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      Physician Experience with Direct-To-Consumer Genetic Testing in Kaiser Permanente

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          Abstract

          Health systems and physicians nationwide aspire to consistently and reliably apply genetic and genomic information to guide disease prevention, management, and treatment. However, clinical information, including genetics/genomics data from within and outside of the care delivery system, is expanding rapidly. Between November 2017 and April 2018, we surveyed 1502 Permanente Medical Group primary care and specialist physicians to assess the degree to which direct-to-consumer genetic test results were being presented to physicians and identify genetics educational needs among physicians (response rate 15%). Adjusted logistic regression (according to respondent characteristics) was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) comparing responses within groups. Results showed 35% and 12% of respondents reported receiving at least one direct-to-consumer health risk genetic result (DTC-health risk) or direct-to-consumer pharmacogenomic test result (DTC-PGx), respectively, from a patient in the past year. Of those receiving at least one test result, 40% (DTC-health risk) and 39% (DTC-PGx) of physicians reported 1+ referral(s); 78% (DTC-health risk) and 42% (DTC-PGx) of referrals were to clinical genetics. In total, 85% of physicians would spend ≥2 h/year on genetics/genomics education.

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          Most cited references54

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          Adoption of pharmacogenomic testing by US physicians: results of a nationwide survey.

          To develop a benchmark measure of US physicians' level of knowledge and extent of use of pharmacogenomic testing, we conducted an anonymous, cross-sectional, fax-based, national survey. Of 397,832 physicians receiving the survey questionnaire, 10,303 (3%) completed and returned it; the respondents were representative of the overall US physician population. The factors associated with the decision to test were evaluated using χ(2) and multivariate logistic regression. Overall, 97.6% of responding physicians agreed that genetic variations may influence drug response, but only 10.3% felt adequately informed about pharmacogenomic testing. Only 12.9% of physicians had ordered a test in the previous 6 months, and 26.4% anticipated ordering a test in the next 6 months. Early and future adopters of testing were more likely to have received training in pharmacogenomics, but only 29.0% of physicians overall had received any education in the field. Our findings highlight the need for more effective physician education on the clinical value, availability, and interpretation of pharmacogenomic tests.
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            Time allocation in primary care office visits.

            To use an innovative videotape analysis method to examine how clinic time was spent during elderly patients' visits to primary care physicians. Secondary objectives were to identify the factors that influence time allocations. A convenience sample of 392 videotapes of routine office visits conducted between 1998 and 2000 from multiple primary care practices in the United States, supplemented by patient and physician surveys. Videotaped visits were examined for visit length and time devoted to specific topics--a novel approach to study time allocation. A survival analysis model analyzed the effects of patient, physician, and physician practice setting on how clinic time was spent. Very limited amount of time was dedicated to specific topics in office visits. The median visit length was 15.7 minutes covering a median of six topics. About 5 minutes were spent on the longest topic whereas the remaining topics each received 1.1 minutes. While time spent by patient and physician on a topic responded to many factors, length of the visit overall varied little even when contents of visits varied widely. Macro factors associated with each site had more influence on visit and topic length than the nature of the problem patients presented. Many topics compete for visit time, resulting in small amount of time being spent on each topic. A highly regimented schedule might interfere with having sufficient time for patients with complex or multiple problems. Efforts to improve the quality of care need to recognize the time pressure on both patients and physicians, the effects of financial incentives, and the time costs of improving patient-physician interactions.
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              Projecting the Supply and Demand for Certified Genetic Counselors: a Workforce Study

              As of May 2017, there were 4242 Certified Genetic Counselors (CGC) (American Board of Genetic Counseling, Inc. 2017) and 41 graduate-level genetic counseling training programs (Accreditation Council for Genetic Counseling 2017) in North America, and the demand for CGCs continues to increase. In the Fall of 2015 the Genetic Counselor Workforce Working Group, comprised of representatives from the American Board of Genetic Counseling (ABGC), the Accreditation Council for Genetic Counseling (ACGC), the Association of Genetic Counseling Program Directors (AGCPD), the American Society of Human Genetics (ASHG), and the National Society of Genetic Counselors (NSGC) commissioned a formal workforce study to project supply of and demand for CGCs through 2026. The data indicate a shortage of genetic counselors engaged in direct patient care. Assuming two scenarios for demand, supply is expected to reach equilibrium between 2024 and 2030. However, given the rate of growth in genetic counseling training programs in the six months since the study was completed, it is reasonable to expect that the number of new programs may be higher than anticipated by 2026. If true, and assuming that growth in programs is matched by equivalent growth in clinical training slots, the supply of CGCs in direct patient care would meet demand earlier than these models predict.
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                Author and article information

                Journal
                J Pers Med
                J Pers Med
                jpm
                Journal of Personalized Medicine
                MDPI
                2075-4426
                01 November 2019
                December 2019
                : 9
                : 4
                : 47
                Affiliations
                [1 ]Mid-Atlantic Permanente Research Institute, Mid-Atlantic Permanente Medical Group, Kaiser Permanente Mid-Atlantic States, Rockville, MD 20852, USA
                [2 ]Mid-Atlantic Permanente Medical Group, Kaiser Permanente Mid-Atlantic States, Rockville, MD 20852, USA; Pim.Suwannarat@ 123456kp.org (P.S.); ChristinexTruong@ 123456gmail.com (C.T.)
                [3 ]Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO 80014, USA; Andrea.N.Burnett-Hartman@ 123456kp.org (A.B.-H.); Nikki.M.Carroll@ 123456kp.org (N.C.); Erica.Blum-Barnett@ 123456kp.org (E.B.-B.)
                [4 ]University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Michelle.Turner@ 123456cuanschutz.edu
                [5 ]Kaiser Permanente National Quality, Oakland, CA 94611, USA; Kristen.X.Janes@ 123456kp.org
                [6 ]Variant Genomics, Inc., Oakland, CA 94611, USA; Nazneen.Aziz@ 123456variant-genomics.com
                [7 ]Kaiser Permanente Research, Pasadena, CA 91101, USA; Elizabeth.A.McGlynn@ 123456kp.org
                Author notes
                [* ]Correspondence: Cabell.Jonas@ 123456kp.org ; Tel.: 1-301-816-7371
                Article
                jpm-09-00047
                10.3390/jpm9040047
                6963876
                31683813
                f91c40c3-fc23-405b-baa9-b9183f4eae7f
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 October 2019
                : 30 October 2019
                Categories
                Article

                physician survey,genetics,genomics,physician education,direct-to-consumer genetic testing,pharmacogenomic testing

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