1364Predicting obesity and smoking using medication data: a machine-learning approach

Background Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to develop and validate machine learning (ML)-based models using medication data from Australia’s Pharmaceutical Benefits Scheme (PBS) database to predict obesity and smoking. Methods We used data from the D-Health Trial (N = 18,000) and the QSkin Study (N = 43,794). Smoking history, and height and weight were self-reported at study entry. Linkage to the PBS dataset captured 5 years of medication data after cohort entry. We used age, sex, and medication use, classified using Anatomical Therapeutic Classification codes, as potential predictors of smoking and obesity. We trained gradient-boosted machine learning models using data for the first 80% of participants enrolled; models were validated using the remaining 20%. We assessed model performance overall and by sex and age, and compared models generated using 3 and 5 years of PBS data. Results Based on the validation dataset using 3 years of PBS data, the area under the receiver operating characteristic curve (AUC) was 0.70 (95% confidence interval (CI) 0.68 – 0.71) for predicting obesity and 0.71 (95% CI 0.70 – 0.72) for predicting smoking. Models performed better in women than in men. Using 5 years of PBS data resulted in marginal improvement. Conclusions Medication data in combination with age and sex can be used to predict obesity and smoking. These models may be of value to researchers using data collected for administrative purposes.

“Drugs to avoid” to improve quality use of medicines: how is Australia faring?

Background Each year, the French independent bulletin Prescrire publishes a list of medicines, “Drugs to avoid”, that should not be used in clinical practice as their risk-to-benefit ratio is unfavourable. This study assessed the market approval, reimbursement and use of these medicines in Australia. Methods The approval status of the medicines included in 2019 Prescrire “Drugs to avoid” list was assessed by searching the Australian Register of Therapeutic Goods website. Funding status was assessed on the Pharmaceutical Benefits Scheme (PBS) website, the Australian public insurance system. Use levels were determined by examining governmental reports on prescribing rates including the Australian Statistics on Medicines (ASM) reports, drug use reports released by the Drug Utilisation Sub Committee (DUSC) and PBS statistics. Results Of the 93 medicines included in the Prescrire 2019 “Drug to avoid” list included, 57 (61%) were approved in Australia in 2019 including 9 (16%) that were sold as over-the-counter medicines, 35 (38%) were listed on the PBS, 22 (24%) were registered but not listed on the PBS. Although most of these medicines were used infrequently, 16 (46%) had substantial use despite serious safety concerns. Dipeptidyl peptidase-4 (DPP-4) inhibitors were used by 22% of patients receiving a treatment for diabetes in 2016. More than 50,000 patients received an anti-dementia medicine in 2014, a 19% increase since 2009. Denosumab became the 8th medicine, in terms of total sales, funded by the Australian Government in 2017–2018. Conclusions Prescrire’s assessments provide a reliable external benchmark to assess the current use of medicines in Australia. Sixteen “drugs to avoid”, judged to be more harmful than beneficial based on systematic, independent evidence reviews, are in substantial use in Australia. These results raise serious concerns about the awareness of Australian clinicians of medicine safety and efficacy. Medicines safety has become an Australian National Health Priority. Regulatory and reimbursement agencies should review the marketing and funding status of medicines which have not been shown to provide an efficacy and safety at least similar to alternative therapeutic options.

The impact of COVID-19 on antipsychotic prescriptions for patients with schizophrenia in Australia

Objective: To assess the impact, in the Australian setting, of the COVID-19 lockdown on antipsychotic supplies for patients with schizophrenia following a prescription from a new medical consultation when compared to the same periods in the previous 4 years. A secondary objective was to assess the volume of all antipsychotic supplies, from new and repeat prescriptions, over these same periods. Methods: A retrospective pharmaceutical claims database study was undertaken, using the Department of Human Services Pharmaceutical Benefits Scheme 10% sample. The study population included all adult patients with three or more supplies of oral or long-acting injectable antipsychotics for the treatment of schizophrenia at any time between 1 June 2015 and 31 May 2020. The primary outcome compared volumes of dispensed antipsychotics from new prescriptions (which require a medical consultation) between 1 April and 31 May each year from 2016 to 2020. This was to analyse the period during which the Australian Government imposed a lockdown due to COVID-19 (April to May 2020) when compared the same periods in previous years. Results: There was a small (5.7%) reduction in the number of antipsychotics dispensed from new prescriptions requiring a consultation, from 15,244 to 14,372, between April and May 2019 and the same period in 2020, respectively. However, this reduction was not statistically significant ( p = 0.75) after adjusting for treatment class, age, gender, location and provider type. Conclusion: The COVID-19 restrictions during April and May 2020 had no significant impact on the volume of antipsychotics dispensed from new prescriptions for patients with schizophrenia when compared to the volume of antipsychotics dispensed from new prescriptions during the same period in previous years.

Toilet Paper, Minced Meat and Diabetes Medicines: Australian Panic Buying Induced by COVID-19

The COVID-19 pandemic has impacted the management of non-communicable diseases in health systems around the world. This study aimed to understand the impact of COVID-19 on diabetes medicines dispensed in Australia. Publicly available data from Australia’s government subsidised medicines program (Pharmaceutical Benefits Scheme), detailing prescriptions by month dispensed to patients, drug item code and patient category, was obtained from January 2016 to November 2020. This study focused on medicines used in diabetes care (Anatomical Therapeutical Chemical code level 2 = A10). Number of prescriptions dispensed were plotted by month at a total level, by insulins and non-insulins, and by patient category (general, concessional). Total number of prescriptions dispensed between January and November of each year were compared. A peak in prescriptions dispensed in March 2020 was identified, an increase of 35% on March 2019, compared to average growth of 7.2% in previous years. Prescriptions dispensed subsequently fell in April and May 2020 to levels below the corresponding months in 2019. These trends were observed across insulins, non-insulins, general and concessional patient categories. The peak and subsequent dip in demand have resulted in a small unexpected overall increase for the period January to November 2020, compared to declining growth for the same months in prior years. The observed change in consumer behaviour prompted by COVID-19 and the resulting public health measures is important to understand in order to improve management of medicines supply during potential future waves of COVID-19 and other pandemics.

Longer duration on a Chronic Disease Management plan is associated with long-term adherence to antihypertensive and antithrombotic medications following stroke

Introduction and PurposeChronic Disease Management (CDM) plans are used by general practitioners to manage chronic diseases such as stroke. However, there is limited evidence that being on these plans improve adherence to secondary prevention medications after stroke. We aimed to assess the association of the duration on a CDM plan in improving adherence to secondary prevention medications following stroke. MethodsAustralian survivors of stroke or transient ischaemic attack were participants from the STAND FIRM trial. Patients were individually linked with claims for CDM plans from Medicare and dispensings of secondary prevention medications from the Pharmaceutical Benefits Scheme. We estimated (1) duration on a CDM plan based on the timing and Medicare items claimed and (2) the proportion of days that patients would have been covered by these medications (PDC), while accounting for deaths and instances of over-supply. Dosage for each quantity of medication was determined by the regularity in which patients returned for a refill. Logistic regression was used to evaluate factors associated with ≥80% adherence, up to 3 years after stroke, for each of antihypertensive, antithrombotic and lipid-modifying drugs. ResultsThe median PDC for 563 patients (median age 70yrs; 36% female) ranged from 92% to 95% among the three classes of medications. Approximately 27% did not take up a CDM plan, 33% were on plans for <1.5 years and 40% for 1.5-3 years. Duration on a CDM plan (quintiles) was associated with adherence for antihypertensive (Odds Ratio (OR) 1.18, 95% confidence interval (95%CI) 1.00-1.40, p=0.029) and antithrombotic medications (OR 1.22, 95%CI 1.03-1.46, p=0.024), but not for lipid-lowering medications. ConclusionPeople on a CDM plan for longer had better adherence to antihypertensive and antithrombotic medications in the long-term after stroke. Use and ongoing reviews of CDM plans should be encouraged to improve adherence to secondary prevention medications after stroke.

Consent to Data Linkage in LSAC

IntroductionLinking the existing longitudinal data assets with administrative datasets provide the opportunity to transform longitudinal data into valuable assets to inform research and policy development. Objectives and ApproachThis paper will focus on Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) data linkage landscape and consents which are invaluable for the development of evidence-based health-social-economic policies. ResultsLSAC is Australia’s first nationally-representative longitudinal study of child development. Since 2004, two cohorts of 5,000 children and their parents have been interviewed every two years (B (baby) cohort and K (kindergarten) cohort). Over the years, multiple data linkage has been undertaken based on either parental consent or study child consent. In 2004 parents were asked to consent on behalf of the study child to link Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS)/Repatriation Pharmaceutical Benefits Scheme (RPBS) and Australian Childhood Immunisation Register (ACIR) administrative data to LSAC. The consent rate was 93% was for MBS, PBS and ACIR. Nearly 90% of B cohort parents provided consent to link Australian Early Development Census (AEDC)/National Assessment Program – Literacy and Numeracy (NAPLAN) and 95.4% of K cohort parents provided consent to link NAPLAN.Then ten years later, children in the K cohort were asked to consent to MBS/PBS and income-support administrative data. The rates were 86.6% for MBS, 85.4% for PBS and 81.2% for income-support administrative data. Parental consent to link their MBS, PBS and income-support administrative data was also sought and these rates varied between 60% to 88%. Conclusion/ImplicationsThe discussion will focus on differences in consent rates by time of consent, consenting individual and type of administrative data to be linked. Challenges and considerations that researches should be aware of when designing the linkage consent methodology will also be discussed.