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Electronic Health Records

The problem with problem lists

Imagine if your dictated visit notes could update patient EMRs. Clinical language understanding can make that happen.

By Davide Zaccagnini, M.D. M

ore than 40 years ago, the introduction of problem lists in clinical care was aimed at controlling the complexity of the rapidly expanding universe of specialized medi- cine. It was a way to provide physicians with a complete, concise and clinically consistent view or “entry point” into a clinical case. While their value in patient care has been demonstrated in countless studies, physicians have historically adopted them with much less enthusiasm than one would expect.

The advent of electronic medical records (EMR) fos- tered hopes that the problem list could become the pri- mary reference for care providers approaching a patient. And yet, according to multiple studies,1 creating and maintaining computerized problem lists has proven to be an elusive goal, even for the most diligent practitioners equipped with the most advanced EMR systems.

Cumbersome data entry, I presume

There are many reasons for the lack of adoption of electronic problem lists, but the most common is that they need to be entered and updated manually, a tedious and time-consuming task for physicians. The result? While patients’ diseases, symptoms and risk factors evolve and change, the corresponding items on the electronic problem list tend to age rapidly and may soon become irrelevant or even inaccurate. For example, a certain symptom may have disappeared, or an initial diagnosis may have been further defi ned, making the initial description too ge- neric to guide actual care. Additionally, as multiple specialists engage with a patient, they focus on prob- lems that are both different and overlapping. While each

Davide Zaccagnini, M.D., is director of medical informatics, Nuance Communications. For more information on Nuance Communications:

provider contributes to the problem lists (from different perspectives), patient data rapidly becomes repetitive or redundant, rendering the electronic problem list less useful. This could help explain why, in Massachusetts

30 November 2010

where the adoption of EMRs is about four times higher than the national average, problem lists are routinely used by less than 50 percent of doctors using EMRs.2 The gap between clinically active problems and the data in the EMR affects not just problem lists. Clinical applications that support proactive care protocols, such as case management and real-time decision support, are severely hindered when patient data is missing or out of date. In order to function correctly, these tools require the most current and up-to-date problem lists and other clinical information, some of which is continuously being generated during the episode of care that could still be unfolding during ongoing hospitalization.

Clinical language understanding (CLU) is a developing technology that automatically captures problems and other key patient clinical data from dictated visit notes. This data is standardized and saved into the EMR and other clinical systems directly from dictation, saving physicians the time and tedium of entering data manually.

Most modern EMRs offer integrated and customiz- able tools and pick lists for physicians to create and manage patient problems in the EMR using keyboard and mouse. Unfortunately, physicians fi nd these data- entry modalities ineffi cient and hard to use. Not only do they take away valuable time from direct patient care, but many also complain that the resulting data sets do not fully observe the natural fl ow of clinical thinking. Conversely, narrative-based documentation methods are viewed as able to preserve detailed and expressive descriptions of patients and their stories and are commonly accepted as the best way to capture and


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