Background: Electronic medical records (EMRs) and laboratory information systems (LISs) commonly utilize patient identifiers such as legal name, sex, medical record number, and date of birth. There have been recommendations from some EMR working groups (e.g., the World Professional Association for Transgender Health) to include preferred name, pronoun preference, assigned sex at birth, and gender identity in the EMR. These practices are currently uncommon in the United States. There has been little published on the potential impact of these changes on pathology and LISs. Methods: We review the available literature and guidelines on the use of preferred name and gender identity on pathology, including data on changes in laboratory testing following gender transition treatments. We also describe pathology and clinical laboratory challenges in the implementation of preferred name at our institution. Results: Preferred name, pronoun preference, and gender identity have the most immediate impact on the areas of pathology with direct patient contact such as phlebotomy and transfusion medicine, both in terms of interaction with patients and policies for patient identification. Gender identity affects the regulation and policies within transfusion medicine including blood donor risk assessment and eligibility. There are limited studies on the impact of gender transition treatments on laboratory tests, but multiple studies have demonstrated complex changes in chemistry and hematology tests. A broader challenge is that, even as EMRs add functionality, pathology computer systems (e.g., LIS, middleware, reference laboratory, and outreach interfaces) may not have functionality to store or display preferred name and gender identity. Conclusions: Implementation of preferred name, pronoun preference, and gender identity presents multiple challenges and opportunities for pathology.

Context: Hepatitis C virus (HCV) genotyping at our institution is performed using the Versant HCV genotype 2.0 Line Probe Assay (LiPA). The last steps of this procedure are manual, laborious, and error-prone process that involves the comparison of the banding pattern on a test strip to a physical reference table. Aim: We developed a web-based HCV genotype interpretation platform that utilizes a scanned image to generate the genotypes, thus minimizing interpretation time and reducing error. Subjects and Methods: HCV Genie 2 utilizes a database of banding patterns in conjuncture with image analysis algorithms to determine the genotype for any number of scanned LiPA strips. HCV Genie 2 is built with client-side JavaScript; allowing the program to run in the user' browser rather than on an unknown server, essentially eliminating data and patient privacy concerns. Results: HCV Genie 2 was tested over 2 months and proved identical to human expert interpretation for 148 samples (>1000 bands identified). Manual intervention was required only for two faint bands and one false-positive band; this was done utilizing the built-in-user interface. Utilizing the original method, the trained laboratory technician interpretation time for 16 samples was 13.8 (±0.96) min as compared to 5.0 (±1.09) min with HCV Genie 2, a 63.8% decrease. In addition to the time savings, the new method provides an additional validation step, which decreases the potential for errors. Conclusions: Our institution has moved exclusively to utilize the new techniques and tools described here. Both experienced technicians and the molecular pathologists at our institution prefer the workflow using HCV Genie. It is easier for the technicians to prepare and document, and the pathologists are more rapidly able to review and confirm results. The use of this tool will lead to increase the quality of patient care delivered through this test methodology by decreasing the potential for error. The algorithms developed here can be ported to similar band identification platforms, most directly to other LiPAs.

Background: Numerous studies have revealed widespread clinician frustration with the usability of electronic health records (EHRs) that is counterproductive to adoption of EHR systems to meet the aims of health-care reform. With poor system usability comes increased risk of negative unintended consequences. Usability issues could lead to user error and workarounds that have the potential to compromise patient safety and negatively impact the quality of care.^[1] While there is ample research on EHR usability, there is little information on the usability of laboratory information systems (LISs). Yet, LISs facilitate the timely provision of a great deal of the information needed by physicians to make patient care decisions.^[2] Medical and technical advances in genomics that require processing of an increased volume of complex laboratory data further underscore the importance of developing user-friendly LISs. This study aims to add to the body of knowledge on LIS usability. Methods: A survey was distributed among LIS users at hospitals across the United States. The survey consisted of the ten-item System Usability Scale (SUS). In addition, participants were asked to rate the ease of performing 24 common tasks with a LIS. Finally, respondents provided comments on what they liked and disliked about using the LIS to provide diagnostic insight into LIS perceived usability. Results: The overall mean SUS score of 59.7 for the LIS evaluated is significantly lower than the benchmark of 68 (P < 0.001). All LISs evaluated received mean SUS scores below 68 except for Orchard Harvest (78.7). While the years of experience using the LIS was found to be a statistically significant influence on mean SUS scores, the combined effect of years of experience and LIS used did not account for the statistically significant difference in the mean SUS score between Orchard Harvest and each of the other LISs evaluated. Conclusions: The results of this study indicate that overall usability of LISs is poor. Usability lags that of systems evaluated across 446 usability surveys.