Women report more intense pain than men in virtually every disease category, according to Stanford University School of Medicine investigators who scanned a large collection of electronic medical records to establish the broad gender difference to a high level of statistical significance.
Their study, published online in the Journal of Pain, suggests that stronger efforts should be made to recruit women subjects in population and clinical studies in order to find out why this gender difference exists. The study also shows the value of EMR data mining for research purposes.
Using a novel database designed especially for research, the Stanford scientists examined more than 160,000 pain scores reported for more than 72,000 adult patients. From these, they extracted cases where disease-associated pain was first reported, and then stratified these findings by disease and gender.
"None of these data were initially collected for research, but this study shows that we can use it in that capacity," said lead author Atul Butte. The medical literature contains numerous reports indicating that women report more pain than men for one or another particular disease, noted Butte, a professor of systems medicine in pediatrics. "We're certainly not the first to find differences in pain among men and women,” he said.
“But we focused on pain intensity, whereas most previous studies have looked at prevalence: the percentage of men versus women with a particular clinical problem who are in pain. “To the best of our knowledge, this is the first-ever systematic use of data from electronic medical records to examine pain on this large a scale, or across such a broad range of diseases."
In this case, the scientists tapped an existing data archive that has been designed specifically for ease of research: the Stanford Translational Research Integrated Database Environment, or STRIDE. STRIDE aggregates clinical data on patients cared for at Stanford Hospital & Clinics and Lucile Packard Children's Hospital, making this data searchable for approved research projects.
Butte's team selected only adult records and looked for gender-related differences in pain intensity as reported on 1-to-10 scales, in which a zero stands for "no pain" and 10 for "worst imaginable." Their search algorithm combed through de-identified EMR data for more than 72,000 patients, and came up with more than 160,000 instances, ranging across some 250 different disease categories, in which a pain score had been reported.