Data and real-world evidence
Clinical data quality, how health data is structured and shared, and how clinicians and life-sciences teams build evidence from everyday care in India.
- Clinical data
Clinical data quality: why AI in healthcare starts with clean records
Incomplete, inconsistent or wrongly coded records make AI unreliable. How to measure clinical data quality, where it goes wrong, and how to fix it at source.
- Health data standards
Health data standards in India: ICD-10, LOINC, FHIR, ABDM and OMOP explained
Which health data standard does what: ICD-10 for diagnoses, LOINC for tests, FHIR and ABDM for exchange, and OMOP for research across many sites.
- Real-world evidence
Building real-world evidence in oncology and immunology in India
Why oncology and immunology need Indian real-world evidence, what registries exist, what a specialty evidence network must record, and how clinicians take part.
- Real-world evidence
Real-world evidence in India: what it is, the rules, and how studies are built
What real-world data and evidence are, what Indian rules say about post-marketing and observational studies, and how a study built with clinicians works.