CSER & emerge Consor.a EHR Working Group Collabora.on on Display and Storage of Gene.c Informa.on in Electronic Health Records

Transcription

1 electronic Medical Records and Genomics CSER & emerge Consor.a EHR Working Group Collabora.on on Display and Storage of Gene.c Informa.on in Electronic Health Records Brian Shirts, MD, PhD University of Washington September 11 th

2 EHR Workgroup Chair: Brian Shirts - Past Chair: Peter Tarczy- Hornoch 2

3 Purpose & Structure Explore, within an ac1ve clinical se4ng, the applica1on of genomic sequence data to the care of pa1ents. 1. Genera1on of genomic sequence data, 2. Interpreta1on and transla1on of data for the physician 3. Communica1on to the pa1ent Three (3) Project Teams per Site 1. Prac1ce: clinical se4ng being studied and what medical outcomes measured 2. Lab: sequencing and repor1ng of genome- scale results to clinicians/emr 3. ELSI: ethical and psychosocial implica1ons of bringing broad genomic data into the clinic Plon: Overview of CSER, Fall

4 The Big QuesCons for CSER What are the best prac1ces in moving whole genome sequencing, using Next Genera1on technologies, from medical science to the clinical prac1ce? What are the pa1ent characteris1cs that signal poten1al u1lity (or lack thereof) for applying genome- scale sequencing? What are the best approaches to analyzing data? Are there special considera1ons in different popula1ons? How should relevant informa1on be best represented in the EMR? What criteria are most useful in guiding which results should be returned (and how) to the pa1ent and physician? How should we deal with the plethora of highly heterogeneous non- target data generated when performing sequencing? Evans: Overview of CSER, Fall 2013 and NHGRI staff 4

5 CSER EMR Working Group Mission: Understand and facilitate cross site collabora.on na.onally around informa.cs work as related to variant annota.on, priori.za.on, integra.on into electronic medical record, and integra.on into decision support. Latest publica.on: Tarczy- Hornoch P et al. A survey of informa.cs approaches to whole- exome and whole- genome clinical repor.ng in the electronic health record. Genet Med Oct;15(10):

6 EHR Integra.on Workgroup Co- Chairs: Drs Jus.n Starren and Marc Williams 6

7 emerge EHR Integra.on WG Charter The emerge II consor.um supports research by exis.ng biorepositories with linked electronic health records to incorporate current genomic knowledge into clinical research and ongoing clinical care. The EMR Integra.on workgroup will develop emerge II consensus and concepts for EMR integra.on of genomic informa.on and delivery of clinical genomic decision support u.lizing EMR. 7

8 The emerge EHR Workgroup Delineate common and dis.nct approaches and challenges for EMR integra.on of relevant genomic informa.on for clinical pharmacogenomic, monogenic disorders, and common disease risk applica.ons. Share best prac3ces that support each emerge site to develop, implement and evaluate tools for clinical genomic decision support in EMRs Establish and apply features and benchmarks for clinical genomic decision support implementa.on research, including data ascertainment and outcomes analysis Address challenges and approaches for u.liza.on of whole genome/exome sequence- associated informa.on in EMR/decision support Establish and maintain dialog with, and disseminate findings and best prac.ces to, the EMR vendor community Support the use and evalua3on of CDS tools in emerge II clinical implementa.on projects 8

9 CSER/eMERGE EHR WG Collabora.on Conversa.ons between CSER and emerge EHR working groups CSER EHR WG began project to explore representa.on of gene.c informa.on in the EHR in early 2014 Invited emerge to join in Spring 2014 Objec.ves: Describe current state of clinical gene.c data representa.on at CSER and emerge site EHRs Establish consensus about most important and feasible improvements in clinical representa.on of gene.c data Publish a manuscript on current state and ideal future state Influence EHR providers and policy makers to improve the presenta.on of clinical gene.c informa.on in EHRs 9

10 Ini.al Survey Internal survey to explore how CSER and emerge sites currently represent all forms of gene.c informa.on in the EHRs 18 ques.ons yes/no and open ended 17 CSER and emerge sites par.cipated Faculty from many different departments with different exper.se in gene.cs and awareness of EHR structure 10

11 Results Summary Majority of ins.tu.ons report gene.c informa.on entering EHR through mul.ple sources Local hospital laboratory Primary reference tes.ng laboratory Mul.ple independent specialty gene.cs laboratories Gene.c informa.on also entered medical record through physician notes at majority of ins.tu.ons. 11

12 Results Summary For laboratory based data the source laboratory was the main determinant of the end loca.on of the informa.on in the EHR. Gene.c informa.on was displayed in mul.ple places in the EHR at most ins.tu.ons. Gene.c results were most oien reported in the laboratory tab, but were also reported in pathology, clinic notes, problem lists, outside medical records tabs, and other loca.ons. About 1/3 of ins.tu.ons had a separate gene.cs sub- tab. 12

13 Results Summary Gene.c results were stored as PDF documents at all ins.tu.ons Defined text blob results were the next most common way gene.c results were stored Gene.c results stored as discrete, machine readable codes were not common Gene.c results performed at ins.tu.onal affiliated laboratories were more likely to be represented as discrete elements. 13

14 Results Summary Although most ins.tu.ons have mechanisms to trigger alerts for high- risk ac.onable laboratory results, few have alert systems in place for ac.onable gene.c and pharmacogene.c results. About half of ins.tu.ons have a mechanism to tag gene.c informa.on as sensi.ve. Few ins.tu.ons have EHRs that support gene.c risk scores. Few ins.tu.ons have mechanisms for transmikng gene.c results to other family members, even in the specific case of migra.ng fetal results into a child s medical record. 14

15 Ongoing Efforts Informed by current prac.ce, survey CSER and emerge faculty have suggested recommenda.ons to improve how gene.c informa.on is represented in the EHR Delphi survey to determine priori.za.on and rela.ve feasibility of implemen.ng recommenda.ons electronic Medical Records and Genomics 15