Implementation pathway report: Community Resource Person An intervention by the Technical Support Unit Uttar Pradesh, India, February 2015

A report describing the methodology behind an implementation pathway for the Community Resource Person innovation being implemented by the Technical Support Unit (a large-scale collaboration between the Bill & Melinda Gates Foundation and the Uttar Pradesh government) in Uttar Pradesh, India

Synchronous Counting and Computational Algorithm Design

Consider a complete communication network on $n$ nodes, each of which is a state machine. In synchronous 2-counting, the nodes receive a common clock pulse and they have to agree on which pulses are "odd" and which are "even". We require that the solution is self-stabilising (reaching the correct operation from any initial state) and it tolerates $f$ Byzantine failures (nodes that send arbitrary misinformation). Prior algorithms are expensive to implement in hardware: they require a source of random bits or a large number of states. This work consists of two parts. In the first part, we use computational techniques (often known as synthesis) to construct very compact deterministic algorithms for the first non-trivial case of $f = 1$. While no algorithm exists for $n < 4$, we show that as few as 3 states per node are sufficient for all values $n \ge 4$. Moreover, the problem cannot be solved with only 2 states per node for $n = 4$, but there is a 2-state solution for all values $n \ge 6$. In the second part, we develop and compare two different approaches for synthesising synchronous counting algorithms. Both approaches are based on casting the synthesis problem as a propositional satisfiability (SAT) problem and employing modern SAT-solvers. The difference lies in how to solve the SAT problem: either in a direct fashion, or incrementally within a counter-example guided abstraction refinement loop. Empirical results suggest that the former technique is more efficient if we want to synthesise time-optimal algorithms, while the latter technique discovers non-optimal algorithms more quickly.Comment: 35 pages, extended and revised versio

The effectiveness and cost-effectiveness of shared care: protocol for realist review

BACKGROUND: Shared care (an enhanced information exchange over and above routine outpatient letters) is commonly used to improve care coordination and communication between a specialist and primary care services for people with long-term conditions. Evidence of the effectiveness and cost-effectiveness of shared care is mixed. Informed decision-making for targeting shared care requires a greater understanding of how it works, for whom it works, in what contexts and why. This protocol outlines how realist review methods can be used to synthesise evidence on shared care for long-term conditions. A further aim of the review is to explore economic evaluations of shared care. Economic evaluations are difficult to synthesise due to problems in accounting for contextual differences that impact on resource use and opportunity costs. Realist review methods have been suggested as a way to overcome some of these issues, so this review will also assess whether realist review methods are amenable to synthesising economic evidence. METHODS/DESIGN: Database and web searching will be carried out in order to find relevant evidence to develop and test programme theories about how shared care works. The review will have two phases. Phase 1 will concentrate on the contextual conditions and mechanisms that influence how shared care works, in order to develop programme theories, which partially explain how it works. Phase 2 will focus on testing these programme theories. A Project Reference Group made up of health service professionals and people with actual experience of long-term conditions will be used to ground the study in real-life experience. Review findings will be disseminated through local and sub-national networks for integrated care and long-term conditions. DISCUSSION: This realist review will explore why and for whom shared care works, in order to support decision-makers working to improve the effectiveness of care for people outside hospital. The development of realist review methods to take into account cost and cost-effectiveness evidence is particularly innovative and challenging, and if successful will offer a new approach to synthesising economic evidence. This systematic review protocol is registered on the PROSPERO database (registration number: CRD42012002842)

An integration framework for managing rich organisational process knowledge

The problem we have addressed in this dissertation is that of designing a pragmatic framework for integrating the synthesis and management of organisational process knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a methodological approach to acquiring information about the process domain. We show that this initial domain specification can be translated into a common constraint-based model of activity (based on the work of Tate, 1996c and 1996d) which can then be operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a sorted first-order logic. The model combines perspectives covering both the space of behaviour as well as the space of decisions. Synthesised or modified processes/plans can be translated to and from the common representation in order to support knowledge sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf

Thunderstriking constraints with JUPITER

We present JUPITER, a tool for analysing multi-constrained systems. JUPITER was built to explore three basic ideas. First, how to use controller synthesis so as to find the exact conditions under which a particular constraint will be satisfied. Second, how to successively refine the models used for the controller synthesis so as to obtain a series of more easily understandable and more robust controllers. Last but not least, how to structure & explain the synthesised controllers and provide hints to designers for further optimisations through the use of machine learning techniques. Thus, JUPITER can help in the design and analysis of multi-constraint systems through the automatic synthesis of control logic for certain of the constraints and the aid it provides to designers for discovering further optimisations. The controllers it synthesises can be easily implemented on top of a standard real-time OS

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

Achieving change in primary care—causes of the evidence to practice gap : systematic reviews of reviews

Acknowledgements The Evidence to Practice Project (SPCR FR4 project number: 122) is funded by the National Institute of Health Research (NIHR) School for Primary Care Research (SPCR). KD is part-funded by the National Institute for Health Research (NIHR) Collaborations for Leadership in Applied Research and Care West Midlands and by a Knowledge Mobilisation Research Fellowship (KMRF-2014-03-002) from the NIHR. This paper presents independent research funded by the National Institute of Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Funding This study is funded by the National Institute for Health Research (NIHR) School for Primary Care Research (SPCR).Peer reviewedPublisher PD