The Problem with Problem Lists

A colleague and friend wrote this great piece for Health Management Technology : The Problem with Problem Lists in which he reviews the history of the problem list (now over 40 years old!) and while

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.

They are not as prevalent or pervasive as you might expect. IN fact this was subject to an extensive discussion on a list serv and I made the point here that managing these expanding list of problems can be a significant challenge for any system. It tends to be easy to add problems but as Davide points out 

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 defined, making the initial description too generic to guide actual care. Additionally, as multiple specialists engage with a patient, they focus on problems that are both different and overlapping. While each provider contributes to the problem lists (from different perspectives), patient data rapidly becomes repetitive or redundant, rendering the electronic problem list less useful

As one of the commentators pointed out clearly defining what should be captured and documented int he problem list is a god place to start and supplementing that by cleaning up old information (archiving old details, problems and information that perhaps was relevant but has now either been over taken by events (OBE) or was relevant for a specific episode of care but is now not.

But capturing the latest information from the range of inputs remains a challenge and facilitating narrative based documentation 

to preserve detailed and expressive descriptions of patients and their stories and are commonly accepted as the best way to capture and arrange the informational background on which effective diagnostic reasoning is based.

Is preferred by many but unfortunately 

The final output of such systems is a textual clinical note.

Technology is now starting to address this problem by providing tools that analyze the content of the narrative, understanding the underlying clinical description and intent of the physician.

Consider this sentence: “The otitis media for which the patient was seen last month appears to be fully resolved.” CLU automatically and reliably assesses that the “otitis media” is “resolved” and thus should be removed from the list of current problems. Today, this action would require manual editing of the data. However, with CLU this happens automatically, with the physician confirming the deletion.

Thereby bridging the clinical divide between the physicians desire and need to document the full clinical condition in narrative form capturing all nuanced detail of the patient's history and the need to automatically extract clinical data and facilitate the integration of structured semantically interoperable data directly into the EMR.

Timely innovation given the major push towards electronic medical records as part of the governments incentives in ARRA and HITECH and relevant in any clinical setting where narrative remains the key data captured.

Posted via email from drnic's posterous