Family Health History in Diverse Care Settings
This study is currently recruiting participants. (see Contacts and Locations)
Verified June 2016 by Duke University
Information provided by (Responsible Party):
First received: September 30, 2013
Last updated: June 23, 2016
Last verified: June 2016
The outcome of this research will be a demonstration that family health history (FHH) risk data can be used efficiently to deliver more effective healthcare in geographically and ethnically diverse clinical care environments. Although FHH is a standard component of the medical interview its widespread adoption is hindered by three major barriers: (1) a dearth of standard collection methods; (2) the absence of health care provider access to complete FHH information; and (3) the need for clinical guidance for the interpretation and use of FHH. In addition, the time constraints of the busy provider and poor integration of FHH with paper medical records or electronic medical records (EMR) impede its widespread use. The investigators hypothesize that patient-driven and electronic collection of FHH for risk stratification will promote more informed decision-making by patients and providers, and improves adherence to risk-stratified preventive care guidelines. The study team will use an implementation sciences approach to integrate an innovative FHH system that collects FHH from patients. Intermountain Healthcare will provide the information technology expertise with EMR design to develop an innovative solution to a storage model standard for FHH data as well as a centralized standards-compliant open clinical decision support (OpenCDS) rule development architecture to analyze FHH and to generate evidence-based, individualized, disease risk, preventive care recommendations for both patients and providers.
|Study Design:||Allocation: Randomized
Endpoint Classification: Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Health Services Research
|Official Title:||Family Health History in Diverse Care Settings|
Further study details as provided by Duke University:
Primary Outcome Measures:
- Increasing uptake of risk-management evidence based preventive strategies for the clinical decision support conditions [ Time Frame: Baseline, 3 and 12 months ] [ Designated as safety issue: No ]How many patients identified to be at increased risk for the clinical decision support conditions, how many providers order the recommended prevention strategy, and how many patients adhere to the provider recommendation.
Secondary Outcome Measures:
- Measure patient-related outcomes associated with using the MeTree tool [ Time Frame: 3 months and 12 months ] [ Designated as safety issue: No ]The study will assess satisfaction, comfort, anxiety, and preparedness associated with using the MeTree tool via survey 3 and 12 months after completing the family history collection.
- Measure physician experience with MeTree [ Time Frame: 3 months ] [ Designated as safety issue: No ]Evaluate physicians' perceptions of satisfaction, the tool's impact on work load and its effectiveness via survey and informal interviews at 3 months.
- Implementation parameters for MeTree [ Time Frame: up to 3 years ] [ Designated as safety issue: No ]Formative evaluation of the implementation process which includes barriers and solutions to implementing MeTree into clinical practice setting.
- uptake of MeTree by clinical practices [ Time Frame: 1 year ] [ Designated as safety issue: No ]Evaluate which clinics/providers are successfully using MeTree in their clinical work flow and which patients are successfully using MeTree for their care. (surveys, monitoring of clinical workflow, patient recruitment reflects underlying clinic population)
|Study Start Date:||April 2014|
|Estimated Study Completion Date:||April 2017|
|Estimated Primary Completion Date:||December 2016 (Final data collection date for primary outcome measure)|
Active Comparator: MeTree
MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to patients and providers as clinical decision support.
Software program collecting family health history and generating clinical decision support for risk-based preventive care
No Intervention: Control
to compare rates of risk management strategies in standard care during the time of MeTree use in the intervention arm.
Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, and the University of North Texas Health Science Center. The study will take place in 'real world' clinical, socio-cultural, and demographically diverse (rural, underserved, academic, family medicine) care clinics (n=34) in 5 states (CA, MN, NC, WI, TX) that include genomic medicine 'early adopter' and 'naïve' sites, as well as those that are EMR-enabled and others that are not. The study team will recruit a minimum of 7000 English or Spanish speaking adults over a 3-year period and will capture process metrics and outcomes that are measured in the course of usual care. The goals are: 1) To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers, 2) to export FHH data to an OpenCDS platform and return CDS results to providers and patients (and to EMRs where relevant) and to explore the integration of genetic risk and FHH data at selected sites, 3) to assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system, and 4) to take a leadership role in the dissemination of guidelines for FHH intervention across in diverse practice settings.
Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01956773
Please refer to this study by its ClinicalTrials.gov identifier: NCT01956773
|Contact: Dana Baker, MS||(919) email@example.com|
|United States, California|
|David Grant Medical Center||Terminated|
|Fairfield, California, United States, 94535|
|United States, Minnesota|
|Essentia Institute of Rural Health||Recruiting|
|Duluth, Minnesota, United States, 55805|
|Contact: Laurie Hall Laurie.Hall@EssentiaHealth.org|
|Contact: Joe Bianco, MD Joseph.Bianco@EssentiaHealth.org|
|Principal Investigator: Catherine McCarty, MD|
|United States, North Carolina|
|Duke University Medical Center||Recruiting|
|Durham, North Carolina, United States, 27710|
|Contact: Dana Baker, MS 919-668-2341 firstname.lastname@example.org|
|Principal Investigator: Geoffrey Ginsburg, MD PhD|
|Sub-Investigator: Lori Orlando, MD MHS|
|United States, Texas|
|University of North Texas Health Science Center||Recruiting|
|Fort Worth, Texas, United States, 76107|
|Contact: Kimberly S Fulda, DrPH email@example.com|
|Principal Investigator: Kimberly Fulda, DrPH|
|United States, Wisconsin|
|Medical College of Wisconsin||Recruiting|
|Milwaukee, Wisconsin, United States, 53226|
|Contact: Jennifer Geurts firstname.lastname@example.org|
|Principal Investigator: David Dimmock, MD|
Sponsors and Collaborators
|Principal Investigator:||Geoffrey S Ginsburg, MD PHD||Duke University, Institute for Genome Science and Policy|
|Principal Investigator:||Lori Orlando, MD||Duke University, Department of Medicine|