Enhancing neurosurgical navigation operation flow management through personal digital assistant technology

Purpose This prospective cohort study aims to evaluate the impact of digital health technology especially Personal Digital Assistants (PDA) in neurosurgical procedure management, focusing on surgical safety check accuracy, efficiency, and patient satisfaction. Methods The study included 211 neurosurgical cases from January to December 2022. The control group of 106 patients followed traditional verification methods, while the experimental group of 105 patients used PDA. The PDA system facilitated real-time data collection, verification, and transmission. The study compared both groups in terms of check times, accuracy rates, and patient satisfaction, and used multivariate regression to assess the impact of baseline parameters on these outcomes. Results The study found that the experimental group using the PDA system reduced the average verification time by approximately 8 min, achieving 100.0% accuracy in preoperative and postoperative checks, significantly better than the control group (91.5% pre- and post-operation). Multivariate regression confirmed a 48.1% reduction in postoperative verification time due to the PDA system ( p < 0.001), with the model showing high explanatory power (R 2 = 0.911). Other examined factors, including patient age and nurse experience, had no significant effects. Similarly, the PDA’s introduction markedly improved verification accuracy, with no significant impact from other variables ( p = 0.010). Conclusion The application of the PDA system in neurosurgical operations significantly enhanced the accuracy and efficiency of surgical safety checks, reduced nursing errors, optimized nursing workflows, and improved patient satisfaction. These results provide valuable insights for the application of PDA technology in high-risk medical fields, demonstrating potential of digital health tools in enhancing surgical safety and efficiency

Cohort · Digital health · Health care · Medical emergency · Medical physics · Prospective cohort study · Artificial Intelligence in Healthcare and Education · Computer Science · Medicine · Patient Safety and Medication Errors · Surgical Simulation and Training · Internal Medicine · Surgery