Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up.

2023

04/2023

1527-974X

OBJECTIVE: We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds.

MATERIALS AND METHODS: We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work.

RESULTS: We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care.

DISCUSSION: Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction.

CONCLUSION: By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

10.1093/jamia/ocad070

J Am Med Inform Assoc

37080563

Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up.

2023

04/2023

1527-974X

OBJECTIVE: We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds.

MATERIALS AND METHODS: We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work.

RESULTS: We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care.

DISCUSSION: Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction.

CONCLUSION: By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

10.1093/jamia/ocad070

J Am Med Inform Assoc

37080563

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

2023

100006

04/2023

1530-0366

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

10.1016/j.gim.2023.100006

Genet Med

36621880

Genetic correlations between COVID-19 and a variety of traits and diseases.

2021

100112

2021 Apr 29

2666-6758

10.1016/j.xinn.2021.100112

Innovation (N Y)

33942034

Ciliopathies: Coloring outside of the lines.

2020

2020 Dec 25

1552-4833

<p>Ciliopathy syndromes are a diverse spectrum of disease characterized by a combination of cystic kidney disease, hepatobiliary disease, retinopathy, skeletal dysplasia, developmental delay, and brain malformations. Though generally divided into distinct disease categories based on the pattern of system involvement, ciliopathy syndromes are known to display certain phenotypic overlap. We performed next-generation sequencing panel testing, clinical exome sequencing, and research-based exome sequencing reanalysis on patients with suspected ciliopathy syndromes with additional features. We identified biallelic pathogenic variants in BBS1 in a child with features of cranioectodermal dysplasia, and biallelic variants in BBS12 in a child with the clinical stigmata of Bardet-Biedl syndrome, but also with anal atresia. We additionally identified biallelic pathogenic variants in WDR35 and DYNC2H1 in children with predominant liver disease and ductal plate malformation without skeletal dysplasia. Our study highlights the phenotypic and genetic diversity of ciliopathy syndromes, the importance of considering ciliopathy syndromes as a disease-spectrum and screening for all associated complications in all patients, and describes exclusive extra-skeletal manifestations in two classical skeletal dysplasia syndromes.</p>

10.1002/ajmg.a.62013

Am J Med Genet A

33369054

Unsupervised Modeling and Genome-Wide Association Identify Novel Features of Allergic March Trajectories.

2020

2020 Jul 07

1097-6825

<p><strong>BACKGROUND: </strong>The allergic march refers to the natural history of allergic conditions during infancy and childhood. However, population-level disease incidence patterns do not necessarily reflect the development of allergic disease in individuals. A better understanding of the factors that predispose to different allergic trajectories is needed.</p>

<p><strong>OBJECTIVE: </strong>Determine the demographic and genetic features that associate with the major allergic march trajectories.</p>

<p><strong>METHODS: </strong>Presence or absence of common allergic conditions (atopic dermatitis, AD; IgE-mediated food allergy, IgE-FA; asthma; and allergic rhinitis, AR) was ascertained in a pediatric primary care birth cohort of 158,510 subjects. Hierarchical clustering and decision tree modeling was used to associate demographic features with allergic outcomes. Genome-wide association study (GWAS) tested for risk loci associated with specific allergic trajectories.</p>

<p><strong>RESULTS: </strong>We found an association between self-identified "Black" race and progression from AD to asthma. Conversely, "Asian or Pacific Islander" race associated with AD to IgE-FA, and "White" race associated with AD to AR. GWAS of trajectory groups identified risk loci associated with progression from AD to Asthma (rs60242841), and AD to AR (rs9565267, rs151041509, rs78171803). Consistent with our epidemiologic associations, rs60242841 is more common in individuals of African ancestry (AA) than European ancestry (EA), while rs9565267 and rs151041509 are more common in EA than AA individuals.</p>

<p><strong>CONCLUSION: </strong>We identify novel associations between race and progression along distinct allergic trajectories. Ancestral genetic differences may contribute to these associations. These results uncover important health disparities, refine the concept of the allergic march, and represent a step towards developing individualized medical approaches for these conditions.</p>

10.1016/j.jaci.2020.06.026

J. Allergy Clin. Immunol.

32650023