dfeng423 / onc_patient_matching

PATIENT MATCHING & DEDUPLICATION

Patient matching is a process of comparing data from different health IT systems to see if data sources match and belong to the same patient to obtain a complete record of the patient’s health history and medical care. If they match, those patient’s records are combined to eliminate duplication and confusion.

Patient matching makes it possible to integrate data from different providers and health IT systems, including electronic health records (EHR) and personal health records (PHR). It has been identified as a key component of achieving interoperability between United States health IT infrastructure systems.

Generally people name this kind of problems as 'record-linkage', which includes patient matching and other information linkage. In recent years, a growing number of packages in R and Python help us in this field. Through the use of data analytics and algorithms, patient matching compares demographics, health indicators and other aspects of patient data from different sources. With adequate information about a patient, similarities can be picked out until a match is more or less certain. The resulting pooled information creates a better data set to support future care decisions. Duplicate records are also eliminated reducing confusion.

In this project, three different types of methods are used. See them in the report and slides.