Tracking dangerous diseases

Tracking dangerous diseases

July 21, 2014


By Anne Craig, Communications Officer

Researchers at Queen’s University have created and validated computerized algorithms that identify eight common chronic conditions in primary health care. Tyler Williamson (Epidemiology) and his colleagues used information contained in patients’ electronic medical records (EMR) to create definitions of eight diseases.

The information can be used to monitor disease prevalence and incidence, guide policy and potentially improve treatment effectiveness in people suffering from dementia, depression, diabetes, hypertension, osteoarthritis, Parkinsonism, epilepsy and chronic obstructive pulmonary disease.

“Our study has demonstrated that our case definitions are valid and appropriate for use in primary care as well as to inform policy for these diseases,” says Dr. Williamson.

Researchers reviewed 1,920 patient charts from the Canadian Primary Care Sentinel Surveillance Network, Canada’s first national EMR data repository. Dr. Williamson has concluded CPCSSN has developed valid primary care EMR case definitions for identifying patients with these eight common chronic conditions.

These case definitions can be used for a variety of data-driven activities in primary care, including surveillance, routine practice evaluation, feedback and quality improvement, and research.

The research was recently published in the July/August edition of the Annals of Family Medicine.

Health Sciences