RDMP

RDMP manages and curates longitudinal healthcare and clinical datasets to produce reproducible, updateable datasets for defined research cohorts.

Key Features:

• Data Management: Facilitates loading, managing, cleaning, and curating longitudinal healthcare datasets and produces reproducible, updateable datasets for defined research cohorts.
• Efficiency and Productivity: Increased data releases per month from 7.1 to 25.3 and reduced error rate from 12.7% to 3.1% between 2013 and 2017.
• Time Efficiency: Reduced data management time per release from an average of 24.6 hours to 3.0 hours.
• Reduced Waiting Time: Researchers receive datasets in under one week after agreeing specifications compared with approximately six months previously.
• Scalability and Capacity: Manages 163 datasets, produced 1,321 data extracts, and supports extracts integrating up to 70 distinct datasets.

Scientific Applications:

• Data cleaning and transformation: Enables reproducible cleaning, transformation, summarization, and quality assessment of routine healthcare data.
• Cohort generation: Produces anonymized, updateable research cohorts derived from routine clinical datasets to support answering research questions.

Methodology:

Implements a structured process for handling clinical datasets that preserves provenance and provides transparent, systematic data provision.