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Building a Research Data Repository for Chronic Condition Self-Management Using Harmonized Data
Shirley M Moore1, Carol M Musil, Megan L Alder
1Shirley M. Moore, PhD, RN, is Professor Emerita, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Carol M. Musil, PhD, RN, is Dean and Professor, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Megan L. Alder, BSN, RN, is PhD student, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Grant Pignatiello, PhD, RN, is Postdoctoral Fellow, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Patricia Higgins, PhD, RN, is Associate Professor Emerita, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Allison Webel, PhD, RN, is Associate Professor, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio. Kathy D. Wright, PhD, RN, CNS, is Assistant Professor and Chief Diversity Officer, College of Nursing, The Ohio State University, Columbus.
Background:
Building nursing research data repositories with the goal of comparing and synthesizing results across numerous studies and public sharing of data is still in early stages of development.
Objectives:
We describe the process of using common data elements (CDEs) to build a data repository for research addressing self-management of chronic conditions. Issues in the development of CDEs, lessons learned in the creation of a combined data set across seven studies of different chronic condition populations, and recommendations for creating and sharing harmonized nursing research data sets are provided.
Methods:
In 2014, at initiation of a National Institutes of Health-funded Centers of Excellence in Self-Management Research, our center investigators defined a set of CDEs for use in future center-funded pilot studies consisting of populations having different chronic conditions with the intent to combine the study data sets. Over the next 4 years, center investigators were provided with standardized codebooks and data collection protocols for applying the CDEs and data storage. Data from seven pilot studies were subsequently combined.
Results:
Although each pilot study was small-with sample sizes ranging from 18 to 31 participants-our combined data set of 179 participants provides us with a sample size sufficient to conduct analyses that could not be done with the individual small samples alone. The research data repository addressing self-management of chronic conditions will soon be available for public sharing.
Discussion:
Our experience demonstrates that, with careful, upfront planning and ongoing vigilant oversight, CDEs can be applied across studies consisting of different chronic condition populations to combine data sets to create research data repositories for public sharing.
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