Enhancing Traceability in Clinical Research Data through a Metadata Framework

Abstract 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.

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Designing research studies in writer’s cramp dystonia: an analysis of automated writing measures

10.1101/2021.03.02.21252036 ◽

2021 ◽

Author(s):

Noreen Bukhari-Parlakturk ◽

Michael Lutz ◽

Alec McConnell ◽

Hussein Al-Khalidi ◽

Joyce En-Hua Wang ◽

...

Keyword(s):

Clinical Research ◽

Sample Size ◽

Rare Disease ◽

Sensitivity And Specificity ◽

Healthy Subjects ◽

Rating Scales ◽

Research Study ◽

High Sensitivity ◽

Clinical Research Study ◽

Research Studies

ABSTRACTBackgroundWriter’s cramp (WC) dystonia presents with abnormal postures during the task of writing and is an ideal dystonia subtype to study disease mechanisms for all forms of focal dystonia. Development of novel therapies is contingent on identifying sensitive and specific measures that can relate to the clinical syndrome and achieve a realistic sample size to power clinical research study for a rare disease. Although there have been prior studies employing automated measures of writing kinematics, it remains unclear which measures can distinguish WC subjects with high sensitivity and specificity and how these measures relate to clinician rating scales and patient-reported disability. The goal of this study was to: 1-identify automated writing measures that distinguish WC from healthy subjects, 2-measure sensitivity and specificity of these automated measures as well as their association with established dystonia rating scales, and 3-determine the sample size needed for each automated measure to power a clinical research study.Methods21 WC dystonia and 22 healthy subjects performed a sentence-copying assessment on a digital tablet in a kinematic software and hand recognition software. The sensitivity and specificity of automated measures was calculated using a logistic regression model. Measures were then correlated with examiner and patient rating scales. Power analysis was performed for 2 clinical research designs using these automated measures.ResultsOf the 23 automated writing measures analyzed, only 3 measures showed promise for use in a clinical research study. The automated measures of writing legibility, duration, and peak acceleration were able to distinguish WC from healthy controls with high sensitivity and specificity, correlated with examiner-rated dystonia sub-score measures and demonstrated relatively smaller sample sizes suitable for research studies in a rare disease population.DiscussionWe identified novel automated writing outcome measures for use in clinical research studies of WC subjects which capture key aspects of the clinical disease and can serve as important readout of dystonia disease mechanism as well as future disease interventions.

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Communication and Recruitment to Clinical Research Studies

Oxford Research Encyclopedia of Communication ◽

10.1093/acrefore/9780190228613.013.73 ◽

2016 ◽

Cited By ~ 3

Author(s):

Janice L. Krieger ◽

Jordan M. Neil

Keyword(s):

Clinical Research ◽

Research Study ◽

Information Overload ◽

Informed Choice ◽

Strategic Communication ◽

Careful Consideration ◽

Outcome Evaluation ◽

Message Content ◽

Clinical Research Study ◽

Research Studies

Strategic communication is an essential component in the science and practice of recruiting participants to clinical research studies. Unfortunately, many clinical research studies do not consider the role of communication in the recruitment process until efforts to enroll patients in a timely manner have failed. The field of communication is rich with theory and research that can inform the development of an effective recruitment plan from the inception of a clinical research study through informed consent. The recruitment context is distinct from many other health contexts in that there is often not a behavioral response that can be universally promoted to patients. The appropriateness of a clinical research study for an individual is based on a number of medical, psychological, and contextual factors, making it impossible to recommend that everyone who is eligible for a clinical research study enroll. Instead, clinical research study recruitment efforts must utilize strategic communication principles to ensure that messages promote awareness of clinical research, maximize personal relevance, minimize information overload, and facilitate informed choice. This can be accomplished through careful consideration of various aspects of the communication context described in this chapter, including audience segmentation, message content, message channels, and formative, process, and outcome evaluation, as well as the enrollment encounter.

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