Special Issue "Biobanking and EHR/EMR"

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A special issue of Journal of Personalized Medicine (ISSN 2075-4426).

Deadline for manuscript submissions: closed (31 January 2015)

Special Issue Editor

Guest Editor
Dr. Lori A. Orlando

Duke Center for Personalized Medicine & Duke Institute for Genome Sciences & Policy, 3475 Erwin Road, Wallace Clinic Ste 204, Durham, NC 27705, USA
Website | E-Mail
Interests: implementation research; primary care; decision modeling; cost-effectiveness; family health history; family history; health services research

Special Issue Information

Dear Colleagues,

This special issue is a call for papers about less commonly published aspects of Biobanking with a focus on electronic medical record linked Biobanks. These include study design and management, ethical considerations and potential solutions, and best practices in information technology tools for Biobank management. Retrospective reviews of well established biobanks, case studies, and implementation research papers all lend themselves well to this topic. Other topics along these lines are also welcome.

Dr. Lori A. Orlando
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 500 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.


Published Papers (6 papers)

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Research

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Open AccessArticle Prioritizing Approaches to Engage Community Members and Build Trust in Biobanks: A Survey of Attitudes and Opinions of Adults within Outpatient Practices at the University of Maryland
J. Pers. Med. 2015, 5(3), 264-279; doi:10.3390/jpm5030264
Received: 13 May 2015 / Revised: 4 July 2015 / Accepted: 8 July 2015 / Published: 28 July 2015
Cited by 2 | PDF Full-text (706 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Background: Achieving high participation of communities representative of all sub-populations is needed in order to ensure broad applicability of biobank study findings. This study aimed to understand potentially mutable attitudes and opinions commonly correlated with biobank participation in order to inform approaches
[...] Read more.
Background: Achieving high participation of communities representative of all sub-populations is needed in order to ensure broad applicability of biobank study findings. This study aimed to understand potentially mutable attitudes and opinions commonly correlated with biobank participation in order to inform approaches to promote participation in biobanks. Methods: Adults from two University of Maryland (UMD) Faculty Physicians, Inc. outpatient practices were invited to watch a video and complete a survey about a new biobank initiative. We used: Chi-square to assess the relationship between willingness to join the biobank and participant characteristics, other potentially mutable attitudes and opinions, and trust in the UMD. We also used t-test to assess the relationship with trust in medical research. We also prioritize proposed actions to improve attitudes and opinions about joining biobanks according to perceived responsiveness. Results: 169 participants completed the study, 51% of whom indicated a willingness to join the biobank. Willingness to join the biobank was not associated with age, gender, race, or education but was associated with respondent comfort sharing samples and clinical information, concerns related to confidentiality, potential for misuse of information, trust in UMD, and perceived health benefit. In ranked order, potential actions we surveyed that might alleviate some of these concerns include: increase chances to learn more about the biobank, increase opportunities to be updated, striving to put community concerns first, including involving community members as leaders of biobank research, and involving community members in decision making. Conclusions: This study identified several attitudes and opinions that influence decisions to join a biobank, including many concerns that could potentially be addressed by engaging community members. We also demonstrate our method of prioritizing ways to improve attitudes and opinions about joining a biobank according to perceived responsiveness. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)
Open AccessArticle Phenotype-Driven Plasma Biobanking Strategies and Methods
J. Pers. Med. 2015, 5(2), 140-152; doi:10.3390/jpm5020140
Received: 31 January 2015 / Accepted: 5 May 2015 / Published: 14 May 2015
Cited by 2 | PDF Full-text (721 KB) | HTML Full-text | XML Full-text
Abstract
Biobank development and integration with clinical data from electronic medical record (EMR) databases have enabled recent strides in genomic research and personalized medicine. BioVU, Vanderbilt’s DNA biorepository linked to de-identified clinical EMRs, has proven fruitful in its capacity to extensively appeal to numerous
[...] Read more.
Biobank development and integration with clinical data from electronic medical record (EMR) databases have enabled recent strides in genomic research and personalized medicine. BioVU, Vanderbilt’s DNA biorepository linked to de-identified clinical EMRs, has proven fruitful in its capacity to extensively appeal to numerous areas of biomedical and clinical research, supporting the discovery of genotype-phenotype interactions. Expanding on experiences in BioVU creation and development, we have recently embarked on a parallel effort to collect plasma in addition to DNA from blood specimens leftover after routine clinical testing at Vanderbilt. This initiative offers expanded utility of BioVU by combining proteomic and metabolomic approaches with genomics and/or clinical outcomes, widening the breadth for potential research and subsequent future impact on clinical care. Here, we describe the considerations and components involved in implementing a plasma biobank program from a feasibility assessment through pilot sample collection. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)
Open AccessArticle Public Trust in Health Information Sharing: Implications for Biobanking and Electronic Health Record Systems
J. Pers. Med. 2015, 5(1), 3-21; doi:10.3390/jpm5010003
Received: 25 November 2014 / Revised: 19 December 2014 / Accepted: 7 January 2015 / Published: 3 February 2015
Cited by 3 | PDF Full-text (593 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Biobanks are made all the more valuable when the biological samples they hold can be linked to health information collected in research, electronic health records, or public health practice. Public trust in such systems that share health information for research and health care
[...] Read more.
Biobanks are made all the more valuable when the biological samples they hold can be linked to health information collected in research, electronic health records, or public health practice. Public trust in such systems that share health information for research and health care practice is understudied. Our research examines characteristics of the general public that predict trust in a health system that includes researchers, health care providers, insurance companies and public health departments. We created a 119-item survey of predictors and attributes of system trust and fielded it using Amazon’s MTurk system (n = 447). We found that seeing one’s primary care provider, having a favorable view of data sharing and believing that data sharing will improve the quality of health care, as well as psychosocial factors (altruism and generalized trust) were positively and significantly associated with system trust. As expected, privacy concern, but counterintuitively, knowledge about health information sharing were negatively associated with system trust. We conclude that, in order to assure the public’s trust, policy makers charged with setting best practices for governance of biobanks and access to electronic health records should leverage critical access points to engage a diverse public in joint decision making. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)

Review

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Open AccessReview Linking a Population Biobank with National Health Registries—The Estonian Experience
J. Pers. Med. 2015, 5(2), 96-106; doi:10.3390/jpm5020096
Received: 3 February 2015 / Revised: 1 April 2015 / Accepted: 8 April 2015 / Published: 16 April 2015
Cited by 2 | PDF Full-text (705 KB) | HTML Full-text | XML Full-text
Abstract
The Estonian population-based biobank, with 52,000 participants’ genetic and health data, is the largest epidemiological cohort in the Baltic region. Participants were recruited through a network of medical professionals throughout Estonia (population 1.34 million). Unique legislation as well as a broad consent form
[...] Read more.
The Estonian population-based biobank, with 52,000 participants’ genetic and health data, is the largest epidemiological cohort in the Baltic region. Participants were recruited through a network of medical professionals throughout Estonia (population 1.34 million). Unique legislation as well as a broad consent form give the Estonian Genome Center, a research institute of the University of Tartu, permission to re-contact participants and to retrieve participants’ data from national registries and databases. In addition to two re-contacting projects to update the health data of participants, extensive clinical characterizations have been retrieved from national registries and hospital databases regularly since 2010. Acquiring data from electronic health records and registries has provided a means to update and enhance the database of the Genome Center in a timely manner and at low cost. The resulting database allows a wide spectrum of genomic and epidemiological research to be conducted with the aim of benefitting public health. Future plans include linking the genome center database with the national health information system through X-road and exchanging data in real time, as well as using the genetic data and the technical infrastructure available for piloting personalized medicine in Estonia. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)

Other

Jump to: Research, Review

Open AccessTechnical Note The Da Vinci European BioBank: A Metabolomics-Driven Infrastructure
J. Pers. Med. 2015, 5(2), 107-119; doi:10.3390/jpm5020107
Received: 8 January 2015 / Revised: 2 April 2015 / Accepted: 16 April 2015 / Published: 22 April 2015
PDF Full-text (1015 KB) | HTML Full-text | XML Full-text
Abstract
We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it). The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fiorgen.net/), a nonprofit organization that promotes research in the field of pharmacogenomics and personalized
[...] Read more.
We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it). The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fiorgen.net/), a nonprofit organization that promotes research in the field of pharmacogenomics and personalized medicine. The way operating procedures concerning samples and data have been developed at daVEB largely stems from the strong metabolomics connotation of Fiorgen and from the involvement of the scientific collaborators of the foundation in international/European projects aimed to tackle the standardization of pre-analytical procedures and the promotion of data standards in metabolomics. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)
Open AccessCommentary The Genotype-Tissue Expression (GTEx) Project: Linking Clinical Data with Molecular Analysis to Advance Personalized Medicine
J. Pers. Med. 2015, 5(1), 22-29; doi:10.3390/jpm5010022
Received: 24 October 2014 / Revised: 31 December 2014 / Accepted: 28 January 2015 / Published: 5 February 2015
Cited by 6 | PDF Full-text (361 KB) | HTML Full-text | XML Full-text
Abstract
Evaluation of how genetic mutations or variability can directly affect phenotypic outcomes, the development of disease, or determination of a tailored treatment protocol is fundamental to advancing personalized medicine. To understand how a genotype affects gene expression and specific phenotypic traits, as well
[...] Read more.
Evaluation of how genetic mutations or variability can directly affect phenotypic outcomes, the development of disease, or determination of a tailored treatment protocol is fundamental to advancing personalized medicine. To understand how a genotype affects gene expression and specific phenotypic traits, as well as the correlative and causative associations between such, the Genotype-Tissue Expression (GTEx) Project was initiated The GTEx collection of biospecimens and associated clinical data links extensive clinical data with genotype and gene expression data to provide a wealth of data and resources to study the underlying genetics of normal physiology. These data will help inform personalized medicine through the identification of normal variation that does not contribute to disease. Additionally, these data can lead to insights into how gene variation affects pharmacodynamics and individualized responses to therapy. Full article
(This article belongs to the Special Issue Biobanking and EHR/EMR)

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