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Background: There is an urgent need to reduce preventable deaths and hospitalizations from prescription opioid harms and minimize the negative effect opioid misuse can have on injured individuals, families, and the wider community. Data linkage between administrative hospitalization records for injured patients and community opioid dispensing can improve our understanding of the health and surgical trajectories of injured persons and generate insights into corresponding opioid dispensing patterns. Objective: The Community Opioid Dispensing after Injury (CODI) study aims to link inpatient hospitalization data with opioid dispensing data to examine the distribution and predictive factors associated with high or prolonged community opioid dispensing among adults, for 2 years following an injury-related hospital admission. Methods: This is a retrospective population-based cohort study of adults aged 18 years or older hospitalized with an injury in Queensland, Australia. The study involves the linkage of statewide hospital admissions, opioid prescription dispensing, and mortality data collections. All adults hospitalized for an injury between January 1, 2014, and December 31, 2015, will be included in the cohort. Demographics and injury factors are recorded at the time of the injury admission. Opioid dispensing data will be linked and extracted for 3 months prior to the injury admission date to 2 years after the injury separation date (last date December 31, 2017). Deaths data will be extracted for the 2-year follow-up period. The primary outcome measure will be opioid dispensing (frequency and quantity) in the 2 years following the injury admission. Patterns and factors associated with community opioid dispensing will be examined for different injury types, mechanisms, and population subgroups. Appropriate descriptive statistics will be used to describe the cohort. Regression models will be used to examine factors predictive of levels and duration of opioid use. Nonparametric methods will be applied when the data are not normally distributed. Results: The project is funded by the Royal Brisbane and Women's Hospital Foundation. As of November 2021, all ethics and data custodian approvals have been granted. Data extraction and linkage has been completed. Data management and analysis is underway with results relating to an analysis for blunt chest trauma patients expected to be published in 2022. Conclusions: Little is currently known of the true prevalence or patterns of opioid dispensing following injury across Queensland. This study will provide new insights about factors associated with high and long-term opioid dispensing at a population level. This information is essential to inform targeted public policy and interventions to reduce the risk of prolonged opioid use and dependence for those injured. The novel work undertaken for this project will be vital to planning, delivering, monitoring, and evaluating health care services for those injured. The findings of this study will be used to inform key stakeholders as well as clinicians and pain management services. International Registered Report Identifier (IRRID): RR1-10.2196/36357 [ABSTRACT FROM AUTHOR]

Background Erroneous patient birthdates are common in health databases. Detection of these errors usually involves manual verification, which can be resource intensive and impractical. By identifying a frequent manifestation of birthdate errors, this paper presents a principled and statistically driven procedure to identify erroneous patient birthdates. Results Generalized additive models (GAM) enabled explicit incorporation of known demographic trends and birth patterns. With false positive rates controlled, the method identified birthdate contamination with high accuracy. In the health data set used, of the 58 actual incorrect birthdates manually identified by the domain expert, the GAM-based method identified 51, with 8 false positives (resulting in a positive predictive value of 86.0% (51/59) and a false negative rate of 12.0% (7/58)). These results outperformed linear time-series models. Conclusions The GAM-based method is an effective approach to identify systemic birthdate errors, a common data quality issue in both clinical and administrative databases, with high accuracy. [ABSTRACT FROM AUTHOR]

Background and Aims Design, setting, participants, measurements Findings Conclusions Between 2018 and 2020, Australia implemented major policy changes to improve the quality and safety of opioid prescribing, with a specific focus on oxycodone. This study used wastewater‐based epidemiology to assess the efficacy of Australia's regulatory reforms by measuring change in consumption of oxycodone via exploratory analysis.Wastewater analysis data on oxycodone consumption was from the National Wastewater Drug Monitoring Program. The program captures data from more than 50 wastewater treatment plant catchments across Australia, equivalent to more than 50% of the national population. Geographic trend analyses were conducted for both major cities and regional areas within all states and territories of Australia over a 6‐year period between 2017 and 2023.Oxycodone consumption showed a statistically significant increase nationally from 78 mg/day/1000 people (95% confidence interval [CI] = 71, 84) in 2017 to 120 mg/day/1000 people in August 2019 (95% CI = 110, 120), an increase of 52% (95% CI = 42, 62, P < 0.0001). From August 2019 to December 2020, there was a statistically significant decrease from 120 to 65 mg/day/1000 people (95% CI = 60, 71), a decrease of 45% (95% CI = 40, 51), followed by a modest 2.4% increase to the end of the study period in April 2023 (95% CI [2.0,2.7]).A 45% reduction in oxycodone consumption in Australia from 2019 to 2020 coincided with national policy changes that aimed to reduce consumption of prescription opioids. The overall declining trend in consumption was suggestive of the effectiveness of national interventions in reducing pharmaceutical opioid use. Wastewater‐based epidemiology provides an effective approach for assessing the effectiveness of controlled substances policy changes. [ABSTRACT FROM AUTHOR]