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  • Big Data Research in Neurosurgery: A Critical Look at this Popular New Study Design

    Final Number:
    543

    Authors:
    Chesney Oravec; Kevin Reed BS; Mustafa Motiwala; Andrew J. Gianapp; Paul Klimo MD MPH

    Study Design:
    Other

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2017 Annual Meeting

    Introduction: The use of “big data” in neurosurgical research has become increasingly popular. However, using this type of data comes with limitations. This study aimed to shed light on this new approach to clinical research.

    Methods: We compiled a list of commonly used databases that were not specifically created to study neurosurgical procedures, conditions, or diseases. Three North American journals were manually searched for articles utilizing these and other non-neurosurgery–specific databases. Data regarding study topic, question, database used, sample size, journal, publication date, and others were then collected, tallied, and analyzed.

    Results: A total of 324 articles were identified since 2000 with an exponential increase since 2011 (257/324, 79%). The Journal of Neurosurgery Publishing Group published the greatest total number (n=200). The National Inpatient Sample (NIS) was the most commonly used database (n=136). The average study size was 114,841 subjects (range, 30–4,146,777). The most prevalent topics were vascular (n=77) and neuro-oncology (n=66). When categorizing study objective (recognizing that many papers reported more than one type of study objective), “Outcomes” was the most common (n=154). The top 10 institutions by primary or senior author accounted for 45–50% of all publications. Harvard Medical School was the top institution, using this research technique with 59 representations (31 by primary author and 28 by senior).

    Conclusions: The increasing use of data from non-neurosurgery–specific databases presents a unique challenge to the interpretation and application of the study conclusions. The limitations of these studies must be more strongly considered in designing and interpreting these studies.

    Patient Care: In the age of evidence-based medicine, we need vigilance in the use and interpretation of data so as to provide the best possible patient care. By bringing awareness to this pervasive research method, the neurosurgical community can continue to investigate the best methods for “big data” usage.

    Learning Objectives: By the conclusion of this session, participants should understand the rising trend in usage of “big data” in neurosurgical research as well as the origin and intended function of administrative databases. Participants are encouraged to discuss and deliberate the validity and reliability of “big data” for research purposes, the circumstances in which administrative databases are appropriate for neurosurgical research, and the inherent limitations in drawing and applying conclusions from this type of study design.

    References:

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