The poem: Well, it's not it's not the usual doggerel you see with this sort of thing. It's a quatrain…
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 21st 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.
This is warmed over Weed and it has the same problem: when there’s a diagnosis yet to be made, the necessary item isn’t on the problem list yet to receive all the connections you’re talking about. That requires someone, or potentially some thing, to go through unconnected data, have the lightbulb moment, and put the problem in the list. If you had the “thing” I just referred to I think you’d be blowing your horn that you do.
I agree with Robert, but I would also argue that the premise of the article presupposes that interoperability is solved because of a couple of ‘acts’. Yet, show me the battery of tests that bring in the Problems, Allergies, Medications, Immunizations, Procedures, Labs, Images –from all major to minor vendors — and then have them accurately and correctly reconcile and incorporate into the receiving systems.
The state of the art today, even with the CURES act, is essentially a PDF in the form of a CCDA.
I have seen one EHR that was able to reconcile and incorporate data from another EHR. But the receiving EHR was the same brand and version — I believe that is the unicorn in the herd.
I welcome comments that indicate differently as there are many vendors in the wild and some may have done the work needed to be able to R&I data from any valid source. None that I have seen to date
Simply put, Epic’s Care Everywhere has been able to reconcile meds/problems/allergies from non-Epic systems for at least about eight years. Immunizations got added a few years after. As long as standard/non-proprietary codes are used when the C-CDA is created, it works fairly well (especially the very simple CVX codes used for immunizations).
Granted, poorly constructed C-CDA documents from other vendors can lead to difficulties in figuring out when changes have been made to med ABC and thus can require multiple discards of a med that’s already been ingested…but it does work and has been chugging along for a long time now.
Yeah, it’s extremely common to go in to reconcile meds, problems, allergies, etc., and see data from Cerner or Allscripts or whoever. Can’t yet trust it without a clinician signing off on it (and with so much junk or duplicate data sent, that’s understandable), but it’s all available.