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Johnson D, Del Fiol G, Kawamoto K, Romagnoli KM, Sanders N, Isaacson G, Jenkins E, Williams MS. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc 2024; 31:1183-1194. [PMID: 38558013 PMCID: PMC11031215 DOI: 10.1093/jamia/ocae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVES Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.
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Affiliation(s)
- Darren Johnson
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Katrina M Romagnoli
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Nathan Sanders
- School of Medicine, Geisinger Health Systems, Danville, PA 17822, United States
| | - Grace Isaacson
- Family Medicine, Penn Highlands Healthcare, DuBois, PA 16830, United States
| | - Elden Jenkins
- School of Medicine, Noorda College of Osteopathic Medicine, Provo, UT 84606, United States
| | - Marc S Williams
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
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2
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Barak-Corren Y, Tsurel D, Keidar D, Gofer I, Shahaf D, Leventer-Roberts M, Barda N, Reis BY. The value of parental medical records for the prediction of diabetes and cardiovascular disease: a novel method for generating and incorporating family histories. J Am Med Inform Assoc 2023; 30:1915-1924. [PMID: 37535812 PMCID: PMC10654871 DOI: 10.1093/jamia/ocad154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/16/2023] [Accepted: 07/24/2023] [Indexed: 08/05/2023] Open
Abstract
OBJECTIVE To determine whether data-driven family histories (DDFH) derived from linked EHRs of patients and their parents can improve prediction of patients' 10-year risk of diabetes and atherosclerotic cardiovascular disease (ASCVD). MATERIALS AND METHODS A retrospective cohort study using data from Israel's largest healthcare organization. A random sample of 200 000 subjects aged 40-60 years on the index date (January 1, 2010) was included. Subjects with insufficient history (<1 year) or insufficient follow-up (<10 years) were excluded. Two separate XGBoost models were developed-1 for diabetes and 1 for ASCVD-to predict the 10-year risk for each outcome based on data available prior to the index date of January 1, 2010. RESULTS Overall, the study included 110 734 subject-father-mother triplets. There were 22 153 cases of diabetes (20%) and 11 715 cases of ASCVD (10.6%). The addition of parental information significantly improved prediction of diabetes risk (P < .001), but not ASCVD risk. For both outcomes, maternal medical history was more predictive than paternal medical history. A binary variable summarizing parental disease state delivered similar predictive results to the full parental EHR. DISCUSSION The increasing availability of EHRs for multiple family generations makes DDFH possible and can assist in delivering more personalized and precise medicine to patients. Consent frameworks must be established to enable sharing of information across generations, and the results suggest that sharing the full records may not be necessary. CONCLUSION DDFH can address limitations of patient self-reported family history, and it improves clinical predictions for some conditions, but not for all, and particularly among younger adults.
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Affiliation(s)
- Yuval Barak-Corren
- Predictive Medicine Group, Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - David Tsurel
- Predictive Medicine Group, Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts, USA
- Clalit Research Institute, Ramat Gan, Israel
- The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Daphna Keidar
- Predictive Medicine Group, Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts, USA
- Clalit Research Institute, Ramat Gan, Israel
| | - Ilan Gofer
- Clalit Research Institute, Ramat Gan, Israel
| | - Dafna Shahaf
- The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Maya Leventer-Roberts
- Clalit Research Institute, Ramat Gan, Israel
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Noam Barda
- Clalit Research Institute, Ramat Gan, Israel
| | - Ben Y Reis
- Predictive Medicine Group, Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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Frey MK, Ahsan MD, Webster E, Levi SR, Brewer JT, Lin J, Blank SV, Krinsky H, Nchako C, Wolfe I, Thomas C, Christos P, Cantillo E, Chapman-Davis E, Holcomb K, Sharaf RN. Web-based tool for cancer family history collection: A prospective randomized controlled trial. Gynecol Oncol 2023; 173:22-30. [PMID: 37062188 PMCID: PMC10310435 DOI: 10.1016/j.ygyno.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 04/18/2023]
Abstract
OBJECTIVES Approximately 1% of individuals have a hereditary cancer predisposition syndrome, however, the majority are not aware. Collecting a cancer family history (CFH) can triage patients to receive genetic testing. To rigorously assess different methods of CFH collection, we compared a web-based tool (WBT) to usual care (clinician collects CFH) in a randomized controlled trial. METHODS New gynecologic oncology patients (seen 9/2019-9/2021) were randomized to one of three arms in a 2:2:1 allocation ratio: 1) usual care clinician CFH collection, 2) WBT completed at home, or 3) WBT completed in office. The WBT generated a cancer-focused pedigree and scores on eight validated cancer risk models. The primary outcome was collection of an adequate CFH (based on established guidelines) with usual care versus the WBT. RESULTS We enrolled 250 participants (usual care - 110; WBT home - 105; WBT office - 35 [closed early due to COVID-19]). Within WBT arms, 109 (78%) participants completed the tool, with higher completion for office versus home (33 [94%] vs. 76 [72%], P = 0.008). Among participants completing the WBT, 63 (58%) had an adequate CFH versus 5 (5%) for usual care (P < 0.001). Participants completing the WBT were significantly more likely to complete genetic counseling (34 [31%] vs. 15 [14%], P = 0.002) and genetic testing (20 [18%] vs. 9 [8%], P = 0.029). Participant and provider WBT experience was favorable. CONCLUSIONS WBTs for CFH collection are a promising application of health information technology, resulting in more comprehensive CFH and a significantly greater percentage of participants completing genetic counseling and testing.
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Affiliation(s)
- Melissa K Frey
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America.
| | - Muhammad Danyal Ahsan
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Emily Webster
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Sarah R Levi
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Jesse T Brewer
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Jenny Lin
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Stephanie V Blank
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Icahn School of Medicine at Mount Sinai, United States of America
| | - Hannah Krinsky
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Corbyn Nchako
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Isabel Wolfe
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Charlene Thomas
- Population Health Sciences, Division of Biostatistics and Epidemiology, Weill Cornell Medicine, New York, NY, United States of America
| | - Paul Christos
- Population Health Sciences, Division of Biostatistics and Epidemiology, Weill Cornell Medicine, New York, NY, United States of America
| | - Evelyn Cantillo
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Eloise Chapman-Davis
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Kevin Holcomb
- Department of Obstetrics and Gynecology, Division of Gynecology Oncology, Weill Cornell Medicine, New York, NY, United States of America
| | - Ravi N Sharaf
- Division of Gastroenterology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States of America; Division of Epidemiology, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States of America
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4
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Meunier PY, Raynaud C, Guimaraes E, Gueyffier F, Letrilliart L. Barriers and Facilitators to the Use of Clinical Decision Support Systems in Primary Care: A Mixed-Methods Systematic Review. Ann Fam Med 2023; 21:57-69. [PMID: 36690490 PMCID: PMC9870646 DOI: 10.1370/afm.2908] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 09/08/2022] [Accepted: 10/10/2022] [Indexed: 01/24/2023] Open
Abstract
PURPOSE To identify and quantify the barriers and facilitators to the use of clinical decision support systems (CDSSs) by primary care professionals (PCPs). METHODS A mixed-methods systematic review was conducted using a sequential synthesis design. PubMed/MEDLINE, PsycInfo, Embase, CINAHL, and the Cochrane library were searched in July 2021. Studies that evaluated CDSSs providing recommendations to PCPs and intended for use during a consultation were included. We excluded CDSSs used only by patients, described as concepts or prototypes, used with simulated cases, and decision supports not considered as CDSSs. A framework synthesis was performed according to the HOT-fit framework (Human, Organizational, Technology, Net Benefits), then a quantitative synthesis evaluated the impact of the HOT-fit categories on CDSS use. RESULTS A total of 48 studies evaluating 45 CDSSs were included, and 186 main barriers or facilitators were identified. Qualitatively, barriers and facilitators were classified as human (eg, perceived usefulness), organizational (eg, disruption of usual workflow), and technological (eg, CDSS user-friendliness), with explanatory elements. The greatest barrier to using CDSSs was an increased workload. Quantitatively, the human and organizational factors had negative impacts on CDSS use, whereas the technological factor had a neutral impact and the net benefits dimension a positive impact. CONCLUSIONS Our findings emphasize the need for CDSS developers to better address human and organizational issues, in addition to technological challenges. We inferred core CDSS features covering these 3 factors, expected to improve their usability in primary care.
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Affiliation(s)
- Pierre-Yves Meunier
- Collège universitaire de médecine générale, Université Claude Bernard Lyon 1, Lyon, France
- Research on Healthcare Performance (RESHAPE), INSERM U1290, Université Claude Bernard Lyon 1, Lyon, France
| | - Camille Raynaud
- Collège universitaire de médecine générale, Université Claude Bernard Lyon 1, Lyon, France
| | - Emmanuelle Guimaraes
- Collège universitaire de médecine générale, Université Claude Bernard Lyon 1, Lyon, France
| | - François Gueyffier
- Laboratoire de biométrie et biologie évolutive, département biostatistiques et modélisation pour la santé et l'environnement, CNRS UMR5558, Université Claude Bernard Lyon 1, Lyon, France
- Fédération de Recherche Santé Lyon Est, PAM Santé Publique, Hospices Civils de Lyon, Lyon, France
| | - Laurent Letrilliart
- Collège universitaire de médecine générale, Université Claude Bernard Lyon 1, Lyon, France
- Research on Healthcare Performance (RESHAPE), INSERM U1290, Université Claude Bernard Lyon 1, Lyon, France
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5
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Miroševič Š, Klemenc-Ketiš Z, Peterlin B. Family history tools for primary care: A systematic review. Eur J Gen Pract 2022; 28:75-86. [PMID: 35510897 PMCID: PMC9090347 DOI: 10.1080/13814788.2022.2061457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Background Many medical family history (FH) tools are available for various settings. Although FH tools can be a powerful health screening tool in primary care (PC), they are currently underused. Objectives This review explores the FH tools currently available for PC and evaluates their clinical performance. Methods Five databases were systematically searched until May 2021. Identified tools were evaluated on the following criteria: time-to-complete, integration with electronic health record (EMR) systems, patient administration, risk-assessment ability, evidence-based management recommendations, analytical and clinical validity and clinical utility. Results We identified 26 PC FH tools. Analytical and clinical validity was poorly reported and agreement between FH and gold standard was commonly inadequately reported and assessed. Sensitivity was acceptable; specificity was found in half of the reviewed tools to be poor. Most reviewed tools showed a capacity to successfully identify individuals with increased risk of disease (6.2–84.6% of high and/or moderate or increased risk individuals). Conclusion Despite the potential of FH tools to improve risk stratification of patients in PC, clinical performance of current tools remains limited as well as their integration in EMR systems. Twenty-one FH tools are designed to be self-administered by patients.
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Affiliation(s)
- Špela Miroševič
- Department of Family Medicine, Medical Faculty Ljubljana, Ljubljana, Slovenia
| | - Zalika Klemenc-Ketiš
- Department of Family Medicine, Medical Faculty Ljubljana, Ljubljana, Slovenia.,Department of Family Medicine, Faculty of Medicine, University of Maribor, Maribor, Slovenia.,Community Health Centre Ljubljana, Ljubljana, Slovenia
| | - Borut Peterlin
- Clinical Institute for Medical Genetics, University Medical Centre Ljubljana, Ljubljana, Slovenia
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6
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Taber P, Ghani P, Schiffman JD, Kohlmann W, Hess R, Chidambaram V, Kawamoto K, Waller RG, Borbolla D, Del Fiol G, Weir C. Physicians' strategies for using family history data: having the data is not the same as using the data. JAMIA Open 2021; 3:378-385. [PMID: 34632321 PMCID: PMC7660959 DOI: 10.1093/jamiaopen/ooaa035] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 06/02/2020] [Indexed: 12/12/2022] Open
Abstract
Objective To identify needs in a clinical decision support tool development by exploring how primary care providers currently collect and use family health history (FHH). Design Survey questionnaires and semi-structured interviews were administered to a mix of primary and specialty care clinicians within the University of Utah Health system (40 surveys, 12 interviews). Results Three key themes emerged regarding providers' collection and use of FHH: (1) Strategies for collecting FHH vary by level of effort; (2) Documentation practices extend beyond the electronic health record's dedicated FHH module; and (3) Providers desire feedback from genetic services consultation and are uncertain how to refer patients to genetic services. Conclusion Study findings highlight the varying degrees of engagement that providers have with collecting FHH. Improving the integration of FHH into workflow, and providing decision support, as well as links and tools to help providers better utilize genetic counseling may improve patient care.
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Affiliation(s)
- Peter Taber
- VA Salt Lake City Health Care System, Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS 2.0), Salt Lake City, Utah, USA
| | - Parveen Ghani
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Joshua D Schiffman
- Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, USA.,Family Cancer Assessment Clinic, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Wendy Kohlmann
- Family Cancer Assessment Clinic, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA.,Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Rachel Hess
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA.,Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Valli Chidambaram
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Rosalie G Waller
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Damian Borbolla
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Charlene Weir
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
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7
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Li X, Kahn RM, Wing N, Zhou ZN, Lackner AI, Krinsky H, Badiner N, Fogla R, Wolfe I, Bergeron H, Nelson BB, Thomas C, Christos PJ, Sharaf RN, Cantillo E, Holcomb K, Chapman-Davis E, Frey MK. Leveraging Health Information Technology to Collect Family Cancer History: A Systematic Review and Meta-Analysis. JCO Clin Cancer Inform 2021; 5:775-788. [PMID: 34328789 PMCID: PMC8812651 DOI: 10.1200/cci.21.00004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Collection of family cancer histories (FCHs) can identify individuals at risk for familial cancer syndromes. The aim of this study is to evaluate the literature on existing strategies whereby providers use information technology to assemble FCH. METHODS A systematic search of online databases (Ovid MEDLINE, Cochrane, and Embase) between 1980 and 2020 was performed. Statistical heterogeneity was assessed through the chi-square test (ie, Cochrane Q test) and the inconsistency statistic (I2). A random-effects analysis was used to calculate the pooled proportions and means. RESULTS The comprehensive search produced 4,005 publications. Twenty-eight studies met inclusion criteria. Twenty-seven information technology tools were evaluated. Eighteen out of 28 studies were electronic surveys administered before visits (18, 64.3%). Five studies administered tablet surveys in offices (5, 17.8%). Four studies collected electronic survey via kiosk before visits (4, 14.3%), and one study used animated virtual counselor during visits (1, 3.6%). Among the studies that use an FCH tool, the pooled estimate of the overall completion rate was 86% (CI, 72% to 96%), 84% (CI, 65% to 97%) for electronic surveys before visits, 89% (CI, 0.74 to 0.98) for tablet surveys, and 85% (CI, 0.66 to 0.98) for surveys via kiosk. Mean time required for completion was 31.0 minutes (CI, 26.1 to 35.9), and the pooled estimate of proportions of participants referred to genetic testing was 12% (CI, 4% to 23%). CONCLUSION Our review found that electronic FCH collection can be completed successfully by patients in a time-efficient manner with high rates of satisfaction.
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Affiliation(s)
- Xuan Li
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Ryan M Kahn
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Noelani Wing
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Zhen Ni Zhou
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Andreas Ian Lackner
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Hannah Krinsky
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Nora Badiner
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Rhea Fogla
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Isabel Wolfe
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Hannah Bergeron
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Becky Baltich Nelson
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Charlene Thomas
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Paul J Christos
- Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY
| | - Ravi N Sharaf
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Evelyn Cantillo
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Kevin Holcomb
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Eloise Chapman-Davis
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
| | - Melissa K Frey
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, New York, NY
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8
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Leventer-Roberts M, Gofer I, Barak Corren Y, Reis BY, Balicer R. Constructing data-derived family histories using electronic health records from a single healthcare delivery system. Eur J Public Health 2021; 30:212-218. [PMID: 31550373 DOI: 10.1093/eurpub/ckz152] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND In order to examine the potential clinical value of integrating family history information directly from the electronic health records of patients' family members, the electronic health records of individuals in Clalit Health Services, the largest payer/provider in Israel, were linked with the records of their parents. METHODS We describe the results of a novel approach for creating data-derived family history information for 2 599 575 individuals, focusing on three chronic diseases: asthma, cardiovascular disease (CVD) and diabetes. RESULTS In our cohort, there were 256 598 patients with asthma, 55 309 patients with CVD and 66 324 patients with diabetes. Of the people with asthma, CVD or diabetes, the percentage that also had a family history of the same disease was 22.0%, 70.8% and 70.5%, respectively. CONCLUSIONS Linking individuals' health records with their data-derived family history has untapped potential for supporting diagnostic and clinical decision-making.
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Affiliation(s)
- Maya Leventer-Roberts
- Clalit Research Institute, Tel Aviv, Israel.,Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ilan Gofer
- Clalit Research Institute, Tel Aviv, Israel
| | - Yuval Barak Corren
- Predictive Medicine Group & Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.,Pediatrics Department, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Ben Y Reis
- Predictive Medicine Group & Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Ran Balicer
- Clalit Research Institute, Tel Aviv, Israel.,Public Health Department, Ben-Gurion University of the Negev, Israel
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9
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Abstract
In order to improve the youth mental health system, there is an international movement toward developing community-based service hubs that provide integrated, collaborative care to youth. However, the implementation of multisystem collaboration is complex and can be hampered by barriers. This paper presents a formative evaluation of the YouthCan IMPACT integrated youth services project based on the Consolidated Framework for Implementation Research (CFIR), to identify facilitators and barriers to successful implementation. Results highlight that previous positive working relationships along with collaborative investment of resources from partnering organizations are essential to implement an integrated youth service model. In addition, it is important that representative members of all key stakeholder groups, including staff, youth, and caregivers, be involved in the development and execution of the project to ensure effective implementation. Attention to the facilitators and barriers to implementation may help teams seeking to implement highly collaborative, integrated models of service delivery for youth in the community.
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10
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Effect of genetics clinical decision support tools on health-care providers’ decision making: a mixed-methods systematic review. Genet Med 2021; 23:593-602. [DOI: 10.1038/s41436-020-01045-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 11/12/2020] [Accepted: 11/13/2020] [Indexed: 02/05/2023] Open
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11
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Bajracharya AS, Crotty BH, Kowoloff HB, Safran C, Slack WV. Patient experience with family history tool: analysis of patients' experience sharing their family health history through patient-computer dialogue in a patient portal. J Am Med Inform Assoc 2020; 26:603-609. [PMID: 30946464 DOI: 10.1093/jamia/ocz008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 10/15/2018] [Accepted: 01/08/2019] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE The collection and use of a family health history are important for assessing the patient's risk of disease, but history taking is often impeded by practical barriers in the office. Provision for patient-computer dialogue, linked with the electronic health record, may enable patients to contribute their history while bypassing these barriers. We sought to assess the patient experience using such a tool. MATERIALS AND METHODS We linked the family history module of a computer-based medical history to the patient portal of a large academic health system. The interview consisted of 39 primary questions with a predetermined high test-retest reliability. Patients' results were structured and summarized, and available within their electronic health record. Patients optionally completed a survey about their experience. We inductively analyzed free-text responses collected between 2014 and 2016. RESULTS Among 97 781 patient portal users, 9562 patients accessed and 4223 patients completed the family medical history interview. Of these patients, 1451 completed our survey. Main themes that were identified included (1) patient empowerment, (2) anticipated value, (3) validity concerns, (4) privacy concerns, and (5) reflections on patient-computer dialogue. Patients also provided suggestions for the improvement of future family history tools. DISCUSSION Patients providing their family health information is an example of collaborative electronic work with clinicians and was seen as valuable by those who participated. Concerns related to contextual information and uncertainty need to be addressed. CONCLUSIONS Patient-computer dialogue to collect family medical history empowered patients and added perceived value and efficiency to the patient experience of care.
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Affiliation(s)
- Adarsha S Bajracharya
- Department of Medicine, University of Massachusetts Medical School, Worchester, Massachusetts, USA
| | - Bradley H Crotty
- Collaborative for Healthcare Delivery Science, Center for Advancing Population Science, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Hollis B Kowoloff
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Charles Safran
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Warner V Slack
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
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12
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Snir M, Nazareth S, Simmons E, Hayward L, Ashcraft K, Bristow SL, Esplin ED, Aradhya S. Democratizing genomics: Leveraging software to make genetics an integral part of routine care. AMERICAN JOURNAL OF MEDICAL GENETICS. PART C, SEMINARS IN MEDICAL GENETICS 2020; 187:14-27. [PMID: 33296144 DOI: 10.1002/ajmg.c.31866] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 11/16/2020] [Accepted: 11/17/2020] [Indexed: 12/25/2022]
Abstract
Genetic testing can provide definitive molecular diagnoses and guide clinical management decisions from preconception through adulthood. Innovative solutions for scaling clinical genomics services are necessary if they are to transition from a niche specialty to a routine part of patient care. The expertise of specialists, like genetic counselors and medical geneticists, has traditionally been relied upon to facilitate testing and follow-up, and while ideal, this approach is limited in its ability to integrate genetics into primary care. As individuals, payors, and providers increasingly realize the value of genetics in mainstream medicine, several implementation challenges need to be overcome. These include electronic health record integration, patient and provider education, tools to stay abreast of guidelines, and simplification of the test ordering process. Currently, no single platform offers a holistic view of genetic testing that streamlines the entire process across specialties that begins with identifying at-risk patients in mainstream care settings, providing pretest education, facilitating consent and test ordering, and following up as a "genetic companion" for ongoing management. We describe our vision for using software that includes clinical-grade chatbots and decision support tools, with direct access to genetic counselors and pharmacists within a modular, integrated, end-to-end testing journey.
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13
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Giang TT, Nguyen TP, Tran DH. Stratifying patients using fast multiple kernel learning framework: case studies of Alzheimer's disease and cancers. BMC Med Inform Decis Mak 2020; 20:108. [PMID: 32546157 PMCID: PMC7296686 DOI: 10.1186/s12911-020-01140-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Accepted: 05/28/2020] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Predictive patient stratification is greatly emerging, because it allows us to prospectively identify which patients will benefit from what interventions before their condition worsens. In the biomedical research, a number of stratification methods have been successfully applied and have assisted treatment process. Because of heterogeneity and complexity of medical data, it is very challenging to integrate them and make use of them in practical clinic. There are two major challenges of data integration. Firstly, since the biomedical data has a high number of dimensions, combining multiple data leads to the hard problem of vast dimensional space handling. The computation is enormously complex and time-consuming. Secondly, the disparity of different data types causes another critical problem in machine learning for biomedical data. It has a great need to develop an efficient machine learning framework to handle the challenges. METHODS In this paper, we propose a fast-multiple kernel learning framework, referred to as fMKL-DR, that optimise equations to calculate matrix chain multiplication and reduce dimensions in data space. We applied our framework to two case studies, Alzheimer's disease (AD) patient stratification and cancer patient stratification. We performed several comparative evaluations on various biomedical datasets. RESULTS In the case study of AD patients, we enhanced significantly the multiple-ROIs approach based on MRI image data. The method could successfully classify not only AD patients and non-AD patients but also different phases of AD patients with AUC close to 1. In the case study of cancer patients, the framework was applied to six types of cancers, i.e., glioblastoma multiforme cancer, ovarian cancer, lung cancer, breast cancer, kidney cancer, and liver cancer. We efficiently integrated gene expression, miRNA expression, and DNA methylation. The results showed that the classification model basing on integrated datasets was much more accurate than classification model basing on the single data type. CONCLUSIONS The results demonstrated that the fMKL-DR remarkably improves computational cost and accuracy for both AD patient and cancer patient stratification. We optimised the data integration, dimension reduction, and kernel fusion. Our framework has great potential for mining large-scale cohort data and aiding personalised prevention.
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Affiliation(s)
- Thanh-Trung Giang
- VNU University of Engineering and Technology, Hanoi, Vietnam.,TayBac University, Son La, Vietnam
| | - Thanh-Phuong Nguyen
- Life Sciences Research Unit, Belval, University of Luxembourg, Luxembourg City, Luxembourg. .,Megeno S.A., Belval, Esch-sur-Alzette, Luxembourg.
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14
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Primary care physician experiences utilizing a family health history tool with electronic health record-integrated clinical decision support: an implementation process assessment. J Community Genet 2020; 11:339-350. [PMID: 32020508 DOI: 10.1007/s12687-020-00454-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/23/2020] [Indexed: 10/25/2022] Open
Abstract
Family health history (FHH) screening plays a key role in disease risk identification and tailored disease prevention strategies. Primary care physicians (PCPs) are in a frontline position to provide personalized medicine recommendations identified through FHH screening; however, adoption of FHH screening tools has been slow and inconsistent in practice. Information is also lacking on PCP facilitators and barriers of utilizing family history tools with clinical decision support (CDS) embedded in the electronic health record (EHR). This study reports on PCPs' initial experiences with the Genetic and Wellness Assessment (GWA), a patient-administered FHH screening tool utilizing the EHR and CDS. Semi-structured interviews were conducted with 24 PCPs who use the GWA in a network of community-based practices. Four main themes regarding GWA implementation emerged: benefits to clinical care, challenges in practice, CDS-specific issues, and physician-recommended improvements. Sub-themes included value in improving patient access to genetic services, inadequate time to discuss GWA recommendations, lack of patient follow-through with recommendations, and alert fatigue. While PCPs valued the GWA's clinical utility, a number of challenges were identified in the administration and use of the GWA in practice. Based on participants' recommendations, iterative changes have been made to the GWA and workflow to increase efficiency, upgrade the CDS process, and provide additional education to PCPs and patients. Future studies are needed to assess a diverse sample of physicians' and patients' perspectives on the utility of FHH screening utilizing EHR-based genomics recommendations.
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15
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Read P, Yashar BM, Robinson L, Marvin M. Optimizing efficiency and skill utilization: Analysis of genetic counselors' attitudes regarding delegation in a clinical setting. J Genet Couns 2019; 29:67-77. [DOI: 10.1002/jgc4.1181] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 10/02/2019] [Accepted: 10/03/2019] [Indexed: 11/09/2022]
Affiliation(s)
- Parker Read
- Simmons Comprehensive Cancer Center UT Southwestern Medical Center Dallas TX USA
| | - Beverly M. Yashar
- Department of Human Genetics University of Michigan Ann Arbor MI USA
| | - Linda Robinson
- Simmons Comprehensive Cancer Center UT Southwestern Medical Center Dallas TX USA
| | - Monica Marvin
- Department of Human Genetics University of Michigan Ann Arbor MI USA
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16
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Bucheit L, Johansen Taber K, Ready K. Validation of a digital identification tool for individuals at risk for hereditary cancer syndromes. Hered Cancer Clin Pract 2019; 17:2. [PMID: 30651894 PMCID: PMC6330430 DOI: 10.1186/s13053-018-0099-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 11/15/2018] [Indexed: 01/05/2023] Open
Abstract
Background The number of individuals meeting criteria for genetic counseling and testing for hereditary cancer syndromes (HCS) is far less than the number that actually receive it. To facilitate identification of patients at risk for HCS, Counsyl developed a digital identification tool (digital ID tool) to match personal and family cancer history to National Comprehensive Cancer Network (NCCN) BRCA-related Hereditary Breast and Ovarian Cancer (HBOC), Lynch syndrome, and polyposis testing criteria in one-to-one, automated fashion. The purpose of this study was to validate the ability of the digital ID tool to accurately identify histories that do and do not meet NCCN testing criteria. Methods Third-party recorded three-generation pedigrees were retrospectively reviewed by a certified genetic counselor (CGC) to determine if independent events included in pedigree histories met NCCN guidelines, and were then sorted into groups: high risk events (meets criteria) and low risk events (does not meet criteria). Events were entered into the digital ID tool to determine the extent of its concordance with events sorted by CGC review. Statistical tests of accuracy were calculated at a 95% confidence interval (CI). Results One hundred ninety-seven pedigrees were reviewed consecutively representing 765 independent events for analysis across groups. 382/382 (100%) high risk events identified by the digital ID tool and 381/383 (99.47%) low risk events identified by the digital ID tool were concordant with CGC sorting. The digital ID tool had a sensitivity of 100% (99.04–100% CI) and specificity of 99.48% (98.13–99.94% CI). The overall accuracy of the digital ID tool was estimated to be 99.74% (99.06–99.97% CI), reflecting the rate at which the digital ID tool reached the same conclusion as that of CGC review of pedigree events for the recommendation of genetic testing for individuals at risk for HCS. Conclusions The digital ID tool accurately matches NCCN criteria in one-to-one fashion to identify at-risk individuals for HCS and may be useful in clinical practice, specifically for BRCA-related HBOC and Lynch Syndrome. Electronic supplementary material The online version of this article (10.1186/s13053-018-0099-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Leslie Bucheit
- Counsyl, 180 Kimball Way, South San Francisco, CA 98040 USA
| | | | - Kaylene Ready
- Counsyl, 180 Kimball Way, South San Francisco, CA 98040 USA
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17
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Keyworth C, Hart J, Armitage CJ, Tully MP. What maximizes the effectiveness and implementation of technology-based interventions to support healthcare professional practice? A systematic literature review. BMC Med Inform Decis Mak 2018; 18:93. [PMID: 30404638 PMCID: PMC6223001 DOI: 10.1186/s12911-018-0661-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 09/27/2018] [Indexed: 02/02/2023] Open
Abstract
Background Technological support may be crucial in optimizing healthcare professional practice and improving patient outcomes. A focus on electronic health records has left other technological supports relatively neglected. Additionally, there has been no comparison between different types of technology-based interventions, and the importance of delivery setting on the implementation of technology-based interventions to change professional practice. Consequently, there is a need to synthesise and examine intervention characteristics using a methodology suited to identifying important features of effective interventions, and the barriers and facilitators to implementation. Three aims were addressed: to identify interventions with a technological component that are successful at changing professional practice, to determine if and how such interventions are theory-based, and to examine barriers and facilitators to successful implementation. Methods A literature review informed by realist review methods was conducted involving a systematic search of studies reporting either: (1) behavior change interventions that included technology to support professional practice change; or (2) barriers and facilitators to implementation of technological interventions. Extracted data was quantitative and qualitative, and included setting, target professionals, and use of Behaviour Change Techniques (BCTs). The primary outcome was a change in professional practice. A thematic analysis was conducted on studies reporting barriers and facilitators of implementation. Results Sixty-nine studies met the inclusion criteria; 48 (27 randomized controlled trials) reported behavior change interventions and 21 reported practicalities of implementation. The most successful technological intervention was decision support providing healthcare professionals with knowledge and/or person-specific information to assist with patient management. Successful technologies were more likely to operationalise BCTs, particularly “instruction on how to perform the behavior”. Facilitators of implementation included aligning studies with organisational initiatives, ensuring senior peer endorsement, and integration into clinical workload. Barriers included organisational challenges, and design, content and technical issues of technology-based interventions. Conclusions Technological interventions must focus on providing decision support for clinical practice using recognized behavior change techniques. Interventions must consider organizational context, clinical workload, and have clearly defined benefits for improving practice and patient outcomes. Electronic supplementary material The online version of this article (10.1186/s12911-018-0661-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- C Keyworth
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Coupland 1 Building, Oxford Road, Manchester, M13 9PL, UK.
| | - J Hart
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Coupland 1 Building, Oxford Road, Manchester, M13 9PL, UK.,Division of Medical Education, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Oxford Road, Manchester, M13 9PL, UK
| | - C J Armitage
- Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Coupland 1 Building, Oxford Road, Manchester, M13 9PL, UK.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9PL, UK.,NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester, UK
| | - M P Tully
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Stopford Building, Oxford Road, Manchester, M13 9PL, UK
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18
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Cleophat JE, Nabi H, Pelletier S, Bouchard K, Dorval M. What characterizes cancer family history collection tools? A critical literature review. ACTA ACUST UNITED AC 2018; 25:e335-e350. [PMID: 30111980 DOI: 10.3747/co.25.4042] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background Many tools have been developed for the standardized collection of cancer family history (fh). However, it remains unclear which tools have the potential to help health professionals overcome traditional barriers to collecting such histories. In this review, we describe the characteristics, validation process, and performance of existing tools and appraise the extent to which those tools can support health professionals in identifying and managing at-risk individuals. Methods Studies were identified through searches of the medline, embase, and Cochrane central databases from October 2015 to September 2016. Articles were included if they described a cancer fh collection tool, its use, and its validation process. Results Based on seventy-nine articles published between February 1978 and September 2016, 62 tools were identified. Most of the tools were paper-based and designed to be self-administered by lay individuals. One quarter of the tools could automatically produce pedigrees, provide cancer-risk assessment, and deliver evidence-based recommendations. One third of the tools were validated against a standard reference for collected fh quality and cancer-risk assessment. Only 3 tools were integrated into an electronic health records system. Conclusions In the present review, we found no tool with characteristics that might make it an efficient clinical support for health care providers in cancer-risk identification and management. Adequately validated tools that are connected to electronic health records are needed to encourage the systematic identification of individuals at increased risk of cancer.
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Affiliation(s)
- J E Cleophat
- Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC.,Université Laval, Faculté de pharmacie, Quebec City, QC.,Centre de recherche sur le cancer, Quebec City, QC
| | - H Nabi
- Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC.,Centre de recherche sur le cancer, Quebec City, QC.,inserm, U1018, Centre de recherche en épidémiologie et santé des populations, Villejuif, France
| | - S Pelletier
- Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC.,Centre de recherche sur le cancer, Quebec City, QC
| | - K Bouchard
- Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC.,Centre de recherche sur le cancer, Quebec City, QC
| | - M Dorval
- Centre de recherche du chu de Québec, Axe Oncologie, Quebec City, QC.,Université Laval, Faculté de pharmacie, Quebec City, QC.,Centre de recherche sur le cancer, Quebec City, QC.,Centre de recherche du cisss Chaudière-Appalaches, Lévis, QC
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19
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Welch BM, Wiley K, Pflieger L, Achiangia R, Baker K, Hughes-Halbert C, Morrison H, Schiffman J, Doerr M. Review and Comparison of Electronic Patient-Facing Family Health History Tools. J Genet Couns 2018; 27:381-391. [PMID: 29512060 PMCID: PMC5861014 DOI: 10.1007/s10897-018-0235-7] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 02/05/2018] [Indexed: 01/23/2023]
Abstract
Family health history (FHx) is one of the most important pieces of information available to help genetic counselors and other clinicians identify risk and prevent disease. Unfortunately, the collection of FHx from patients is often too time consuming to be done during a clinical visit. Fortunately, there are many electronic FHx tools designed to help patients gather and organize their own FHx information prior to a clinic visit. We conducted a review and analysis of electronic FHx tools to better understand what tools are available, to compare and contrast to each other, to highlight features of various tools, and to provide a foundation for future evaluation and comparisons across FHx tools. Through our analysis, we included and abstracted 17 patient-facing electronic FHx tools and explored these tools around four axes: organization information, family history collection and display, clinical data collected, and clinical workflow integration. We found a large number of differences among FHx tools, with no two the same. This paper provides a useful review for health care providers, researchers, and patient advocates interested in understanding the differences among the available patient-facing electronic FHx tools.
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Affiliation(s)
- Brandon M Welch
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
- Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.
- ItRunsInMyFamily.com, Inc., Charleston, SC, USA.
| | - Kevin Wiley
- Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Lance Pflieger
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA
| | - Rosaline Achiangia
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Karen Baker
- Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA
| | - Chanita Hughes-Halbert
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | | | - Joshua Schiffman
- ItRunsInMyFamily.com, Inc., Charleston, SC, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
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20
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Gordon ES, Babu D, Laney DA. The future is now: Technology's impact on the practice of genetic counseling. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2018. [DOI: 10.1002/ajmg.c.31599] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
| | | | - Dawn A. Laney
- Department of Human GeneticsEmory School of MedicineDecatur Georgia
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21
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Niendorf KB, Geller MA, Vogel RI, Church TR, Leininger A, Bakke A, Madoff RD. A model for patient-direct screening and referral for familial cancer risk. Fam Cancer 2017; 15:707-16. [PMID: 27350384 DOI: 10.1007/s10689-016-9912-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Patients at increased familial risk of cancer are sub-optimally identified and referred for genetic counseling. We describe a systematic model for information collection, screening and referral for hereditary cancer risk. Individuals from three different clinical and research populations were screened for hereditary cancer risk using a two-tier process: a 7-item screener followed by review of family history by a genetic counselor and application of published criteria. A total of 869 subjects participated in the study; 769 in this high risk population had increased familial cancer risk based on the screening questionnaire. Of these eligible participants, 500 (65.0 %) provided family histories and 332 (66.4 %) of these were found to be at high risk of a hereditary cancer syndrome, 102 (20.4 %) at moderate familial cancer risk, and 66 (13.2 %) at average risk. Three months following receipt of the risk result letter, nearly all respondents found the process at least somewhat helpful (98.4 %). All participants identified as high-risk were mailed a letter recommending genetic counseling and were provided appointment tools. After 1 year, only 13 (7.3 %) of 179 high risk respondents reported pursuit of recommended genetic counseling. Participants were willing to provide family history information for the purposes of risk assessment; however, few patients pursued recommended genetic services. This suggests that cancer family history registries are feasible and viable but that further research is needed to increase the uptake of genetic counseling.
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Affiliation(s)
- Kristin B Niendorf
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, MMC 450, Minneapolis, MN, 55455, USA. .,Division of Colon and Rectal Surgery, Department of Surgery, University of Minnesota, Minneapolis, MN, USA.
| | - Melissa A Geller
- Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Women's Health, University of Minnesota, Minneapolis, MN, USA
| | - Rachel Isaksson Vogel
- Masonic Cancer Center, University of Minnesota, 420 Delaware Street SE, MMC 450, Minneapolis, MN, 55455, USA
| | - Timothy R Church
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | | | - Angela Bakke
- Maternal-Fetal Medicine Center, Burnsville, MN, USA
| | - Robert D Madoff
- Division of Colon and Rectal Surgery, Department of Surgery, University of Minnesota, Minneapolis, MN, USA
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22
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Saul RA, Trotter T, Sease K, Tarini B. Survey of family history taking and genetic testing in pediatric practice. J Community Genet 2017; 8:109-115. [PMID: 28064391 DOI: 10.1007/s12687-016-0291-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 12/26/2016] [Indexed: 12/12/2022] Open
Abstract
Family health history collection and genetic testing are core elements for the successful translation of genomics into primary care practice. Yet, little is known about how pediatric providers implement these elements in practice. We surveyed the membership of the American Academy of Pediatrics regarding family health history (FHH) collection and genetic testing in the primary care setting. Three hundred forty-nine (349) responses were analyzed with the initial response rate of 43.3%. Four principal findings were noted-(1) family health history is still recognized as a critical part of the medical evaluation; (2) perceived obstacles for FHH are time in obtaining the FHH and concerns about the family's knowledge of their FHH; (3) a 3-generation family history is out of the scope of routine care and alternate methods should be considered; (4) most primary care providers (PCPs) do not feel comfortable ordering, interpreting, and counseling regarding current genetic testing. Expanded genetic/genomic education at multiple levels (undergraduate medical education, graduate medical education, and maintenance of certification) is clearly indicated to allow PCPs to integrate these vital elements into a current evaluation (acute care or health maintenance) in the primary care setting.
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Affiliation(s)
- Robert A Saul
- Center for Pediatric Medicine, Children's Hospital, Greenville Health System, 20 Medical Ridge Drive, Greenville, SC, 29605, USA.
| | | | - Kerry Sease
- Center for Pediatric Medicine, Children's Hospital, Greenville Health System, 20 Medical Ridge Drive, Greenville, SC, 29605, USA
| | - Beth Tarini
- Stead Family Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IL, USA
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23
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Carroll JC, Campbell-Scherer D, Permaul JA, Myers J, Manca DP, Meaney C, Moineddin R, Grunfeld E. Assessing family history of chronic disease in primary care: Prevalence, documentation, and appropriate screening. CANADIAN FAMILY PHYSICIAN MEDECIN DE FAMILLE CANADIEN 2017; 63:e58-e67. [PMID: 28115461 PMCID: PMC5257240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
OBJECTIVE To assess the proportion of primary care patients who report a family history (FH) of type 2 diabetes, coronary artery disease, breast cancer, or colorectal cancer (CRC); assess concordance of FH information derived from the electronic medical record (EMR) compared with patient-completed health questionnaires; and assess whether appropriate screening was informed by risk based solely on FH. DESIGN Data from the BETTER (Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care) trial were used. Patients were mailed questionnaires. Baseline FH and screening data were obtained for enrolled patients from the EMR and health questionnaires. SETTING Ontario and Alberta. PARTICIPANTS Randomly selected patients from 8 family practices. MAIN OUTCOME MEASURES Agreement on FH between the EMR and questionnaire was determined; logistic regression was used to assess significant predictors of screening. RESULTS In total, 775 of 789 (98%) patients completed the health questionnaire. The mean age of participants was 52.5 years and 72% were female. A minimum of 12% of patients (range 12% to 36%) had a reported FH of 1 of 4 chronic diseases. Among patients with positive FH, the following proportions of patients had that FH recorded in the EMR compared with the questionnaire: diabetes, 24% in the EMR versus 36% on the questionnaire, κ = 0.466; coronary artery disease, 35% in the EMR versus 22% on the questionnaire, κ = 0.225; breast cancer, 21% in the EMR versus 22% on the questionnaire, κ = 0.241; and CRC, 12% in the EMR versus 14% on the questionnaire, κ = 0.510. There was moderate agreement for diabetes and CRC. The presence of FH was a significant predictor of CRC screening (odds ratio 1.9, 95% CI 1.1 to 3.1). CONCLUSION A moderate prevalence of FH was found for 4 conditions for which screening recommendations vary with risk based on FH. Having patients self-complete an FH was thought to be feasible; however, questions about FH accuracy and completeness from both self-report and EMR remain. Work is needed to determine how to facilitate the adoption of FH tools into practice as well as strategies linking familial risk to appropriate screening.Trial registration number ISRCTN07170460 (ISRCTN Registry).
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Affiliation(s)
- June C Carroll
- Professor and Sydney G. Frankfort Chair in the Department of Family and Community Medicine of the Sinai Health System at the University of Toronto in Ontario.
| | - Denise Campbell-Scherer
- Associate Professor in the Department of Family Medicine at the University of Alberta in Edmonton
| | - Joanne A Permaul
- Research associate in the Ray D. Wolfe Department of Family Medicine in the Sinai Health System
| | - Jesse Myers
- Second-year family medicine resident at Women's College Hospital at the University of Toronto
| | - Donna P Manca
- Director of Research in the Department of Family Medicine Research Program at the University of Alberta
| | - Christopher Meaney
- Biostatistician in the Department of Family and Community Medicine at the University of Toronto
| | - Rahim Moineddin
- Biostatistician in the Department of Family and Community Medicine at the University of Toronto
| | - Eva Grunfeld
- Giblon Professor and Vice Chair of Research in the Department of Family and Community Medicine at the University of Toronto and Director of Knowledge Translation Research in the Health Services Research Program at the Ontario Institute for Cancer Research
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24
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Sellers SL, Moss ME, Calzone K, Abdallah KE, Jenkins JF, Bonham VL. Nurses' Use of Race in Clinical Decision Making. J Nurs Scholarsh 2016; 48:577-586. [PMID: 27676232 DOI: 10.1111/jnu.12251] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/02/2016] [Indexed: 11/30/2022]
Abstract
PURPOSE To examine nurses' self-reported use of race in clinical evaluation. DESIGN This cross-sectional study analyzed data collected from three separate studies using the Genetics and Genomics in Nursing Practice Survey, which includes items about use of race and genomic information in nursing practice. The Racial Attributes in Clinical Evaluation (RACE) scale was used to measure explicit clinical use of race among nurses from across the United States. METHODS Multivariate regression analysis was used to examine associations between RACE score and individual-level characteristics and beliefs in 5,733 registered nurses. FINDINGS Analysis revealed significant relationships between RACE score and nurses' race and ethnicity, educational level, and views on the clinical importance of patient demographic characteristics. Asian nurses reported RACE scores 1.41 points higher than White nurses (p < .001), and Black nurses reported RACE scores 0.55 points higher than White nurses (p < .05). Compared to diploma-level nurses, the baccalaureate-level nurses reported 0.69 points higher RACE scores (p < .05), master's-level nurses reported 1.63 points higher RACE scores (p < .001), and doctorate-level nurses reported 1.77 points higher RACE scores (p < .01). In terms of clinical importance of patient characteristics, patient race and ethnicity corresponded to a 0.54-point increase in RACE score (p < .001), patient genes to a 0.21-point increase in RACE score (p < .001), patient family history to a 0.15-point increase in RACE score (p < .01), and patient age to a 0.19-point increase in RACE score (p < .001). CONCLUSIONS Higher reported use of race among minority nurses may be due, in part, to differential levels of racial self-awareness. A relatively linear positive relationship between level of nursing degree nursing education and use of race suggests that a stronger foundation of knowledge about genetic ancestry, population genetics and the concept "race" and genetic ancestry may increase in clinical decision making could allow nurses to more appropriately use of race in clinical care. Integrating patient demographic characteristics into clinical decisions is an important component of nursing practice. CLINICAL RELEVANCE Registered nurses provide care for diverse racial and ethnic patient populations and stand on the front line of clinical care, making them essential for reducing racial and ethnic disparities in healthcare delivery. Exploring registered nurses' individual-level characteristics and clinical use of race may provide a more comprehensive understanding of specific training needs and inform nursing education and practice.
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Affiliation(s)
- Sherrill L Sellers
- *Associate Dean for Undergraduate Education and Professor, Department of Family Studies and Social Work, Miami University, Oxford, OH, USA.
| | - Melissa E Moss
- *Postbaccalaureate Intramural Research Training Award (IRTA) Fellow, Health Disparities Unit, Social and Behavioral Research Branch, Division of Intramural Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kathleen Calzone
- Senior Nurse Specialist, Research, National Cancer Institute, Center for Cancer Research, Genetics Branch, National Institutes of Health, Bethesda, MD, USA
| | - Khadijah E Abdallah
- Research Analyst, Health Disparities Unit, Social and Behavioral Research Branch, Division of Intramural Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jean F Jenkins
- Clinical Advisor, Office of the Director, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Vence L Bonham
- Associate Investigator, Health Disparities Unit, Social and Behavioral Research Branch, Division of Intramural Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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25
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Lowery JT, Ahnen DJ, Schroy PC, Hampel H, Baxter N, Boland CR, Burt RW, Butterly L, Doerr M, Doroshenk M, Feero WG, Henrikson N, Ladabaum U, Lieberman D, McFarland EG, Peterson SK, Raymond M, Samadder NJ, Syngal S, Weber TK, Zauber AG, Smith R. Understanding the contribution of family history to colorectal cancer risk and its clinical implications: A state-of-the-science review. Cancer 2016; 122:2633-45. [PMID: 27258162 PMCID: PMC5575812 DOI: 10.1002/cncr.30080] [Citation(s) in RCA: 117] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2015] [Revised: 01/08/2016] [Accepted: 01/15/2016] [Indexed: 12/14/2022]
Abstract
Persons with a family history (FH) of colorectal cancer (CRC) or adenomas that are not due to known hereditary syndromes have an increased risk for CRC. An understanding of these risks, screening recommendations, and screening behaviors can inform strategies for reducing the CRC burden in these families. A comprehensive review of the literature published within the past 10 years has been performed to assess what is known about cancer risk, screening guidelines, adherence and barriers to screening, and effective interventions in persons with an FH of CRC and to identify FH tools used to identify these individuals and inform care. Existing data show that having 1 affected first-degree relative (FDR) increases the CRC risk 2-fold, and the risk increases with multiple affected FDRs and a younger age at diagnosis. There is variability in screening recommendations across consensus guidelines. Screening adherence is <50% and is lower in persons under the age of 50 years. A provider's recommendation, multiple affected relatives, and family encouragement facilitate screening; insufficient collection of FH, low knowledge of guidelines, and poor family communication are important barriers. Effective interventions incorporate strategies for overcoming barriers, but these have not been broadly tested in clinical settings. Four strategies for reducing CRC in persons with familial risk are suggested: 1) improving the collection and utilization of the FH of cancer, 2) establishing a consensus for screening guidelines by FH, 3) enhancing provider-patient knowledge of guidelines and communication about CRC risk, and 4) encouraging survivors to promote screening within their families and partnering with existing screening programs to expand their reach to high-risk groups. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2633-2645. © 2016 American Cancer Society.
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Affiliation(s)
- Jan T Lowery
- Colorado School of Public Health, Aurora, Colorado
| | - Dennis J Ahnen
- School of Medicine and Gastroenterology of the Rockies, University of Colorado, Boulder, Colorado
| | - Paul C Schroy
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Heather Hampel
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio
| | | | | | - Randall W Burt
- Huntsman Cancer Institute, University of Utah Health Care, Salt Lake City, Utah
| | - Lynn Butterly
- Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire
| | | | | | - W Gregory Feero
- Maine Dartmouth Family Medicine Residency Program, Augusta, Maine
| | | | - Uri Ladabaum
- Stanford University School of Medicine, Stanford, California
| | | | | | - Susan K Peterson
- The University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | - N Jewel Samadder
- Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
| | | | | | - Ann G Zauber
- Memorial Sloan Kettering Cancer Center, New York, New York
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26
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SHAHMORADI L, FARZANEHNEJAD AR, ARJI G. Guideline-based Clinical Decision Support Systems as an Inseparable Tool for Better Cancer Care Management. IRANIAN JOURNAL OF PUBLIC HEALTH 2016; 45:962-3. [PMID: 27517010 PMCID: PMC4980358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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27
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Orlando LA, Wu RR, Myers RA, Buchanan AH, Henrich VC, Hauser ER, Ginsburg GS. Clinical utility of a Web-enabled risk-assessment and clinical decision support program. Genet Med 2016; 18:1020-8. [DOI: 10.1038/gim.2015.210] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Accepted: 12/09/2015] [Indexed: 12/13/2022] Open
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28
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Baumgart LA, Postula KJV, Knaus WA. Initial clinical validation of Health Heritage, a patient-facing tool for personal and family history collection and cancer risk assessment. Fam Cancer 2015; 15:331-9. [DOI: 10.1007/s10689-015-9863-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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29
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Hergenroeder AC, Wiemann CM, Cohen MB. Current Issues in Transitioning from Pediatric to Adult-Based Care for Youth with Chronic Health Care Needs. J Pediatr 2015; 167:1196-201. [PMID: 26340879 DOI: 10.1016/j.jpeds.2015.08.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 07/13/2015] [Accepted: 08/03/2015] [Indexed: 10/23/2022]
Abstract
For over 25 years, with medical advances increasing the lifespan of YYASHCN, we have been aware of the need to improve health care transition to adult-based care services. Barriers to health care transition have been identified and in a number of settings, recognition of the problem and preliminary success has been achieved for pilot programs. Evidence-based solutions to improve health care transition for YYASHCN are needed. There are barriers at the patient, family, pediatric, and adult provider, and insurance system levels that must be overcome.
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Affiliation(s)
| | | | - Mitchell B Cohen
- University of Alabama at Birmingham Children's of Alabama, Birmingham, AL
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30
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Wiemann CM, Hergenroeder AC, Bartley KA, Sanchez-Fournier B, Hilliard ME, Warren LJ, Graham SC. Integrating an EMR-based Transition Planning Tool for CYSHCN at a Children's Hospital: A Quality Improvement Project to Increase Provider Use and Satisfaction. J Pediatr Nurs 2015; 30:776-87. [PMID: 26209173 PMCID: PMC4944386 DOI: 10.1016/j.pedn.2015.05.024] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 05/28/2015] [Accepted: 05/29/2015] [Indexed: 11/24/2022]
Abstract
An electronic medical record (EMR)-based transition planning tool (TPT) designed to facilitate transition from pediatric to adult-based health care for youth (16-25 years) with special health care needs was introduced at a large children's hospital. Activities to increase provider use were implemented in five plan-do-study-act cycles. Overall, 22 of 25 (88%) consenting providers in four pediatric subspecialty services used the TPT during 303 patient encounters, with nurses and case-managers the top users and physicians the least likely users. Use was highest with intensive technical assistance and following the introduction of an upgraded tool. Provider satisfaction with the TPT and self-reported transition planning activities notably increased across the PDSA cycles.
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Affiliation(s)
| | | | - Krystle A Bartley
- Center for Clinical Effectiveness, Baylor College of Medicine, Houston, TX
| | | | | | | | - Sarah C Graham
- Department of Pediatrics, Baylor College of Medicine, Houston, TX
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31
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Patel R, Green W, Shahzad MW, Larkin C. Use of Mobile Clinical Decision Support Software by Junior Doctors at a UK Teaching Hospital: Identification and Evaluation of Barriers to Engagement. JMIR Mhealth Uhealth 2015; 3:e80. [PMID: 26272411 PMCID: PMC4705011 DOI: 10.2196/mhealth.4388] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2015] [Revised: 06/04/2015] [Accepted: 06/19/2015] [Indexed: 01/20/2023] Open
Abstract
Background Clinical decision support (CDS) tools improve clinical diagnostic decision making and patient safety. The availability of CDS to health care professionals has grown in line with the increased prevalence of apps and smart mobile devices. Despite these benefits, patients may have safety concerns about the use of mobile devices around medical equipment. Objective This research explored the engagement of junior doctors (JDs) with CDS and the perceptions of patients about their use. There were three objectives for this research: (1) to measure the actual usage of CDS tools on mobile devices (mCDS) by JDs, (2) to explore the perceptions of JDs about the drivers and barriers to using mCDS, and (3) to explore the perceptions of patients about the use of mCDS. Methods This study used a mixed-methods approach to study the engagement of JDs with CDS accessed through mobile devices. Usage data were collected on the number of interactions by JDs with mCDS. The perceived drivers and barriers for JDs to using CDS were then explored by interviews. Finally, these findings were contrasted with the perception of patients about the use of mCDS by JDs. Results Nine of the 16 JDs made a total of 142 recorded interactions with the mCDS over a 4-month period. Only 27 of the 114 interactions (24%) that could be categorized as on-shift or off-shift occurred on-shift. Eight individual, institutional, and cultural barriers to engagement emerged from interviews with the user group. In contrast to reported cautions and concerns about the impact of clinicians’ use of mobile phone on patient health and safety, patients had positive perceptions about the use of mCDS. Conclusions Patients reported positive perceptions toward mCDS. The usage of mCDS to support clinical decision making was considered to be positive as part of everyday clinical practice. The degree of engagement was found to be limited due to a number of individual, institutional, and cultural barriers. The majority of mCDS engagement occurred outside of the workplace. Further research is required to verify these findings and assess their implications for future policy and practice.
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Affiliation(s)
- Rakesh Patel
- University of Leicester, Department of Medical & Social Care Education, Leicester, United Kingdom.
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32
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Ngeow J, Eng C. Whole-genome sequencing: not yet making the clinical grade. Per Med 2014; 11:471-475. [PMID: 29758773 DOI: 10.2217/pme.14.32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Affiliation(s)
- Joanne Ngeow
- Division of Medical Oncology, National Cancer Centre, Singapore.,Oncology Academic Program, Duke-NUS Graduate Medical School, Singapore.,Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, OH 44195, USA
| | - Charis Eng
- Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, OH 44195, USA.,Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, OH 44195, USA.,Taussig Cancer Institute, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, OH 44195, USA.,Stanley Shalom Zielony Institute of Nursing Excellence, Cleveland Clinic, 9500 Euclid Avenue, NE-50, Cleveland, OH 44195, USA.,Department of Genetics & CASE Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
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