem. This diagnostically filtered presentation could be viewed longitudinally and supported by millions of mappings from standard terminologies and code sets.

Such a unique diagnostic relevancy engine would provide both the semantic – and diagnostic – interoperability that enables clinicians to not only see what they need at the point of care, but also to harness the flood of interoperability-driven data that will soon complicate their work.