Public involvement in health research: a case study of one NHS project over 5 years

Background: Public involvement, both in the National Health Service (NHS) and in clinical research, is promoted as an important democratic principle. The declared aims are to reduce professional autocracy and allow a broader ownership of the research agenda; also to improve the design of, and recruitment and retention of patients to, clinical studies. There have been a number of national initiatives in the UK to improve public input to clinical research activities, but very few reports of effective and sustainable partnerships over time. This study reports the evaluation of one example, which is embedded in the NHS and university partnerships in the Norfolk area of England. Objectives Evaluate: • Putting principles into practice of public involvement in research over a 5 year period for one specific project (Patient and Public Involvement in Research). • How the model contributes to, and impacts upon, all stages of the research process. • Attitudes of the research community and lay volunteers to their mutual experiences of public involvement. • Key factors and strengths of this project, and areas for improvement. Methods: A mixed methods approach related to the 5 years from start of 2003 to end of 2007. This used descriptive statistics of volunteer activity, interviews with key stakeholders (13), questionnaires (53% response rate), and focus group with 10 volunteers to explore emergent themes. We analysed findings using a policy framework approach. Results: About 47 of the original 55 volunteers remained on the panel after 5 years. All have undertaken training, 38% have been involved in the full range of research activities offered, and 75% have attended at least one research project meeting. Some are active in governance, ethics, and advisory committees. Both the research community and the volunteers are very positive about the project. The researchers find it provides well prepared personnel, and gives a speedy and efficient way of fulfilling the expectations of funders for lay input. The volunteers find it gives them important opportunities to influence the quality of research and thus support improvements in patient care. Areas for improvement include increasing social diversity among the volunteers, and improving feedback on input from volunteers, without which volunteers tend to lose confidence and motivation. Conclusion: Long-term sustainable and valuable public input to research is possible. Key factors are committing resources, embedding the service in the infrastructure of a research consortium, and ongoing responsiveness by NHS staff and researchers. Additional activity to recruit and support access may be needed to attract people from a broad range of sociodemographic backgrounds. Some volunteers want more involvement than this model currently offers

Analyzing Failure Recovery To Improve Planner Design

Plans fail for many reasons. During planner development, failure can often be traced to actions of the planner itself. Failure recovery analysis is a procedure for analyzing execution traces of failure recovery to discover how the planner's actions may be causing failures. The four step procedure involves statistically analyzing execution data for dependencies between actions and failures, mapping those dependencies to plan structures, explaining how the structures might produce the observed dependencies, and recommending modifications. The procedure is demonstrated by applying it to explain how a particular recovery action may lead to a particular failure in the Phoenix planner. The planner is modified based on the recommendations of the analysis, and the modifcations are shown to improve the planner's performance by removing a source of failure and so reducing the overall incidence of failure

Accepting the inevitable: The role of failure recovery in the design of planners

Failures are inevitable for many types of computer systems. Designers who seek to limit the frequency and impact of failures can adopt two basic approaches: automated failure recovery and debugging failures. This dissertation describes how automated failure recovery can both repair failures and expedite debugging of an autonomous planner, the Phoenix planner, in a dynamic environment. The automated failure recovery component applies general methods to recover from failures detected by the Phoenix planner. The design of the failure recovery component was developed by applying a methodology of first constructing a model of expected cost of failure recovery and then evaluating whether changes in the design of failure recovery result in improvements in the evaluation of expected cost. Additionally, the model was used to derive a control strategy for best selecting from a set of recovery methods. The expected cost model, its assumptions and the failure recovery component were tested in a set of three experiments. The first determined performance baselines for failure recovery, the second evaluated the performance of the control strategy, and the third compared the performance of an initial set of recovery methods to a new set augmented to lower the expected cost of recovery. As predicted, the control strategy and the augmented set of recovery methods improved performance by reducing the overall cost of recovery and increasing the overall recovery rate. Failure recovery analysis (FRA) is a procedure for analyzing execution traces of failure recovery to discover how the planner\u27s actions might be causing failures. The procedure involves statistically analyzing execution traces for dependencies between actions and failures, mapping those dependencies to plan structures, and explaining how the structures might produce the observed dependencies. Failure Recovery Analysis is a partially automated procedure that can be applied by designers to identify cases in which the plan library may be causing its own failures (i.e., bugs) and to implement and evaluate modifications to the plan library intended to eliminate the bugs. FRA is demonstrated by analyzing some of the data from the three experiments testing failure recovery. This research shows how failure recovery can help a planner repair failures due to both unexpected events and plan bugs and help planner designers determine how plan failures depend on the planner\u27s actions and evaluate design changes over time. The primary contributions of the thesis are: an empirical methodology for designing and evaluating failure recovery in planning and a tool for debugging a plan library

Integrating Failure Recovery with Planner Debugging

Automated failure recovery and debugging are two common methods of reducing the impact of failures. This paper proposes an integration of the two methods in a system for helping designers tune failure recovery and debug a plan knowledge base. The system will collect information about failures and their recovery during planner execution and use that information to identify possible flaws in failure recovery and in the plans. The system will be an automated and extended version of previous research on Failure Recovery Analysis [3]