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Aims: To identify best practice about how palliative and end of life (P&EoLC) research outputs should be presented to key stakeholders [clinicians, managers and service users]. Methods: We conducted 3 consultation workshops with CECo: 2 with patients/carers, 1 with clinicians/managers about how P&EoLC research results should be presented. Prior to workshops participants were sent P&EoLC research overviews aimed at the public. Clinicians/managers were also sent journal abstracts. Following discussion, nominal group techniques were used to produce recommendations for how research should be presented which were rated. Narrative comments were collected. Results: Service user workshops comprised 18 participants making 41 recommendations. There was consensus that clarity of information and use of lay language was most important. Also more than primary endpoints should be given; include quality of life and a description of ‘what it was like to be on a study’. Users wanted independent indicators of quality such as a star rating system. Links to more information or help were needed as results could be upsetting. Despite lengthy discussion no consensus was reached on whether there should be explicit reference to P&EoLC. Clinician/manager workshops comprised 12 participants making 19 recommendations. The main recommendation was the need to define what terms mean: end of life, palliative care, advanced care. More direct information about clinical and financial implications of research should be available. They wanted abstracts to be more accessible and readable. Conclusions: Researchers need to be aware of numerous audiences when preparing research outputs. Increasingly lay people access research findings themselves via the internet, highlighting the need for clear and relevant research reports. Clinicians want reports that show both clinical and financial implications for practice. No consensus could be reached on use of terminology, replicating the EAPC 2009 position paper.

Aims: To identify agreed best practice for health economic evaluation in palliative and end of life (P&EoLC) research. Methods: We used the MORECare Transparent Expert Consultation approach to conduct consultation workshops with experts in health economics in P&EoLC research. Prior to workshops participants were sent overviews of pertinent issues in health economics in P&EoLC. Following workshop presentations and discussion, nominal group techniques were used to produce candidate recommendations. These were subsequently rated online by participating experts. Descriptive statistics were used to permit analysis of consensus and rated importance. Narrative comments were collated. Results: The workshop comprised 28 participants making 27 recommendations. The top three recommendations were: 1. The need to develop robust methods for assessing outcomes which take into account preferences and the way these change over time. 2. Researchers should give consideration to the implications of decisions on the equitable distribution of care. 3. Costing should be from the societal perspective and as well as statutory services include costs of other formal care (e.g. hospices and third sector) and informal care unless a clear rationale for using a different perspective is provided. The main area which failed to reach consensus were on the use of Quality Adjusted Life Years (QALYs) and whether individual opportunity costs should be used to measure the costs of informal care. Conclusions: When designing studies in P&EoLC it is recommended that outcome measures are responsive over time and costings should come from a societal perspective taking into account the equitable distribution of care. More research is needed given the lack of consensus in this area so that future recommendations can be made.

Aims: To identify agreed best practice for statistical methods in palliative and end of life (P&EoLC) research. Background: Carrying out statistical analysis in P&EoLC research can be problematic due to high levels of missing data and attrition as patients’ disease progresses. Methods: We used the MORECare Transparent Expert Consultation approach to conduct consultation workshops with experts in statistical methods in P&EoLC research. Prior to workshops participants were sent overviews of pertinent issues in statistical methods in P&EoLC. Following workshop presentations and discussion, nominal group techniques were used to produce candidate recommendations. These were subsequently rated online by participating experts. Descriptive statistics were employed to permit analysis of consensus and rated importance. Narrative comments were collated. Results: The statistical methods expert workshop comprised 20 participants making 19 recommendations. There was broad agreement across most recommendations, the top 5 recommendations were: 1. Types and amount of missing data should be reported along with imputation methods. 2. Pattern of missing data should be investigated to inform imputation method. 3. A statistical analysis plan should be in place. 4. A taxonomy should be devised to define types of attrition. 5. Use of transition questions and minimally important difference approach provides insight into response shift. Conclusions: When designing studies in P&EoLC it is recommended that high rates of attrition should not be seen as indicative of poor design and that a clear statistical analysis plan is in place to account for missing data and attrition. More research is required in statistical methods to assess these areas but also develop the emerging area of response shift.

Aims: To identify agreed best practice for statistical methods in palliative and end of life (P&EoLC) research. Background: Carrying out statistical analysis in P&EoLC research can be problematic due to high levels of missing data and attrition as patients’ disease progresses. Methods: We used the MORECare Transparent Expert Consultation approach to conduct consultation workshops with experts in statistical methods in P&EoLC research. Prior to workshops participants were sent overviews of pertinent issues in statistical methods in P&EoLC. Following workshop presentations and discussion, nominal group techniques were used to produce candidate recommendations. These were subsequently rated online by participating experts. Descriptive statistics were employed to permit analysis of consensus and rated importance. Narrative comments were collated. Results: The statistical methods expert workshop comprised 20 participants making 19 recommendations. There was broad agreement across most recommendations, the top 5 recommendations were: 1. Types and amount of missing data should be reported along with imputation methods. 2. Pattern of missing data should be investigated to inform imputation method. 3. A statistical analysis plan should be in place. 4. A taxonomy should be devised to define types of attrition. 5. Use of transition questions and minimally important difference approach provides insight into response shift. Conclusions: When designing studies in P&EoLC it is recommended that high rates of attrition should not be seen as indicative of poor design and that a clear statistical analysis plan is in place to account for missing data and attrition. More research is required in statistical methods to assess these areas but also develop the emerging area of response shift.