Enhancing Traceability in Clinical Research Data through a Metadata Framework.
Background: The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tool...
| Published in: | Methods of Information in Medicine Vol. 59; no. 2/3; pp. 75 - 86 |
|---|---|
| Main Authors: | , , |
| Format: | research tables/charts Journal Article |
| Published: |
Thieme Medical Publishing Inc.
2020
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146704665&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146704665 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00261270 W7M jtl: Methods of Information in Medicine issn: 00261270 maglogo: N pubinfo: dt: 2020 vid: 59 iid: 2/3 pid: 2811 pub: Thieme Medical Publishing Inc. place: New York, New York artinfo: ui: 146704665 146704665 NLM32894879 146704665 10.1055/s-0040-1714393 NLM32894879 146704665 ppf: 75 ppct: 11 formats: tig: atl: Enhancing Traceability in Clinical Research Data through a Metadata Framework. aug: au: Hume, Samuel Sarnikar, Surendra Noteboom, Cherie affil: Department of Data Science, CDISC, 843 S. Sparks Street, State College, PA 16801, United States sug: subj: Research, Medical Communication Data Collection Reproducibility of Results Software Algorithms Scales ab: Background: The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across all phases of the data lifecycle.Objectives: To develop a metadata traceability framework that can help query and visualize traceability metadata, identify traceability gaps, and validate metadata traceability to improve data lineage and reproducibility within clinical research studies.Methods: This research follows the design science research paradigm where the objective is to create and evaluate an information technology (IT) artifact that explicitly addresses an organizational problem or opportunity. The implementation and evaluation of the IT artifact demonstrate the feasibility of both the design process and the final designed product.Results: We present Trace-XML, a metadata traceability framework that extends standard clinical research metadata models and adapts graph traversal algorithms to provide clinical research study traceability queries, validation, and visualization. Trace-XML was evaluated using analytical and qualitative methods. The analytical methods show that Trace-XML accurately and completely assesses metadata traceability within a clinical research study. A qualitative study used thematic analysis of interview data to show that Trace-XML adds utility to a researcher's ability to evaluate metadata traceability within a study.Conclusion: Trace-XML benefits include features that (1) identify traceability gaps in clinical study metadata, (2) validate metadata traceability within a clinical study, and (3) query and visualize traceability metadata. The key themes that emerged from the qualitative evaluation affirm that Trace-XML adds utility to the task of creating and assessing end-to-end clinical research study traceability. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|