Accuracy of symptom reporting in EHR

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.

http://www.medscape.com/viewarticle/875016

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Valikodath NG, Newman-Casey PA, Lee PP, Musch DC, Niziol LM, Woodward MA. Agreement of Ocular Symptom Reporting Between Patient-Reported Outcomes and Medical Records. JAMA Ophthalmol. 2017 Jan 26. doi:10.1001/jamaophthalmol.2016.5551. [Epub ahead of print]

Abstract

IMPORTANCE:

Accurate documentation of patient symptoms in the electronic medical record (EMR) is important for high-quality patient care.

OBJECTIVE:

To explore inconsistencies between patient self-report on an Eye Symptom Questionnaire (ESQ) and documentation in the EMR.

DESIGN, SETTING, AND PARTICIPANTS:

This investigation was an observational study in comprehensive ophthalmology and cornea clinics at an academic institution among a convenience sample of 192 consecutive eligible patients, of whom 30 declined participation. Patients were recruited at the Kellogg Eye Center from October 1, 2015, to January 31, 2016. Patients were eligible to be included in the study if they were 18 years or older.

MAIN OUTCOMES AND MEASURES:

Concordance of symptoms reported on an ESQ with data recorded in the EMR. Agreement of symptom report was analyzed using κ statistics and McNemar tests. Disagreement was defined as a negative symptom report or no mention of a symptom in the EMR for patients who reported moderate to severe symptoms on the ESQ. Logistic regression was used to investigate if patient factors, physician characteristics, or diagnoses were associated with the probability of disagreement for symptoms of blurry vision, pain or discomfort, and redness.

RESULTS:

A total of 162 patients (324 eyes) were included. The mean (SD) age of participants was 56.6 (19.4) years, 62.3% (101 of 162) were female, and 84.9% (135 of 159) were white. At the participant level, 33.8% (54 of 160) had discordant reporting of blurry vision between the ESQ and EMR. 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]), with poor to fair agreement (κ range, -0.02 to 0.42). Discordance of symptom reporting was more frequently characterized by positive reporting on the ESQ and lack of documentation in the EMR (Holm-adjusted McNemar P < .03 for 7 of 8 symptoms except for blurry vision [P = .59]). Return visits at which the patient reported blurry vision on the ESQ had increased odds of not reporting the symptom in the EMR compared with new visits (odds ratio, 5.25; 95% CI, 1.69-16.30; Holm-adjusted P = .045).

CONCLUSIONS AND RELEVANCE:

Symptom reporting was inconsistent between patient self-report on an ESQ and documentation in the EMR, with symptoms more frequently recorded on a questionnaire. These results suggest that documentation of symptoms based on EMR data may not provide a comprehensive resource for clinical practice or "big data" research.