In this post, I describe risk adjustment, an important tool in health analytics. I’ll cover what it is, how it is used, how it is done and how well it performs. What it is In the sport of boxing, matches are held between two boxers of the same weight class and gender. A match would … Continue reading Risk Adjustment 101
In this post I describe how I would go about using health analytics to identify patients most at risk of an opioid overdose. The Facts In 2016, there were 42,249 deaths in the US that involved opioids. That equates to a 13.3/100,000 mortality rate, and approx. one opioid related death every 10 minutes! By the time … Continue reading On Opioids and Analytics
In this post, I show you the core SQL commands that will address a lot of the data management work you will do as a health data analyst. If you work with data in a large organization that has lots of it, you probably use SQL. Put another way, knowing SQL will open the door … Continue reading An intro to SQL – your key to databases
This is the fourth post in a series in which I describe the common types of healthcare data you will come across, namely, diagnoses, procedures, demographic, drug, laboratory result data, clinical notes and financial data. A quick recap previous posts: Diagnosis codes, such as ICD9 and ICD10s, record the REASON for a visit to a … Continue reading What’s blood got to do with it – LOINC!
As mentioned before, I'm not a fan of using advanced analytic techniques for the sake of intellectual pursuits. I'm a HUGE fan of asking good questions, framing analysis well, knowing data well, quickly arriving at actionable insights. A trained data scientist's toolbox has many statistical techniques, each of which has strengths and weaknesses. A health … Continue reading Decision Trees – intro