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A novel method using electronic health record coding to generate a unique, multipurpose database for aerodigestive
Lindsey Mortensen1, Alexander Dwyer1, Benjamin Palatnik1
1Department of Otolaryngology, University of Minnesota, MMC396, 420 Delaware St SE, Minneapolis, MN 55455, USA.
Background:
Upper aerodigestive/head and neck cancer affects over 45,000 patients annually in the oral cavity and oropharynx alone. This burden may be reduced through surveillance of patients with oral potentially malignant disorders (OPMD). Here we describe a readily accessible pilot study evaluating a database-generating approach that captures our longstanding Cancer Active Surveillance Program (CASP). Our methods can be applied to other premalignancies and disease conditions to fuel clinically relevant research related to cancer risk, disease progression, interception, and outcomes.
Methods:
Electronic medical record data from the senior author's head and neck cancer practice, which harbors a significant primary screening component, was interrogated for 35 International Classification of Disease 9 and 10 codes. These codes represent over 300 unique mucosal lesion descriptors or conditions associated with heightened risk for oral cancer. These data were subject to a proof-of-concept analysis to assess geographic and racial representation in the CASP.
Results:
Automated extraction from the electronic medical record identified 1576 individuals with OPMDs with lower cost and higher fidelity than manual chart review. CASP patients were overrepresented relative to the state population within urban centers, with underrepresentation in more rural areas. More Black patients and fewer Asian/Pacific Islander patients were seen in CASP relative to our cancer catchment's demography.
Conclusions:
Automated medical record queries can identify patients in the catchment area with precancerous or other at-risk conditions for cancer.
Impact:
This information informs resource utilization to improve inclusivity of underrepresented groups and streamlines identification of potential participants for cancer prevention clinical trials.
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