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Fraud costs the US health system a lot. As do wasteful spending and abuse of health services. In many organizations the process to detecting these are ad hoc, opportunistic, relying on tip offs, hunches and the curiosity and perseverance of investigators. While these are methods can be effective in isolated cases, they are manual, time consuming, … Continue reading Automating Healthcare Fraud Detection
In a previous post, I described how to format typical physician productivity data to enable further analyses, finding useful insight. I dig deeper to find more actionable insights in this post. Refresher: we had office visit data for 3 doctors over 2 month period; we added RVUs to the office visit procedure codes; we added … Continue reading Confessions of health data -2
In this post, I describe the statistical concepts that I have found most relevant in health data analytics. First and foremost, I’m not a fan of using advanced statistical techniques for the sake of using them. In healthcare, the audience of your analysis is often non-statisticians (bio statistics research arena aside), so advanced statistical concepts … Continue reading Just the Statistics you need
In a previous post, I wrote about the 5 reasons to switch to a health analytics career. To pursue a career in health analytics, some quantitative skills are necessary. However, to really thrive in a health analytics role, I believe softer skills and personal traits are also important. Here are 6 skills/traits health analysts need … Continue reading 6 skills/traits health data analysts need
The Analytics Pro 