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Medicine & Health
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The co-design and implementation of embedded monitoring, evaluation and learning into the standard practice of NGO-delivered services for high-risk young people(2022) Trudgett, SkyeThesisYoung people who engage in multiple risky behaviours (high-risk young people), such as substance abuse, antisocial behaviour, or suicidal ideation, are more likely to experience serious harms later in life. Despite these harms, there is extraordinarily little intervention research available to guide policy makers’ or service providers’ decision making about investing in effective programs for high-risk young people (HRYP). One potential reason for this is that most interventions available for vulnerable populations globally, are implemented by NGO’s (Non-Government Organisations) that typically lack the capacity and capability to conduct rigorous evaluation in addition to their primary service delivery roles. There is also little to no consideration given to the application of Indigenous Data Sovereignty (IDS) principles in the context of generating evidence with young Indigenous peoples. This thesis presents a range of methods that could be adopted by NGOs to design and deliver evidence-based programs for HRYP, and to explore the capacity to integrate more routine monitoring and evaluation into NGO’s delivery of those programs. This thesis seeks to demonstrate how research can be grounded in principles of IDS and considers methods for how research might best be operationalised in the context of NGO-delivered programs for HRYP. It is hoped that this approach may provide an exemplar for other programs, research projects and organisations that use data from Indigenous controlled organisations and from Indigenous peoples. The implications of the findings from this thesis, and recommendations for future research and practice implementation, are discussed. Dissemination of the methods described in this thesis will not only improve the internal capacity and capability of NGO-delivered programs to conduct evaluations in collaboration with researchers but will also increase the capacity of Indigenous peoples and communities to advocate for greater sovereignty in relation to the data and research methods with which they choose to engage. These improvements will lead to better outcomes for HRYP and their communities.
(2021) Hilder, LisaThesisChapter 1 - Introduction. This provides an overview of mental and behavioural disorders (MBD) definitions and current knowledge about MBD in pregnancy. Maternal MBD in pregnancy are often overlooked. Most studies of MBD in pregnancy focused on a single class of MBD. This thesis used linked data from NSW Perinatal Data Collection and the NSW Admitted Patient Data Collection to assess diagnosed MBD in NSW maternities between 2002 and 2006. Chapter 2 – Methods. Describes data linkage, MBD definitions and preliminary data processing. Chapter 3 – Admissions for MBD in pregnancy. A study to compare rates of MBD admissions in pregnancy relative to MBD admissions in a baseline period. Overall, admissions for MBD were lower in early pregnancy (RR 0.71) and higher in late pregnancy (RR 1.91). Drug disorder admissions were more than 3-fold higher in late pregnancy. Schizophrenia admissions increased from early pregnancy and alcohol admissions remained lower throughout pregnancy. Baseline MBD admissions rates were higher for multiparous than primiparous maternities. Chapter 4 – Admissions with MBD in pregnancy. MBD prevalence in pregnancy was 2.4% overall, 1.4% for drug/alcohol disorders (DA) and 1.2% mental disorders (MD). Pregnancy DA prevalence was the same, psychotic disorder prevalence was half, affective disorder a third and anxiety a tenth that of comparable disorders in women of reproductive age. Coexisting MBD ranged from 23.6% for anxiety to 91.5% for sedative disorders. Smokers and residents in outer regional or more remote locations were identified as maternity populations at high risk of MBD. Chapter 5 – Neonatal outcomes. Assessed relative risks of individual classes of MBD on perinatal mortality, preterm birth, small size at birth, neonatal morbidity, and admission to neonatal intensive care (NICU). Adverse outcomes were on average 3- 4-fold higher for MBD relative to no MBD. Effects were universally attenuated by adjustment for smoking and co-existing MBD. Independent effects of opiate and cannabis disorders remained for most adverse neonatal outcomes, but not for schizophrenia or bipolar disorder. Chapter 6 – Discussion and conclusions. This thesis demonstrates the value of linked population data; has added to the evidence for pregnancy as risk for MBD; provided the first comprehensive prevalence estimates of MBD in pregnancy for all maternities in NSW, including both high and low prevalence MBD; provided evidence to support findings elsewhere of an independent association of alcohol, cannabis, or opiate disorder with poor neonatal outcomes, but not for schizophrenia or bipolar disorder.
Linked data for pharmacoepidemiology research in Australia: Examining medicine use and outcomes among people with opioid dependence(2023) Bharat, ChriannaThesisDespite strong evidence for the effectiveness of a range of interventions to improve the health and wellbeing of people who are dependent on opioids, morbidity and mortality in this population remains higher than that of the general population. There is a need for innovative approaches to monitor and improve the quality use and safety of available medicines, and to better understand risk factors impacting adverse outcomes in this population. In this thesis, routinely collected administrative data on people with opioid dependence in New South Wales (NSW), Australia, were used to investigate medicine use, including Opioid Agonist Treatment (OAT), opioid analgesics, and other psychotropic medicines. Studies in this thesis examined novel methodological approaches to evaluate medicine exposure and quantify risk, both observed and predicted. This thesis used a diverse range of data sources, including controlled drug registries and pharmaceutical claims databases, linked with health service use and mortality records; and implemented a range of statistical methodologies, including generalised estimating equations, Cox proportional hazards models, and deep learning algorithms. Specifically, this thesis aimed to: (i) estimate retention in OAT and identify person, treatment, and prescriber characteristics that are associated with retention; (ii) develop, evaluate and compare models predicting OAT cessation risk at entry to treatment; (iii) examine trends in opioid analgesic utilisation during periods in and out of OAT; (iv) review methods for generating exposure periods from pharmaceutical dispensing data; and (v) evaluating the all-cause and cause-specific mortality risk associated with opioid analgesics, benzodiazepines, gabapentinoids, and OAT. The first study found retention in OAT to be affected not only by characteristics of the person and their treatment, but also of their prescriber, with longer prescribing tenure associated with increased retention of people in OAT. The results from the second study indicated time-to-event prediction models may be limited in their ability to identify individuals at high cessation risk on entry to OAT. Of the methods used in model development, machine learning approaches performed similarly to traditional statistical methods. In the third study, people with opioid dependence were found to have high rates of recent psychotropic medicine utilisation at the time of opioid analgesic initiation, and reduced opioid analgesic dispensing while engaged in OAT. The fourth study describes a novel method for generating medicine exposure periods from dispensing claims data, developed especially for application to medicines with complex and variable dosing regimens. Finally, in the fifth study, benzodiazepines and gabapentinoids appear to increase mortality risk when used in combination with opioid analgesics, although the risk may be reduced when engaged in OAT. This thesis demonstrates the utility of person-level data linkage and innovative analytical methods to generate real-world evidence about the use and outcomes of prescribed medicines among people with opioid dependence. Awareness of harms in clinical settings and evaluating outcome risk during medicine use would give clinicians the ability to understand who needs prevention and treatment services, ensuring efforts and resources are targeted towards those most at-risk. These represent important strategies for improving quality medicine use and reducing harms among people with opioid dependence.