Interrupted time-series analysis: studying trends in neurosurgery

Area of Science:

• Neurosurgery
• Health Services Research
• Biostatistics

Background:

• Traditional neurosurgery studies often use linear analysis for intervention effects.
• Linear analysis has limitations in accounting for pre- and post-intervention trends and confounding factors.

Purpose of the Study:

• To illustrate interrupted time-series analysis (ITSA) within neurosurgery research.
• To highlight the potential of ITSA for future neurosurgical studies.

Main Methods:

• Comparative analysis of traditional neurosurgical study methods versus ITSA methodology.
• Application of ITSA to a neurosurgical literature example.

Main Results:

• ITSA effectively isolates intervention effects on health outcomes, independent of underlying trends.
• ITSA quantifies immediate intervention impact and subsequent trend changes.
• ITSA provides a more precise measure of causal effects compared to traditional methods.

Conclusions:

• ITSA is a significant advancement over traditional observational designs for quantifying intervention impact in neurosurgery.
• ITSA is valuable for sophisticated big-data analytics, economics, and health services research in evolving neurosurgery.
• The adoption of ITSA can enhance the rigor of neurosurgical research.