Introduction
Record linkage is the task of identifying pieces of scattered information that refer to the same thing. Patient matching is a specific application, in which we try to identify records that belong to the same patient among different data sources. These sources can range from patient data collected at different hospitals to external information from governmental institutions, such as death master file etc.
One of the interesting and challenging aspects of this project is to deal with erroneous data, for instance when your name is misspelled or your birth date is entered incorrectly. These kinds of things often happen in reality, and we can account for them by using flexible distance metrics and statistical models.
Why is then record linkage important and what are the benefits?
Well, we are living in an exciting period of globalization, where computers and internet make world-wide collaboration easy and necessary. Patient linkage and data aggregation techniques will allow medical institutions to store their own data, yet at the same time work together with others to offer better treatment to patients.
For instance, patients often forget their test results at home, or old tests get lost eventually. Imagine that all your medical records are stored in digital format, and when you go to Hospital A, a doctor there can examine your tomogram taken 4 years ago at Hospital B where your name was misspelled by the clerk
Downloads
http://modules.openmrs.org/modules/view.jsp?module=patientmatching
http://source.openmrs.org/browse/Modules/patientmatching/
What the module does
The OpenMRS module wraps around the patientmatching jar to facilitate creating the matching file setup and merging patients that are found to be duplicates
Difference between "Must Match" and "Should Match"
"Must Match" is used for grouping the blocks.
"Should Match" is to contribute the scores.
What the standalone jar does
There is a main() method in the org.regenstrief.linkage.gui.RecMatch