Value of unstructured patient narratives
Current EHRs capture most information – patient demographics, medications and problem lists – as structured data, and often codify the details to support billing instead of clinical activities.
By Jeffrey Barry L
isten closely to the country’s fervent discussion about healthcare reform and the push towards electronic health records (EHRs), and a steady drumbeat will emerge, forewarning the sacrifi ce
of the patient narrative.
Jeffrey Barry is research fellow, Healthcare Innovation and Technology Lab, and 2010 MPH Candidate at the Columbia University Mailman School of Public Health. For more information on the Healthcare Innovation and Technology Lab: www.rsleads.com/007ht-209
Cautionary tales of throwing the patient out with the paper – in technical terms, failing to fully utilize unstructured clinicians’ notes in the EHR – are surfacing everywhere. In her April 22 New York Times commen- tary, Pauline Chen, MD, discussed the importance of the patient narrative, and the challenges of replicating nu- ances of care in current EHRs. A month earlier, Gordon Schiff, MD, and David W. Bates, MD, wrote in The New England Journal of Medicine that “free-text narrative will often be superior to point- and-click boilerplate in ac- curately capturing a patient’s history.”
Thought-critical, free- text physicians’ notes are under threat. Current EHRs capture most information – patient demographics,
medications and problem lists – as structured data, and often codify the details to support billing instead of clinical activities. The frequent use of the word “structured” in the defi nition for meaningful use released by the Centers for Medicare and Medicaid Services (CMS) may further encourage and compound this trend.
Doctors may be vocalizing the issue, but public health researchers also stand to gain from a richer electronic patient narrative. The ability to access and mine robust databases of patient information would enable public health researchers to more effectively perform nuanced, descriptive research. In turn, advanced technology to cap- ture and report clinical documentation may better meet meaningful-use requirements for providing electronic syndromic surveillance data, immunization registries, and reportable lab results to public health agencies. Academic and research hospitals that unlock the unstructured data’s
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enormous potential could also use it to attract both quality investigators and increased funding.
Providing color and context
The unstructured free text of the physician’s progress notes provides color to the structured data’s black and white. Notes contain the doctor’s comments following a patient visit, along with helpful reminders, patient his- tory, intake, examination and discharge information. The information is also essential for physicians to communi- cate about a common patient. A recent study by Nuance Communications illustrated that 94 percent of physicians felt that it was important to include doctors’ notes in the patient record.”
Notes also show great potential to meet CMS measures for disease surveillance, as well as for adverse event report- ing and nuanced public health research.
Syndromic surveillance of epidemics, cancer clusters and even bioterrorism from unstructured data in EHRs could help target resources to slow disease spread. In 2008, Jeff Friedlin and colleagues at Regenstrief Institute and Indiana University School of Medicine used a data-mining tool with natural language processing (NLP) technology – a program that seeks to understand the context and connotation of text – to scour electronic free-text culture test reports and detect incidence of methicillin-resistant Staphylococcus aurerus (MRSA). The researchers were able to produce sensitivity, specifi city and positive pre- dictive values exceeding 99 percent. If this technology could be applied to other forms of unstructured data and diseases, it could be harnessed to alert the local health department to possible outbreaks signifi cantly faster. Additionally, relying on caregivers to report adverse events can lead to an underestimation of their frequency by a factor of around 20, according to another study by Bates and colleagues. Manually reviewing charts is gener- ally effective but prohibitively expensive. Using NLPs can streamline this process. This could greatly improve post- market surveillance for new drugs and medical devices. According to Dr. James G. Jollis and his colleagues from the Duke University Medical Center, electronic
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