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Linking clinical research data to population databases
Linda S Edelman1, Jia-Wen Guo, Alison Fraser
1Linda S. Edelman, PhD, RN, is Assistant Professor; and Jia-Wen Guo, PhD, RN, is Assistant Professor, College of Nursing, University of Utah, Salt Lake City. Alison Fraser, MSPH,is Senior Database Analyst, University of Utah Huntsman Cancer Institute, Salt Lake City. Susan L. Beck, PhD, APRN, FAAN, is Professor and Robert S. and Beth M. Carter Endowed Chair in Nursing, College of Nursing, University of Utah, Salt Lake City.
Background:
Most clinical nursing research is limited to funded study periods. However, if clinical research data can be linked to population databases, researchers can study relationships between study measures and poststudy long-term outcomes.
Objectives:
The objective was to describe the feasibility of linking research participant data to data from population databases in order to study long-term poststudy outcomes. As an exemplar, participants were linked from a completed oncology nursing research trial to outcomes data in two state population databases.
Methods:
Participant data from a previously completed symptom management study were linked to the Utah Population Database and the Utah Emergency Department Database. The final data set contained demographic, cancer diagnosis and treatment and baseline data from the oncology study linked to poststudy long-term outcomes from the population databases.
Results:
One hundred twenty-nine of 144 (89.6%) study were linked to their individual data in the population databases. Of those, 73% were linked to hospitalization records, 60% were linked to emergency department visit records, and 28% were identified as having died.
Discussion:
Study participant data were successfully linked to population databases data to describe poststudy emergency department visit and hospitalization numbers and mortality. The results suggest that data linkage success can be improved if researchers include linkage and human subjects protection plans related to linkage in the initial study design.
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