Translating Data Analytics Into Improved Spine Surgery Outcomes: A Roadmap for Biomedical Informatics Research in 2021

Abstract

Study Design: Narrative review. Objectives: There is growing interest in the use of biomedical informatics and data analytics tools in spine surgery. Yet despite the rapid growth in research on these topics, few analytic tools have been implemented in routine spine practice. The purpose of this review is to provide a health information technology (HIT) roadmap to help translate data assets and analytics tools into measurable advances in spine surgical care. Methods: We conducted a narrative review of PubMed and Google Scholar to identify publications discussing data assets, analytical approaches, and implementation strategies relevant to spine surgery practice. Results: A variety of data assets are available for spine research, ranging from commonly used datasets, such as administrative billing data, to emerging resources, such as mobile health and biobanks. Both regression and machine learning techniques are valuable for analyzing these assets, and researchers should recognize the particular strengths and weaknesses of each approach. Few studies have focused on the implementation of HIT, and a variety of methods exist to help translate analytic tools into clinically useful interventions. Finally, a number of HIT-related challenges must be recognized and addressed, including stakeholder acceptance, regulatory oversight, and ethical considerations. Conclusions: Biomedical informatics has the potential to support the development of new HIT that can improve spine surgery quality and outcomes. By understanding the development life-cycle that includes identifying an appropriate data asset, selecting an analytic approach, and leveraging an effective implementation strategy, spine researchers can translate this potential into measurable advances in patient care.

Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research

“…Corresponding to unabated grow in healthcare data, there is rapidly growing interest in using “big data” in spine surgery. 7 , 24 , 25 Although administrative billing are a highly accessible source for multicenter analyses, there is growing recognition that such datasets are limited both in the accuracy and breadth of the variables available. 24 , 26 Clinical registries offer a high quality alternative, 27 - 29 but their high cost and potentially restrictive data sharing policies limit their growth.…”

“… 7 , 24 , 25 Although administrative billing are a highly accessible source for multicenter analyses, there is growing recognition that such datasets are limited both in the accuracy and breadth of the variables available. 24 , 26 Clinical registries offer a high quality alternative, 27 - 29 but their high cost and potentially restrictive data sharing policies limit their growth. 30 , 31 Additionally, clinical registries typically rely on manual data abstraction and do not incorporate comprehensive laboratory and prescription records, limiting potential uses.…”