CPCSSN data are generated through an innovative process which maximizes national-level excellence in cleaning and coding of extracted Electronic Medical Record information
What we collect and clean from the Electronic Medical Record:
- Lab values- fasting glucose, glucose tolerance, HbA1C, HDL, LDL, tot chol, triglycerides, microalbumin, urine albumin creatinine ratio, creatinine, INR, hemoglobin, eGFR, TSH
- Encounter/ Encounter Diagnoses/Visits
- Health conditions/problem list
- Examination data- ht, wt, BMI, PEFR, s/dBP, waist circumference, hip waist ratio
- Procedure data
- Risk Factors
- Referrals - smoking, alcohol, obesity, exercise, diet
- Family History
- Physical exam findings
Our Developed and Validated Case Definitions: We currently have 8 chronic diseases for which we have validated case definitions to identify patients with hypertension, diabetes, depression, COPD, osteoarthritis, dementia, epilepsy and parkinsonism. These case definitions were developed and validated using data from billing codes, encounter diagnoses, problem list, labs and medications. These case definitions are used for trustworthy surveillance, practice evaluation, feedback, quality improvement and research.
Please see our publication in the Annals of Family Medicine for more information.
What we are working on next:
- Data Linkage: We are working to link electronic health record data with administrative datasets in order to facilitate more comprehensive surveillance, research and richer quality improvement opportunities.
- New Case Definitions: Multiple Sclerosis, Affective Disorders, Psychotic Disorders, Attention Deficit Hyperactivity Disorder/Attention Deficit Disorder, Stroke, Congestive Heart Failure, Cardiovascular Disease, Community-Acquired Pneumonia, Opioid Dependency, Diabetic Retinopathy, Asthma in Adults, and Hearing Loss