Data-driven surgical scheduling system improves efficiency

Editor's Note

Compared to the historical mean (HM) scheduling approach, the data-driven regression modeling (RM) method improves multiple measures of operative suite efficiency and personnel satisfaction without adversely affecting clinical outcomes, this study finds.

The HM approach included case duration of the most recent 4 years, and the RM system accounted for operative and patient characteristics.

Of 207 operative days allocated to either the RM or HM scheduling methodology:

• The mean imprecision in predicting the end of the operative day was higher with HM (30.8 vs 7.2 minutes).
• RM was associated with higher throughput (379 vs 356 cases).
• The composite rate of adverse 30-day events was similar (2.2% vs 3.2%).
• The mean depersonalization score was higher (3.2 vs 2.0) and mean personal accomplishment score was lower with HM (37.5 vs 40.5).

Though operative suite efficiency is a critical determinant of access to healthcare services, the methodologies are simplistic and do not account for all the available characteristics of individual surgical cases that data-driven scheduling provides, the researchers say.