OBJECTIVE
The development of new treatment approaches for degenerative lumbar spondylolisthesis (DLS) has introduced many questions about comparative effectiveness and long-term outcomes. Patient registries collect robust, longitudinal data that could be combined or aggregated to form a national and potentially international research data infrastructure to address these and other research questions. However, linking data across registries is challenging because registries typically define and capture different outcome measures. Variation in outcome measures occurs in clinical practice and other types of research studies as well, limiting the utility of existing data sources for addressing new research questions. The purpose of this project was to develop a minimum set of patient- and clinician-relevant standardized outcome measures that are feasible for collection in DLS registries and clinical practice.
METHODS
Nineteen DLS registries, observational studies, and quality improvement efforts were invited to participate and submit outcome measures. A stakeholder panel was organized that included representatives from medical specialty societies, health systems, government agencies, payers, industries, health information technology organizations, and patient advocacy groups. The panel categorized the measures using the Agency for Healthcare Research and Quality’s Outcome Measures Framework (OMF), identified a minimum set of outcome measures, and developed standardized definitions through a consensus-based process.
RESULTS
The panel identified and harmonized 57 outcome measures into a minimum set of 10 core outcome measure areas and 6 supplemental outcome measure areas. The measures are organized into the OMF categories of survival, clinical response, events of interest, patient-reported outcomes, and resource utilization.
CONCLUSIONS
This effort identified a minimum set of standardized measures that are relevant to patients and clinicians and appropriate for use in DLS registries, other research efforts, and clinical practice. Collection of these measures across registries and clinical practice is an important step for building research data infrastructure, creating learning healthcare systems, and improving patient management and outcomes in DLS.
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