Disaggregation of Medical Research Data Reveals Outcome Differences in Demographic Groups and Presents Opportunity to Improve Patient Care.
Michael J RossiJames H LubowitzMark P CoteElizabeth MatzkinPublished in: Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association (2024)
Disaggregation, in the medical literature, means separation into demographic groups. This results in an opportunity to discover differences in outcomes by group, which could improve future treatments and provide outcome data, by group, that could be included in future systematic reviews. In research, the term disaggregation is most often used in reference to addressing inequities. We support the Sex and Gender Equity Research (SAGER) guidelines and encourage authors to examine how sex and gender are taken into account in their study and ensure adequate representation by sex and gender. (We respect that not all studies can or are designed to capture data by sex and gender, and that gender is "complex" and "fluid.") Disaggregation is encouraged, when possible, for other demographic variables allowing evaluation of all marginalized (as well as nonmarginalized) populations, so that we can better care for patients.
Keyphrases
- mental health
- healthcare
- electronic health record
- systematic review
- palliative care
- ejection fraction
- newly diagnosed
- randomized controlled trial
- prognostic factors
- public health
- skeletal muscle
- chronic kidney disease
- insulin resistance
- weight loss
- data analysis
- clinical practice
- deep learning
- patient reported outcomes
- health insurance
- gestational age