Shawn Mc Ghie

Doctor On Demand’s mission is to improve the world’s health through compassionate care and innovation. We believe that health is personal, and means so much more than treating illness.

● Created the long-term data and analytics product vision to combine clinical and social media data on both patients and physicians for targeting rare disease and oncology therapies. ● Developed roadmap for SaaS platform with leadership, business, product, data science, and data engineering to support new and existing products. ● Directed product definition and strategy for Pharmaceutical Sales Representative KOL/KOI application to target physicians by identifying peer networks in social media, clinical data referrals, PubMed articles, grants, and patient targeting with Rx/Dx and disease specific population management views (i.e., who are the patients in a geographical area that need care). ● Formed agile Data Science team integrated within the Product organization, focusing on measuring the impact of products on clinical workflow, delivering against our value propositions, and providing product analytics to identify opportunities for improvement. ● Led development of clinical data warehouse infrastructure on AWS with Data Lake (S3, Redshift DB) to access data across multiple source systems, including EMR (Electronic Medical Records)/EHR, payer claims, and SFDC (CRM). ● Accountable for directing the voice of the customer, strategy, roadmap, requirement definition and prioritization, market opportunities, clinical expertise, project management, integrating data science and engineering, and pricing.

● Created the Data and Analytics vision for Proteus digital medicines, to drive patient activation, adherence monitoring, and clinical outcomes for oncology, rare disease, cardiovascular, HIV, Hep-C, and TB. ● Led development of clinical data warehouse infrastructure on AWS (HIPAA secured) with associated big data storage in a Data Lake (S3, Redshift DB) to access data across multiple source systems, including EMR (Electronic Medical Records)/EHR, payer claims, device data (medication monitoring, heart rate, activity, and sleep), Truven 3rd party data, and SFDC (CRM). ● Implemented patient selection and risked based population management apps with full EMR integrations (Epic, NextGen) including data transfers and point of care (iframe, SSO).

• Responsible for overall product management of the healthcare application group across life science sectors, including provider, payer, pharmaceutical, and government. • Managing the development of two platforms (provider/payer and pharmaceutical) and 12 analytic applications. • Accountable for directing the voice of the customer, strategy, roadmap, requirement definition and prioritization, market opportunities, clinical expertise, project management, integrating data science and engineering, and pricing. • Areas of concentration include disease risk models, population management, clinical care variation, cost takeout, physician referral network optimization, revenue cycle, revenue leakage, clinical trial analytics, pharmaceutical pricing, physician targeting, adverse events compliance, AI, ML, BI, and NLP.

• Led overall development of the IndiGO (Individualized Guidelines and Outcomes) disease risk model for patients at the point of care. The model can take into account more than 30 person-specific biomarkers (BP, Chol, FPG, A1c) and comorbidities, to calculate both current disease risk and reduction in risk from drugs. This outcome-based model includes cardiovascular diseases (MI, stroke), diabetes (onset, complications), renal progression, depression, COPD, cancer screenings, and individual drug efficacy. The primary purposes of the model are increasing adherence to medications and population management for risk-bearing entities. • Implemented IndiGO solution at Kaiser Permanente (Southern California, Colorado, Georgia, Hawaii), Intermountain healthcare, Stanford, Fairview (MN), NCQA, Bayer, American College of Cardiology, and Office of National Coordinator (ONC) beacon consortiums in Colorado and Tulsa. • Integrated IndiGO application at the point of care for Epic, GE, Pentahoe, and Optum. • Developed Business Intelligence (BI) tool in Tableau to enable population management, or clinical decision support. This platform sits on top of EMR/EHR data used in the model, claims data, and model risk/benefit calculations. Standard dashboards include patient longitudinal views of risk and biomarkers, physician performance outcome scores, benchmarking, standard guidelines vs. outcomes models comparisons, and data validation/completeness. Articles: Kaiser Permanente study on model: http://www.ajmc.com/journals/issue/2016/2016-vol22-n5/Potential-of-Risk-Based-Population-Guidelines-to-Reduce-Cardiovascular-Risk-in-a-Large-Integrated-Health-System New York Times article on model: http://well.blogs.nytimes.com/2011/05/19/finding-the-patient-in-a-sea-of-guidelines/?scp=1&sq=archimedes&st=cse Annals of Internal Medicine paper on the model http://annals.org/content/154/9/627.abstract

• Responsible for the overall development of clinical care variation scorecards, dashboards, and individual physician performance results against goals. Gathered clinical requirements from CMO, physicians, sales teams, and state benchmarks. Elements included statistically significant peer measurements of DRG-ALOS, average case cost, severity, and no readmissions in 30 days (outcome). • Developed methodology for disease pathway predictive models, based on optimal treatments to reduce ALOS and minimize readmissions. • Created a roadmap for dynamic statistical calculations through 3rd party vendors (SPSS) and massively parallel processing (to get around limitations of SQL and OLAP).