Probabilistic modeling approach to reducing healthcare costs with reflex testing

Abstract

Objective: Statistical methods can be utilized to optimize the order for reflex diagnostic testing to attenuate patient and hospital costs without affecting quality of care. Our objective is to demonstrate the method of developing an order for testing and to apply this method to an illustrative example. Methods: An algorithm was developed for minimizing costs for any given number of diagnostic tests, and it was retrospectively applied to a sample. Results: The actual scenario of using both tests on all patients was compared to 2 other hypothetical reflex testing approaches: all patients are given 1 test, and those patients who tested negative were then given the second test. The 2 scenarios would have saved 37.1% and 17.4% in testing costs, respectively. Conclusion: These calculations could be applied to numerous situations to reduce costs for patients and hospitals. We propose that this methodology would be best used in conjunction with any existing quality improvement initiatives.