Accuracy and efficiency of utilizing Microsoft Excel search functions and artificial intelligence for retrospective data analysis

Abstract

Background: Artificial intelligence (AI) has become integrated into many aspects of modern medicine, including medical research. Manual retrospective chart review has been regarded as an effective yet time-consuming and taxing process. Methods: To identify an accurate yet faster process, a retrospective electronic chart analysis was performed comparing three modalities: Microsoft Excel search function and Microsoft CoPilot were compared against manual review in identifying appendiceal neoplasms in patients undergoing laparoscopic or open appendectomy from an extracted database. The time taken to identify key words establishing neoplastic processes and the number of words found were recorded for manual search, Microsoft Excel search function, and Microsoft CoPilot. Results: The Microsoft Excel search function identified more terms than Microsoft CoPilot; however, it did not find all the instances found in manual search. The Microsoft Excel search function process took the least amount of time (2 minutes), and manual search took the most (2 hours 22 minutes). Although Microsoft CoPilot was the most dynamic tool, it was not as fast as the Microsoft Excel search function, nor as accurate as the other two modalities. Conclusions: Although the Microsoft Excel search function had the best speed, it was a static tool that did not find every key word and could not extrapolate data. Based on this paper and other literature, AI has the potential to assist in retrospective chart analysis. However, the search function remains faster and much more accurate than AI at this time.

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