Scientists Advance Lupus Research, Identifying a New and Improved Way to Analyze Electronic Health Records
Researchers have discovered a new approach to patient data collection that can enhance lupus research. The new method allows researchers to use electronic health records (EHRs) not only identify diagnoses and symptoms based on standardized EHR codes, but also analyze much more nuanced free text that healthcare providers add to patients’ charts.
The method is known as text mining. It’s a systematic way of sifting through and categorizing a large amount of patient information in the EHR that’s typed in free-hand. Text mining is important, particularly for complex diseases like lupus, because it allows researchers to analyze more subtle and context-specific details about individual patients.
The newly developed text-mining algorithm was able to identify people with lupus out of more than 4,600 electronic patient records with a high degree of accuracy. Additionally, the new text-mining method effectively identified potentially life-threatening issues, like inflammation of the kidneys and lungs. Before this development, critically important free-text information had to be assessed manually in each patient’s EHR, a time-consuming process that’s prone to error with limited use in research settings.
If your doctor utilizes electronic health records, talk to your doctor and see if you can provide more information by tracking your symptoms.