Planetary Health Informatics (PHI)
Welcome to the Planetary Health Informatics Group. We use artificial intelligence and remote monitoring technology with international real-world health and environment data, in order to further our understanding of disease and fills the gaps in global health, leveraging common data models and federated network analytics.
We work closely with clinicians, engineers, epidemiologists, conservationists, data scientists, and public and patient groups in the UK, Europe, Latin America, South Asia, and Africa to co-create models for equitable and ethical solutions for planetary health problems.
OUR KEY FOCUS AREAS ARE
- Artificial intelligence for equitable and ethical healthcare
- Digital platforms and open-science tools for linked health, environment, and climate
- Health data science via common data models (OMOP), federated distributed analytics (FDN), and trusted research environments (TRE)
We teach a number of health data science courses at NDORMS and University-wide including but not limited to the NDORMS/MSD DPhil module on "Observational health data science: epidemiology, machine learning, and health economics", the NIHR BRC training course on “Data analysis: statistics - designing clinical research and biostatistics", and as faculty members, the "Real World Evidence using the OMOP Common Data Model" summer school.
Recent publications
A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data
Journal article
Khalid S. et al, (2021), Computer methods and programs in biomedicine, 211, 106394 - 106394
Association of Tramadol vs Codeine Prescription Dispensation With Mortality and Other Adverse Clinical Outcomes.
Journal article
Xie J. et al, (2021), Jama, 326, 1504 - 1515
Costes y beneficios del programa de prevención de fractura FLS en España
Conference paper
PINEDO VILLANUEVA R. et al, (2021)
One- and 2-year incidence of osteoporotic fracture: a multi-cohort observational study using routinely collected real-world data.
Journal article
Khalid S. et al, (2021), Osteoporos int
Predicting Imminent Fractures in Patients With a Recent Fracture or Starting Oral Bisphosphonate Therapy: Development and International Validation of Prognostic Models.
Journal article
Khalid S. et al, (2021), J bone miner res, 36, 2162 - 2176
Latest news
New advanced analytics research to deliver next level of insights into COVID-19
11 November 2021
NDORMS is leading one of nine new studies awarded total of £2m to use large-scale linked data to address priority research questions that will improve understanding of the pandemic and inform the continued policy response.