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Objective: The ability to apply results from a study to a broader population remains a primary objective in translational science. Distinct from intrinsic elements of scientific rigor, the extrinsic concept of generalization requires there be alignment between a study cohort and population in which results are expected to be applied. Widespread efforts have been made to quantify representativeness of study cohorts. These techniques, however, often consider the study and target cohorts as monolithic collections that can be directly compared. Overlooking known impacts to health from socio-demographic and environmental factors tied to individual's geographical location, and potentially obfuscating misalignment in underrepresented population subgroups. This manuscript introduces several measures to account for geographic information in the assessment of cohort representation., Methods: Metrics were defined across two themes: First, measures of recruitment, to assess if a study cohort is drawn at an expected rate and in an expected geographical pattern with respect to individuals in a reference cohort. Second, measures of individual characteristics, to assess if the individuals in the study cohort accurately reflect the sociodemographic, clinical, and geographic diversity observed across a reference cohort while accounting for the geospatial proximity of individuals., Results: As an empirical demonstration, methods are applied to an active clinical study examining asthma in Black/African American patients at a US Midwestern pediatric hospital. Results illustrate how areas of over- and under-recruitment can be identified and contextualized in light of study recruitment patterns at an individual-level, highlighting the ability to identify a subset of features for which the study cohort closely resembled the broader population. In addition they provide an opportunity to dive deeper into misalignments, to identify study cohort members that are in some way distinct from the communities for which they are expected to represent., Conclusion: Together, these metrics provide a comprehensive spatial assessment of a study cohort with respect to a broader target population. Such an approach offers researchers a toolset by which to target expected generalization of results derived from a given study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Persistent inequities in genomic medicine and research contribute to health disparities. This analysis uses a context-specific and equity-focused strategy to evaluate enrollment patterns for Genomic Answers for Kids (GA4K), a large, metropolitan-wide genomic study on children., Methods: Electronic health records for 2247 GA4K study participants were used to evaluate the distribution of individuals by demographics (race, ethnicity, and payor type) and location (residential address). Addresses were geocoded to produce point density and 3-digit zip code maps showing local and regional enrollment patterns. Health system reports and census data were used to compare participant characteristics with reference populations at different spatial scales., Results: Racial and ethnic minoritized and populations with low-income were underrepresented in the GA4K study cohort. Geographic variation demonstrates inequity in enrollment and participation among children from historically segregated and socially disadvantaged communities., Conclusion: Our findings illustrate inequity in enrollment related to both GA4K study design and structural inequalities, which we suspect may exist for similar US-based studies. Our methods provide a scalable framework for continually evaluating and improving study design to ensure equitable participation in and benefits from genomic research and medicine. The use of high-resolution, place-based data represents a novel and practical means of identifying and characterizing inequities and targeting community engagement., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Patient context - the "envirome" - can have a significant impact on patient health. While envirome indicators are available through large scale public data sources, they are not provided in a format that can be easily accessed and interpreted at the point of care by healthcare providers with limited time during a patient encounter. We developed a clinical decision support tool to bring envirome indicators to the point of care in a large pediatric hospital system in the Kansas City region. The Envirome Web Service (EWS) securely geocodes patient addresses in real time to link their records with publicly available context data. End-users guided the design of the EWS, which presents summaries of patient context data in the electronic health record (EHR) without disrupting the provider workflow. Through surveys, focus groups, and a formal review by hospital staff, the EWS was deployed into production use, integrating publicly available data on food access with the hospital EHR. Evaluation of EWS usage during the 2020 calendar year shows that 1,034 providers viewed the EWS, with a total of 29,165 sessions. This suggests that the EWS was successfully integrated with the EHR and is highly visible. The results also indicate that 63 (6.1%) of the providers are regular users that opt to maintain the EWS in their custom workflows, logging more than 100 EWS sessions during the year. The vendor agnostic design of the EWS supports interoperability and makes it accessible to health systems with disparate EHR vendors., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The era of "Personalized Medicine," guided by individual molecular variation in DNA, RNA, expressed proteins and other forms of high volume molecular data brings new requirements and challenges to the design and implementation of Electronic Health Records (EHRs). In this article we describe the characteristics of biomolecular data that differentiate it from other classes of data commonly found in EHRs, enumerate a set of technical desiderata for its management in healthcare settings, and offer a candidate technical approach to its compact and efficient representation in operational systems., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The integration of patient-specific genomic information into the electronic medical record (EMR) will create many opportunities to improve patient care. Key to the successful incorporation of genomic information into the EMR will be the development of laboratory information systems capable of appropriately formatting molecular diagnostic and cytogenetic findings in the EMR. Due to the lack of granular genomics-related content in existing medical vocabularies, the adoption of new standards for describing clinically significant genomic information will be an important step toward recognizing the genome-enabled EMR. Appropriate capture of patient-specific genomic results in the EMR will generate new opportunities to utilize this information in clinical decision support, including automated response to pharmacogenomic-based risks.

The records of 21 patients who underwent operation for symptoms attributable to vascular ring were reviewed. The study covered 33 years, 1958 to 1991, and the mean follow-up was 6.8 years. The patients ranged from 7 days to 26 years old with a mean age of 2.9 years. Twenty patients were symptomatic. Symptoms were due to tracheal compression in 16 patients, esophageal compression in 2, and both causes in 2. During the first 30 years, chest roentgenography, barium swallow, and aortography constituted the diagnostic workup in the majority of the patients. During the last 3 years, magnetic resonance imaging replaced aortography. The surgical diagnosis included five variants of vascular ring. The surgical approach consisted of left thoracotomy in 19 patients and right thoracotomy in 2. These 2 had the diagnosis of right aortic arch with posterior left subclavian artery. In both instances, preoperative angiographic data determined the surgical approach. Barium swallow may be sufficient for the diagnosis of vascular ring; however, additional data are useful in determining the surgical approach. Magnetic resonance imaging can yield accurate data without subjecting the patient to the risks associated with angiography.