Laboratory data are a major driver of medical decision making and it is estimated that 4-5 billion tests are performed annually in the US. Thousands of laboratory investigations are used in clinical practice and the number is increasing especially in molecular diagnostics and genetic testing. Healthcare providers struggle to pick laboratory tests that are both appropriate for clinical decision-making and are eligible for reimbursement. Not being familiar with the test and not being sure if it will be paid by the insurances, physicians might not be ordering the appropriate test leading to delayed diagnosis. On the other hand, it is estimated that at least 20% of the 5 billion laboratory orders submitted annually are inappropriate. Studies have shown that overutilization and/or underutilization of laboratory tests occurs 20.6% and 44.8% of the time, respectively, both of which dramatically impact clinical care and healthcare costs. These inappropriate tests not only lead to slower or incorrect diagnoses for patients but also add a significant financial burden. Every test ordered and procedure performed by the laboratory should be paid or reimbursed by Medicare or commercial healthcare insurance. However, many ordered tests are not reimbursed, and the main reason is a medical necessity; not ordering the right test that meets the medical necessity, and not providing the right diagnostic code for a particular disease or health problem. Such tests may also not be covered by Medicare because they aren’t appropriate for the medical condition or were ordered with the wrong ICD-10 diagnostic code, not meeting the medical necessity. Therefore, current clinical laboratory test ordering procedures suffer from a quality gap. Providers do not have access to an appropriate tool that uses evidence-based guidelines or algorithms to make sure that tests are not duplicated, over-, or under-utilized. Hence, it is crucial to have an automated laboratory Clinical Decision Support System (CDDS) that helps providers to order the right test for the right disease and documents the right reason or medical necessity to payers to pay for the testing.
Laboratory Decision System - LDS® developed by Medical Database is the only automated test utilization management system that uses evidence-based guidelines and industry best practices to assist healthcare providers to understand, select, order, and optimally utilize tests for disease diagnosis and management. This algorithm-based testing selection and ordering database rates and scores potential tests for any given disease and assigns an easily interpretable numeric (1-10) and color-coded score based on clinical relevance, medical necessity, and testing indication. Importantly, every order using LDS will also have the right CPT and ICD-10 codes assigned to meet the medical necessity and improve reimbursement. We assessed the effectiveness of LDS to improve test utilization and reimbursement by studying 96,170 laboratory requests comprising 374,423 test orders from a reference laboratory. Of these, 44,671 tests were accompanied by ICD10 that are described by Medicare as “never covered” because of the lack of a system to check or support the medical necessity of each order. A total of 160,449 tests were subject to a 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 freely accessed from https://app.medicaldatabase.com/site/api/cpoe or interfaced with EMR, to determine if the system would have improved test selection and reimbursement. Providers can search by the name of a disease or clinical condition and the system displays all the laboratory investigations relevant to the condition under four categories – Screening, Diagnosis, Management and Alternative Test. Each of the tests under these subsections is assigned with a score from 0-10. Scores from 7-10 appear green and are considered highly relevant (very specific to disease), and ordering physicians are likely to order such tests with little or no questioning. 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, demonstrating that the LDS system would correct inappropriate orders if employed as a testing utilization management system.
Our study implicates that the use of an automated test ordering system (LDS) would be extremely helpful for providers, laboratories, and payers. The system is designed to help providers order the right test and meet their medical necessity compliance, help laboratories to electronically receive the order with the right medical necessity and diagnostic code and CPT code so it will be paid, and help payers in claim verification and prior authorization by automating the system and avoiding any manual work which leads to denials and extra expense. The automated system suggests providers the list of tests that are highly relevant to the clinical condition based on scientific literature and guidelines with correct ICD codes. The system also contains a detailed explanation of each lab investigation to help interpretation of the result for better clinical decision. Therefore, the use of an automated test utilization platform would be extremely helpful to fill the gap in the quality test ordering and utilization process.