Dataset Information

Oncology Clinic-Based Hereditary Cancer Genetic Testing in a Population-Based Health Care System.

ABSTRACT: New streamlined models for genetic counseling and genetic testing have recently been developed in response to increasing demand for cancer genetic services. To improve access and decrease wait times, we implemented an oncology clinic-based genetic testing model for breast and ovarian cancer patients in a publicly funded population-based health care setting in British Columbia, Canada. This observational study evaluated the oncology clinic-based model as compared to a traditional one-on-one approach with a genetic counsellor using a multi-gene panel testing approach. The primary objectives were to evaluate wait times and patient reported outcome measures between the oncology clinic-based and traditional genetic counselling models. Secondary objectives were to describe oncologist and genetic counsellor acceptability and experience. Wait times from referral to return of genetic testing results were assessed for 400 patients with breast and/or ovarian cancer undergoing genetic testing for hereditary breast and ovarian cancer from June 2015 to August 2017. Patient wait times from referral to return of results were significantly shorter with the oncology clinic-based model as compared to the traditional model (403 vs. 191 days; p < 0.001). A subset of 148 patients (traditional n = 99; oncology clinic-based n = 49) completed study surveys to assess uncertainty, distress, and patient experience. Responses were similar between both models. Healthcare providers survey responses indicated they believed the oncology clinic-based model was acceptable and a positive experience. Oncology clinic-based genetic testing using a multi-gene panel approach and post-test counselling with a genetic counsellor significantly reduced wait times and is acceptable for patients and health care providers.

SUBMITTER: Richardson M

PROVIDER: S-EPMC7072228 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Oncology Clinic-Based Hereditary Cancer Genetic Testing in a Population-Based Health Care System.

Richardson Matthew M Min Hae Jung HJ Hong Quan Q Compton Katie K Mung Sze Wing SW Lohn Zoe Z Nuk Jennifer J McCullum Mary M Portigal-Todd Cheryl C Karsan Aly A Regier Dean D Brotto Lori A LA Sun Sophie S Schrader Kasmintan A KA

Cancers 20200203 2

New streamlined models for genetic counseling and genetic testing have recently been developed in response to increasing demand for cancer genetic services. To improve access and decrease wait times, we implemented an oncology clinic-based genetic testing model for breast and ovarian cancer patients in a publicly funded population-based health care setting in British Columbia, Canada. This observational study evaluated the oncology clinic-based model as compared to a traditional one-on-one appro ...[more]

PMID: 32028617

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Project description:BackgroundIntegration of genetic testing into routine oncology care could improve access to testing. This systematic review investigated interventions and the tailored implementation strategies aimed at increasing access to genetic counselling and testing and identifying hereditary cancer in oncology.MethodsThe search strategy results were reported using the PRISMA statement and four electronic databases were searched. Eligible studies included routine genetic testing for breast and ovarian cancer or uptake after universal tumour screening for colorectal or endometrial cancer. The titles and abstracts were reviewed and the full text articles screened for eligibility. Data extraction was preformed using a designed template and study appraisal was assessed using an adapted Newcastle Ottawa Scale. Extracted data were mapped to Proctor's et al outcomes and the Consolidated Framework for Implementation Research and qualitatively synthesised.ResultsTwenty-seven studies, published up to May 2020, met the inclusion criteria. Twenty-five studies ranged from poor (72%), fair to good (28%) quality. Most interventions identified were complex (multiple components) such as; patient or health professional education, interdisciplinary practice and a documentation or system change. Forty-eight percent of studies with complex interventions demonstrated on average a 35% increase in access to genetic counselling and a 15% increase in testing completion. Mapping of study outcomes showed that 70% and 32% of the studies aligned with either the service and client or the implementation level outcome and 96% to the process or inner setting domains of the Consolidated Framework for Implementation Research.ConclusionExisting evidence suggests that complex interventions have a potentially positive effect towards genetic counselling and testing completion rates in oncology services. Studies of sound methodological quality that explore a greater breadth of pre and post implementation outcomes and informed by theory are needed. Such research could inform future service delivery models for the integration of genetics into oncology services.

Project description:Ovarian cancer is usually diagnosed at a late stage when outcomes are poor. Personalised ovarian cancer risk prediction, based on genetic and epidemiological information and risk stratified management in adult women could improve outcomes. Examining health care professionals' (HCP) attitudes to ovarian cancer risk stratified management, willingness to support women, self-efficacy (belief in one's own ability to successfully complete a task), and knowledge about ovarian cancer will help identify training needs in anticipation of personalised ovarian cancer risk prediction being introduced.An anonymous survey was distributed online to HCPs via relevant professional organisations in the UK. Kruskal-Wallis tests and pairwise comparisons were used to compare knowledge and self-efficacy scores between different types of HCPs, and attitudes toward population-based genetic testing and risk stratified management were described. Content analysis was undertaken of free text responses concerning HCPs willingness to discuss risk management options with women.One hundred forty-six eligible HCPs completed the survey: oncologists (31%); genetics clinicians (30%); general practitioners (22%); gynaecologists (10%); nurses (4%); and 'others'. Scores for knowledge of ovarian cancer and genetics, and self-efficacy in conducting a cancer risk consultation were generally high but significantly lower for general practitioners compared to genetics clinicians, oncologists, and gynaecologists. Support for population-based genetic testing was not high (<50%). Attitudes towards ovarian cancer risk stratification were mixed, although the majority of participants indicated a willingness to discuss management options with patients.Larger samples are required to investigate attitudes to population-based genetic testing for ovarian cancer risk and to establish why some HCPs are hesitant to offer testing to all adult female patients. If ovarian cancer risk assessment using genetic testing and non-genetic information including epidemiological information is rolled out on a population basis, training will be needed for HCPs in primary care to enable them to provide appropriate support to women at each stage of the process.

Project description:BackgroundThe population-based integrated health care system called "Gesundes Kinzigtal" (Integrierte Versorgung Gesundes Kinzigtal, IVGK) was initiated more than 10 years ago in the Kinzig River Valley region, which is located in the Black Forest in the German state of Baden-Württemberg. IVGK is intended to optimize health care while maximizing cost-effectiveness. It consists of programs for promoting health and for enabling cooperation among service providers, as well as of a shared-savings contract that has enabled resources to be saved every year. The goal of the present study was to investigate trends in the quality of care provided by IVGK over the past ten years in comparison to conventional care.MethodsThis is a non-randomized observational study with a control-group design (Kinzig River Valley versus 13 structurally comparable control regions), employing data collected by AOK, a large statutory health-insurance provider in Germany, over the period 2006-2015. Quality assessment was conducted with the aid of a set of indicators, developed by the authors, that was based exclusively on claims data. The statistical analysis of the trends in these indicators over time was conducted with preset criteria for the relevance of any observed changes, as well as preset mechanisms of controlling for confounding factors.ResultsFor 88 of the 101 evaluable indicators, no relevant difference was seen between the trend over time in the region of the intervention and the average trend in the control regions. Relevant differences in favor of the IVGK were observed for six indicators, and negatively divergent trends compared to the controls were observed for seven indicators. In the main summarizing statistical analysis, no positive or negative difference was found between the Kinzig River Valley and the other regions with respect to trends in the health-care indicators over time.ConclusionAn evaluation based on 101 indicators derived from health-insurance data did not reveal any improvement of the quality of care by IVGK and the totality of the programs that were implemented under it. However, under the conditions of the shared-savings contract, no relevant diminution in the quality of care was observed over a period of 10 years either, compared with structurally similar control regions without an integrated care model.

Dataset Information

Oncology Clinic-Based Hereditary Cancer Genetic Testing in a Population-Based Health Care System.

Publications

Oncology Clinic-Based Hereditary Cancer Genetic Testing in a Population-Based Health Care System.

Similar Datasets

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