How to Convert to Longitudinal Level

Converting Encounter to Longitudinal Representation Key Points

Note: In this walkthrough, we continued to use the synthetic dataset from the previous walkthrough.

1. Inspect the data!

Remember that when working with longitudinal data it is vitally important that we inspect the data.

2. Create a new dataframe that groups the data by "patient_id". Again you can use groupby() and agg() methods.

3. Inspect and compare the data again by selecting a single patient and compare the "encounter", "principal_diagnosis", and "procedure_codes".

You should see all of these codes represented in arrays/lists for each patient.

Example:

 list(longitudinal_example_patient_history['encounter_id'].values)

Output: [['encounter_id_2352', 'encounter_id_7434','encounter_id_1393']]