Thomas Manzo

Sr Manager, IT at Duke University Health System

Based in Raleigh-Durham-Chapel Hill, United States

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Seniority

Manager

Department

Information Technology

Location

Raleigh-Durham-Chapel Hill

Industry

Hospitals and Health Care

Company size

12K

Contact information

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Email

1 credit

t•••••••@dukehealth.org

Phone

5 credits

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Background

About Thomas Manzo

As a seasoned Business Intelligence Professional, I specialize in SQL-based reporting, with expertise in large third-party SQL extracts and certifications across Epic's Cogito modules: Access, Revenue, and Clinical. My work centers on Epic Clarity and Caboodle, leveraging both platforms for robust data extraction, transformation, and reporting. I have extensive experience integrating data from multiple sources into Caboodle’s dimensional structure, optimizing it for analysis of patient populations and operational workflows. I am proficient in developing complex PL/SQL and T-SQL queries, ensuring seamless compatibility across Oracle and Microsoft SQL Server environments. My expertise includes Epic reporting tools such as Radar, Reporting Workbench, and SlicerDicer, allowing me to deliver actionable insights to end-users. Additionally, I create automated SQL extracts for third-party vendors, utilizing stored procedures to enhance data reliability and efficiency. I also build dashboards and reports in Tableau and Crystal Reports, transforming complex data into intuitive visual insights. With a strong background in collaboration, I work closely with different teams from all aspects of the organization to ensure reporting needs align with organizational objectives. Professional Highlights: • Developed large-scale SQL extracts in Oracle and Microsoft SQL Server for third-party vendors, ensuring seamless integration with external payors and regulatory bodies. • Built SQL reports in MS SQL Server for Press Ganey, automating patient survey selection based on federal compliance guidelines using SSIS and scheduled network extractions. • Created Oracle SQL extracts that compiled eligibility and demographic data from multiple sources, ensuring managed care network compliance with state reporting requirements. • Led data extraction initiatives for large healthcare systems, optimizing claim and demographic reporting to reduce denials and maximize reimbursements. • Automated and improved reporting processes for vendor data extracts, managing the full cycle from data mapping to final validation.

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