In this (technical) post, I illustrate how to calculate commonly used goodness of fit statistics. Goodness of fit statistics are essential components to doing statistical model building. They are how you tell whether your model is performing well ito explaining the patterns in your data. In practice, most of these are done automatically from the … Continue reading On being Sensitive and Specific – analytically speaking
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 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!
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