Economic evaluations of clinical pharmacy services in Ireland, 2007-2015

Introduction The concept of this thesis was driven by stagnation within the Irish healthcare system. Multiple reports from pharmacy organisations had outlined possible future directions for the profession but progress was minimal, especially in comparison with other countries. The author’s directive was to evaluate the economic impact of a series of clinical pharmacy services (CPS) in hospital and community settings. Methods A systematic review of economic evaluations of clinical pharmacy services in hospital patients was undertaken to gain insight into recent research in the field. Eligible studies were evaluated using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS), to establish the quality, consistency and transparency of relevant research. A retrospective analysis of an internal hospital pharmacy interventions database was conducted. A method first described by Nesbit et al. was implemented to estimate the level of cost avoidance achieved. A cost-effectiveness analysis based on data from a randomised controlled trial of a pharmacist-supervised patient self-testing (PST) of warfarin therapy is presented. Outcome measure was the incremental cost associated with six months of intervention management. A similar cost-effectiveness analysis based on previously published RCT data was used to evaluate a novel structured pharmacist review of medication in older hospitalised patients. Cost-effectiveness analysis was presented in the form of an incremental cost-effectiveness ratio (ICER). An ICER is an additional cost per unit effect, in the case of this study, the cost of preventing an additional non-trivial ADR in hospital. A method described by Preaud et al. was adapted to estimate the clinical and economic benefit gained from vaccination of patients by a community pharmacist in Ireland in 2013/14. Sample demographic data was obtained from a national chain of community pharmacies and applied to overall national vaccination data. Results Systematic review identified twenty studies which were eligible for inclusion. Overall, pharmacist interventions had a positive impact on hospital budgets. Only three studies (15%) were deemed to be “good-quality” studies. No ‘novel’ clinical pharmacist intervention was identified during the course of this review. Analysis of internal hospital database identified 4,257 interventions documented on 2,147 individual patients over a 12 month period. Substantial cost avoidance of €710,000 was generated over a 1 year period from the perspective of the health care provider. Mean cost avoidance of €166 per intervention was generated. The cost of providing these interventions was €82,000. Substantial net cost-benefits of €626,279 and a cost-benefit ratio of 8.64 : 1 were generated based on this evaluation of pharmacist interventions. Results from an evaluation of a novel pharmacist-led form of warfarin management indicated indicated that on a per patient basis, PST was slightly more expensive than established anticoagulant management. On a per patient basis over a six month period, PST resulted in an incremental cost of €59.08 in comparison with routine care. Overall cost of managing a patient through pharmacist-supervised PST for a six month period is €226.45. However, for this increase in cost a clinically significant improvement in care was provided. Patients achieved a significantly higher time in therapeutic range during the PST arm in comparison with routine care, (72 ± 19.7% vs 59 ± 13.5%). Difference in overall cost was minimal and PST was the dominant strategy in some scenarios examined during sensitivity analysis. Structured pharmacist review of medication was determined to be dominant in comparison to usual pharmaceutical care. Even if the healthcare payer was unwilling to pay any money for the prevention of an ADR, the intervention strategy is still likely to be cost-effective (probability of being determined cost-effective = 0.707). Implementation of pharmacist-led influenza vaccination has resulted in substantial clinical and economic benefits to the healthcare system. The majority of patients (64.9%) who availed of this service had identifiable influenza-related risk factors. Of patients with influenza-related risk factors, age ≥65 year was the most commonly cited risk factor. Pharmacist vaccination services averted a total of 848 influenza cases across all age groups during the 2013/2014 influenza season. Due to receipt of vaccination in a pharmacy setting, 444 influenza-related GP visits were prevented. In terms of more serious influenza-associated events, 11 hospitalisations and five influenza-related deaths were averted. Costs averted were approximately €305,000. These were principally wider societal-related costs associated with lost productivity. Conclusion Overall, clinical pharmacy services are adding value to the Irish healthcare system in both hospital and community settings, but provision of additional funding for new services would enable them to offer a great deal more.

Are migratory animals superspreaders of infection?

Migratory animals are simultaneously challenged by the physiological demands of long-distance movements and the need to avoid natural enemies including parasites and pathogens. The potential for animal migrations to disperse pathogens across large geographic areas has prompted a growing body of research investigating the interactions between migration and infection. However, the phenomenon of animal migration is yet to be incorporated into broader theories in disease ecology. Because migrations may expose animals to a greater number and diversity of pathogens, increase contact rates between hosts, and render them more susceptible to infection via changes to immune function, migration has the potential to generate both "superspreader species" and infection "hotspots". However, migration has also been shown to reduce transmission in some species, by facilitating parasite avoidance ("migratory escape") and weeding out infected individuals ("migratory culling"). This symposium was convened in an effort to characterize more broadly the role that animal migrations play in the dynamics of infectious disease, by integrating a range of approaches and scales across host taxa. We began with questions related to within-host processes, focusing on the consequences of nutritional constraints and strenuous movement for individual immune capability, and of parasite infection for movement capacity. We then scaled-up to between-host processes to identify what types, distances, or patterns of host movements are associated with the spread of infectious agents. Finally, we discussed landscape-scale relationships between migration and infectious disease, and how these may be altered as a result of anthropogenic changes to climate and land use. We are just beginning to scratch the surface of the interactions between infection and animal migrations; yet, with so many migrations now under threat, there is an urgent need to develop a holistic understanding of the potential for migrations to both increase and reduce infection risk.

Geographic variation in seasonality and its influence on the dynamics of an infectious disease

Seasonal changes in environmental drivers - such as temperature, rainfall, and resource availability - have the potential to shape infection dynamics through their reverberating effects on biological processes including host abundance and susceptibility to infection. However, seasonality varies geographically. We therefore expect marked differences in infection dynamics between regions with different seasonal patterns. By pairing extensive Avian Influenza Virus (AIV) surveillance data - 65 358 individual bird samples from 12 species of dabbling ducks sampled at 174 locations across North America - with quantification of seasonality using remote sensed data indicative for primary productivity (normalised differenced vegetation index, NDVI), we provide evidence that seasonal dynamics influence infection dynamics across a continent. More pronounced epidemics were seen to occur in regions experiencing a higher degree of seasonality, and epidemics of lower amplitude and longer duration occurred in regions with a more protracted and lower seasonal amplitude. These results demonstrate the potential importance of geographic variation in seasonality for explaining geographic variation in the dynamics of infectious diseases in wildlife.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

Análisis de los cambios epigenéticos en la metilación del DNA inducidos por la diabetes y sus posibles mecanismos

Los cambios epigenéticos son responsables de la aparición de muchas patologías humanas y sus causas son debido a factores ambientales como genéticos. Se ha descrito en enfermedades crónicas como la Diabetes Mellitus tipo 2 (T2DM) que se caracteriza por los estados de hiperglucemia y el incremento en el estrés oxidativo que conlleva a complicaciones micro y macro vasculares, asociado a una desmetilación global del genoma. Nuestra hipótesis corresponde a que los órganos diana son afectados por las alteraciones como la metilación e hidroximetilación como consecuencia del estrés oxidativo que luego repercuten en la persistencia de la enfermedad. Métodos: A partir de sangre periférica se analizaron los cambios globales en la metilación del DNA que son afectados por el estado metabólico de 60 individuos (40 pacientes, 20 controles sanos). Por técnicas de cuantificación se compararon los resultados obtenidos con los de la expresión de las enzimas involucradas. Por último, se realizó un estudio de microarreglos de metilación del DNA y de expresión obtenidos de la base de datos GEO para así comparar los resultados con nuestros datos experimentales. Resultados: Los pacientes diabéticos con pobre control metabólico presentaron mayores niveles de metilación que el grupo control y no se encontró alteración en las enzimas involucradas en este proceso. Los resultados fueron concordantes con el estudio de microarreglos. Conclusión: Los estudios experimentales y de microarreglos demostraron que la metilación es tejido específico y que existe una mayor oxidación en pacientes. Por ello proponemos una vía alterna de desmetilación no enzimática, basada en la oxidación directa de los grupos metilos generados por los estados oxidativos característicos de esta enfermedad.