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Related Experiment Video

Updated: Jun 17, 2026

Endoscopic Bilateral Nipple-sparing Mastectomy via a Single Axillary Incision with Immediate Pre-pectoral Implant-based Breast Reconstruction
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Endoscopic Bilateral Nipple-sparing Mastectomy via a Single Axillary Incision with Immediate Pre-pectoral Implant-based Breast Reconstruction

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Computer-based learning module increases shared decision making in breast reconstruction.

Bernard T Lee1, Chen Chen, Janet H Yueh

  • 1Division of Plastic and Reconstructive Surgery, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. blee3@bidmc.harvard.edu

Annals of Surgical Oncology
|December 30, 2009
PubMed
Summary
This summary is machine-generated.

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A computer-based learning module significantly enhances patient involvement in breast reconstruction decisions. This tool improves satisfaction with information and increases the number of options patients consider.

Area of Science:

  • Medical Informatics
  • Surgical Oncology
  • Patient Education

Background:

  • Shared decision making (SDM) integrates evidence-based medicine with patient preferences for improved healthcare outcomes.
  • Patient engagement in healthcare management correlates with increased compliance, satisfaction, and better health results.
  • This study investigates if a computer-based learning module can enhance patient involvement in breast reconstruction decision-making.

Purpose of the Study:

  • To evaluate the impact of a computer-based learning module on patient participation in breast reconstruction decisions.
  • To assess whether this educational tool improves patient satisfaction with the information provided during consultations.

Main Methods:

  • A cohort of women undergoing breast reconstruction between 2004-2007 at an academic hospital was identified.

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  • Patients received either a standard surgeon consultation or one supplemented with a computer-based decision aid.
  • Questionnaires assessed demographics, information resources, and decision-making processes.

    • Main Results:

    • Patients using the computer-based module reported a significantly greater role in selecting reconstruction type (P < .001).
    • These patients also reported a higher number of reconstructive options presented (P < .001).
    • Satisfaction with the amount of information from surgeons was higher among module users (P = .049).

    Conclusions:

    • Computer-based learning modules empower patients to actively participate in choosing breast reconstruction methods.
    • This educational approach is a simple and effective strategy for enhancing shared decision-making in breast reconstruction.
    • Utilizing digital tools can optimize patient engagement and satisfaction in reconstructive surgery planning.