Gordon Lemmon
Senior Knowledge Engineer @Motive Medical Intelligence
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WORK HISTORY
Senior Knowledge Engineer @Motive Medical Intelligence
San Francisco, CA, US
Motive specializes in the development of clinical quality measures (CQMs) and clinical decision support (CDS). These knowledge artifacts are coded in Clinical Quality Language (CQL) and make use of the FHIR (Fast Healthcare Interoperable Resource) data model. My first project involved helping a large insurance provider transition to these open standards. I develop software tools to convert their 8500 bespoke clinical rules into CQL.Now I am part of a team that scores physicians based on \"appropriateness of care\" and \"quality of care\" metrics. The team has developed hundreds of these metrics and I focus on assessing and improving the reliability of these metrics.
EDUCATION
Georgia Institute of Technology
Master of Science (MS), Computer Science
Brigham Young University
Bachelor of Science (BS), Microbiology, Bioinformatics, Chemistry, Music
Vanderbilt University
Doctor of Philosophy (PhD), Chemical & Physical Biology
SKILLS
ABOUT GORDON LEMMON
I have extensive experience building end-to-end data analysis and machine learning pipelines. With dual education in data science and computer science I apply principles of software engineering to the field of data science to create analysis pipelines that are reliable, scalable, and extensible.My research focus is in predicting how a patient’s medical history, family history, and demographics affect the probability they will receive a specific medical diagnosis within some time horizon. Likewise, we can predict which procedures the patient is likely to need. These predictions are used to identify at-risk patients for research studies, clinical trials, and preemptive screenings. They can be used in precision medicine to compare treatment options and used to improve decision making and counseling between the care provider and the patient. Hospitals and insurance providers can use these probabilities to improve care delivery and predict cost.
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