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/DESIGN: 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. DISCUSSION: 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. TRIAL REGISTRATION: NCT01956773.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1186/s13012-015-0352-8

Publication Info

Wu, R Ryanne, Rachel A Myers, Catherine A McCarty, David Dimmock, Michael Farrell, Deanna Cross, Troy D Chinevere, Geoffrey S Ginsburg, et al. (2015). Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study. Implement Sci, 10. p. 163. 10.1186/s13012-015-0352-8 Retrieved from https://hdl.handle.net/10161/11500.

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Scholars@Duke

Wu

Rebekah Ryanne Wu

Adjunct Associate Professor in the Department of Medicine

Dr. Wu is an internal medicine physician and health services researcher. Her main research interest is studying the implementation of precision medicine applications to improve clinical care. She is involved in projects currently looking at a patient-facing family history risk assessment tool, MeTree, which provides individualized risk stratification and clinical decision support recommendations to clinicians and patients. In addition she is also involved in a large scale sequencing program in Singapore looking at the intersection of family health history and genomics to better understand how these data elements can complement one another and create more precise risk predictions.  She is a member of NHGRI's IGNITE network as a co-investigator on a multi-site pragmatic clinical trial of the impact of pharmacogenetic testing on management of depression and acute, and chronic pain.  She is the implementation science advisor for the VA's Pharmacogenomic Testing for Veterans (PHASER) program, which is working to complete preemptive PGx testing on up to 250,000 Veterans by 2024.

Myers

Rachel Myers

Research Scientist, Senior

I am a bioinformatician cross trained as biostatistician and research scientist with the Department of Medicine Clinical Research Unit. In this role, I manage the Bioinformatics and Clinical Analytics Team, a team of bioinformaticians, biostatisticians, and data scientists in supporting the data and quantitative research needs of the Department of Medicine. 

I am interested in genomic translational research and enjoy studying all aspects of genomic translation, from the discovery of new signatures and biomarkers of drug or infection exposure through the implementation of genomics interventions in the clinical setting. I enjoy the complex analysis of "Omic datasets and generating new knowledge. My favorite part of the analysis is when all the clinical and 'omic datasets come together and I can start exploring the data. On the other end of the spectrum, I enjoy watching data accumulate for a clinical trial and preparing for testing the primary and secondary endpoints as well as designing new ways to use the data. 



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