The development and comparative effectiveness of a patient-centered pathology report for breast cancer care: a randomized clinical trial


Purpose

Pathology reports can be difficult for patients newly diagnosed with breast cancer to understand. We studied how patient-centered pathology reports (PCPRs), which use simpler language, can help patients better understand their results.

Methods

We involved sixty-six patients who were recently diagnosed with breast cancer. They were divided into two groups: one group received both a PCPR and a standard report (intervention group), while the other group received only the standard report (control group). We surveyed the patients at the time of receiving their pathology results and again one month later to see how much they understood about their breast cancer and how confident they felt in making treatment decisions.

Results

Patients in the intervention group showed a better understanding of their breast cancer, with 66% accurately knowing key information compared to 50% in the control group. The intervention group particularly excelled in understanding their cancer type and surgical margin status.

However, there were no significant differences between the two groups in terms of how well they communicated or how confident they felt about their treatment decisions.

Conclusions

The use of PCPRs made it easier for patients to grasp their breast cancer diagnosis and was well-received by both patients and healthcare providers. This approach has the potential to be widely implemented to enhance patient understanding and improve their experience during diagnosis.

Measurable Outcomes

To enhance breast cancer care, it is important to:

  • Improve patient knowledge through simplified reports.
  • Set clear goals to measure the effectiveness of these new reports.

Selecting AI Tools

Choosing AI solutions that cater to the specific needs of clinics and patients will be crucial in providing better care based on the findings from this trial.

Implementation Steps

Start small with a pilot project using the new reports. Track the results and expand the use of AI solutions to monitor the real-world impact based on research outcomes.

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