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A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine.

Evans JP, Wilhelmsen KC, Berg J, Schmitt CP, Krishnamurthy A, Fecho K, Ahalt SC - EGEMS (Wash DC) (2016)

Bottom Line: However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients.We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data.The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, University of North Carolina at Chapel Hill; Department of Medicine, University of North Carolina at Chapel Hill.

ABSTRACT

Introduction: In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework.

Framework: We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.

Conclusion: The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other '-omics' fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

No MeSH data available.


Proposed Framework for Genomic Clinical Decision SupportNotes: CDSS = Clinical Decision Support System.Source: Image courtesy of RENCI.
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f1-egems1198: Proposed Framework for Genomic Clinical Decision SupportNotes: CDSS = Clinical Decision Support System.Source: Image courtesy of RENCI.

Mentions: To meet these emerging challenges and facilitate the optimal use of genomic data for patientcentered care and clinical research, we advocate for the development of a two-pronged Clinical Decision Support System (CDSS) for genomics that will: (1) provide the clinician with a dynamic visual snapshot of only those genomic data that are relevant to an individual patient; and (2) capture, store, and curate more comprehensive genomic data for ready access to address future clinical needs and enable genomic research (Figure 1). Our framework focuses on genomics, as this is a rapidly emerging field of medicine, but we have conceptualized our framework in relation to any data-intensive field of medicine.


A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine.

Evans JP, Wilhelmsen KC, Berg J, Schmitt CP, Krishnamurthy A, Fecho K, Ahalt SC - EGEMS (Wash DC) (2016)

Proposed Framework for Genomic Clinical Decision SupportNotes: CDSS = Clinical Decision Support System.Source: Image courtesy of RENCI.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862762&req=5

f1-egems1198: Proposed Framework for Genomic Clinical Decision SupportNotes: CDSS = Clinical Decision Support System.Source: Image courtesy of RENCI.
Mentions: To meet these emerging challenges and facilitate the optimal use of genomic data for patientcentered care and clinical research, we advocate for the development of a two-pronged Clinical Decision Support System (CDSS) for genomics that will: (1) provide the clinician with a dynamic visual snapshot of only those genomic data that are relevant to an individual patient; and (2) capture, store, and curate more comprehensive genomic data for ready access to address future clinical needs and enable genomic research (Figure 1). Our framework focuses on genomics, as this is a rapidly emerging field of medicine, but we have conceptualized our framework in relation to any data-intensive field of medicine.

Bottom Line: However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients.We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data.The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, University of North Carolina at Chapel Hill; Department of Medicine, University of North Carolina at Chapel Hill.

ABSTRACT

Introduction: In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework.

Framework: We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.

Conclusion: The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other '-omics' fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

No MeSH data available.