ObjectivesTo provide a map of Anatomical Therapeutic Chemical (ATC) Classification System codes to individual Rx-Risk comorbidities and to validate the Rx-Risk Comorbidity Index.DesignThe 46 comorbidities in the Rx-Risk Index were mapped to dispensing’s indicative of each condition using ATC codes. Prescription dispensing claims in 2014 were used to calculate the Rx-Risk. A baseline logistic regression model was fitted using age and gender as covariates. Rx-Risk was added to the base model as an (1) unweighted score, (2) weighted score and as (3) individual comorbidity categories indicating the presence or absence of each condition. The Akaike information criterion and c-statistic were used to compare the models.SettingModels were developed in the Australian Government Department of Veterans’ Affairs health claims data, and external validation was undertaken in a 10% sample of the Australian Pharmaceutical Benefits Scheme Data.ParticipantsSubjects aged 65 years or older.Outcome measuresDeath within 1 year (eg, 2015).ResultsCompared with the base model (c-statistic 0.738, 95% CI 0.734 to 0.742), including Rx-Risk improved prediction of mortality; unweighted score 0.751, 95% CI 0.747 to 0.754, weighted score 0.786, 95% CI 0.782 to 0.789 and individual comorbidities 0.791, 95% CI 0.788 to 0.795. External validation confirmed the utility of the weighted index (c-statistic=0.833).ConclusionsThe updated Rx-Risk Comorbidity Score was predictive of 1-year mortality and may be useful in practice to adjust for confounding in observational studies using medication claims data.
The Pharmaceutical Benefits Scheme (PBS) dataset provides detailed information about subsidised medicines dispensed in Australia and is increasingly used for pharmacoepidemiological research. Use of the PBS dataset provides unique opportunities for such research, but comes with its own set of challenges that must be considered and addressed. This paper outlines some issues that commonly arise when using PBS data − relating to accurate identification of medicine dispensings and how to define medicine exposure − and suggests some possible approaches for dealing with them. The paper is intended as an introductory resource for researchers. IntroductionThe Pharmaceutical Benefits Scheme (PBS) is an Australian Government program that provides residents with access to a wide range of subsidised prescription medicines.1 The scheme is managed by the Department of Health and administered by the Department of Human Services. The PBS dataset is the administrative record of medicines dispensed to individuals through the scheme. This dataset is increasingly used for research and has major advantages compared with self-reported information on medicines or clinical chart review. PBS data for particular studies can be requested and accessed by approved researchers; identifiers are removed from records to protect consumer privacy. A 10% random sample of the Australian population's PBS data is also available to the medicines industry and other research groups. 2The PBS dataset captures community-based dispensings of prescription medicines subsidised by the Australian Government. However, in general terms, it does not capture information on medicines supplied by nonapproved pharmacies or hospitals 3 , private prescriptions (for medicines not listed on the PBS), over-the-counter medicines, and medicines covered under schemes Using Australian Pharmaceutical Benefits Scheme data for pharmacoepidemiological research: challenges and approaches
Summary Extended‐release opioids are often prescribed to manage postoperative pain despite being difficult to titrate to analgesic requirements and their association with long‐term opioid use. An Australian/New Zealand organisational position statement released in March 2018 recommended avoiding extended‐release opioid prescribing for acute pain. This study aimed to evaluate the impact of this organisational position statement on extended‐release opioid prescribing among surgical inpatients. Secondary objectives included predictors and clinical outcomes of prescribing extended‐release opioids among surgical inpatients. We conducted a retrospective, dual centre, 11‐month before‐and‐after study and time‐series analysis by utilising electronic medical records from two teaching hospitals in Sydney, Australia. The primary outcome was the proportion of patients prescribed an extended‐release opioid. For surgical patients prescribed any opioid (n = 16,284), extended‐release opioid prescribing decreased after the release of the position statement (38.4% before vs. 26.6% after, p < 0.001), primarily driven by a reduction in extended‐release oxycodone (31.1% before vs. 14.1% after, p < 0.001). There was a 23% immediate decline in extended‐release opioid prescribing after the position statement release (p < 0.001), followed by an additional 0.2% decline per month in the following months. Multivariable regression showed that the release of the position statement was associated with a decrease in extended‐release opioid prescribing (OR 0.54, 95%CI 0.50–0.58). Extended‐release opioid prescribing was also associated with increased incidence of opioid‐related adverse events (OR 1.52, 95%CI 1.35–1.71); length of stay (RR 1.44, 95%CI 1.39–1.51); and 28‐day re‐admission (OR 1.26, 95%CI 1.12–1.41). Overall, a reduction in extended‐release opioid prescribing was observed in surgical inpatients following position statement release.
Background: Varenicline, bupropion and nicotine replacement therapy (NRT) are three effective pharmacotherapies for smoking cessation, but data about their safety in pregnancy are limited. We assessed the risk of adverse perinatal outcomes and major congenital anomalies associated with the use of these therapies in pregnancy in Australia. Methods: Perinatal data for 1,017,731 deliveries (2004 to 2012) in New South Wales and Western Australia were linked to pharmaceutical dispensing, hospital admission and death records. We identified 97,875 women who smoked during pregnancy; of those, 233, 330 and 1057 were exposed to bupropion, NRT and varenicline in pregnancy, respectively. Propensity scores were used to match exposed women to those who were unexposed to any smoking therapy (1:10 ratio). Propensity scores and gestational age at exposure were used to match varenicline-exposed to NRT-exposed women (1:1 ratio). Time-dependent Cox proportional hazards models estimated hazard ratios (HR) with 95% confidence intervals (95% CI) for any adverse perinatal event (a composite of 10 unfavourable maternal and neonatal outcomes) and any major congenital anomaly. Results: The risk of any adverse perinatal event was not significantly different between bupropion-exposed and unexposed women (39.2% versus 39.3%, HR 0.93, 95% CI 0.73-1.19) and between NRT-exposed and unexposed women (44.8% vs 46.3%, HR 1.02, 95% CI 0.84-1.23), but it was significantly lower in women exposed to varenicline (36.9% vs 40.1%, HR 0.86, 95% CI 0.77-0.97). Varenicline-exposed infants were less likely than unexposed infants to be born premature (6.5% vs 8.9%, HR 0.72, 95% CI 0.56-0.92), be small for gestational age (11.4% vs 15.4%, HR 0.68, 95% CI 0.56-0.83) and have severe neonatal complications (6.6% vs 8.2%, HR 0.74, 95% CI 0.57-0.96). Among infants exposed to varenicline in the first trimester, 2.9% had a major congenital anomaly (3.5% in unexposed infants, HR 0.91, 95% CI 0.72-1.15). Varenicline-exposed women were less likely than NRT-exposed women to have an adverse perinatal event (38.7% vs 51.4%, HR 0.58, 95% CI 0.33-1.05).
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