scholarly journals vcf2fhir: a utility to convert VCF files into HL7 FHIR format for genomics-EHR integration

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Robert H. Dolin ◽  
Shaileshbhai R. Gothi ◽  
Aziz Boxwala ◽  
Bret S. E. Heale ◽  
Ammar Husami ◽  
...  
Keyword(s):  
Web Application ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Real World Data ◽  
Integration Platform ◽  
Hl7 Fhir ◽  
Diagnostic Report ◽  
Genomic Regions ◽  
Generation Sequencing ◽  
Phase Relationships

Abstract Background VCF formatted files are the lingua franca of next-generation sequencing, whereas HL7 FHIR is emerging as a standard language for electronic health record interoperability. A growing number of FHIR-based clinical genomics applications are emerging. Here, we describe an open source utility for converting variants from VCF format into HL7 FHIR format. Results vcf2fhir converts VCF variants into a FHIR Genomics Diagnostic Report. Conversion translates each VCF row into a corresponding FHIR-formatted variant in the generated report. In scope are simple variants (SNVs, MNVs, Indels), along with zygosity and phase relationships, for autosomes, sex chromosomes, and mitochondrial DNA. Input parameters include VCF file and genome build (‘GRCh37’ or ‘GRCh38’); and optionally a conversion region that indicates the region(s) to convert, a studied region that lists genomic regions studied by the lab, and a non-callable region that lists studied regions deemed uncallable by the lab. Conversion can be limited to a subset of VCF by supplying genomic coordinates of the conversion region(s). If studied and non-callable regions are also supplied, the output FHIR report will include ‘region-studied’ observations that detail which portions of the conversion region were studied, and of those studied regions, which portions were deemed uncallable. We illustrate the vcf2fhir utility via two case studies. The first, 'SMART Cancer Navigator', is a web application that offers clinical decision support by linking patient EHR information to cancerous gene variants. The second, 'Precision Genomics Integration Platform', intersects a patient's FHIR-formatted clinical and genomic data with knowledge bases in order to provide on-demand delivery of contextually relevant genomic findings and recommendations to the EHR. Conclusions Experience to date shows that the vcf2fhir utility can be effectively woven into clinically useful genomic-EHR integration pipelines. Additional testing will be a critical step towards the clinical validation of this utility, enabling it to be integrated in a variety of real world data flow scenarios. For now, we propose the use of this utility primarily to accelerate FHIR Genomics understanding and to facilitate experimentation with further integration of genomics data into the EHR.

scholarly journals A Clinical Decision Support System to integrate Scientific Knowledge at bedside (Preprint)

2018 ◽  
Author(s):  
Alicia MARTÍNEZ-GARCÍA ◽  
Ana Belén NARANJO-SAUCEDO ◽  
José RIVAS-GONZÁLEZ ◽  
Antonio ROMERO-TABARES ◽  
Ana María MARÍN-CASSINELLO ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Scientific Knowledge ◽  
Web Application ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
University Hospital ◽  
Healthcare Personnel ◽  
Evaluation Of Evidence

BACKGROUND The Evidence-Based Medicine (EBM) paradigm requires the development of skills of healthcare personnel in the efficient search of the literature and the application of formal rules for the evaluation of evidence contained in the medical literature. Incorporating this methodology into the decision-making process of routine clinical practice allows to improve the patients’ healthcare, leading to increase the patient safety and to optimize resource efficiency. OBJECTIVE To enable physicians to carry out decision-making processes based on EBM during their regular clinical practice in an agile method. METHODS Two basic components integrate the KNOWBED system: a knowledge station (web application) and a mobile application. KNOWBED system has been tested in in the context of the bronchiolitis pathology from the Paediatrics Unit from the “Virgen Macarena” University Hospital (Seville, Spain). The system was evaluated using two indicators: usability and effectiveness. RESULTS A technological system (KNOWBED system) has been designed, developed and validated to support clinical decision making in mobility based in standards that has been incorporated into the practice of physicians. From this tool, physicians can consult existing scientific knowledge at bedside and access of recommendations of clinical protocols established based on EBM. CONCLUSIONS KNOWBED system is considered a useful and innovative system by physicians. The surveys of usability filled in by the users of the system show that it is particularly easy to access the knowledge bases. However, this article sets out certain improvements to be made in future experiences.

scholarly journals Best Paper Selection

2018 ◽  
Vol 27 (01) ◽  
pp. 127-128
Keyword(s):  
Decision Support ◽  
Postoperative Delirium ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Free Text ◽  
Health Records ◽  
Support Tool ◽  
Team Selection ◽  
Order Sets

Chen JH, Alagappan M, Goldstein MK, Asch SM, Altman RB. Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets. Int J Med Inform 2017 Jun;102:71-9 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28495350/ Ebadi A, Tighe PJ, Zhang L, Rashidi P. DisTeam: A decision support tool for surgical team selection. Artif Intell Med 2017 Feb;76:16-26 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28363285/ Fung KW, Kapusnik-Uner J, Cunningham J, Higby-Baker S, Bodenreider O. Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support. J Am Med Inform Assoc 2017 Jul 1;24(4):806-12 https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocx010 Mikalsen KØ, Soguero-Ruiz C, Jensen K, Hindberg K, Gran M, Revhaug A, Lindsetmo RO, Skrøvseth SO, Godtliebsen F, Jenssen R. Using anchors from free text in electronic health records to diagnose postoperative delirium. Comput Methods Programs Biomed 2017 Dec;152:105-14 https://linkinghub.elsevier.com/retrieve/pii/S0169-2607(17)31154-9

scholarly journals Exploring functionally annotated transcriptional consensus regulatory elements with CONREL

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Davide Dalfovo ◽  
Samuel Valentini ◽  
Alessandro Romanel
Keyword(s):  
Cell Lines ◽  
Web Application ◽  
Regulatory Networks ◽  
Regulatory Elements ◽  
Levels Of Abstraction ◽  
Binding Motifs ◽  
Extensive Collection ◽  
Transcription Factor Binding Motifs ◽  
Gene Regulatory ◽  
Genomic Regions

Abstract Understanding the interaction between human genome regulatory elements and transcription factors is fundamental to elucidate the structure of gene regulatory networks. Here we present CONREL, a web application that allows for the exploration of functionally annotated transcriptional ‘consensus’ regulatory elements at different levels of abstraction. CONREL provides an extensive collection of consensus promoters, enhancers and active enhancers for 198 cell-lines across 38 tissue types, which are also combined to provide global consensuses. In addition, 1000 Genomes Project genotype data and the ‘total binding affinity’ of thousands of transcription factor binding motifs at genomic regulatory elements is fully combined and exploited to characterize and annotate functional properties of our collection. Comparison with other available resources highlights the strengths and advantages of CONREL. CONREL can be used to explore genomic loci, specific genes or genomic regions of interest across different cell lines and tissue types. The resource is freely available at https://bcglab.cibio.unitn.it/conrel.

Quality criteria for Real-World Data in pharmaceutical research and healthcare decision making. An Austrian Expert Consensus (Preprint)

2021 ◽  
Author(s):  
Peter Klimek ◽  
Dejan Baltic ◽  
Martin Brunner ◽  
Alexander Degelsegger-Marquez ◽  
Gerhard Garhöfer ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Research ◽  
Real World ◽  
Pharmaceutical Medicine ◽  
Pharmaceutical Research ◽  
Quality Criteria ◽  
Clinical Decision ◽  
European Medicines Agency ◽  
Real World Data ◽  
World Data

UNSTRUCTURED Real-world data (RWD) collected in routine healthcare processes and transformed to real-world evidence (RWE) has become increasingly interesting within research and medical communities to enhance medical research and support regulatory decision making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which quality RWD must meet in order to be acceptable for decision making within regulatory or routine clinical decision support. An Austrian expert group led by GPMed (Gesellschaft für Pharmazeutische Medizin, Austrian Society for Pharmaceutical Medicine) reviewed drafted guidelines, published recommendations or viewpoints to derive a consensus statement on quality criteria for RWD to be used more effectively for medical research purposes beyond registry-based studies discussed in the European Medicines Agency (EMA) guideline for registry-based studies

scholarly journals XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study

10.2196/17512 ◽  
2020 ◽  
Vol 4 (10) ◽  
pp. e17512
Author(s):  
Ever Augusto Torres Silva ◽  
Sebastian Uribe ◽  
Jack Smith ◽  
Ivan Felipe Luna Gomez ◽  
Jose Fernando Florez-Arango
Keyword(s):  
Decision Support ◽  
Antenatal Care ◽  
Clinical Decision Support ◽  
Web Application ◽  
Clinical Care ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structure Design ◽  
Mobile App ◽  
Clinical Workflow

Background Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. Objective This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. Methods We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. Results In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. Conclusions Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.

scholarly journals Design of an Interactive Web Application for Teaching Uncertainty Interpretations of Clinical Tests

2021 ◽  
Author(s):  
Sebastian Neher ◽  
Lorenz A. Kapsner ◽  
Hans-Ulrich Prokosch ◽  
Dennis Toddenroth
Keyword(s):  
Medical Students ◽  
Web Application ◽  
Clinical Decision ◽  
Local Learning ◽  
Interactive Software ◽  
Potential Utility ◽  
Software Module ◽  
Future Developments ◽  
Negative Results ◽  
Clinical Investigations

Background: Assessing the uncertainty of diagnostic findings is essential for advising patients. Previous research has demonstrated the difficulty of computing the expected correctness of positive or negative results, although clinical decision support (CDS) tools promise to facilitate adequate interpretations. Objectives: To teach the potential utility of CDS tools to medical students, we designed an interactive software module that computes and visualizes relevant probabilities from typical inputs. Methods: We reviewed the literature on recommended graphical approaches and decided to support contingency tables, plain table formats, tree diagrams, and icon arrays. Results: We implemented these functions in a single-page web application, which was configured to complement our local learning management system where students also access interpretation tasks. Conclusion: Our technical choices promoted a rapid implementation. We intend to explore the utility of the tool during some upcoming courses. Future developments could also model a more complex clinical reality where the likelihood of alternative diagnoses is estimated from sets of clinical investigations.

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