In 2016, Medicare paid more than $82 billion in payments to 91 types of providers, including physicians, therapists, ambulance services, surgical centers and more. Continue reading
The site uses data that was voluntarily submitted by states on “selected health and program indicators.” An introduction to the site says it offers information about these questions: Continue reading
These massive datasets have many advantages, such as the ability to narrow down a specific population through inclusion or exclusion criteria, having adequate participation to achieve statistical power, being able to analyze and compare subgroups based on demographics or other differences and the ability to get diverse, representative populations. Continue reading
Looking for p-hacking or other statistical red flags is challenging, particularly for journalists who don’t have training in statistics or medical research design or access to the complete data sets a researcher may be using. But that doesn’t mean you can’t learn a few tips on how to scrutinize studies that analyze huge datasets. In fact, three statistical editors of JAMA Surgery — Amy H. Kaji, M.D., Ph.D.; Alfred W. Rademaker, Ph.D.; and Terry Hyslop, Ph.D. — recently penned an editorial aimed at researchers that journalists can benefit from as well. Continue reading
We’ve covered in another blog post what to be cautious about in scrutinizing an observational study that uses data from a massive database or dataset. And we’ve introduced a new section in the Data section of the Medical Studies Core Topic that describes characteristics and considerations of several large datasets that researchers may frequently use for such studies.
But sometimes you want to get really granular on deconstructing a study. Continue reading