Quality improvement in neurosurgery: A systematic review.

Medicine international Pub Date : 2025-02-24 eCollection Date: 2025-05-01 DOI:10.3892/mi.2025.222
Mohamed M Madan, Ahmed M Alshereiqi, Noor M Abdulla, Maryam Albreiki, Tariq Al-Saadi
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Abstract

Quality improvement (QI) is crucial for advancing patient care and safety in surgical practices. Despite the presence of numerous systematic reviews on various types of surgeries, no current QI systematic review for neurosurgery is available, at least to the best of our knowledge. The present study thus aimed to explore existing QI frameworks, interventions and outcome measures, which are used to enhance patient care and efficiency in neurosurgery. For this purpose, a systematic review was conducted by identifying 75 articles using key words, such as 'Quality', 'Control', 'Improvement', 'Neurosurgical' and 'Neurosurgery' across various databases, including PubMed, Google Scholar, Scopus, Wiley, ScienceDirect and Microsoft Academic. Each article was assessed based on inclusion and exclusion criteria, without a time limit for selection. The analysis of the 75 publications revealed an uneven distribution across neurosurgical fields: Adult neurosurgery (70.5%), spine surgery (22.5%), pediatric neurosurgery (4%) and neuro-oncology (3%). This pattern was reflected in the patient distribution (n=621,293), with 87.07% involved in spine surgery QI initiatives. Cranial-only and combined cranial and spinal studies accounted for only 0.21% of patients. QI interventions included mainly new protocols (18.67%), ERAS (17.33%), data analysis (16%), modified checklists (14.67%) and new sterilization devices (13.3%). By contrast, only a limited number of articles addressed the effectiveness of new technology, prediction models, incident reporting and staff education. On the whole, the QI studies enhanced neurosurgical care, focusing mainly on adult neurosurgery and targeting specifically spinal cases. The main interventions included new protocols, ERAS, data analysis and checklists. Further research is required to address QI initiatives in cranial surgery and evaluate the effectiveness of less commonly used methods, such as new technologies and predictive models.

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