title: Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study.
abstract: BACKGROUND
  Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study's protocol.
  
  
  METHODS
  MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff.
  
  
  CONCLUSIONS
  This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness.
  
  
  BACKGROUND
  NCT01956773.
authors.affiliation: Duke Center for Applied Genomics & Precision Medicine and Duke Department of Medicine, Duke University, 411 West Chapel Hill Street, Ste. 500, Durham, NC, 27705, USA. ryanne.wu@duke.edu.
authors.forename: R Ryanne
authors.initials: RR
authors.lastname: Wu
authors.affiliation: Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA. rachel.myers@dm.duke.edu.
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Myers
authors.affiliation: Essentia Institute of Rural Health, Duluth, MN, USA. CMcCarty@eirh.org.
authors.forename: Catherine A
authors.initials: CA
authors.lastname: McCarty
authors.affiliation: Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI, USA. ddimmock@mcw.edu.
authors.forename: David
authors.initials: D
authors.lastname: Dimmock
authors.affiliation: Center for Urban Population Health, Aurora University of Wisconsin, Milwaukee, WI, USA. Michael.H.Farrell@aurora.org.
authors.forename: Michael
authors.initials: M
authors.lastname: Farrell
authors.affiliation: Department of Molecular and Medical Genetics, University of North Texas, Fort Worth, TX, USA. Deanna.cross@christushealth.org.
authors.forename: Deanna
authors.initials: D
authors.lastname: Cross
authors.affiliation: Clinical Investigations Facility, David Grant Medical Center, U.S. Air Force, Travis, CA, USA. troy.chinevere@us.af.mil.
authors.forename: Troy D
authors.initials: TD
authors.lastname: Chinevere
authors.affiliation: Duke Center for Applied Genomics & Precision Medicine and Duke Department of Medicine and Pathology, Duke University, Durham, NC, USA. geoffrey.ginsburg@dm.duke.edu.
authors.forename: Geoffrey S
authors.initials: GS
authors.lastname: Ginsburg
authors.affiliation: Duke Center for Applied Genomics & Precision Medicine and Duke Department of Medicine, Duke University, Durham, NC, USA. lorlando@duke.edu.
authors.forename: Lori A
authors.initials: LA
authors.lastname: Orlando
mesh_terms: D000465:Algorithms; D000554:Ambulatory Care Facilities / Q000458:organization & administration*; D034201:Computers, Handheld; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D057286:Electronic Health Records / Q000458:organization & administration*; D020022:Genetic Predisposition to Disease; D006801:Humans; D010353:Patient Education as Topic; D017410:Practice Guidelines as Topic; D011320:Primary Health Care / Q000458:organization & administration*; D012107:Research Design; D018570:Risk Assessment; D014584:User-Computer Interface