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Refining Information Technology Support for Genetics in Medicine

Open (Enrolling)
Hypertrophic Cardiomyopathy, Hearing Loss, Cancer

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Trial Information

Refining Information Technology Support for Genetics in Medicine

A. Specific Aims

Aim 1: To assess the usability of successive versions of our EHR genetic display screens and
variant-based patient search functionality.

Formal usability studies will be conducted with each new release of the GeneInsight Clinic
(GIC) application in order to maximize its effectiveness and efficiency, and user
satisfaction. Results from these studies will be used along with functional and technical
requirements in designing enhancements to each successive version of the software.

Hypothesis: The usability of GeneInsight Clinic and the application's effectiveness,
efficiency, and user satisfaction will improve with each successive version.

Aim 2. To assess the decision-making process associated with issuing alerts relating to new
knowledge on germline variants.

Changes to cardiomyopathy and hearing loss variant level information will be placed in a
queue for evaluation. A board-certified clinical laboratory geneticist will determine which
changes should be released as an "alert" resulting in an update to the GIC and a
notification to the clinician. This decision-making process will be evaluated.

Hypothesis: Evaluation of decision-making regarding release of genetic variant update alerts
will identify patient and physician characteristics, and levels of significance of genetic
variant updates that influence alerting decisions.

Aim 3. To measure the impact on efficiency of new genetic knowledge being incorporated into
clinical care as a result of improved genetic IT infrastructure support.

Currently, clinicians learn of germline genetic variant updates when they choose to call the
genetic laboratories to check for any possible new information on genetic tests of interest.
With the GIC alerting system, treating clinicians will proactively receive genetic variant
updates relevant to their patients. For cancer genotyping tests, once an associated variant
is determined to have clinical significance, treating oncologists are interested in
identifying all their patients with this variant to evaluate whether the patient's care plan
should be modified. With the GIC patient search functionality, treating clinicians will be
able to identify all their patients with the genetic variant of interest.

Hypothesis: The availability of the GIC tool will greatly reduce the time delay associated
with distributing updated variant information to treating clinicians and will reduce the
number of calls the Laboratory of Molecular Medicine (LMM) receives requesting variant
updates. The efficiency of identifying all patients with clinically significant variants
will be improved through use of the PGE tool.

Aim 4: To evaluate the satisfaction of treating clinicians, perceived impact on clinical
care, and net effect on clinician workload associated with deploying genetic infrastructure.

Hypothesis: The introduction and subsequent revisions of the PGE tool will result in
improved satisfaction, a perceived reduction in clinician workload, and a perceived
improvement in clinical care.

Inclusion Criteria:

Study subjects selected from Partners HealthCare and non-Partners study sites include:

- treating clinicians

- geneticists

- genetic counselors

- pathologists

Exclusion Criteria:

- N/A

Type of Study:


Study Design:

Observational Model: Cohort, Time Perspective: Prospective

Outcome Measure:

Efficiency of Obtaining Updated Genetic Variant Information

Outcome Description:

Phone and email logging procedures will be implemented before study onset to establish a solid baseline. Laboratory staff will log each time they receive a phone call or email requesting updated information on a genetic variant. These logs will be maintained throughout the study period even once the GIC tool becomes available. System auditing processes will capture data on when genetic variants are updated, when alerts are sent, and clinician accesses to online screens. Centralized system data will be evaluated to track usage of the GIC patient search functions, using a flagging approach.

Outcome Time Frame:

Continuous across 21 months

Safety Issue:


Principal Investigator

David W Bates, MD, MSc

Investigator Role:

Principal Investigator

Investigator Affiliation:

Brigham and Women's Hospital, Harvard Medical School, Partners HealthCare, Inc.


United States: Food and Drug Administration

Study ID:




Start Date:

September 2009

Completion Date:

December 2012

Related Keywords:

  • Hypertrophic Cardiomyopathy
  • Hearing Loss
  • Cancer
  • Genetic Information
  • Variant Updates
  • Information Technology
  • Hypertrophic Cardiomyopathy
  • Hearing Loss
  • Oncology
  • Cardiomyopathy, Hypertrophic
  • Hearing Loss
  • Deafness
  • Hypertrophy
  • Cardiomyopathies



Brigham and Women's Hospital Cardiovascular Genetics Center Boston, Massachusetts  02115
Massachusetts General Hospital's Diagnostic Molecular Pathology Laboratory Boston, Massachusetts  02115
Massachusetts General Hospital's Hypertrophic Cardiomyopathy Clinic Boston, Massachusetts  02115
Massachusetts General Hospital's Medical Genetics Clinic Boston, Massachusetts  02115
Massachusetts General Hospital Division of Pulmonary Oncology Boston, Massachusetts  02115
Children's Hospital Boston's Ear, Nose, and Throat Clinic Boston, Massachusetts  02115
Children's Hospital Boston's Cardiovascular Genetics Clinic Boston, Massachusetts  02115
University of Michigan Cardiovascular Center Ann Arbor, Michigan  48109