Developing and Implementing a Patient-Centered Opioid Prescribing Algorithm among Gynecological Oncology Patients

Area of Science:

• Oncology
• Pain Management
• Public Health

Background:

• The opioid epidemic poses a significant public health challenge.
• Established opioid prescription guidelines are lacking in gynecological oncology.
• Patient-reported pain data is not adequately incorporated into current recommendations.

Purpose of the Study:

• To evaluate opioid prescribing patterns and utilization in gynecological oncology patients.
• To assess patient-reported pain control following hysterectomy.
• To develop and validate an opioid prescription algorithm.

Main Methods:

• A two-phase prospective cohort study was conducted.
• Phase 1: Collected postoperative opioid use (standardized to oral morphine milligram equivalents - MMEs) and identified predictors of outpatient use.
• Phase 2: Implemented a developed opioid prescription algorithm and compared pain control.

Main Results:

• Opioid amounts prescribed significantly exceeded amounts used in Phase 1.
• Surgical route and inpatient MME use were key predictors of outpatient opioid needs.
• The implemented algorithm did not significantly alter pain scores in Phase 2.

Conclusions:

• Opioids are substantially overprescribed for gynecological oncology patients undergoing hysterectomy.
• A standardized algorithm using surgical route and inpatient MME use effectively predicts outpatient opioid requirements.
• The developed algorithm provides a validated approach to optimize opioid prescribing and improve pain management.