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.

Identification and safe storage of look-alike, sound-alike medicines in automated dispensing cabinets.

OBJECTIVES: Automated dispensing cabinets (ADCs) are used in hospitals to improve medication safety and decrease costs. However, ADCs do not completely eliminate the risk of mistakes between look-alike, sound-alike (LASA) medicines. The aim of this study was to identify the characteristics of LASA medicines and determine the factors related to their safe storage in ADCs. METHODS: The medication selection of one hospital pharmacy's ADC located in an intensive care unit was observed. The study consisted of five parts: a determination of criteria to identify LASA medications, an analysis of an ADCs' inventory reports, assessment of the storage of identified LASA medicines, a visual observation of the medicine packages stored in the same storage compartment and qualitative analysis of the medication-use process from prescribing a medicine to removing it from an ADC. RESULTS: Approximately 70% (n=355/488) of the ADCs selection had a LASA risk with at least one product. Moreover, 20% (n=84/355) of the LASA medicines identified were high-alert medications. Approximately 16% (n=58/355) of the identified LASA medicines were stored unsafely close to at least one other LASA medicine. Less than 4% (n=13/355) of the LASA medicines were unsafely stored high-alert medications. CONCLUSIONS: ADCs reduce the risks of LASA medication errors when used correctly, but automation can also increase them, for example, when placing multiple LASA medicines in the same storage compartment. Attention should be paid to the identification and safe storage of LASA medicines to promote safe use of ADCs in hospitals.

Safety, time and cost evaluation of automated and semi-automated drug distribution systems in hospitals: a systematic review.

OBJECTIVES: To systematically review automated and semi-automated drug distribution systems (DDSs) in hospitals and to evaluate their effectiveness on medication safety, time and costs of medication care. METHODS: A systematic literature search was conducted in MEDLINE Ovid, Scopus, CINAHL and EMB Reviews covering the period 2005 to May 2016. Studies were included if they (1) concerned technologies used in the drug distribution and administration process in acute care hospitals and (2) reported medication safety, time and cost-related outcomes. RESULTS: Key outcomes, conclusions and recommendations of the included studies (n=30) were categorised according to the dispensing method: decentralised (n=19 studies), centralised (n=6) or hybrid system (n=5). Patient safety improved (n=27) with automation, and reduction in medication errors was found in all three systems. Centralised and decentralised systems were reported to support clinical pharmacy practice in hospitals. The impact of the medication distribution system on time allocation such as labour time, staffing workload or changes in work process was explored in the majority of studies (n=24). Six studies explored economic outcomes. CONCLUSIONS: No medication distribution system was found to be better than another in terms of outcomes assessed in the studies included in the systematic review. All DDSs improved medication safety and quality of care, mainly by decreasing medication errors. However, many error types still remained-for example, prescribing errors. Centralised and hybrid systems saved more time than a decentralised system. Costs of medication care were reduced in decentralised systems mainly in high-expense units. However, no evidence was shown that implementation of decentralised systems in small units would save costs. More comparable evidence on the benefits and costs of decentralised and hybrid systems should be available. Changes in processes due to a new DDS may create new medication safety risks; to minimise these risks, training and reallocation of staff resources are needed.