The inaugural Big Data and Analytical Unit (BDAU) Data Summit & Researchers Meeting, hosted by the Institute of Global Health Innovation’s Centre for Health Policy, will take place from 13:30 on Thursday 26th November.
The BDAU brings together experts from the fields of computer science, artificial intelligence, statistics, epidemiology, and informatics, to create a data-driven evidence base for healthcare policy.
The multidisciplinary team conducts complex and innovative analyses and develops new analytical methods to gain insight from large datasets including the National Reporting and Learning System (NRLS) which holds all of the patient safety incident records for the NHS, Hospital Episode Statistics (HES), Clinical Practice Research Datalink (CPRD) which documents healthcare provision for England on a population level, Patient Reported Outcome Measures (PROMs) which describes the quality of surgical care and Twitter collections on a keyword/user basis which can be used to supplement sentiment analysis where required.
This summit will hear from a number of academics within the field and will discuss how big data is aiding and shaping global health policy.
Agenda
13:30 – 13:40 – Introduction and Welcome
13:40 – 14:05 – ‘Using electronic health records to study respiratory disease’, Dr Jennifer K Quint, National Heart and Lung Institute, Imperial College London.
14:05 – 14:30 – ‘Unbiased Biomarkers for the Prediction of respiratory disease outcomes’, Xian Yang, Data Science Institute, Imperial College London.
14:30 – 14:50 – Tea & Coffee Break
14:50 – 15:15 – ‘The Role of Twitter in Public Health’, Dr Sunir Gohil, BDAU, Centre for Health Policy, Imperial College London.
15:15 – 15:40 – ‘Using linked databases to measure harm across integrated health systems’, George Bouras, BDAU, Centre for Health Policy, Imperial College London.
15:40 – 16:20 Keynote ‘Learning health systems’, Professor Brendan Delaney, Centre for Patient Safety and Service Quality (CPSSQ), Imperial College London.
16:20 – 16:30 – Closing Remarks.