1. Analysis of Electronic Medical Record Systems Jonathan S. Schildcrout

2. Electronic Medical Records Facilitate communication – Improve outcomes, reduce preventable adverse events and death Permit decision support systems – Synthesize large amounts of information to provide alerts related to adverse events, patient safety, treatment course, etc. Vanderbilt has been effectively paperless since 1996.

3. Using EMR for research What we want vs. what we have What we want: Randomized clinical trial – Randomly assignment to treatment – We observe participants at meaningful times. – Data acquisition and all aspects of data is focused on addressing a scientific question. What we have: Casually collected EMR – Data acquisition process not aligned with any scientific questions – This causes problems when we want to do data analysis. – Not only do we have observational data but there is deliberate intervention into the system we are attempting to study.

4. EMR data analysis (cont.) Selection bias: bias occurring because the observed sample is not representative of the target population. The key is to clearly identify the target population is… – Study results based on an inpatient sample generally should not be generalized to a population of people who are not hospitalized – Healthier subjects tend to be hospitalized for shorter time periods than sicker patients If baseline time occurs at admission, then over time healthy patients drop out. Sample represents an increasingly unhealthy population. – When subjects become sick, they tend to be observed more frequently than healthier patients. – Observation times are likely to be informative. – Sicker patients get different treatments than healthier patients Confounding by indication

5. EMR data analysis We should: – Make sure we define the target population clearly and carefully – Imagine how we would design a study that addresses our scientific question – Consider how the actual data acquisition process differs from the one we wish we had – Conduct analysis that intend to explicitly addresses the differences between 1) the data we have and the population represented by the sample 2) The data we wish we had the target population.