• Journal of women's health · May 2024

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

    • Ashlee Candelaria, Lauren Marek, Deborah Kanda, Jamie Griego, and Teresa Rutledge.
    • Department of Obstetrics and Gynecology, University of New Mexico, Albuquerque, New Mexico, USA.
    • J Womens Health (Larchmt). 2024 May 6.

    AbstractBackground: The opioid epidemic is a public health crisis. However, opioid prescription recommendations have not been established in gynecological oncology, and guidelines that incorporate patient-reported pain are lacking. Objectives: The article aims to evaluate prescribing patterns, utilization, and patient-reported pain control in gynecological oncology patients at a large tertiary academic center. Methods: This was a two-phase, prospective cohort study. For Phase 1, patients undergoing hysterectomy through the gynecological oncology division at the University of New Mexico were enrolled. Postoperative opioid use was collected and standardized to oral morphine milligram equivalents (MMEs). The factors associated with outpatient opioid use were used to develop an opioid prescription algorithm. In Phase 2, we evaluated the implementation of the prescription algorithm. For both phases, patients completed a demographic survey, satisfaction survey, and validated pain questionnaires. Results: In Phase 1, the amount of opioids used was significantly lower than the amount of opioids prescribed. Factors that correlated with postoperative opioid use included surgical procedures and last 24-hour inpatient MME use. A standardized opioid prescription algorithm was developed by incorporating these factors. In Phase 2, the opioid prescribing algorithm there was no significant difference in pain scores between the two phases. Conclusions: Opioids were substantially overprescribed in gynecological oncology patients undergoing hysterectomy. Our study found that the surgical route and last 24-hour MME inpatient usage were reliable predictors of outpatient opioid use. We developed and implemented a standardized opioid prescription algorithm that was validated by comparing the pain control measures in the two phases.

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