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Using Patient Management Report to Identify Ideal Patients for Targeted Marketing

Introduction

The Patient Management report is a good place to view or gather patient data to help healthcare clinics understand their “best” or “ideal” patients. By reviewing metrics such as total visits, payments collected, collections per visit, location (zip code), age, gender, referral source, and insurance details, clinics can create data-driven patient profiles. These profiles enable more effective marketing campaigns - reaching similar high-value patients while reducing wasted spend on poor fits.

Important HIPAA Note

Always work with de-identified data only. Never export or analyze Protected Health Information (PHI) such as names, dates of birth (in identifiable form), full addresses, phone numbers, email addresses, medical record numbers, or specific diagnosis details that could re-identify a patient.

Step-by-Step: How to Generate and Use Ideal Patient Insights

  1. Access the Patient Management Report

    • Log in to your TrackStat dashboard.

    • Navigate to Patient Management.

    • This report displays key metrics including:

      • Total visits

      • Total payment (patient + insurance)

      • Collections per visit

      • Insurance company & fee schedule

      • Referral source

      • Age range / gender (filters)

      • Zip code (filter)

  2. Apply Filters to Focus on Relevant Data

    • Use the built-in filters to narrow the dataset before exporting:

      • Visit Date range (e.g., last 3–6 months)

      • Age range (e.g., 35–55)

      • Zip code or radius (to focus on local high-value areas)

  3. Export the Data

    • Click Download button to save as a .csv file.

    • Store the file securely and delete it after analysis per your clinic’s data retention policy.

  4. Analyze the Data to Build Ideal Patient Profiles Common approaches include:

    • Manual review in spreadsheet software (Excel/Google Sheets): Sort by total payment or visits, use pivot tables.

    • AI-powered analysis (recommended for deeper insights):

      • Upload the de-identified CSV to a secure AI tool (ChatGPT, Claude, Google Gemini, or your preferred HIPAA-compliant analytics platform).

      • Prompt example: “Analyze this de-identified patient data. Identify the top 20% of patients by collections per visit. Summarize common characteristics: referral sources and insurance types. Suggest marketing targeting criteria.”

    Typical insights you may discover:

    • “Our highest-value patients were referred by existing patients with XYZ insurance.”

    • This directly informs ad targeting, email lists, and content strategy.

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