Symptoms and General Pathology

All Conditions

Ear, Nose, and Throat Diseases

Nervous System Diseases

Heart and Blood Diseases

Rare Diseases

Hypertrophy

Hearing Loss

Deafness

Cardiomyopathies

Cardiomyopathy, Hypertrophic

Heart Diseases

Hearing Disorders

Ear Diseases

Otorhinolaryngologic Diseases

Sensation Disorders

Neurologic Manifestations

Pathological Conditions, Anatomical

Constriction, Pathologic

Aortic Valve Stenosis

Aortic Valve Disease

Heart Valve Diseases

The Group/Cohort in this study are geneticists, physicians, and genetic counselors who are using the GeneInsight Clinic (previously known as Patient Genome Explorer) to receive and store genetic test reports and variant update information.

GeneInsight Clinic (GIC) is a clinical interface tool that provides genetics IT support infrastructure designed to address key genetic data and knowledge management issues.

The GIC enables the delivery of patient specific alerts when new information is learned about a variant after it has been reported to a treating clinician. The prototype for this study shows multiple tests, Hypertrophic Cardiomyopathy test updates, hearing loss test updates and broad spectrum genotyping test updates. Our intention is to build this functionality in a scalable manner that will ultimately accommodate whole genome sequencing.

GeneInsight Clinic (GIC)

David W Bates, MD, MSc

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.

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.

Refining Information Technology Support for Genetics in Medicine

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.

Surveys will be constructed that ask treating clinicians about their experience with using the GIC and its perceived impact on workload. The surveys will be distributed both pre and post implementation of the GIC system to provide comparative data. Interviews will also be conducted, transcribed, coded for themes, and open-ended comments will be classified to reflect issues relating to clinician experience with the GIC. Call logs and centralized system audit information which can track time spent using the tool will be used to determine time and effort required to get updated information.

Surveys will be constructed that ask treating clinicians about their satisfaction with using the GIC. The surveys will be distributed both pre and post implementation of the GIC system to provide comparative data. Interviews will also be conducted, transcribed, coded for themes, and open-ended comments will be classified to reflect issues relating to clinician experience with the GIC. Call logs and centralized system audit information which can track time spent using the tool will be used to determine time and effort required to get updated information.

Surveys will be constructed that ask treating clinicians about their experiences with using the GIC and its perceived impact on clinical care. The surveys will be distributed Both pre and post implementation of the GIC system to provide comparative data. Interviews will also be conducted, and those along with open-ended comments will be classified to reflect issues relating to clinician experience with the GIC. Call logs and centralized system audit information which can track time spent using the tool will be used to determine time and effort required to get updated information.

Spots Global Cancer Trial Database for genetic information