Clinical trial NCT01225978: Refining Information Technology Support for Genetics in Medicine
Official title: Refining Information Technology Support for Genetics in Medicine
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Hypertrophic Cardiomyopathy
Hearing Loss
Cancer
Keywords: Genetic Information
Variant Updates
Information Technology
Hypertrophic Cardiomyopathy
Hearing Loss
Oncology
Lead sponsor: Brigham and Women's Hospital
Sponsor class: OTHER
Collaborators: name: National Institutes of Health (NIH)
name: National Library of Medicine (NLM)
First posted: 2010-10-21
Enrollment: 40
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The subjects in this study will be treating clinicians, geneticists, genetic counselors, and pathologists who are involved in ordering or processing genetic tests relating to cardiomyopathy, hearing loss, and cancer genotyping tests.

Brief summary: The clinical use of genetic testing is expanding and, as a result, the number of variants identified in patients is growing. Knowledge of the clinical impact of these variants improves over time. However, the combination of more testing and the rapid evolution of genetic knowledge make it impossible for clinicians to fully account for the latest implications of their patients' genetic profiles as patient care decisions are made. This proposed study plans to enhance and evaluate IT infrastructure developed to provide timely genetic variant updates and patient search functionality to clinicians to assist in optimizing patient care.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

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

* treating clinicians
* geneticists
* genetic counselors
* pathologists

Exclusion Criteria:

* N/A

Primary outcomes:
measure: Efficiency of Obtaining Updated Genetic Variant Information
timeFrame: Continuous across 21 months
Secondary outcomes:
measure: Perception of Impact of Variant Update Significance Level Alerting on Clinician Workload
timeFrame: Continuous Across 21 months
measure: Perception of Impact of Variant Update Significance Level Alerting on Clinician Satisfaction
timeFrame: Continuous Across 21 months
measure: Perception of Impact of Variant Update Significance Level Alerting on Clinical Care
timeFrame: Continuous Across 21 months
Other outcomes:
Locations:
city: Boston
country: United States
facility: Brigham and Women's Hospital Cardiovascular Genetics Center
state: Massachusetts
city: Boston
country: United States
facility: Children's Hospital Boston's Cardiovascular Genetics Clinic
state: Massachusetts
city: Boston
country: United States
facility: Children's Hospital Boston's Ear, Nose, and Throat Clinic
state: Massachusetts
city: Boston
country: United States
facility: Massachusetts General Hospital Division of Pulmonary Oncology
state: Massachusetts
city: Boston
country: United States
facility: Massachusetts General Hospital's Diagnostic Molecular Pathology Laboratory
state: Massachusetts
city: Boston
country: United States
facility: Massachusetts General Hospital's Hypertrophic Cardiomyopathy Clinic
state: Massachusetts
city: Boston
country: United States
facility: Massachusetts General Hospital's Medical Genetics Clinic
state: Massachusetts
city: Ann Arbor
country: United States
facility: University of Michigan Cardiovascular Center
state: Michigan
city: Toronto
country: Canada
facility: Fred A. Litwin Centre for Clinical Genetics and Genomic Medicine
state: Ontario
Study officials:
affiliation: Brigham and Women's Hospital, Harvard Medical School, Partners HealthCare, Inc.
name: David W Bates, MD, MSc
role: PRINCIPAL_INVESTIGATOR
References:
citation: Klinkenberg-Ramirez S, Neri PM, Volk LA, Samaha SJ, Newmark LP, Pollard S, Varugheese M, Baxter S, Aronson SJ, Rehm HL, Bates DW. Evaluation: A Qualitative Pilot Study of Novel Information Technology Infrastructure to Communicate Genetic Variant Updates. Appl Clin Inform. 2016 Jun 1;7(2):461-76. doi: 10.4338/ACI-2015-11-RA-0162. eCollection 2016.