Clinical utility of a Web-enabled risk-assessment and clinical decision support program.

PURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce "overuse" and "underuse" of increased-risk services.Genet Med 18 10, 1020-1028.

Family health history: an essential starting point for personalized risk assessment and disease prevention.

Family health history (FHH) information is well established as a basis for assessing a patient's personal disease risk, but is underutilized for diagnosis and making medical recommendations. Epidemiological and genetic information have heightened the value of FHH to an individual's health. This has motivated the development of new FHH collection tools and strategies for family members, but will require greater awareness and knowledge by both patients and practitioners. FHH will be increasingly important as genomic data become a mainstay of medical diagnostics, since in many cases, a medically important FHH results from lineage-specific genetic variants. The impact of complementary FHH and genomic information will drive the pursuit of personalized and precise targeting of treatments and interventions aimed at maintaining patient health.

Implementing family health history risk stratification in primary care: impact of guideline criteria on populations and resource demand.

UNLABELLED: The Genomic Medicine Model aims to facilitate patient engagement, patient/provider education of genomics/personalized medicine, and uptake of risk-stratified evidence-based prevention guidelines using MeTree, a patient-facing family health history (FHH) collection and clinical decision support (CDS) program. Here we report the number of increased risk (above population-level risk) patients identified for breast/ovarian cancer, colon cancer, hereditary syndrome risk, and thrombosis; the prevalence of FHH elements triggering increased-risk status; and the resources needed to manage their risk. STUDY DESIGN: hybrid implementation-effectiveness study of adults with upcoming well-visits in 2 primary care practices in Greensboro, NC. PARTICIPANTS: 1,184, mean age = 58.8, female = 58% (N = 694), non-white = 20% (N = 215). Increased Risk: 44% (N = 523). RECOMMENDATIONS: genetic counseling = 26% (N = 308), breast MRI = 0.8% (N = 10), breast chemoprophylaxis = 5% (N = 58), early/frequent colonoscopies = 19% (N = 221), ovarian cancer screening referral = 1% (N = 14), thrombosis testing/counseling = 2.4% (N = 71). FHH elements: 8 FHH elements lead to 37.3% of the increased risk categorizations (by frequency): first-degree-relative (FDR) with polyps age ≥60 (7.1%, N = 85), three relatives with Lynch-related cancers (5.4%, N = 65), FDR with polyps age <60 (5.1%, N = 61), three relatives on same side of family with same cancer (4.9%, N = 59), Gail score ≥1.66% (4.9%, N = 58), two relatives with breast cancer (one ≤age 50) (4.1%, N = 49), one relative with breast cancer ≤age 40 (4.1%, N = 48), FDR with colon cancer age ≥60 (1.7%, N = 20). MeTree identifies a high percentage of individuals in the general primary care population needing non-routine risk management/prevention for the selected conditions. Implementing risk-stratification in primary care will likely increase demand for related-resources, particularly colon screening and GC. Understanding the prevalence of FHH elements helps predict resource needs and may aid in guideline development.

Quality of family history collection with use of a patient facing family history assessment tool.

BACKGROUND: Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree. DESIGN: A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. SETTING: Two community primary care clinics in Greensboro, NC. PARTICIPANTS: All non-adopted adult English speaking patients with upcoming appointments were invited to participate. INTERVENTION: Education about and collection of FHH with entry into MeTree. MEASURES: We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives' lineage, (3) relatives' gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479-495, 2004.). RESULTS: Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.). CONCLUSION: Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level. TRIAL NUMBER: NCT01372553.

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.

The use of a family history risk assessment tool within a community health care system: views of primary care providers.

Primary care providers (PCPs) offered input regarding the incorporation of a family health history (FHH) risk assessment tool into a community health care system (CHCS). Sixteen PCPs participated in one of three focus groups. Perceived impediments included the lack of standard screening guidelines, effective screening tests, genetic counseling resources, and services for high-risk patients. The PCPs were concerned about their level of expertise, the cost of preventive health care, and genetic discrimination. They also were concerned about the use of a FHH tool by oncologists within the CHCS because of communication gaps between oncologists and PCPs, lack of clarity regarding follow-up and legal liability, and reimbursement issues. To integrate a FHH tool into a CHCS, PCPs will need consultation and referral services, evidence-based recommendations, and "just-in-time" educational resources. Oncologists who use the tool will need to develop a streamlined communication system with PCPs, establish clearly defined roles, and ensure patient follow-up.

Findings from a community education needs assessment to facilitate the integration of genomic medicine into primary care.

PURPOSE: To assess the lay public's knowledge of, and beliefs about, genetics and genetic testing to create an educational initiative that promotes acceptance and utilization of genomic medicine in primary health care. METHODS: A telephone survey of English-speaking adults in Guilford County, North Carolina was conducted in 2006 to identify community members' educational needs regarding genetics and genetic testing. RESULTS: Most respondents recognized the connection between family history and disease risk. A majority did not appear to know about: (1) basic principles of inheritance, (2) laws prohibiting genetic discrimination, and (3) the availability and limitations of genetic tests. About 25% thought that they could not reduce their risk if they have a genetic predisposition for disease. Knowledge level was affected by education, experience, age, and race. CONCLUSION: If primary care providers use family history as a risk assessment tool, community education programs must address (1) the collection of family health history, (2) legislation regarding genetic nondiscrimination, (3) benefits and limitations of existing genetic tests, and (4) genetic determinism. Programs emphasizing practical, "how to" information can be targeted to individuals likely to collect family history information and address misperceptions about discrimination, testing, and determinism.