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The Third Reader

If the pathology report is our work, then making sure the patient can understand what we have said is part of our work as well

By Kamran Mirza 09/08/2026 Opinion 10 min read

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Objective:

To explore the implications of patients accessing pathology reports directly and the challenges in understanding them.

Approach:
  • Study on Patient Understanding: A randomized study of 2,238 adults published in JAMA in early 2025 assessed comprehension of standard versus patient-centered pathology reports, finding significant differences in understanding.
  • Survey on Cancer Diagnosis Communication: A survey of 2,412 cancer patients conducted by Sheena Bhalla and colleagues at UT Southwestern in 2024 examined how patients learned about their diagnosis, revealing varied preferences for communication.
  • AI in Patient Communication: A prospective controlled trial published in Radiology in November 2025 evaluated the effectiveness of AI-generated simplified reports in improving patient comprehension, showing notable improvements.
Key Findings:
  • 39% of patients understood standard reports correctly, while 93% understood patient-centered versions (JAMA, 2025).
  • 7% of patients learned their diagnosis through an online portal, often alone and without immediate support (UT Southwestern, 2024).
  • AI can improve readability of medical reports but may still contain factual errors and omissions (Radiology, 2025).
Interpretation:

The shift in access to pathology reports has created a need for clearer communication tailored to patients, as traditional reports were not designed for patient understanding.

Limitations:
  • Patients often turn to AI tools for interpretation without clinician supervision, which can lead to misunderstandings.
  • AI-generated reports still require professional review to ensure accuracy and prevent misinformation.
Conclusion:

The evolving landscape of patient access to medical information necessitates new approaches to communication, balancing patient autonomy with the need for accurate understanding.

Sources:

References

  1. CJ Lapedis et al., "Knowledge and worry following review of standard vs patient-centered pathology reports," JAMA, 333, 8 (2025). PMID: 39745765.
  2. S Bhalla et al., "Contemporary trends in reviewing test results through the electronic patient portal among patients with cancer," JAMA Oncol, 10, 1 (2024). PMID: 38032648.
  3. K Ruder, "Running your lab results by ChatGPT? Here is what to keep in mind," NPR Shots (2025). Available at https://www.npr.org/sections/shots-health-news/2025/09/11/nx-s1-5537067/ai-medicine-privacy-test-results
  4. M Presiado et al., "Health misinformation tracking poll: artificial intelligence and health information," KFF (20240 Available at https://www.kff.org/public-opinion/kff-health-misinformation-tracking-poll-artificial-intelligence-and-health-information/
  5. P Prucker et al., "A prospective controlled trial of large language model-based simplification of oncologic CT reports for patients with cancer," Radiology, 317, 2 (2025). PMID: 41251553.
  6. J Naidu et al., "Large language models in radiologist-patient communication: a narrative review for clinical practice," Cureus, 18, 1 (2026). PMID: 41728578.
  7. H Armitage, "AI tool assists doctors in sharing lab results," Stanford Medicine News (2025). Available at https://med.stanford.edu/news/all-news/2025/01/ai-test-results.html
  8. Quest Diagnostics, "Quest Diagnostics introduces AI Companion to help patients understand and act on lab test results," press release, March 2, 2026. Available at https://ir.questdiagnostics.com/press-releases/press-release-details/2026/Quest-Diagnostics-Introduces-AI-Companion-to-Help-Patients-Understand-and-Act-on-Lab-Test-Results/default.aspx
  9. College of American Pathologists, "Cancer protocol templates: cancer reporting and biomarker reporting protocols," Q2 2026 release, 17 June 2026. Available at https://www.cap.org/protocols-and-guidelines/cancer-protocols/current-cancer-protocols/
  10. AL Booth et al., "Please help me see the dragon I am slaying: implementation of a novel patient-pathologist consultation program and survey of patient experience," Arch Pathol Lab Med, 143, 7 (2019). PMID:30398913.
  11. E Shachar et al., "Pathology consultation clinic for patients with cancer: meeting the clinician behind the microscope," JCO Oncol Pract, 17, 10 (2021). PMID: 33797957.
  12. C Lapedis et al., "The patient-pathologist consultation program: a mixed-methods study of interest and motivations in cancer patients," Arch Pathol Lab Med, 144, 4 (2020). PMID: 31429605.
  13. SE Bergholtz et al., "A mixed-methods study of clinicians' attitudes toward pathology explanation clinics," Am J Clin Pathol, 159, 5 (2023). PMID: 36821476.
  14. H Bristow, "Pathology clinics: bringing the lab out of the basement," The Pathologist (2026). Available at https://thepathologist.com/issues/2026/articles/january/pathology-clinics-bringing-the-lab-out-of-the-basement/
  15. American Society for Clinical Pathology, "ASCP deepens commitment to pathologist workforce development," press release, September 11, 2025. Available at https://www.ascp.org/news/news-details/2025/09/11/ascp-deepens-commitment-to-pathologist-workforce-development?srsltid=AfmBOoptJ48DIsub9BeZ_WDQqjGCktfoUiId4rfXJcXdZ7TpwYKOm587
  16. Artera, "Artera receives US FDA De Novo marketing authorization for AI-digital pathology software," press release, August 13, 2025. Available at https://artera.ai/news/artera-receives-u-s-fda-de-novo-marketing-authorization-for-ai-digital-pathology-software-revolutionizing-prostate-cancer-care

About the Author(s)

Kamran Mirza

Kamran M. Mirza, MD, PhD, FCAP, FASCP, Godfrey D. Stobbe Professor of Pathology Education, University of Michigan Medical School; Assistant Chair for Education, Department of Pathology, Michigan Medicine.

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