The coordination of public services is an enduring challenge and an important policy priority. One way to achieve collaboration across organizational boundaries, which is being considered in public services such as the English National Health Service (NHS), is through the adoption of alliance contracting, prime provider contracting and outcome-based contracting. This article reviews the cross-sectoral literature concerning the characteristics of these new contractual models, how they function, their impact, and their relation to public sector governance objectives. These new contractual forms are characterized as models which, in line with the New Public Management (NPM)/post-NPM agenda, seek to incentivize providers through the transfer of risk from the commissioners to the providers of services. Key findings are that the models are likely to incur high transaction costs relating to the negotiation and specification of outcomes and rely heavily on the relational aspects of contracting. There is also found to be a lack of convincing cross-sectoral evidence of the impact of the models, particularly in relation to improving coordination across organizations. The article questions the reconciliation of the use of these new contractual models in settings such as the English NHS with the requirements of public sector governance for transparency and accountability. The models serve to highlight the problems inherent in the NPM/post-NPM agenda of the transfer of risk away from commissioners of services in terms of transparency and accountability.

ObjectiveThe Health and Social Care Act 2012 (‘HSCA 2012’) introduced a new, statutory, form of regulation of competition into the National Health Service (NHS), while at the same time recognising that cooperation was necessary. NHS England's policy document, The Five Year Forward View (‘5YFV’) of 2014 placed less emphasis on competition without altering the legislation. We explored how commissioners and providers understand the complex regulatory framework, and how they behave in relation to competition and cooperation.DesignWe carried out detailed case studies in four clinical commissioning groups, using interviews and documentary analysis to explore the commissioners’ and providers’ understanding and experience of competition and cooperation.Setting/participantsWe conducted 42 interviews with senior managers in commissioning organisations and senior managers in NHS and independent provider organisations (acute and community services).ResultsNeither commissioners nor providers fully understand the regulatory regime in respect of competition in the NHS, and have not found that the regulatory authorities have provided adequate guidance. Despite the HSCA 2012 promoting competition, commissioners chose mainly to use collaborative strategies to effect major service reconfigurations, which is endorsed as a suitable approach by providers. Nevertheless, commissioners are using competitive tendering in respect of more peripheral services in order to improve quality of care and value for money.ConclusionsCommissioners regard the use of competition and cooperation as appropriate in the NHS currently, although collaborative strategies appear more helpful in respect of large-scale changes. However, the current regulatory framework contained in the HSCA 2012, particularly since the publication of the 5YFV, is not clear. Better guidance should be issued by the regulatory authorities.

This paper is based on ethnographic research of data practices in a public health project called Weather Health and Air Pollution. (All names are pseudonyms.) I examine two different kinds of practices that make air pollution data, focusing on how they relate to particular modes of sensing and articulating air pollution. I begin by describing the interstitial spaces involved in making measurements of air pollution at monitoring sites and in the running of a computer simulation. Specifically, I attend to a shared dimension of these practices, the checking of a numerical reading for error. Checking a measurement for error is routine practice and a fundamental component of making data, yet these are also moments of interpretation, where the form and meaning of numbers are ambiguous. Through two case studies of modelling and monitoring data practices, I show that making a 'good' (error free) measurement requires developing a feeling for the instrument-air pollution interaction in terms of the intended functionality of the measurements made. These affective dimensions of practice are useful analytically, making explicit the interaction of standardised ways of knowing and embodied skill in stabilising data. I suggest that environmental data practices can be studied through researchers' materialisation of error, which complicate normative accounts of Big Data and highlight the non-linear and entangled relations that are at work in the making of stable, accurate data.