title: Interrupted time-series analysis: studying trends in neurosurgery.
abstract: OBJECT Neurosurgery studies traditionally have evaluated the effects of interventions on health care outcomes by studying overall changes in measured outcomes over time. Yet, this type of linear analysis is limited due to lack of consideration of the trend's effects both pre- and postintervention and the potential for confounding influences. The aim of this study was to illustrate interrupted time-series analysis (ITSA) as applied to an example in the neurosurgical literature and highlight ITSA's potential for future applications. METHODS The methods used in previous neurosurgical studies were analyzed and then compared with the methodology of ITSA. RESULTS The ITSA method was identified in the neurosurgical literature as an important technique for isolating the effect of an intervention (such as a policy change or a quality and safety initiative) on a health outcome independent of other factors driving trends in the outcome. The authors determined that ITSA allows for analysis of the intervention's immediate impact on outcome level and on subsequent trends and enables a more careful measure of the causal effects of interventions on health care outcomes. CONCLUSIONS ITSA represents a significant improvement over traditional observational study designs in quantifying the impact of an intervention. ITSA is a useful statistical procedure to understand, consider, and implement as the field of neurosurgery evolves in sophistication in big-data analytics, economics, and health services research.
authors.affiliation: Department of Neurosurgery, University of South Florida, Tampa, Florida;
authors.forename: Ricky H
authors.initials: RH
authors.lastname: Wong
authors.affiliation: Department of Health Sciences, University of Chicago, Illinois; and.
authors.forename: Fabrice
authors.initials: F
authors.lastname: Smieliauskas
authors.affiliation: Department of Neurosurgery, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas.
authors.forename: I-Wen
authors.initials: IW
authors.lastname: Pan
authors.affiliation: Department of Neurosurgery, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas.
authors.forename: Sandi K
authors.initials: SK
authors.lastname: Lam
mesh_terms: D016208:Databases, Factual / Q000706:statistics & numerical data; D006801:Humans; D009493:Neurosurgery / Q000379:methods / Q000592:standards / Q000639:trends; D019635:Neurosurgical Procedures; D058996:Quality Improvement; D016032:Randomized Controlled Trials as Topic; D013117:Spinal Cord Compression / Q000601:surgery; D013997:Time Factors
keywords: AAOS = American Academy of Orthopaedic Surgeons; ACS NSQIP = American College of Surgeons National Surgical Quality Improvement Program; ITSA = interrupted time-series analysis; N2QOD = National Neurosurgery Quality and Outcomes Database; VAP = vertebral augmentation procedure; VCF = vertebral compression fracture; interrupted time series; kyphoplasty; methodology; segmented time series; trends