Clinical Lab Decision Support System for Quality Test Ordering and Utilization with Increase Reimbursement

Abstract

Abstract Introduction/Objective It is estimated that at least 20% of the 5 billion lab orders submitted annually are inappropriate. Use of an appropriate laboratory test utilization management system (TUMS) can significantly overcome this. Laboratory Decision System (LDS) is the only automated TUMS to assist providers understand, select, order, and optimally utilize tests for disease diagnosis and management. This algorithm-based LDS rates and scores potential tests for any given disease and assigns an interpretable numeric score based on clinical relevance, medical necessity, and indication. Importantly, every orders using LDS will also have right CPT and ICD-10 codes assigned to meet the medical necessity and improve reimbursement. Therefore, in this study, we evaluated the performance of LDS as a testing utilization management system and its ability to improve the reimbursement. Methods/Case Report A total of 96,170 lab orders were analyzed from a reference laboratory. Of these, 814 tests were accompanied by an invalid ICD10 code and 44,671 tests or were accompanied by ICD10 that are described by Medicare as “never covered” because of inability to meet medical necessity. A total of 160,449 tests were subject to an Medicare policy review from which 112,400 tests met coverage criteria and 48,049 tests did not. These orders were then reevaluated using LDS, which can be accessed from app.medicaldatabase.com/site/api/cpoe or interfaced with EMR to determine if the system would have improved test selection and reimbursement. Results (if a Case Study enter NA) Of the original test order sample, 91.5% had an associated LDS score. Of these scored tests, 47.80% met coverage and 43.73% failed to meet coverage, according to the LDS Ranking System. Importantly, LDS provided recommendations for alternative diagnostic ICD10 codes or tests which could have aided physicians in choosing a more appropriate test or submitting a different ICD10 diagnostic code to meet medical necessity. 96.4% with an alternative ICD10 code or test with a score above 5, meeting medical necessity. 80.5% were recommended by the LDS system which would meet Medicare policies. Conclusion Use of such algorithm-based testing selection and ordering database that rates and scores potential tests for any given disease based on clinical relevance, medical necessity, and testing indication, would eventually help providers to select and order right test and reduce miss-utilization of tests.