Decreasing Resource Utilization without Compromising Care through Minimizing Preoperative Laboratories.

Area of Science:

• Healthcare Economics
• Surgical Optimization
• Clinical Pathology

Background:

• Annual expenditure on preoperative testing exceeds $18 billion.
• Unnecessary laboratory tests contribute to increased healthcare costs.
• Optimizing preoperative testing is crucial for cost-efficiency and patient safety.

Purpose of the Study:

• To evaluate the cost-effectiveness of an algorithm designed to minimize preoperative laboratory tests.
• To determine if reducing preoperative tests impacts patient care quality and surgical case cancellations.
• To assess the financial impact of implementing a selective preoperative laboratory testing protocol.

Main Methods:

• A pre-post trial design was employed, comparing data from January 2016-April 2016 with May 2016-July 2017.
• An algorithm was introduced in May 2016 to cancel laboratory tests based on patient and procedural factors.
• Data collected included the number of canceled laboratories, surgical case cancellations, and patient medical optimization rates.

Main Results:

• A significant 2.4% decrease in expected laboratory tests was observed post-intervention.
• Total cost savings amounted to $33,032.00.
• The percentage of patients requiring further medical optimization post-testing decreased from 3.3% to 2.1% (P < 0.01), with no cases canceled due to insufficient lab data.

Conclusions:

• A selective preoperative laboratory testing algorithm effectively reduces costs.
• Minimizing unnecessary laboratory orders leads to fewer surgical case cancellations.
• Implementing this algorithm is a cost-effective strategy that maintains the quality of patient care.