Insurance denials and diagnostic rates in a pediatric genomic research cohort.

PURPOSE: This study aimed to assess the amount and types of clinical genetic testing denied by insurance and the rate of diagnostic and candidate genetic findings identified through research in patients who faced insurance denials. METHODS: Analysis consisted of review of insurance denials in 801 patients enrolled in a pediatric genomic research repository with either no previous genetic testing or previous negative genetic testing result identified through cross-referencing with insurance prior-authorizations in patient medical records. Patients and denials were also categorized by type of insurance coverage. Diagnostic findings and candidate genetic findings in these groups were determined through review of our internal variant database and patient charts. RESULTS: Of the 801 patients analyzed, 147 had insurance prior-authorization denials on record (18.3%). Exome sequencing and microarray were the most frequently denied genetic tests. Private insurance was significantly more likely to deny testing than public insurance (odds ratio = 2.03 [95% CI = 1.38-2.99] P = .0003). Of the 147 patients with insurance denials, 53.7% had at least 1 diagnostic or candidate finding and 10.9% specifically had a clinically diagnostic finding. Fifty percent of patients with clinically diagnostic results had immediate medical management changes (5.4% of all patients experiencing denials). CONCLUSION: Many patients face a major barrier to genetic testing in the form of lack of insurance coverage. A number of these patients have clinically diagnostic findings with medical management implications that would not have been identified without access to research testing. These findings support re-evaluation of insurance carriers' coverage policies.

Process evaluation of an open architecture real-time molecular laboratory platform.

The needs of molecular diagnostic laboratories that perform both Food and Drug Administration-cleared as well as laboratory-developed tests are usually not met on a single analytical platform. Furthermore, little information is available about the direct impact of molecular automation on labor costs and efficiency in clinical laboratories. We performed a process impact analysis from time and motion studies of a novel molecular diagnostic robotic system designed to automate sample preparation, extraction, and analysis. All 27 preanalytical tasks were quantified for the amount of time spent preparing 24 specimens for analysis. These steps were completed in 899 s (14 min, 59 s) followed by 7887 s (131 min, 27 s) of instrument operation independent of operator control (walk-away time). Postanalytical results evaluation required 1 min per specimen. The instrument automatically extracted the nucleic acid from the specimen, added the eluted DNA to the amplification reagents, and performed the analysis. Only 12% of the total instrument operations required relatively unskilled human labor. Thus, the availability of automated molecular diagnostic instruments will facilitate the expansion of molecular testing in the clinical laboratory because they reduce operator costs with respect to time and complexity of the tasks they are asked to perform.