Take control of your Kaiser Permanente blood test results (no coding knowledge required)

ai
github
Author

Andrea Zonca

Published

December 2, 2025

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Want to make sense of your Kaiser Permanente blood test results without needing to be a coding expert? This guide will walk you through using readily available tools to analyze your health summary, specifically focusing on lipid panels, with a step-by-step approach.

Step 1: Download your Health Summary from kp.org

  1. Log in to your kp.org account.
  2. Navigate to “Health Summary”.
  3. Click on “Download Health Summary”.

This action will download a .zip file to your computer.

Step 2: Extract the Data

Locate the downloaded .zip file (usually in your Downloads folder) and double-click it to extract its contents. Inside, you’ll find a folder structure. The actual data you need is typically located within the IHE_XDM/Firstname1/ folder. This folder contains numerous .xml files, each representing different aspects of your health record.

Warning

At this point, you might have many .xml files (e.g., 77 in one instance). Directly feeding all of these into most AI chat interfaces like ChatGPT or Gemini is not feasible, as they often have limitations on the number of files or the total content size they can process simultaneously.

Step 3: Use GitHub and Codex (ChatGPT Plus) for Analysis

While coding experience would allow you to process these files with tools like codex cli or Gemini in the terminal, the easiest non-coding solution is to use Codex, a feature available with ChatGPT Plus (a paid subscription, approximately $20/month).

Here’s how to do it:

  1. Create a free account on Github.com.
  2. Create a New Repository:
    • Click the “+” sign in the top right corner and select “New repository”. :::callout-warning
    • CRITICAL: Make sure to select “Private” for your repository. This step is paramount to ensure your personal health data remains secure and confidential and is not exposed publicly. :::
    • Check “Add a README file” so your repository isn’t empty.
    • Click “Create repository”.
  3. Upload Your XML Files:
    • Once your repository is created, click the “Add file” button, then select “Upload files”.
    • Drag and drop all the .xml files from your IHE_XDM/Firstname1/ folder into the upload area.
    • Commit the changes.
  4. Connect to Codex on ChatGPT:
    • Go to chatgpt.com.
    • Select Codex (available if you have ChatGPT Plus).
    • Follow the prompts to link your GitHub account and choose the private repository where you uploaded your .xml files.
  5. Analyze Your Data:
    • In the Codex chat interface, provide a clear instruction, such as: > “Analyze the XML files and extract all values from the lipid panel of my blood tests to a a csv file named lipid_panel.csv.”
    • Let Codex work. This process might take up to 10 minutes, depending on the number and size of your files.

Step 4: Visualize Your Results

After Codex finishes, it will generate a lipid_panel.csv file. This file will appear as a preview directly within the Codex interface, and you can copy its content from there. You can now use this CSV data for visualization:

  1. Copy the entire content of the lipid_panel.csv preview from the Codex interface.
  2. Paste the content into the regular ChatGPT interface (not Codex).
  3. Ask ChatGPT to create a plot. For example: > “I’ll paste a CSV. Create a 4-panel plot with lipid values (Total Cholesterol, LDL, HDL, Triglycerides). Also add typical healthy limits for each, and shade the ‘bad’ areas (e.g., too high LDL, too low HDL) in red.”

This process empowers you to gain meaningful insights from your health data without writing a single line of code, transforming raw XML into understandable visualizations.