Protocol for implementation of family health history collection and decision support into primary care using a computerized family health history system

In 2002 the CDC launched the Family History Public Health Initiative, founded upon the principle that family history is an under used but effective tool for risk stratification. Two of the stated goals are to develop tools to enhance family health history (FHH) collection and to evaluate whether family history-based strategies work. Given that primary care providers are the first (and sometimes only) provider most patients see and are long-term partners and coordinators in their care, primary care practices play a crucial role in collecting and integrating FHH into an individual's personalized health plan. They, therefore, are a natural choice as partners in studying the implementation of family history collection into the medical decision making process.

Although FHH is considered a standard component of the medical interview and several guidelines tie screening strategies to risk based upon family history, substantial barriers exist to widespread adoption in clinical practice. Barriers can be broadly categorized into those related to collecting family history and those related to acting upon family history. Among those related to collecting family history are: 1) most primary care practices do not have the resources or the time to collect a complete FHH or to update it [1]; 2) many patients are either unaware or have limited knowledge about their FHH and are therefore not able to answer questions accurately and completely at the point of care [2]; and 3) many providers do not have adequate training and thus fail to recognize all but the most straightforward patterns related to inherited syndromes [3, 4]. Among the barriers related to acting upon family history are the lack of clear cut recommendations about how to manage moderate and high risk patients, and the lack of adequate communication and support from family history specialists, genetic counselors, and subspecialists that are necessary to provide appropriate management.

As part of a personalized medicine research program, The Genomedical Connection, a consortium between Duke University, the University of North Carolina at Greensboro, and the Moses Cone Health System in Greensboro, NC funded by the Department of Defense, developed a computerized self-administered FHH collection tool with integrated decision support, MeTree, to overcome barriers to the integration of FHH into primary care.

The Genomedical Connection developed a computerized self-administered FHH collection and decision support tool (MeTree) as part of a model for the practice of genomic medicine in primary care. This study was IRB approved by all three institutional partners as well as by the Department of Defense. The goal of the tool is to assist primary care providers in identifying high risk individuals who may need additional screening or referrals to maximize their preventative health care. It collects a 3 generation FHH on 48 conditions and currently provides decision support for 5 test conditions: breast cancer, ovarian cancer, colon cancer, thrombosis, and hereditary cancer syndromes. Diseases collected by the tool are shown in table 1. Decision support is provided in the form of printed reports. A patient report outlines important points for patients to discuss with their providers, while a provider report contains guideline recommendations for prevention and screening based upon estimated disease risk. Both receive a copy of the pedigree and the provider is given a tabular report of the family history as well. Examples reports are available in Additional File 1, Appendix A (provider report) and Additional File 2, Appendix B (patient report).

The simplest and least expensive form of genetic assessment, family history, is widely overlooked in medical practice. It has long been taught as one of the core foundations of the medical interview, yet over the years these skills have been lost or overwhelmed by the pressures and time constraints of day to day practice. Bringing family history back into the realm of medical decision making is important for multiple reasons. First, disease prevention has the potential to reduce the ever escalating costs of medical care. However, disease prevention relies entirely upon accurate disease risk prediction. Family history has been shown to improve disease risk prediction for colon cancer [9], breast cancer [10], and cardiovascular disease [11], among others. Second, using family history to predict disease requires several skills: understanding what family history is saying about risk, understanding how to communicate risk to patients, and using risk information to motivate behavior change. By developing an electronic family history collection and decision support tool to assist providers, we anticipate that providers will be able to reincorporate family history based decision making into their medical practice. In addition, continued use may permit providers to establish and hone their skills in a way that they can start to apply them to other risk-based fields, thus it may serve as an educational stepping stone to newer and more complicated areas of genetics and genomics.

Despite these benefits of family history taking little is known about its clinical validity or utility [12]. Our study fills this significant gap by directly addressing the question of both validity and utility. Although the one year follow up will not permit the use of hard outcomes such as the incidence of breast, colon, or ovarian cancer, screening is indicated by the United States Preventive Task Force and the American Cancer Society because of evidence that screening reduces morbidity and mortality; but is considerably underutilized [13, 14]. With this in mind screening patterns may be used as an acceptable intermediate endpoint.

Another important gap our study addresses is implementation. Multiple barriers to implementation exist. At the patient level inaccurate or limited information about family history is widespread [12]. At the provider level, as mentioned above, time constraints and lack of training are becoming more and more difficult to address [15]. Developing an electronic tool for collecting family history and providing decision support at the point of care are essential keys to addressing these barriers and our tool, MeTree does just that; however integrating it into practice creates its own set of barriers. Technology can be a barrier for both patients and providers, as can the resources required to integrate it. We monitor all stakeholders and measure every aspect of the implementation process in order to get a clear picture of what barriers have been solved with MeTree and what new ones arise in their place. At the end of this study we expect to have an excellent idea of not only whether such a tool has value in clinical practice but also how best to facilitate widespread adoption. Ultimately, it may serve as a demonstration project to guide integration of other personalized medicine tools, such as health risk assessments, into clinical practice.