A strategy to advance the evidence base in palliative medicine: formation of a palliative care research cooperative group.

BACKGROUND: Palliative medicine has made rapid progress in establishing its scientific and clinical legitimacy, yet the evidence base to support clinical practice remains deficient in both the quantity and quality of published studies. Historically, the conduct of research in palliative care populations has been impeded by multiple barriers including health care system fragmentation, small number and size of potential sites for recruitment, vulnerability of the population, perceptions of inappropriateness, ethical concerns, and gate-keeping. METHODS: A group of experienced investigators with backgrounds in palliative care research convened to consider developing a research cooperative group as a mechanism for generating high-quality evidence on prioritized, clinically relevant topics in palliative care. RESULTS: The resulting Palliative Care Research Cooperative (PCRC) agreed on a set of core principles: active, interdisciplinary membership; commitment to shared research purposes; heterogeneity of participating sites; development of research capacity in participating sites; standardization of methodologies, such as consenting and data collection/management; agile response to research requests from government, industry, and investigators; focus on translation; education and training of future palliative care researchers; actionable results that can inform clinical practice and policy. Consensus was achieved on a first collaborative study, a randomized clinical trial of statin discontinuation versus continuation in patients with a prognosis of less than 6 months who are taking statins for primary or secondary prevention. This article describes the formation of the PCRC, highlighting processes and decisions taken to optimize the cooperative group's success.

Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.