In-hospital postoperative opioid use and its trends in neurosurgery between 2007 and 2018

Background Postoperative opioid use plays an important role in the global opioid crisis, but little is known about in-hospital opioid use trends of large surgical units. We investigated whether postoperative in-hospital opioid consumption changed in a large academic neurosurgical unit between 2007 and 2018. Methods We extracted the data of consumed opioids in the neurosurgical intensive care unit and two bed wards between 2007 and 2018. Besides overall consumption, we analyzed the trends for weak (tramadol and codeine), strong, and the most commonly used opioids. The use of various opioids was standardized using the defined daily doses (DDDs) of each opioid agent. A linear regression analysis was performed to estimate annual treatment day-adjusted changes with 95% confidence intervals. Results Overall, 121 361 opioid DDDs were consumed during the 196 199 treatment days. Oxycodone was the most commonly used postoperative opioid (49% of all used opioids) in neurosurgery. In the bed wards, the use of oral oxycodone increased 375% (on average 13% (9–17%) per year), and the use of transdermal buprenorphine 930% (on average 26% (9–45%) per year) over the 12-year period. Despite the increased use of strong opioids in the bed wards (on average 3% (1–4%) per year), overall opioid use decreased 39% (on average 6% (4–7%) per year) between 2007 and 2018. Conclusions Due to the increase of strong opioid use in the surgical bed wards, we encourage other large teaching hospitals and surgical units to investigate whether their opioid use trends are similarly worrisome and whether the opioid consumption changes in the hospital setting are transferred to opioid use patterns or opioid-related harms after discharge.

Integrating Palliative Care Into a Neurosurgical Intensive Care Unit (NS-ICU): A Quality Improvement (QI) Project

Objectives: We conducted a pilot quality improvement (QI) project with the aim of improving accessibility of palliative care to critically ill neurosurgical patients. Methods: The QI project was conducted in the neurosurgical intensive care unit (NS-ICU). Prior to the QI project, referral rates to palliative care were low. The ICU-Palliative Care collaborative comprising of the palliative and intensive care team led the QI project from 2013 to 2015. The interventions included engaging key stake-holders, establishing formal screening and referral criteria, standardizing workflows and having combined meetings with interdisciplinary teams in ICU to discuss patients’ care plans. The Palliative care team would review patients for symptom optimization, attend joint family conferences with the ICU team and support patients and families post-ICU care. We also collected data in the post-QI period from 2016 to 2018 to review the sustainability of the interventions. Results: Interventions from our QI project and the ICU-Palliative Care collaborative resulted in a significant increase in the number of referrals from 9 in 2012 to 44 in 2014 and 47 the year later. The collaboration was beneficial in facilitating transfers out of ICU with more deaths outside ICU on comfort-directed care (96%) than patients not referred (75.7%, p < 0.05). Significantly more patients had a Do-Not-Resuscitation (DNR) order upon transfer out of ICU (89.7%) compared to patients not referred (74.2.%, p < 0.001), and had fewer investigations in the last 48 hours of life (p < 0.001). Per-day ICU cost was decreased for referred patients (p < 0.05). Conclusions: Multi-faceted QI interventions increased referral rates to palliative care. Referred patients had fewer investigations at the end-of-life and per-day ICU costs.