Introduction: In this era of evidence-based medicine, substantial pressure is being brought on physicians to measure quality of care. Surgical complications directly contribute to patient morbidity and mortality and adequately analyzing them allows better targeting with preventive measures. Currently there is no standardized model for capturing and acting upon adverse events in the subspecialty of neurosurgery.
Methods: A review of literature for suggested adverse outcome classification in neurosurgery was performed. We searched for relevant English language studies until February 2015 using electronic literature databases including Medline, Pubmed and EMBASE. We included any article that explicitly identified the goal to classify the neurosurgical adverse outcomes. The results were compared with the ACS NSQIP database for the neurosurgery specialty. A system incorporating these findings was then conceived and proposed.
Results: Off 227 articles, 21 articles were included and analyzed. In collaboration with the Ottawa Morbidity and Mortality (M&M) model, an integral system incorporating those findings was created. This involves, an appropriate data collection platform with daily input from all neurosurgical staff, monthly discussion of the findings in a collegial non-punitive environment, M&M discussion centered on relevant cases with recommendations at the end of the rounds. A clear system was created to ensure that the actions discussed in M&M rounds are adequately followed and addressed and followed by the divisional committees involved in quality improvement. Moreover, the findings will be linked to an interdisciplinary quality improvement curriculum to ensure that all care providers are appropriately involved.
Conclusions: The ACS NSQIP database provides a broad measure that may not reflect the nuances encountered in neurosurgical care. Although this measure is useful for corporate purpose, refined neurosurgical variables are lacking. There is a need of neurosurgery specific database with key quality metrics allowing us to capture relevant complications in order to direct appropriately our quality improvement efforts.
Patient Care: Integration of this system combined with a coordinated data collection platform designed to measurably improve the quality of care, will allow for a more efficient allocation of healthcare resources and will advance the science of neurosurgical care.
Learning Objectives: By the conclusion of this session, participants should be able to:
1) Identify effective and sustaining quality improvement initiatives
2) Discuss the impact of neurosurgical complications
3) Describe the current available classifications in neurosurgery
4) Discuss the importance of capturing and analyzing systematically the adverse events
5) Discuss about the role of large databases for quality improvement initiatives.
References: 1. Landriel Ibañez FA, Hem S, Ajler P, Vecchi E, Ciraolo C, Baccanelli M et al. A new classification of complications in neurosurgery. World Neurosurg. 2011;75(5-6):709-715.
2. McGirt MJ, Speroff T, Dittus RS, Harrell FE Jr, Asher AL.The National Neurosurgery Quality and Outcomes Database (N2QOD): general overview and pilot-year project description. Neurosurg Focus. 2013;34(1):E6.
3. McLaughlin N, Afsar-manesh N, Ragland V, Buxey F, Martin NA. Tracking and Sustaining Improvement Initiatives. Neurosurgery. 2014;74:235-244.
4. Wong JM, Bader AM, Laws ER, Popp AJ, Gawande AA. Patterns in neurosurgical adverse events and proposed strategies for reduction. Neurosurg Focus. 2012;33(5):E1.
5. Schiavolin S, Broggi M, Acerbi F, Brock S, Schiariti M, Cusin A, Visintini S, Leonardi M, Ferroli P.The impact of neurosurgical complications on patients' health status: a comparison between different grades of complication.World Neurosurg. 2015 Feb 18. [Epub ahead of print]