Objective: The aim of this study was to determine preoperative patient characteristics associated with postoperative outpatient opioid use and assess the frequency of postoperative opioid overprescribing. Summary Background Data: Although characteristics associated with inpatient opioid use have been described, data regarding patient factors associated with opioid use after discharge are lacking. This hampers the development of individualized approaches to postoperative prescribing. Methods: We included opioid-naïve patients undergoing hysterectomy, thoracic surgery, and total knee and hip arthroplasty in a single-center prospective observational cohort study. Preoperative phenotyping included self-report measures to assess pain severity, fibromyalgia survey criteria score, pain catastrophizing, depression, anxiety, functional status, fatigue, and sleep disturbance. Our primary outcome measure was self-reported total opioid use in oral morphine equivalents. We constructed multivariable linear-regression models predicting opioids consumed in the first month following surgery. Results: We enrolled 1181 patients; 1001 had complete primary outcome data and 913 had complete phenotype data. Younger age, non-white race, lack of a college degree, higher anxiety, greater sleep disturbance, heavy alcohol use, current tobacco use, and larger initial opioid prescription size were significantly associated with increased opioid consumption. Median total oral morphine equivalents prescribed was 600 mg (equivalent to one hundred twenty 5-mg hydrocodone pills), whereas median opioid consumption was 188 mg (38 pills). Conclusions: In this prospective cohort of opioid-naïve patients undergoing major surgery, we found a number of characteristics associated with greater opioid use in the first month after surgery. Future studies should address the use of non-opioid medications and behavioral therapies in the perioperative period for these higher risk patients.
OBJECTIVE: To evaluate the effects of shared decision making using a simple decision aid for opioid prescribing after hysterectomy. METHODS: We conducted a prospective quality initiative study including all patients undergoing hysterectomy for benign, nonobstetric indications between March 1, 2018, and July 31, 2018, at our academic institution. Using a visual decision aid, patients received uniform education regarding postoperative pain management. They were then educated on the department's guidelines regarding the maximum number of tablets recommended per prescription and the mean number of opioid tablets used by a similar cohort of patients in a previously published study at our institution. Patients were then asked to choose their desired number of tablets to receive on discharge. Structured telephone interviews were conducted 14 days after surgery. The primary outcome was total opioids prescribed before compared with after implementation of the decision aid. Secondary outcomes included opioid consumption, patient satisfaction, and refill requests after intervention implementation. RESULTS: Of 170 eligible patients, 159 (93.5%) used the decision aid (one patient who used the decision aid was subsequently excluded from the analysis owing to significant perioperative complications), including 110 (69.6%) laparoscopic, 40 (25.3%) vaginal, and eight (5.3%) abdominal hysterectomies. Telephone surveys were completed for 89.2% (n=141) of participants. Student’s t-test showed that patients who participated in the decision aid (post–decision aid cohort) were discharged with significantly fewer oral morphine equivalents than patients who underwent hysterectomy before implementation of the decision aid (pre–decision aid cohort) (92±35 vs 160±81, P<.01), with no significant change in the number of requested refills (9.5% [n=15] vs 5.7% [n=14], P=.15). In the post–decision aid cohort, 76.6% of patients (n=121) chose fewer tablets than the guideline-allotted maximum. Approximately 76% of patients (n=102) reported having leftover tablets. CONCLUSION: This quality improvement initiative illustrates that a simple decision aid can result in a significant decrease in opioid prescribing without compromising patient satisfaction or postoperative pain management.
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