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

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.

PillHarmonics: An Orchestrated Pharmacogenetics Medication Clinical Decision Support Service.

OBJECTIVES: Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of PGx into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study. METHODS: We developed the PillHarmonics service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug-drug/allergy/condition), PharmGKB (drug-gene), and locally curated content (drug-renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview. RESULTS: Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice. CONCLUSION: Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and presents a concise and holistic view of medication knowledge back to the clinician is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication-related CDS.

Sync for Genes Phase 5: Computable artifacts for sharing dynamically annotated FHIR-formatted genomic variants.

Introduction: Variant annotation is a critical component in next-generation sequencing, enabling a sequencing lab to comb through a sea of variants in order to hone in on those likely to be most significant, and providing clinicians with necessary context for decision-making. But with the rapid evolution of genomics knowledge, reported annotations can quickly become out-of-date. Under the ONC Sync for Genes program, our team sought to standardize the sharing of dynamically annotated variants (e.g., variants annotated on demand, based on current knowledge). The computable biomedical knowledge artifacts that were developed enable a clinical decision support (CDS) application to surface up-to-date annotations to clinicians. Methods: The work reported in this article relies on the Health Level 7 Fast Healthcare Interoperability Resources (FHIR) Genomics and Global Alliance for Genomics and Health (GA4GH) Variant Annotation (VA) standards. We developed a CDS pipeline that dynamically annotates patient's variants through an intersection with current knowledge and serves up the FHIR-encoded variants and annotations (diagnostic and therapeutic implications, molecular consequences, population allele frequencies) via FHIR Genomics Operations. ClinVar, CIViC, and PharmGKB were used as knowledge sources, encoded as per the GA4GH VA specification. Results: Primary public artifacts from this project include a GitHub repository with all source code, a Swagger interface that allows anyone to visualize and interact with the code using only a web browser, and a backend database where all (synthetic and anonymized) patient data and knowledge are housed. Conclusions: We found that variant annotation varies in complexity based on the variant type, and that various bioinformatics strategies can greatly improve automated annotation fidelity. More importantly, we demonstrated the feasibility of an ecosystem where genomic knowledge bases have standardized knowledge (e.g., based on the GA4GH VA spec), and CDS applications can dynamically leverage that knowledge to provide real-time decision support, based on current knowledge, to clinicians at the point of care.

Introducing HL7 FHIR Genomics Operations: a developer-friendly approach to genomics-EHR integration.

OBJECTIVE: Enabling clinicians to formulate individualized clinical management strategies from the sea of molecular data remains a fundamentally important but daunting task. Here, we describe efforts towards a new paradigm in genomics-electronic health record (HER) integration, using a standardized suite of FHIR Genomics Operations that encapsulates the complexity of molecular data so that precision medicine solution developers can focus on building applications. MATERIALS AND METHODS: FHIR Genomics Operations essentially "wrap" a genomics data repository, presenting a uniform interface to applications. More importantly, operations encapsulate the complexity of data within a repository and normalize redundant data representations-particularly relevant in genomics, where a tremendous amount of raw data exists in often-complex non-FHIR formats. RESULTS: Fifteen FHIR Genomics Operations have been developed, designed to support a wide range of clinical scenarios, such as variant discovery; clinical trial matching; hereditary condition and pharmacogenomic screening; and variant reanalysis. Operations are being matured through the HL7 balloting process, connectathons, pilots, and the HL7 FHIR Accelerator program. DISCUSSION: Next-generation sequencing can identify thousands to millions of variants, whose clinical significance can change over time as our knowledge evolves. To manage such a large volume of dynamic and complex data, new models of genomics-EHR integration are needed. Qualitative observations to date suggest that freeing application developers from the need to understand the nuances of genomic data, and instead base applications on standardized APIs can not only accelerate integration but also dramatically expand the applications of Omic data in driving precision care at scale for all.

Developing a shared sepsis data infrastructure: a systematic review and concept map to FHIR.

The development of a shared data infrastructure across health systems could improve research, clinical care, and health policy across a spectrum of diseases, including sepsis. Awareness of the potential value of such infrastructure has been heightened by COVID-19, as the lack of a real-time, interoperable data network impaired disease identification, mitigation, and eradication. The Sepsis on FHIR collaboration establishes a dynamic, federated, and interoperable system of sepsis data from 55 hospitals using 2 distinct inpatient electronic health record systems. Here we report on phase 1, a systematic review to identify clinical variables required to define sepsis and its subtypes to produce a concept mapping of elements onto Fast Healthcare Interoperability Resources (FHIR). Relevant papers described consensus sepsis definitions, provided criteria for sepsis, severe sepsis, septic shock, or detailed sepsis subtypes. Studies not written in English, published prior to 1970, or "grey" literature were prospectively excluded. We analyzed 55 manuscripts yielding 151 unique clinical variables. We then mapped variables to their corresponding US Core FHIR resources and specific code values. This work establishes the framework to develop a flexible infrastructure for sharing sepsis data, highlighting how FHIR could enable the extension of this approach to other important conditions relevant to public health.

Kaiser Permanente's Convergent Medical Terminology.

This paper describes Kaiser Permanente's (KP) enterprise-wide medical terminology solution, referred to as our Convergent Medical Terminology (CMT). Initially developed to serve the needs of a regional electronic health record, CMT has evolved into a core KP asset, serving as the common terminology across all applications. CMT serves as the definitive source of concept definitions for the organization, provides a consistent structure and access method to all codes used by the organization, and is KP's language of interoperability, with cross-mappings to regional ancillary systems and administrative billing codes. The core of CMT is comprised of SNOMED CT, laboratory LOINC, and First DataBank drug terminology. These are integrated into a single poly-hierarchically structured knowledge base. Cross map sets provide bi-directional translations between CMT and ancillary applications and administrative billing codes. Context sets provide subsets of CMT for use in specific contexts. Our experience with CMT has lead us to conclude that a successful terminology solution requires that: (1) usability considerations are an organizational priority; (2) "interface" terminology is differentiated from "reference" terminology; (3) it be easy for clinicians to find the concepts they need; (4) the immediate value of coded data be apparent to clinician user; (5) there be a well defined approach to terminology extensions. Over the past several years, there has been substantial progress made in the domain coverage and standardization of medical terminology. KP has learned to exploit that terminology in ways that are clinician-acceptable and that provide powerful options for data analysis and reporting.

Lexical concept distribution reflects clinical practice.

It is not known whether narrative medical text directly reflects clinical reality. We have tested the hypothesis that the pattern of distribution of lexical concept of medication intensification in narrative provider notes correlates with clinical practice as reflected in electronic medication records. Over 29,000 medication intensifications identified in narrative provider notes and 444,000 electronic medication records for 82 anti-hypertensive, anti-hyperlipidemic and anti-hyperglycemic medications were analyzed. Pearson correlation coefficient between the fraction of dose increases among all medication intensifications and therapeutic range calculated from EMR medication records was 0.39 (p = 0.0003). Correlations with therapeutic ranges obtained from two medication dictionaries, used as a negative control, were not significant. These findings provide evidence that narrative medical documents directly reflect clinical practice and constitute a valid source of medical data.

Challenges in exchanging medication information: identifying gaps in clinical document exchange and terminology standards.

The availability of accurate medication history information is invaluable for making sound therapeutic decisions. The Continuity of Care Document (CCD) could serve as a mechanism for exchanging interoperable medication information between EHRs. We evaluate the feasibility of representing a medication and its underlying components in a Healthcare Information Technology Standards Panel (HITSP) compliant CCD. Our evaluation resulted in successfully mapping 94% of medication entries and greater than 92% of medication component mappings to CCD constraints. We identify gaps and provide recommendations for improving the representational adequacy of the Federal Medication Terminology (FMT) to fully represent orderable medication concepts.