Informatics, Statistics and Data Science

Informatics, statistics and data science research at The Farr Institute provided robust theoretical and methodological underpinnings for various types of health informatics research. Delivering the benefits of data analysis to patients required collaboration across many fields. The Institute therefore catalysed significant cross-disciplinary work between statisticians and informaticists with groups including patients and the public, healthcare professionals, biomedical scientists, software developers, e-Infrastucture specialists.

The knowledge that can be gained from the analysis of electronic health records and population-based data has a largely unrealised potential to improve health and care outcomes. A broad perspective is necessary to develop a national strategy in health data analytics research that can implement the beneficial applications of this research on a population-wide scale.

Developments in new statistical approaches and in algorithms and data mining will progress implementation in this area and address challenges such as improving access to necessary information for researchers and enhancing patient privacy.
Advancement in this area relies upon higher precision of information (e.g. through improved coding or extraction of information from electronic health record data) and improving consistency of information by adhering to common data standards and meanings (e.g. in representing diagnoses and outcomes).

Higher quality analysis can generate more trustworthy information to benchmark clinical practices and, in turn, feedback into frontline health services to highlight the improvements that can be made in policy and delivery of service and care.

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