Implementation of an electronic genomic and family health history tool in primary prenatal care.

"The Pregnancy and Health Profile," (PHP) is a free genetic risk assessment software tool for primary prenatal providers that collects patient-entered family (FHH), personal, and obstetrical health history, performs risk assessment, and presents the provider with clinical decision support during the prenatal encounter. The tool is freely available for download at www.hughesriskapps.net. We evaluated the implementation of PHP in four geographically diverse clinical sites. Retrospective chart reviews were conducted for patients seen prior to the study period and for patients who used the PHP to collect data on documentation of FHH, discussion of cystic fibrosis (CF) and hemoglobinopathy (HB) carrier screening, and CF and HB interventions (tests, referrals). Five hundred pre-implementation phase and 618 implementation phase charts were reviewed. Documentation of a 3-generation FHH or pedigree improved at three sites; patient race/ethnicity at three sites, father of the baby (FOB) race/ethnicity at all sites, and ancestry for the patient and FOB at three sites (P < 0.001-0001). CF counseling improved for implementation phase patients at one site (8% vs. 48%, P < 0.0001) and CF screening/referrals at two (2% vs. 14%, P < 0.0001; 6% vs. 14%; P = 0.05). Counseling and intervention rates did not increase for HB. This preliminary study suggests that the PHP can improve documentation of FHH, race, and ancestry, as well as the compliance with current CF counseling and intervention guidelines in some prenatal clinics. Future evaluation of the PHP should include testing in a larger number of clinical environments, assessment of additional performance measures, and evaluation of the system's overall clinical utility.

Evaluation of a novel electronic genetic screening and clinical decision support tool in prenatal clinical settings.

"The Pregnancy and Health Profile" (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher's exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83% (513/618) of patients that provided feedback, 97% felt PHP was easy to use and 98% easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.

Personalizing prenatal care using family health history: identifying a panel of conditions for a novel electronic genetic screening tool.

In the age of genomic medicine, family health history (FHH) remains an important tool for personalized risk assessment as it can inform approaches to disease prevention and management. In primary care, including in prenatal settings, providers recognize that FHH enables them to assess the risk for birth defects and complex conditions that not only affect the fetus health, but also the mother's. However, many providers lack the time to gather FHH or the knowledge to confidently interpret the data. Electronic tools providing clinical decision support using FHH data can aid the busy provider with data collection and interpretation. We describe the scope of conditions included in a patient-entered FHH tool that provides clinical decision support and point-of-care education to assist with patient management. This report details how we selected the conditions for which it is appropriate to use FHH as a means to promote personalized medicine in primary prenatal care.

Reporting of human genome epidemiology (HuGE) association studies: an empirical assessment.

BACKGROUND: Several thousand human genome epidemiology association studies are published every year investigating the relationship between common genetic variants and diverse phenotypes. Transparent reporting of study methods and results allows readers to better assess the validity of study findings. Here, we document reporting practices of human genome epidemiology studies. METHODS: Articles were randomly selected from a continuously updated database of human genome epidemiology association studies to be representative of genetic epidemiology literature. The main analysis evaluated 315 articles published in 2001-2003. For a comparative update, we evaluated 28 more recent articles published in 2006, focusing on issues that were poorly reported in 2001-2003. RESULTS: During both time periods, most studies comprised relatively small study populations and examined one or more genetic variants within a single gene. Articles were inconsistent in reporting the data needed to assess selection bias and the methods used to minimize misclassification (of the genotype, outcome, and environmental exposure) or to identify population stratification. Statistical power, the use of unrelated study participants, and the use of replicate samples were reported more often in articles published during 2006 when compared with the earlier sample. CONCLUSION: We conclude that many items needed to assess error and bias in human genome epidemiology association studies are not consistently reported. Although some improvements were seen over time, reporting guidelines and online supplemental material may help enhance the transparency of this literature.

Tracking the epidemiology of human genes in the literature: the HuGE Published Literature database.

Completion of the human genome sequence has inspired a new wave of epidemiologic studies on the prevalence of gene variants and their associations with diseases in human populations. In 2001, the Human Genome Epidemiology (HuGE) Network launched the HuGE Published Literature database (HuGE Pub Lit), a searchable, online knowledge base of published, population-based epidemiologic studies of human genes. The database contains links to PubMed articles and can be searched by gene, disease, interacting factor, type of study design or analysis, or any combination of terms in these categories. The search output contains a link to each identified article, along with a table summarizing key features of the reported study. As of September 6, 2005, some 17,665 articles were indexed in the database. Most described gene-disease associations (86%); fewer evaluated gene-gene or gene-environment interactions (17%), the prevalence of gene variants (10%), or genetic tests (3%). Although not comprehensive, this database is a unique tool for epidemiologic researchers and others concerned with the role of genetic variation in population health. Here, the authors provide an overview of the database and its characteristics and uses.