Collection of family health history for assessment of chronic disease risk in primary care.

BACKGROUND: Family health history can predict a patient's risk for common complex diseases. This project assessed the completeness of family health history data in medical charts and evaluated the utility of these data for performing risk assessments in primary care. METHODS: Family health history data were collected and analyzed to determine the presence of quality indicators that are necessary for effective and accurate assessment of disease risk. RESULTS: More than 99% of the 390 paper charts analyzed contained information about family health history, which was usually scattered throughout the chart. Information on the health of the patient's parents was collected more often than information on the health of other relatives. Key information that was often not collected included age of disease onset, affected side of the family, and second-degree relatives affected. Less than 4% of patient charts included family health histories that were informative enough to accurately assess risk for common complex diseases. LIMITATIONS: Limitations of this study include the small number of charts reviewed per provider, the fact that the sample consisted of primary care providers in a single geographic location, and the inability to assess ethnicity, consanguinity, and other indicators of the informativeness of family health history. CONCLUSIONS: The family health histories collected in primary care are usually not complete enough to assess the patient's risk for common complex diseases. This situation could be improved with use of tools that analyze the family health history information collected and provide risk-stratified decision support recommendations for primary care.

Development and validation of a primary care-based family health history and decision support program (MeTree).

INTRODUCTION: Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS: We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS: Stakeholder feedback resulted in changes to MeTree's interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree's strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers' needs. LIMITATIONS: The tool was validated in a small cohort. CONCLUSION: MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines.

Genetic counseling and testing for Alzheimer disease: joint practice guidelines of the American College of Medical Genetics and the National Society of Genetic Counselors.

Alzheimer disease is the most common cause of dementia. It occurs worldwide and affects all ethnic groups. The incidence of Alzheimer disease is increasing due, in part, to increased life expectancy and the aging baby boomer generation. The average lifetime risk of developing Alzheimer disease is 10-12%. This risk at least doubles with the presence of a first-degree relative with the disorder. Despite its limited utility, patients express concern over their risk and, in some instances, request testing. Furthermore, research has demonstrated that testing individuals for apolipoprotein E can be valuable and safe in certain contexts. However, because of the complicated genetic nature of the disorder, few clinicians are prepared to address the genetic risks of Alzheimer disease with their patients. Given the increased awareness in family history thanks to family history campaigns, the increasing incidence of Alzheimer disease, and the availability of direct to consumer testing, patient requests for information is increasing. This practice guideline provides clinicians with a framework for assessing their patients' genetic risk for Alzheimer disease, identifying which individuals may benefit from genetic testing, and providing the key elements of genetic counseling for AD.