The effects of copayment policies on adherence to prescription medicines in publicly insured populations

Introduction: Copayments for prescriptions are associated with decreased adherence to medicines resulting in increased health service utilisation, morbidity and mortality. In October 2010 a 50c copayment per prescription item was introduced on the General Medical Services (GMS) scheme in Ireland, the national public health insurance programme for low-income and older people. The copayment was increased to €1.50 per prescription item in January 2013. To date, the impact of these copayments on adherence to prescription medicines on the GMS scheme has not been assessed. Given that the GMS population comprises more than 40% of the Irish population, this presents an important public health problem. The aim of this thesis was to assess the impact of two prescription copayments, 50c and €1.50, on adherence to medicines.Methods: In Chapter 2 the published literature was systematically reviewed with meta-analysis to a) develop evidence on cost-sharing for prescriptions and adherence to medicines and b) develop evidence for an alternative policy option; removal of copayments. The core research question of this thesis was addressed by a large before and after longitudinal study, with comparator group, using the national pharmacy claims database. New users of essential and less-essential medicines were included in the study with sample sizes ranging from 7,007 to 136,111 individuals in different medication groups. Segmented regression was used with generalised estimating equations to allow for correlations between repeated monthly measurements of adherence. A qualitative study involving 24 individuals was conducted to assess patient attitudes towards the 50c copayment policy. The qualitative and quantitative findings were integrated in the discussion chapter of the thesis. The vast majority of the literature on this topic area is generated in North America, therefore a test of generalisability was carried out in Chapter 5 by comparing the impact of two similar copayment interventions on adherence, one in the U.S. and one in Ireland. The method used to measure adherence in Chapters 3 and 5 was validated in Chapter 6. Results: The systematic review with meta-analysis demonstrated an 11% (95% CI 1.09 to 1.14) increased odds of non-adherence when publicly insured populations were exposed to copayments. The second systematic review found moderate but variable improvements in adherence after removal/reduction of copayments in a general population. The core paper of this thesis found that both the 50c and €1.50 copayments on the GMS scheme were associated with larger reductions in adherence to less-essential medicines than essential medicines directly after the implementation of policies. An important exception to this pattern was observed; adherence to anti-depressant medications declined by a larger extent than adherence to other essential medicines after both copayments. The cross country comparison indicated that North American evidence on cost-sharing for prescriptions is not automatically generalisable to the Irish setting. Irish patients had greater immediate decreases of -5.3% (95% CI -6.9 to -3.7) and -2.8% (95% CI -4.9 to -0.7) in adherence to anti-hypertensives and anti-hyperlipidaemic medicines, respectively, directly after the policy changes, relative to their U.S. counterparts. In the long term, however, the U.S. and Irish populations had similar behaviours. The concordance study highlighted the possibility of a measurement bias occurring for the measurement of adherence to non-steroidal anti-inflammatory drugs in Chapter 3. Conclusions: This thesis has presented two reviews of international cost-sharing policies, an assessment of the generalisability of international evidence and both qualitative and quantitative examinations of cost-sharing policies for prescription medicines on the GMS scheme in Ireland. It was found that the introduction of a 50c copayment and its subsequent increase to €1.50 on the GMS scheme had a larger impact on adherence to less-essential medicines relative to essential medicines, with the exception of anti-depressant medications. This is in line with policy objectives to reduce moral hazard and is therefore demonstrative of the value of such policies. There are however some caveats. The copayment now stands at €2.50 per prescription item. The impact of this increase in copayment has yet to be assessed which is an obvious point for future research. Careful monitoring for adverse effects in socio-economically disadvantaged groups within the GMS population is also warranted. International evidence can be applied to the Irish setting to aid in future decision making in this area, but not without placing it in the local context first. Patients accepted the introduction of the 50c charge, however did voice concerns over a rising price. The challenge for policymakers is to find the ‘optimal copayment’ – whereby moral hazard is decreased, but access to essential chronic disease medicines that provide advantages at the population level is not deterred. This evidence presented in this thesis will be utilisable for future policy-making in Ireland.

Self-management education for cystic fibrosis

Background: Self-management education may help patients with cystic fibrosis and their families to choose, monitor and adjust treatment requirements for their illness, and also to manage the effects of illness on their lives. Although self-management education interventions have been developed for cystic fibrosis, no previous systematic review of the evidence of effectiveness of these interventions has been conducted. Objectives: To assess the effects of self-management education interventions on improving health outcomes for patients with cystic fibrosis and their caregivers. Search methods: We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register (date of the last search: 22 August 2013). We also searched databases through EBSCO (CINAHL; Psychological and Behavioural Sciences Collection; PsychInfo; SocINDEX) and Elsevier (Embase) and handsearched relevant journals and conference proceedings (date of the last searches: 01 February 2014 ). Selection criteria: Randomised controlled trials, quasi-randomised controlled trials or controlled clinical trials comparing different types of self-management education for cystic fibrosis or comparing self-management education with standard care or no intervention. Data collection and analysis: Two authors assessed trial eligibility and risk of bias. Three authors extracted data. Main results: Four trials (involving a total of 269 participants) were included. The participants were children with cystic fibrosis and their parents or caregivers in three trials and adults with cystic fibrosis in one trial. The trials compared four different self-management education interventions versus standard treatment: (1) a training programme for managing cystic fibrosis in general; (2) education specific to aerosol and airway clearance treatments; (3) disease-specific nutrition education; and (4) general and disease-specific nutrition education. Training children to manage cystic fibrosis in general had no statistically significant effects on weight after six to eight weeks, mean difference -7.74 lb (i.e. 3.51 kg) (95% confidence interval -35.18 to 19.70). General and disease-specific nutrition education for adults had no statistically significant effects on: pulmonary function (forced expiratory volume at one second), mean difference -5.00 % (95% confidence interval -18.10 to 8.10) at six months and mean difference -5.50 % (95% confidence interval -18.46 to 7.46) at 12 months; or weight, mean difference - 0.70 kg (95% confidence interval -6.58 to 5.18) at six months and mean difference -0.70 kg (95% confidence interval -6.62 to 5.22) at 12 months; or dietary fat intake scores, mean difference 1.60 (85% confidence interval -2.90 to 6.10) at six months and mean difference 0.20 (95% confidence interval -4.08 to 4.48) at 12 months. There is some limited evidence to suggest that self-management education may improve knowledge in patients with cystic fibrosis but not in parents or caregivers. There is also some limited evidence to suggest that self-management education may result in positively changing a small number of behaviours in both patients and caregivers. Authors' conclusions: The available evidence from this review is of insufficient quantity and quality to draw any firm conclusions about the effects of self-management education for cystic fibrosis. Further trials are needed to investigate the effects of self-management education on a range of clinical and behavioural outcomes in children, adolescents and adults with cystic fibrosis and their caregivers.

A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain