What do depression, diabetes, dyslexia, prosthetics, hearing loss, obesity and heart disease all have in common? All are considered disabilities or associated with increased risk of disability. About a quarter of American adults have some type of disability, according to the US Centers for Disease Control and Prevention, including two in five adults over age 65 have a disability.
Photo: Pewari via Flickr
I’ve discussed in previous blog posts ways in which confounding by indication can completely change the way observational research is interpreted: it can flip common wisdom about labor induction and cesarean delivery risk on its head, and it can lead to bizarre conversations illustrating a researchers’ blind spots when it comes to discussing topics like depression and hormonal birth control. Continue reading
Photo: Jess Hamilton via Flickr
I wrote in a previous blog about the importance of understanding confounding by indication and being sure to ask researchers about it when covering observational studies that appear to suggest a particular treatment or intervention might contribute to a specific effect. I’m passionate about this type of study bias because not considering it — which happens a LOT — can lead people to decline otherwise helpful treatments or leave them experiencing more harm and pain because of unfounded fears. Continue reading
Photo by mahalie stackpole via Flickr
One of the biggest challenges in teasing out possible causation or directionality of an exposure and an observed phenomenon, it’s essential to consider confounding by indication. Although it’s described in the Medical Studies Core Topic Key Concepts page, it’s such an important consideration in both evaluating medical studies and in formulating questions for them that it deserves a special call-out — again and again and again.
So I’m writing three blog posts with mini case studies of confounding by indication because I REALLY want to drive home how important it is that reporters covering observational studies think hard about all the possible reasons a correlation might exist between an intervention or exposure and a subsequent intervention, medical condition or negative effect. Continue reading
More than 1,500 peer-reviewed studies have relied on a surgical database known as the National Surgical Quality Improvement Program (NSQIP), or its pediatric counterpart, the NSQIP-P.
These databases, set up by the American College of Surgeons, offer extraordinarily granular information about clinical variables and outcomes (as well as demographic information) for a wide range of surgical procedures. Continue reading
If you cover medical research related to vascular procedures and conditions, you’ve likely come across studies using data from the Society for Vascular Surgery Vascular Quality Initiative (SVS VQI).
As a database designed to improve patient safety, the SVS VQI can be very useful for analyzing outcomes and associated variable for 12 major vascular procedures as long as researchers (and journalists) are aware of the limitations of the data set. Continue reading
