Chairs: Julian Elliott & Jeremy Grimshaw
Facilitators: Julian Elliott, Jeremy Grimshaw, Lisa Bero, Ida Sim
Acknowledgments: Russ Altman, Steven Goodman, David Henry, Malcolm Macleod, Peter Tugwell, Howard White
Our ability to make individual-specific measurements is exploding: “~omics” allow us to sequence complete genomes from patients, pathogens, and tumours; the spread of electronic medical records linked to health administrative data provide access to patients’ lifetime of clinical encounters; personal monitoring devices, mobile health and social applications provide data on physiology, behaviours, exposures and social networks; and the increasing availability of patient level clinical trial data allows us to estimate effects in subsets tailored more closely to individuals.
Unfortunately, these data often exist in fragmented and disparate domains, generated by different methods and scientific communities, and stored in different data infrastructures with varying data conventions, or lack thereof. Inadequate attention to the organisation and synthesis of these data impede the creation of knowledge and decrease society’s return on its scientific investments. We need to develop more fully the methods and systems that enable the synthesis of data drawn from disparate domains, appraising and incorporating the contribution of each data type and enabling sound inference for decision making.
To address these challenges we need to advance the science of data synthesis, drawing on traditional evidence synthesis and other data sciences, with a broad and critical understanding of the strengths and limitations of data from across the spectrum of existing and newer data sources, and a strong focus on the use of appropriate, rigorous methods to support inference and health decision-making. Our objective is to increase the use of analyses that appropriately combine data from diverse sources, the probability that valid inferences are derived and the availability of a coherent understanding, rather than conflicting, siloed interpretations, for health decision makers.
- To become familiar with the new sources of health data becoming available for potential synthesis and health decision making
- To become aware of current approaches to assessing bias and synthesizing disparate data sources
- To discuss current challenges and activities in synthesizing diverse health data
- To discuss potential opportunities to address these challenges and enable the development of methods and technical approaches for synthesis of diverse health data
- Jeremy Grimshaw: Overview of the challenge
- Ida Sim: A ‘traditional' look at non-traditional data sources
- David Henry: Title TBC
- Julian Higgins: Bayesian synthesis: the natural choice for diverse evidence sources
- Julian Elliott: Ways forward
- Panel discussion