This is the home page for an i2b2 related project that identifies "Healthy Normal" Patients in an i2b2 CRC cell.
This project contains a database script that identifies "healthy normal" patients in an i2b2 CRC cell. This is important for clinical trials that need a healthy control group. However, finding these patients is often difficult because healthy patients do not go to the hospital; and, because patients receive care from multiple hospitals, the absence of a diagnosis in one hospital's electronic health record does not mean a patient does not have the disease.
The script uses a set of 10 heuristic filters that attempt to eliminate patients who are sick or abnormal or who might no longer be receiving care at your hospital. It returns only the aggregate counts of the number of patients who pass each heuristic filter and gives the demographic breakdowns of the patients identified as healthy and normal. When run at Partners Healthcare in Boston, only about 1.5% of approximately 2 million patients were identified as healthy and normal.
The first 6 filters are part of a separate project to estimate the fraction of patients who have at least one chronic disease diagnosis code. Note that in identifying healthy patients, the patients with chronic diseases are first eliminated.
This script should be run in a standard implementation of the i2b2 CRC cell (version 1.3 or higher) in Microsoft SQL Server 2005 or later. It may require about 10 GB of storage and 1 hour processing per one million patients, though this can vary greatly depending on the particular data in the i2b2 instance and the database hardware.
Created by Griffin M Weber, MD, PhD
Beth Israel Deaconess Medical Center, Boston, MA
Harvard Medical School, Boston, MA
weber@hms dot harvard dot edu