Nonresponse adjustment using clinical and perioperative patient characteristics is critical for understanding post-discharge opioid consumption

Abstract

Background: Post-discharge opioid consumption is an important source of data in guiding appropriate opioid prescribing guidelines, but its collection is tedious and requires significant resources. Furthermore, the reliability of post-discharge opioid consumption surveys is unclear. Our group developed an automated short messaging service (SMS)-to-web survey for collecting this data from patients. In this study, we assessed its effectiveness in estimating opioid consumption by performing causal adjustment and comparison to a phone-based survey as reference. Methods: Patients who underwent surgical procedures at our institution from 2019-2020 were sent an SMS message with a link to a secure web survey to quantify opioids consumed after discharge. Several patient factors extracted from the EHR were tested for association with survey response. Following targeted learning (TL) nonresponse adjustment using these EHR-based factors, opioid consumption survey results were compared to a prior telephone-based survey at our institution as a reference. Results: 6,553 patients were included. Opioid consumption was measured in 2,883 (44%), including 1,342 (20.5%) through survey response. Characteristics associated with inability to measure opioid consumption included age, length of stay, race, tobacco use, and missing preoperative assessment. Among the top 10 procedures by volume, EHR-based TL nonresponse bias adjustment corrected the median opioid consumption reported by an average of 57%, and corrected the 75th percentile of reported consumption by an average of 11%. This brought median estimates for 6/10 procedures closer to telephone survey-based consumption estimates, and 75th percentile estimates for 3/10 procedures closer to telephone survey-based consumption estimates. Conclusion: We found that applying electronic health record (EHR)-based machine learning nonresponse bias adjustment is essential for debiased opioid consumption estimates from patient surveys. After adjustment, post-discharge surveys can generate reliable opioid consumption estimates. Clinical factors from the EHR combined with TL adjustment appropriately capture differences between responders and nonresponders and should be used prior to generalizing or applying opioid consumption estimates to patient care.

Evaluation of U.S. State Opioid Prescribing Restrictions Using Patient Opioid Consumption Patterns from a Single, Urban, Academic Institution

“…We chose to examine the 75th percentile as prior studies and guidelines have used this value as an outlier threshold for typical opioid consumption. [11][12][13] All data were collected and managed using Research Electronic Data Capture. 14 The study was reviewed and approved by the institutional review board at our institution.…”

“…We also identified procedures for which the median and 75th percentile of opioid consumption exceeded these thresholds. We chose to examine the 75th percentile as prior studies and guidelines have used this value as an outlier threshold for typical opioid consumption 11 – 13…”

Research priorities for the surgical care of patients taking opioids preoperatively

“…While collecting these data may seem like a difficult undertaking, collecting postdischarge consumption data in an automated fashion does not necessitate substantial investment of human capital. Prior groups have described implementing systems for standardized collection of postdischarge opioid consumption data using automated email and short message service (SMS) surveys 13…”

Surgical Residency Programs Should Leverage Recent Advances in National Policy, Real-World Data, and Public Opinion to Improve Post-Surgery Opioid Prescribing

“…Similarly, at our institution, evidence-based educational materials are developed annually for residents using a prospective database of patient opioid consumption data that is continuously updated. Educational seminars, prescribing guidance cards, feedback emails, and an online prescribing guidance dashboard 24 for residents are all informed by this consumption data. 19 We have chosen to use consumption data gathered at our institution to build these resources, since we have previously shown that most national consensus guidelines for post-surgical opioid prescribing significantly overestimate patients' opioid needs.…”

“…Several research groups, including ours, have developing robust models that provide prescribing guidance tailored to patient needs and can be made available to prescribers. 12,24,26 Electronic Prescriptions for Controlled Substances (EPCS) is another important new technology that is removing barriers to reduced prescribing and should be embraced as a tool for mitigating opioid overprescribing by surgical residency programs. Legislation passed by Congress in 2018 promoted the use of EPCS for opioids to combat the opioid crisis: it encouraged providers to prescribe opioids through their electronic health record by transmitting these…”