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OPTIMIZATION OF GENOMICS IN THE EHR

Danielle McKenna, CGC�Certified Genetic Counselor

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DISCLOSURES

  • I am an employee of Ambry Genetics

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Agenda

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03/12/2024

Storage of Genetic Test Results

Lab Integrations

Utilization of Genomics module

PreAct Dashboards

Lessons Learned

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Multiple Changes Took Place Over a Few Years

  • Multiple changes took place including:
    • Development of Precision Medicine Tab within EPIC to store genetic test results
    • HL7 Integration with multiple genetic testing companies
    • Genetics Module of EPIC
    • PreAct Dashboards

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Lau-Min KS, McKenna D, Asher SB, Bardakjian T, Wollack C, Bleznuck J, Biros D, Anantharajah A, Clark DF, Condit C, Ebrahimzadeh JE, Long JM, Powers J, Raper A, Schoenbaum A, Feldman M, Steinfeld L, Tuteja S, VanZandbergen C, Domchek SM, Ritchie MD, Landgraf J, Chen J, Nathanson KL. Impact of integrating genomic data into the electronic health record on genetics care delivery. Genet Med. 2022 Nov;24(11):2338-2350. doi: 10.1016/j.gim.2022.08.009. Epub 2022 Sep 15. PMID: 36107166

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Storage of Genetic Test Results

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Development of Precision Medicine Tab

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December 3, 2024

Dr. Kate Nathanson

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Lab Integrations

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Lab Integrations

  • Can order genetic testing within EPIC vs lab portals with just a few clicks
  • Results automatically come back into EPIC into precision medicine tab
  • Results come with discrete variant data which can trigger genomic indicators
  • HUGE TIME SAVER

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December 2, 2024

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December 2, 2024

Included time study for 8 GCs ordering genetic testing

Avg time spent ordering genetic tests was 2 minutes in EHR vs 8 minutes on individual lab portal

Avg time managing result receipt was 1 minute in EHR vs 5 minutes on lab portal

EHR integration saves ~10 minutes per patient

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Utilizing Genomics Module

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Genomic Indicators

  • A way to label a patient with a genetic condition in a structured way that is searchable within the EHR, part of EPIC Snapshot
  • Can be added manually or automatically from discrete variant data provided via lab integrations
  • Only specific providers have edit access, more reliable than problem list

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02/12/2024

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Patient Facing Genomic Indicator

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BRCA1 Example: Automatically Triggered

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What are the Benefits of Genomic Indicators?

Viewing data in SlicerDicer

Creation of Clinical Decision Support (CDS)

Ability to bulk message patients

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Slicer Dicer Examples

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December 2, 2024

Potential to slice by discrete variant info

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What are the Benefits of Genomic Indicators?

Viewing data in SlicerDicer

Creation of Clinical Decision Support (CDS)

Ability to bulk message patients

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Ability to bulk message

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What are the Benefits of Genomic Indicators?

Viewing data in SlicerDicer

Creation of Clinical Decision Support (CDS)

Ability to bulk message patients

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Clinical Decision Support (CDS)

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December 2, 2024

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Clinician Facing CDS

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Clinician-Facing Clinical Decision Support

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Patient Facing CDS

  • Shows up in same place as general health care reminders (ex: flu shot)

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  • Automated preventive care messages are sent to patients depending on their communication preferences (set by the front desk staff at the time of registration)

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PreAct�Dashboards

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PreAct Dashboards

Product of Penn Center for Health Care Innovation Accelerator Grant (2019)

A Penn-developed clinical dashboard that aides the identification of patients eligible for a specific care pathway

Lives outside of EPIC but could be embedded in EPIC in the future

Created for newly dx ovarian cancer patients but expanded to others

Ability to automate pended orders

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Ovarian Dashboard

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Genetic Testing Rates for Ovarian Cancer Before PreAct

National Average 33%

Penn's Average 65%

Missed patients 35%

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Genetic Testing for Ovarian Cancer After PreAct Implementation

National Average 33%

6%

Penn's Average 94%

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Universal IHC Dashboard

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Universal IHC: Data Pull

Programming: PATTERN MATCHING, which looks for an exact pattern/phrase within a larger set of information

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Required standardization of pathology templates across all specialties

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Saves time versus manual chart review!

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CPD Dashboard (In House Somatic Testing)

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Lessons Learned

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Lessons Learned: EHR Optimization

  • Team effort
      • Multiple genetics departments, IT, third party labs, legal
      • Everyone handles change differently. Find your change makers
  • Shoot for the moon
      • IT was able to do way more than we anticipated
      • Regular meetings with IT and clinical change makers
  • Understand what is discretely in the HER
    • Repeated data validations
    • Data you pull out is only as good as what you put in
  • Plan for the future (ex: gene specific genomic indicators)
  • Pre-implementation requirements

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December 3, 2024

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Acknowledgements

Penn Medicine Abramson Cancer Center

Cancer Moonshot Funding

Kate Nathanson, MD

Kelsey Lau-Min, MD, MSCE

PreAct Innovation Grant

Ashley Haggerty, MD

Lauren Schwartz, MD

Penn Center for Practice Transformation

Charlie Chambers, MCIT

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Penn Information Services

Joseph Bleznuck - EPIC Application Manager

Penn Cancer Genetics Team

Susan Domchek, MD

Bryson Katona, MD, PhD

Payal Shah, MD

Kara Maxwell MD, PhD

Angela Bradbury, MD

Jackie Powers, MS, CGC

Jessica Long, MS, CGC

Dana Farengo Clark, MS, CGC

Jessica Ebrahimzadeh, MS, CGC

Kelsey Spielman, MS, CGC

Derek Mann, MS, CGC

Jackie Cappadocia, MS, CGC

Avi Anantharajah, MS, CGC

Joanna Mercado, MS, CGC

Anna Raper, MS, CGC

Stephanie Asher, MS, CGC

Lauren Cuff

Carleigh Keegan

Samantha Pipito

Many others

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