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Aim \ud The current article provides a detailed account of a behavioral simulation called Lateral Play. Lateral Play aimed to enhance collaborations and optimize shared decision-making across organizations within a newly formed partnership. The current article aims to enhance appreciation of the behavioral simulation methodology and encourage its use. \ud \ud Subjects and Methods \ud Health service leaders from different organizations within a newly formed partnership gathered in the simulated community and took up roles similar to their real-life positions. The simulation presented participants with problems and opportunities similar to those that they would experience in real life, such as the need to consolidate services and create new care pathways. To evaluate Lateral Play’s effectiveness, self-reported and observational data were collected. These data include information about participants’ reactions, learning and behavior, and the newly formed partnership’s organizational results. \ud \ud Results \ud Lateral Play allowed health leaders to better understand how they could enhance collaborations and optimize shared decision-making across their newly formed partnership. The data suggest that simulations can promote effective collaborations. \ud \ud Conclusions \ud Use of behavioral simulations should be encouraged to promote policy awareness and understanding, refine implementation strategies and improve outcomes in newly formed partnerships.

The term “big data” has gotten increasing popular attention, and there is growing focus on how such data can be used to measure and improve health and healthcare. Analytic techniques for extracting information from these data have grown vastly more powerful, and they are now broadly available. But for these approaches to be most useful, large amounts of data must be available, and barriers to use should be low. We discuss how “smart cities” are beginning to invest in this area to improve the health of their populations; provide examples around model approaches for making large quantities of data available to researchers and clinicians among other stakeholders; discuss the current state of big data approaches to improve clinical care including specific examples, and then discuss some of the policy issues around and examples of successful regulatory approaches, including deidentification and privacy protection.

Imagine your elderly parent is admitted to the intensive care unit (ICU) following a respiratory insufficiency. She is intubated for more than 2 days. As the hours go by, there is an increasing risk that stomach fluids and bacteria from her mouth enter into her lungs as the inflatable cuff that holds her tracheal intubation tube in place leaks.1 As a consequence, she develops ventilator-associated pneumonia (VAP), which is associated with a significantly greater risk of dying in the days to come. The good news is that a technology exists—the Venner-PneuX system—that almost entirely prevents such leaking of fluids into the lungs.2 The bad news is that uptake appears low and slow. Worse, most ICU clinicians, nurses, managers and certainly patients are unlikely to be aware of this technology, despite it having been available since 2007. The story of VAP is one of many that helps us understand why the adoption of innovation in the National Health Service (NHS) remains elusive, despite much policy attention. It illustrates that we should turn our attention to those individuals and organisations we wish to take up innovation—rather than solely the innovators themselves. Our key thesis is that efforts to support and promote the creation of innovation itself will not solve this problem. This argument has not been set out sufficiently before. The real challenge is to create healthcare environments in which the benefits of innovations can readily be seen and understood by those who can use them to improve patient care, and in which healthcare organisations can readily support the procurement and integration of those innovations into their systems and processes of care. In order to do this, we need to create organisational cultures, capabilities, infrastructure, processes and resources that make the uptake of innovation more likely. We need to create this …

The vast amount of health data generated and stored around the world each day offers significant opportunities for advances such as the real-time tracking of diseases, predicting disease outbreaks, and developing health care that is truly personalized. However, capturing, analyzing, and sharing health data is difficult, expensive, and controversial. This article explores four central questions that policy makers should consider when developing public policy for the use of "big data" in health care. We discuss what aspects of big data are most relevant for health care and present a taxonomy of data types and levels of access. We suggest that successful policies require clear objectives and provide examples, discuss barriers to achieving policy objectives based on a recent policy experiment in the United Kingdom, and propose levers that policy makers should consider using to advance data sharing. We argue that the case for data sharing can be won only by providing real-life examples of the ways in which it can improve health care.

German post-unification in the 1990s is a period marked by substantial economic and political change, a crucial part of which was a largely politically motivated attempt to build East German wages towards the much higher West German wages. We study the development of the public–private sector pay gap in Germany in the 1990s. We show that throughout the 1990s the overall pay gap between the public and private sectors remained stable in the West and increased considerably in the East. Wage decompositions show a small and stable negative public sector premium in the West, and a large and increasing positive public sector pay premium in the East. Decompositions also show a considerable deterioration in the skill base of the private sector in the East which the paper attributes in part to the improved attractiveness of the public sector. The paper argues that the development in the size and composition of the public–private sector pay gap in the East is an indication of the public sector crowding out the private sector and raises concerns about the future competitiveness of the East.

A substantial proportion of working age individuals in Britain are looking after sick, disabled or elderly people, often combining their work and caring responsibilities. Previous research has shown that informal care is linked with substantial opportunity costs for the individual due to forgone wages as a result of non-labour market participation. In this paper we show that informal carers exhibit further disadvantages even when participating. Using the British Household Panel Study (BHPS) we decompose wage differentials and show that carers can expect lower returns for a given set of characteristics, with this wage penalty varying along the pay distribution and by gender. Furthermore, opportunity costs from forgone wages and wage penalties are estimated and found to be substantial.

There are more than 5 million carers in the UK. These provide a vital low cost resource to support frail older people. Without their continued participation in caring activities, governments would face a steep increase in formal care costs. Therefore the issue of substitution between formal and informal care is a vital policy issue. This paper explores a recent “natural experiment” in care provision. In 2002, the Scottish Parliament agreed to provide personal care free of charge to all those in need of such care. This policy was not followed elsewhere in the UK. Social conditions and data resources are largely uniform throughout the UK; this permits a reasonably rigorous evaluation of the initial impact of the policy of free personal care on informal caring behaviour. Using a difference-in-difference methodology with the British Household Panel Survey, the authors show that informal caring in Scotland did not decrease relative to the rest of the UK after the substantial expansion in formal provision in Scotland. While the finding is in line with other international evidence, the paper argues that it may partly be explained by changes in the type of care that informal carers provide following the policy change.

This paper proceeds from two key assumptions. The first is that European countries are likely to face increased immigration of individuals. The second is that the emigration of jobs from Europe to other regions of the world through offshoring is also likely to increase. It has been widely argued that both factors are contributing to growing insecurity among European workers. This paper has two goals: first, to put the wider discussion of job displacement and wage changes resulting from immigration and offshoring on a firmer empirical foundation; and second, to explore changes in the European social model that will allow the European economies to adjust to the challenges and respond to the opportunities resulting from increased global competition from emerging market economies. Both immigration and offshoring confront European policy makers with trade-offs between efficiency and equity. These tradeoffs can be eased by active labour market and education policies to enhance the flexibility and skills of European workers so that they enjoy the productivity advantages necessary to support high wages and compete in the global economy. Such policies must combine an appropriate balance of incentives, obligations and benefits that focus on the overall employability of workers rather than on the number of jobs in a particular company or sector. A key challenge in designing such policies is how to combine generous income support for jobseekers while at the same time strengthening their incentives to find and accept available jobs.

Background As in many countries around the world, there are high expectations on academic health science centres and networks in England to provide high-quality care, innovative research, and world-class education, while also supporting wealth creation and economic growth. Meeting these expectations increasingly depends on partnership working between university medical schools and teaching hospitals, as well as other healthcare providers. However, academic-clinical relationships in England are still characterised by the “unlinked partners” model, whereby universities and their partner teaching hospitals are neither fiscally nor structurally linked, creating bifurcating accountabilities to various government and public agencies. Discussion This article focuses on accountability relationships in universities and teaching hospitals, as well as other healthcare providers that form core constituent parts of academic health science centres and networks. The authors analyse accountability for the tripartite mission of patient care, research, and education, using a four-fold typology of accountability relationships, which distinguishes between hierarchical (bureaucratic) accountability, legal accountability, professional accountability, and political accountability. Examples from North West London suggest that a number of mechanisms can be used to improve accountability for the tripartite mission through alignment, but that the simple creation of academic health science centres and networks is probably not sufficient. Summary At the heart of the challenge for academic health science centres and networks is the separation of accountabilities for patient care, research, and education in different government departments. Given that a fundamental top-down system redesign is now extremely unlikely, local academic and clinical leaders face the challenge of aligning their institutions as a matter of priority in order to improve accountability for the tripartite mission from the bottom up. It remains to be seen which alignment mechanisms are most effective, and whether they are strong enough to counter the separation of accountabilities for the tripartite mission at the national level, the on-going structural fragmentation of the health system in England, and the unprecedented financial challenges that it faces. Future research should focus on determining the comparative effectiveness of different alignment mechanisms, developing standardised metrics and key performance indicators, evaluating and assessing academic health science centres and networks, and empirically addressing leadership issues.