Provider diversity in the NHS: impact on quality and innovation

The overall objective of the research project has been to assess the impact of provider diversity on quality and innovation in the NHS. The specific research aims were to identify the differences in performance between non-profit Third Sector organisations, for-profit private enterprises, and incumbent public sector institutions within the NHS as providers of health care services, as well as the factors that affect the entry and growth of new private and Third Sector providers. The study used both qualitative and quantitative methods based on case studies of four Local Health Economies (LHEs). Qualitative methods included documentary analysis and interviews with key informants and managers of both commissioning and provider organisations. To provide a focus to the study, two tracer conditions were followed: orthopaedic surgery and home health care for frail older people. In the case of hospital inpatient care, data on patient characteristics were also collected from the HES database. The analysis of this data provided preliminary estimates of the effects of provider type on quality, controlling for client characteristics and case mix. In addition, a survey of patient experience in diverse provider organisations was analysed to compare the different dimensions of quality of provision of acute services between incumbent NHS organisations and new independent sector treatment centres. The research has shown that, in respect of inpatient hospital services, diverse providers supply health services of at least as good quality as traditional NHS providers, and that there is ample opportunity to expand their scale and scope as providers of services commissioned by the NHS. The research used patient experience survey data to investigate whether hospital ownership affects the quality of services reported by NHS patients in areas other than clinical quality. The raw survey data appear to show that private hospitals provide higher quality services than the public hospitals. However, further empirical analysis leads to a more nuanced understanding of the performance differences. Firstly, the analysis shows that each sector offers greater quality in certain specialties. Secondly, the analysis shows that differences in the quality of patients’ reported experience are mainly attributable to patient characteristics, the selection of patients into each type of hospital, and the characteristics of individual hospitals, rather than to hospital ownership as such. Controlling for such differences, NHS patients are on average likely to experience a similar quality of care in a public or privately-run hospital. Nevertheless, for specific groups of patients and for specific types of treatments, especially the more straightforward ones, the private sector provides an improved patient experience compared to the public sector. Elsewhere, the NHS continues to provide a high quality service and outperforms the private sector in a range of services and for a range of clients.

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

Innovation in construction: a sociology of technology approach

An alternative approach to understanding innovation is made using two intersecting ideas. The first is that successful innovation requires consideration of the social and organizational contexts in which it is located. The complex context of construction work is characterized by inter-organizational collaboration, a project-based approach and power distributed amongst collaborating organizations. The second is that innovations can be divided into two modes: ‘bounded’, where the implications of innovation are restricted within a single, coherent sphere of influence, and ‘unbounded’, where the effects of implementation spill over beyond this. Bounded innovations are adequately explained within the construction literature. However, less discussed are unbounded innovations, where many firms' collaboration is required for successful implementation, even though many innovations can be considered unbounded within construction's inter-organizational context. It is argued that unbounded innovations require an approach to understand and facilitate the interactions both within a range of actors and between the actors and technological artefacts. The insights from a sociology of technology approach can be applied to the multiplicity of negotiations and alignments that constitute the implementation of unbounded innovation. The utility of concepts from the sociology of technology, including ‘system building’ and ‘heterogeneous engineering’, is demonstrated by applying them to an empirical study of an unbounded innovation on a major construction project (the new terminal at Heathrow Airport, London, UK). This study suggests that ‘system building’ contains outcomes that are not only transformations of practices, processes and systems, but also the potential transformation of technologies themselves.

Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks

The themes of awareness and influence within the innovation diffusion process are addressed. The innovation diffusion process is typically represented as stages, yet awareness and influence are somewhat under-represented in the literature. Awareness and influence are situated within the contextual setting of individual actors but also within the broader institutional forces. Understanding how actors become aware of an innovation and then how their opinion is influenced is important for creating a more innovation-active UK construction sector. Social network analysis is proposed as one technique for mapping how awareness and influence occur and what they look like as a network. Empirical data are gathered using two modes of enquiry. This is done through a pilot study consisting of chartered professionals and then through a case study organization as it attempted to diffuse an innovation. The analysis demonstrates significant variations across actors’ awareness and influence networks. It is argued that social network analysis can complement other research methods in order to present a richer picture of how actors become aware of innovations and where they draw their influences regarding adopting innovations. In summarizing the findings, a framework for understanding awareness and influence associated with innovation within the UK construction sector is presented. Finally, with the UK construction sector continually being encouraged to be innovative, understanding and managing an actor’s awareness and influence network will be beneficial. The overarching conclusion thus describes the need not only to build research capacity in this area but also to push the boundaries related to the research methods employed.

Innovation clusters: key concepts

Innovation is easier to describe than it is to systematically analyse, and easier to analyse than it is to effectively promote. Part of the problem, of course, is the imprecise way in which the activity of innovation itself is conceptualised. To achieve more precision, the logic of analysis suggests that innovation should be should be systematically analysed and then divided into rough categories to produce a working taxonomy based on a number of key dimensions. A major part of the purpose of this paper is to develop such a working taxonomy.