Development of an intervention to support medication management in patients with multimorbidity in primary care

The overarching aim of this thesis was to develop an intervention to support patient-centred prescribing in the context of multimorbidity in primary care. Methods A range of research methods were used to address different components of the Medical Research Council, UK (MRC) guidance on the development and evaluation of complex interventions in health care. The existing evidence on GPs’ perceptions of the management of multimorbidity was systematically reviewed. In qualitative interviews, chart-stimulated recall was used to explore the challenges experienced by GPs when prescribing for multimorbid patients. In a cross-sectional study, the psychosocial issues that complicate the management of multimorbidity were examined. To develop the complex intervention, the Behaviour Change Wheel (BCW) was used to integrate behavioural theory with the findings of these three studies. A feasibility study of the new intervention was then conducted with GPs. Results The systematic review revealed four domains of clinical practice where GPs experienced difficulties in multimorbidity. The qualitative interview study showed that GPs responded to these difficulties by ‘satisficing’. In multimorbid patients perceived as stable, GPs preferred to ‘maintain the status quo’ rather than actively change medications. In the cross-sectional study, the significant association between multimorbidity and negative psychosocial factors was shown. These findings informed the development of the ‘Multimorbidity Collaborative Medication Review and Decision-making’ (MY COMRADE) intervention. The intervention involves peer support: two GPs review the medications prescribed to a complex multimorbid patient together. In the feasibility study, GPs reported that the intervention was appropriate for the context of general practice; was widely applicable to their patients with multimorbidity; and recommendations for optimising medications arose from all collaborative reviews. Conclusion Applying theory to empirical data has led to an intervention that is implementable in clinical practice, and has the potential to positively change GPs’ behaviour in the management of medications for patients with multimorbidity.

Development of miniaturized wireless sensor nodes suitable for building energy management and modelling

Buildings consume 40% of Ireland's total annual energy translating to 3.5 billion (2004). The EPBD directive (effective January 2003) places an onus on all member states to rate the energy performance of all buildings in excess of 50m2. Energy and environmental performance management systems for residential buildings do not exist and consist of an ad-hoc integration of wired building management systems and Monitoring & Targeting systems for non-residential buildings. These systems are unsophisticated and do not easily lend themselves to cost effective retrofit or integration with other enterprise management systems. It is commonly agreed that a 15-40% reduction of building energy consumption is achievable by efficiently operating buildings when compared with typical practice. Existing research has identified that the level of information available to Building Managers with existing Building Management Systems and Environmental Monitoring Systems (BMS/EMS) is insufficient to perform the required performance based building assessment. The cost of installing additional sensors and meters is extremely high, primarily due to the estimated cost of wiring and the needed labour. From this perspective wireless sensor technology provides the capability to provide reliable sensor data at the required temporal and spatial granularity associated with building energy management. In this paper, a wireless sensor network mote hardware design and implementation is presented for a building energy management application. Appropriate sensors were selected and interfaced with the developed system based on user requirements to meet both the building monitoring and metering requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks associated with minimisation of energy consumption in the built environment and the development of appropriate Building information models(BIM)to enable the design and development of energy efficient spaces.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.