The Use of Novel Linked Databasesto Reduce Postoperative Opioid Use Among Patients Undergoing Inpatient Surgery - PROJECT SUMMARY AND ABSTRACT Surgery places patients at increased for opioid use disorder and persistent postoperative opioid use (PPOU). In addition to its direct impact on patient health, PPOU, which affects 5-6% of surgical patients, is associated with an increased risk of opioid use disorder, opioid overdose, and surgical mortality/morbidity. This issue has particular salience for older adults. Over half of all surgical procedures in the United States occur among older adults, over half of older adults will require a surgery once in their lifetime, and the incidence of PPOU among older adults can be as high as 10%. In this light, the long-term goal of this project is to characterize the effectiveness of perioperative interventions in reducing the risk of long-term outcomes such as PPOU and opioid use disorder among older adults undergoing inpatient surgery. While a wide variety of interventions has been hypothesized to reduce the incidence of PPOU and other post-operative opioid outcomes, there remains a lack of consensus about their effectiveness, in part due to data limitations. In particular, it is often challenging to obtain detailed data on perioperative care (i.e., amount of opioid administered intraoperatively) and data on long-term opioid outcomes. This study builds on a novel dataset that links two datasets: the Multicenter Perioperative Outcomes Group (MPOG), a large, multicenter registry of surgical cases using data extracted from electronic medical records and a healthcare claims data for Medicare fee-for-service patients. This novel dataset unites the best aspects of both datasets: the ability to measure perioperative care and the ability to follow patients in order to assess long-term opioid outcomes. We will accomplish the goals of the project through four specific aims. First, we will augment the existing dataset by developing scalable and generalizable tools to incorporate relevant data from the inpatient stay (i.e. opioid administration and the use of non-opioid adjuncts). Second, we will demonstrate the feasibility of these methods at a single institution and expand their use to five institutions. Third, we will use the augmented dataset to evaluate the association between intraoperative interventions (i.e., opioid administration, use of nerve blocks) and long-term opioid outcomes (i.e., PPOU and opioid use disorder). Finally, we will use the augmented dataset to evaluate the association between inpatient stay interventions (i.e., reduced opioid utilization, reduced prescribing at discharge) and long-term opioid outcomes. The findings of this project will be significant as they will help guide crucial aspects of perioperative decision-making such as intraoperative and postoperative opioid administration. The expected outcomes of this project are relevant to the goals of the HEAL Initiative as they will enhance efforts to reduce the incidence of PPOU and other long-term opioid outcomes such as opioid use disorder. Crucially, throughout the project, we will work with stakeholders to maximize its impact, such as consulting with stakeholders to decide the interventions to study and working with stakeholders to incorporate the project findings into clinical guidelines and policy.
