NMS 2018-2021 Life-sciences and healthcare project "Digital health: curation of healthcare data" - final report

Abstract

NPL Report MS 31 I TERMINOLOGY Data CurationOrganization and integration of data collected from various sources, annotation of the data, and publication and presentation of the data such that the value of the data is maintained over time, and the data remains available for reuse and preservation. Data Interoperability Addresses the ability of systems and services that create, exchange and consume data to have clear, shared expectations for the contents, context and meaning of that data. Data Integration Aggregation of datasets from heterogeneous sources by linking, combination or fusion. Data Provenance A history of the dataset that captures its origin, purpose and all modifications it underwent since its creation. FAIR principles A set of guiding principles to make data Findable, Accessible, Interoperable and Re-usable. MeasurementThe process of experimentally obtaining one or more quantity values that can reasonably be attributed to a quantity. MetadataA set of descriptors of the dataset that make the dataset easier to locate, understand and use. Metadata can include information about the purpose of the dataset creation, the experimental setup or the data formats. Depending on the nature of the investigation, metadata can be data in its own right. OntologyA formal representation of a knowledge domain that comprises a vocabulary of terms, as well as relations between them. An ontology can be presented as a knowledge graph where terms are depicted as vertices and relationships as edges. ReproducibilityCondition of measurement, out of a set of conditions that includes different locations, operators, measuring systems, and replicate measurements on the same or similar objects. TraceabilityProperty of a measurement result whereby the result can be related to a reference through a documented unbroken chain of calibrations, each contributing to the measurement uncertainty. Uncertainty of MeasurementThe parameter characterizing the dispersion of the quantity values being attributed to a measurand

Metrology for data in life sciences, healthcare and pharmaceutical manufacturing: Case studies from the National Physical Laboratory

“…NPL runs an ongoing inter-disciplinary Digital Health programme aimed to use data metrology tools to help solve some of the important and emerging challenges of utilising healthcare data [17]. The project includes several case studies, some of which are briefly described below, and further details can be found in the 2021 report [18].…”

“…We implemented a procedure that includes the device calibration information into the DICOM header information of the patient scan. We expect that the MVCT calibration data can be used to remove the device-related variability and make the patient images more inter-comparable, reduce the variations in the image quality, improving the accuracy of analysis, safety, and efficiency of data-driven clinical interventions [18].…”

Data Metrology for Life Sciences, Medicine and Pharmaceutical Manufacturing

“…A further case study in the Digital Health programme evaluates how data linkage can be used to improve the quality of life and long-term treatment outcomes for prostate cancer patients by using the patient care data acquired outside of clinical trials [13]. We developed an ontology-based data curation framework to identify and collate information about diagnosis, symptoms, and treatment side effects from routine primary care electronic health records.…”