Provider compliance with a tailored opioid prescribing calculator in gynecologic surgery.

OBJECTIVE: To evaluate the impact a tailored opioid prescription calculator has on meeting individual patient opioid needs while avoiding opioid over prescriptions. METHODS: Our group previously developed and published an opioid prescribing calculator incorporating patient risk factors (history of depression, anxiety, chronic opioid use, substance abuse disorder, and/or chronic pain) and type of surgery (laparotomy or laparoscopy). This calculator was implemented on 1/1/2021 and its impact on opioid prescriptions was evaluated until 12/31/21. The primary outcome of the present study is to determine prescriber compliance with the calculator (defined as not overprescribing from the number of pills indicated by the calculator). The secondary outcome is to determine the excess prescription rate (defined as proportion of patients reporting more than 3 pills remaining at 30 days post-surgery). Refill rates and pain related patient phone calls were collected. Descriptive statistics were used to summarize the cohort. RESULTS: Of the 355 patients included, 54.7% (N = 194) underwent laparoscopy and 45.4% (N = 161) underwent laparotomy. One hundred and forty-two patients (40%) had at least one risk factor for opioid usage. The median number of opioid pills prescribed following laparoscopy was 3 (range 0-15) and 6 (0-20) after laparotomy. The prescriber compliance was 88.2% and the excess prescription rate was 25.1% (N = 89 patients). CONCLUSIONS: Our tailored opioid calculator has a high prescriber compliance. Implementation of this calculator led to a standardization of tailored opioid prescribing, while limiting the number of over prescriptions. A free web version of the calculator can be easily accessed at www.opioidcalculator.org.

Optimization of postoperative opioid prescriptions in gynecologic oncology: Striking a balance between opioid reduction and pain control.

OBJECTIVE: To implement a quality-improvement initiative to assess the impact various patient and procedural factors have on postoperative opioid use. To develop a tailored opioid prescribing algorithm for gynecologic oncology patients. METHODS: A retrospective cohort study was performed of patients who underwent a laparoscopy or laparotomy procedure for a suspected or known gynecologic malignancy between 3/2019-9/2020. Patients were assessed preoperatively for the presence of suspected risk factors for opioid misuse (depression, anxiety, chronic pain, current opioid use, or substance abuse). Patients completed a 30-day postoperative questionnaire assessing for total opioid pill use and refills requests. Multivariate models were developed to estimate the independent effect of sociodemographic characteristics, risk factors for opioid misuse and procedural factors on patient reported postoperative opioid use. RESULTS: A total of 390 patients were analyzed. Thirty-nine percent (N = 151/390) of patients reported not using opioids after discharge and 5% (N = 20/390) received an opioid refill. For both minimally invasive procedures and laparotomy procedures, body mass index, comorbidities, intraoperative or postoperative complications and final diagnosis of malignancy were not associated with the amount of opioid consumption. However, younger age and history of risk factors for opioid misuse significantly impacted postoperative opioid use. In multivariate analysis, age (p = 0.038) and risk factors (p < 0.001) remained significant after controlling for other factors. CONCLUSIONS: Two out of every five patients did not use opioids after surgery. Younger patients and those with risk factors for opioid misuse need a tailored approach to prescribing opioids to balance the need for adequate pain control with the risk of misuse.

Aromatase inhibitor use, side effects and discontinuation rates in gynecologic oncology patients.

OBJECTIVE: Aromatase inhibitors (AI) are frequently prescribed in gynecologic oncology. We sought to define the frequency and duration of AI use, characterize AI side effects and determine the reasons for discontinuation in these patients. METHODS: Uterine and ovarian cancer patients with AI use for gynecologic cancer therapy were identified retrospectively. Data were abstracted from the electronic medical record, including cancer type, stage, prior cancer treatments, body mass index, concurrent medications, prevalence of AI side effects before and during AI therapy, length of AI treatment and reason for AI discontinuation. RESULTS: 146 women received AI therapy, with 68 for ovarian cancer (46.6%) and 78 for uterine cancer (53.4%). The majority (71.9%) had advanced stage disease at diagnosis. 54.1% noted AI-associated side effects within the first three visits after starting AI therapy. The most common side effects were arthralgias (29.5%), hot flashes (25.3%), new/worsening fatigue (16.4%), muscle or joint stiffness (8.2%) and myalgias (6.8%). The mean duration of therapy was 14.7 months. Gabapentin or selective serotonin reuptake inhibitor (SSRI) use was associated with decreased musculoskeletal side effects (gabapentin: p < .001, OR 0.88, 95% CI 0.83-0.94; SSRI: p < .001, OR 0.82, 95% CI 0.77-0.89). The most common reason for AI discontinuation was disease progression (87.9%), with 5.0% discontinuing due to side effects and 7.1% for other reasons. CONCLUSION: AI therapy for gynecologic cancers is frequently associated with musculoskeletal side effects, but rarely leads to treatment discontinuation. Thus, AI side effects should be assessed in gynecologic cancer patients to allow potential mitigation of symptoms through adjunct therapies.