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Month: April 2018

On Opioids and Analytics

2018-04-252018-05-16 ~ Ed ~ 3 Comments

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

An intro to SQL – your key to databases

2018-04-202018-04-20 ~ Ed ~ 3 Comments

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

What’s blood got to do with it – LOINC!

2018-04-162018-04-16 ~ Ed ~ 4 Comments

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!

Decision Trees – intro

2018-04-082018-04-16 ~ Ed ~ 4 Comments

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

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Machine learning in healthcare build a predictive model to tackle opioid abuse.

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