Family Health History in Diverse Care Settings (FHH)

NCT ID: NCT01956773

Last Updated: 2023-08-02

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 2620 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2014-04-11
• Study Completion Date: 2017-10-31

Brief Summary

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.

Detailed Description

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.

Conditions

Diabetes; Heart Disease; Cancer

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

MeTree - Patient

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to patients as clinical decision support.

Group Type: EXPERIMENTAL

MeTree

Intervention Type: OTHER

Software program collecting family health history and generating clinical decision support for risk-based preventive care

MeTree - Provider

MeTree collects family health history data and generates risk scores and specific risk-based recommendation for preventive care to providers as clinical decision support.

Group Type: EXPERIMENTAL

MeTree

Intervention Type: OTHER

Software program collecting family health history and generating clinical decision support for risk-based preventive care

Interventions

MeTree

Software program collecting family health history and generating clinical decision support for risk-based preventive care

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Adults 18 years of age
• Scheduled for a well visit appointment in selected clinics
• English and Spanish speaking
• Able to provide informed consent

Exclusion Criteria

• None

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Duke University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Geoffrey S Ginsburg, MD PHD

Role: PRINCIPAL_INVESTIGATOR

Duke University, Institute for Genome Science and Policy

Lori Orlando, MD

Role: PRINCIPAL_INVESTIGATOR

Duke University, Department of Medicine

Locations

David Grant Medical Center

Fairfield, California, United States

Essentia Institute of Rural Health

Duluth, Minnesota, United States

Duke University Medical Center

Durham, North Carolina, United States

University of North Texas Health Science Center

Fort Worth, Texas, United States

Medical College of Wisconsin

Milwaukee, Wisconsin, United States

Countries

United States

References

Wu RR, Myers RA, Neuner J, McCarty C, Haller IV, Harry M, Fulda KG, Dimmock D, Rakhra-Burris T, Buchanan A, Ginsburg GS, Orlando LA. Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities. BMC Health Serv Res. 2022 Dec 6;22(1):1486. doi: 10.1186/s12913-022-08879-2.

Reference Type: DERIVED

PMID: 36474257 (View on PubMed)

Orlando LA, Wu RR, Myers RA, Neuner J, McCarty C, Haller IV, Harry M, Fulda KG, Dimmock D, Rakhra-Burris T, Buchanan A, Ginsburg GS. At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care. BMC Health Serv Res. 2020 Nov 7;20(1):1015. doi: 10.1186/s12913-020-05868-1.

Reference Type: DERIVED

PMID: 33160339 (View on PubMed)

Wu RR, Myers RA, Buchanan AH, Dimmock D, Fulda KG, Haller IV, Haga SB, Harry ML, McCarty C, Neuner J, Rakhra-Burris T, Sperber N, Voils CI, Ginsburg GS, Orlando LA. Effect of Sociodemographic Factors on Uptake of a Patient-Facing Information Technology Family Health History Risk Assessment Platform. Appl Clin Inform. 2019 Mar;10(2):180-188. doi: 10.1055/s-0039-1679926. Epub 2019 Mar 13.

Reference Type: DERIVED

PMID: 30866001 (View on PubMed)

Wu RR, Myers RA, McCarty CA, Dimmock D, Farrell M, Cross D, Chinevere TD, Ginsburg GS, Orlando LA; Family Health History Network. Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study. Implement Sci. 2015 Nov 24;10:163. doi: 10.1186/s13012-015-0352-8.

Reference Type: DERIVED

PMID: 26597091 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

Pro00047666

Identifier Type: OTHER

Identifier Source: secondary_id

Pro00043372

Identifier Type: -

Identifier Source: org_study_id