Symptoms Reported by Patients Often Do Not Match Those in EHR

Marcia Frellick

February 01, 2017

Data in electronic health records (EHRs) may not accurately reflect patient-reported symptoms, according to a study published online January 26 in JAMA Ophthalmology.

The authors of the study and a related commentary note that similar discrepancies have been shown in previous studies and that they have implications for both patient care and the accuracy of big data research that pools information from EHRs.

Nita G. Valikodath, MS, from the Department of Ophthalmology and Visual Sciences at the University of Michigan Medical School in Ann Arbor, and colleagues compared patients' answers on an Eye Symptom Questionnaire with symptom information recorded in EHRs for 162 adult patients who were seen in comprehensive ophthalmology and cornea clinics at the university's Kellogg Eye Center between October 1, 2015, and January 31, 2016.

The patients were given the Eye Symptom Questionnaire while they were waiting to see the physician, and they also were asked about the severity of eight eye symptoms in the last 7 days. The researchers checked those answers against EHR data recorded by any provider.

For 33.8% of patients studied (54 of 160), information on blurry vision did not match between the questionnaire and the EHR.

"Likewise, documentation was discordant for reporting glare (48.1% [78 of 162]), pain or discomfort (26.5% [43 of 162]), and redness (24.7% [40 of 162])," the authors write.

Overall, there was poor to fair agreement (κ range, −0.02 to 0.42) for symptom reporting.

The authors found that it was most often the case that the symptoms were reported in the questionnaire, but not in the EHR. Blurry vision was the exception, being more often reported in the EHR than in the questionnaire.

However, when a patient made a return visit, it was five times more likely, compared with new-patient visits, that symptom reporting for blurry vision would not be recorded in the EHR (odds ratio, 5.25; 95% confidence interval, 1.69 - 16.30; Holm-adjusted P = .045).

"The inconsistencies imply caution for the use of [EHR] data in research studies. Future work should further examine why information is inconsistently reported," the authors write.

Reasons for the disconnect were unclear from the study, but the authors found the following factors were not significantly related to inconsistencies: age and sex of the patient; physician's experience, workload and use of a medical scribe; and presence of urgent or nonurgent anterior segment eye disease.

"As noted by other authors, inconsistency may rather be due to time constraints, system-related errors, and communication lapses," they write.

The authors suggest patient-reported outcomes could be collected with a standardized template and uploaded in to the EHR. That would help make reporting more consistent across patients and allow physicians to focus on the severity and cause of the symptoms.

In an invited commentary, Christina Y. Weng, MD, MBA, from the Cullen Eye Institute, Department of Ophthalmology at Baylor College of Medicine in Houston, Texas, points out some problems with using both paper and electronic templates.

Some practices ask patients to write symptoms on paper, and then those documents can be scanned into the EHR, but they may appear as a separate document and may be overlooked.

Some patients unfamiliar with technology or with physical limitations may not be able to enter their data electronically. However, if staff enter the data, that could raise costs and introduce additional errors, Dr Weng writes.

"Another potential solution would be to use templates so that the clinician would check off positive symptoms, without neglecting to inquire about other symptoms on a standard list. But these templates can result in overdocumentation or inaccuracies because of 'auto-fill' capabilities," she says.

Further investigations of the reasons for discrepancies will help find the right solution and help EHRs live up to their potential for advancing medicine, she says.

"Although data entry processes may still be imperfect, [electronic medical record] systems already offer numerous benefits and will ultimately help us unlock what could be the next frontier in medicine — big data analysis, machine learning, and artificial intelligence, all of which depend on a vast but high-quality data set," Dr Weng writes.

Limitations of the study include that it was conducted at a single center, using one type of EHR.

Coauthors report consultant relationships to Blue Health Intelligence and the Centers for Disease Control and Prevention outside of the submitted work. Researchers were supported by the National Institutes of Health, the National Eye Institute, Research to Prevent Blindness, and the W. K. Kellogg Foundation. Dr Weng has disclosed no relevant financial relationships.

JAMA Ophthal. Published online January 26, 2017. Article full text, Commentary full text

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