Implementing a closed loop clinical decision support system for sustainable preoperative care.

Area of Science:

• Health Informatics
• Surgical Quality Improvement
• Healthcare Economics

Background:

• Unnecessary preoperative testing contributes to patient safety risks, surgical delays, and increased healthcare expenditures.
• Clinical decision support systems (CDSS) integrated into electronic health records (EHR) offer a potential solution to optimize testing protocols.

Purpose of the Study:

• To evaluate the impact of a fully EHR-integrated, closed-loop CDSS on preoperative testing rates.
• To assess the system's effect on patient safety, surgical delays, and healthcare costs.

Main Methods:

• An interrupted time series analysis was conducted over a 69-month period (January 2018 - October 2023) at two teaching hospitals in Madrid.
• The study included 228,671 surgical procedures, comparing data from the pre-CDSS implementation period (78,388 procedures) with the post-implementation period (150,283 procedures).

Main Results:

• A significant reduction was observed in preoperative testing: 83% for chest X-rays, 54% for ECGs, 50% for blood type tests, and 29% for blood test order sets.
• The implementation resulted in overall cost savings of €1,013,666.
• No increase in postoperative adverse events or same-day surgical cancellations was noted.

Conclusions:

• An EHR-embedded closed-loop CDSS effectively reduces avoidable preoperative testing.
• This technological intervention enhances the quality of care and optimizes healthcare expenditure without negatively impacting surgical outcomes or patient safety.