Objective: To develop Logical Observation Identiers Names and Codes (LOINC) codes to represent constitutional cytogenetic test results for electronically exchanging coded and structured result reports. The LOINC codes developed must be exible and sustainable for easy maintenance. The goal is to create a standard set of codes that are exible enough to be used for all unique conventional and molecular cytogenetic results. Design: Patient de-identied sample result reports were obtained from ARUP Laboratories for a variety of normal and abnormal constitutional studies using G-banding, FISH and array-CGH. Information models were created to capture the semantic relationships of the key data elements that existed in the reports. Sample reports were subsequently obtained from Emory and Mayo Clinic Cytogenetics Laboratories to verify the information models. The information models were then used to guide the systematic creation of the LOINC codes. Results: A post-coordinated approach was used in developing the LOINC codes for cytogenetics test results. LOINC panel codes were created to represent the hierarchical structures implied by the reports. A master panel was created to contain three LOINC subpanels; each of the three subpanels held the structure for chromosome analysis results that uses a dierent technique. Conclusion: The LOINC codes we created met our objective and will allow the use of well established health informatics standards to exchange coded and structured cytogenetic test results between testing laboratories and ordering institutions. Use of standard structures and terminologies for cytogenetic results is critical for eective communication between testing laboratories and clinicians. This minimizes misinterpretation, leads to consistency, and provides the EHR systems exibility of customizing formatting to present more clinician-friendly reports.

Simulation is a mainstay of comparative- and cost-effectiveness research when empirical data are not available. The Synthea platform, originally designed for generating realistically coded longitudinal health records for software testing, implements data generation models specified in publicly contributed modules representing patients’ life cycle and disease and treatment progression. We test the hypothesis that Synthea can be used for simulation studies that draw parameters from observational studies and randomized trials. We benchmarked the results and assessed the effort required to create a Synthea module that replicates a recently published cost-effectiveness simulation comparing levofloxacin prophylaxis to usual care for leukemia. A module was iteratively developed using published parameters from the original study; we replicated the initial conditions and simulation endpoints of demographics, health events, costs, and mortality. We compare Synthea’s Generic Module Framework to platforms designed for simulation and show that Synthea can be used, with modifications, for some types of simulation studies.