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Assessing diabetic retinopathy burden and treatment at underserved and academic medical center settings using multi-center electronic medical record data
methods: The HealthLNK database was used to identify 1,933,082 unique patients who visited a participating institution from 2006-2012. HealthLNK includes electronic medical record (EMR) data from 6 federally qualified health centers (FQHCs), and 6 hospitals, including 4 academic medical centers in Chicago. Diabetic patients were defined by ICD-9 codes for diabetes and/or diabetic complications. From this population, patients with diabetic retinopathy codes were elucidated. Diabetic retinopathy patients with CPT codes related to diabetic retinopathy treatment were further categorized. Insurance status was also determined within each subgroup.
results: Of the 1,933,082 patients in the HealthLNK database, 171,427 were identified as diabetics (prevalence of 8.9%). 12,014 patients had diabetic retinopathy (7.0% of diabetics). 2,143 patients had CPT codes related to diabetic retinopathy treatment (17.8% of retinopathy patients). There were differences in the prevalence of diabetic retinopathy in diabetics (5.7% vs. 9.0%, p<0.01) and subsequent treatment (15.4% vs. 20.2%, p<0.01) when comparing "Medicaid/Financial Means Tested/Uninsured" vs. "Medicare/Privately Insured" patients.
conclusions: The prevalence of diabetic retinopathy and procedures varied by insurance status, suggesting screening and treatment disparities may exist. Future work will elucidate the significance and reasons for these differences. This study also demonstrates the effectiveness of using multi-center EMR data to identify healthcare disparities.
Learning Areas:
Communication and informaticsEpidemiology
Provision of health care to the public
Public health or related research
Learning Objectives:
Demonstrate the presence of disparities with diabetic retinopathy detection and subsequent treatment at underserved and academic medical center settings in Chicago.
Keyword(s): Vision Care, Health Disparities/Inequities
Qualified on the content I am responsible for because: I have been a co-investigator on multiple projects focusing on the use of clinical data derived from EHRs for public health/epidemiological studies. Among my scientific interests has been development of algorithms for data mining, new techniques for data extraction, and creation of large multi-site databases for research purposes.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.