Personalized Medicine, Availability, and Group Disparity: An Inquiry into How Physicians Perceive and Rate the Elements and Barriers of Personalized Medicine
Abstract
Background: The success of personalized medicine depends on factors influencing the availability and implementation of its new tools to individualize clinical care. However, little is known about physicians' views of the availability of personalized medicine across racial/ethnic groups and the relationship between perceived availability and clinical implementation. This study examines physicians' perceptions of key elements/tools and potential barriers to personalized medicine in connection with their perceptions of the availability of the latter across subpopulations. Methods: Study subjects consisted of physicians recruited from Cincinnati Children's Hospital Medical Center and UC Health. An electronic survey conducted from September 2012 to November 2012 recruited 104 physicians. Wilcoxon rank sum analysis compared groups. Results: Physicians were divided about whether personalized medicine contributes to health equality, as 37.4% of them believe that personalized medicine is currently available only for some subpopulations. They also rated the importance of racial/ethnic background almost as high as the importance of genetic information in the delivery of personalized medicine. Actual elements of personalized medicine rated highest include family history, drug-drug interaction alerts in medical records, and biomarker measurements to guide therapy. Costs of gene-based therapies and genetic testing were rated the most significant barriers. The ratings of several elements and barriers were associated with perceived availability of personalized medicine across subpopulations. Conclusion: While physicians hold differing views about the availability and implementation of personalized medicine, they likewise establish complex relationships between race/ethnicity and personalized medicine that may carry serious implications for its clinical success.
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Professionals describe a lack in their own knowledge or a limited understanding of precision medicine.
“Professionals also describe a lack in their own knowledge or a limited understanding, as quantitative studies demonstrate [36, 37, 44, 81, 82, 92, 103, 104].”
From Patients’ and professionals’ views related to ethical issues in precision medicine: a mixed research synthesis (2021) · cites this paper as [103]
Only 38.5% of doctors surveyed in the US believed that precision medicine is available to all ethnic groups.
“Only 38.5% of doctors surveyed (n = 104) in the US believed that PM is available to all ethnic groups. [103].”
From Patients’ and professionals’ views related to ethical issues in precision medicine: a mixed research synthesis (2021) · cites this paper as [103]
Cites
The adequacy of response rates to online and paper surveys: what can be done?
Nulty, D. D. (2008) · Assessment & Evaluation in Higher Education · doi:10.1080/02602930701293231 · Cited by 2,581 · see citing works
Internet Versus Mailed Questionnaires: A Randomized Comparison
Ritter, P., Lorig, K., Laurent, D., & Matthews, K. (2004) · Journal of Medical Internet Research · doi:10.2196/jmir.6.3.e29 · Cited by 427 · see citing works
Rare diseases, orphan drugs and their regulation: questions and misconceptions
Tambuyzer, E. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3275 · Cited by 182 · see citing works
Meyer, U. A., Zanger, U. M., & Schwab, M. (2013) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010510-100502 · Cited by 157 · see citing works
Bloche, M. G. (2004) · New England Journal of Medicine · doi:10.1056/nejmp048271 · Cited by 150 · see citing works
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Maglo, K. N., Mersha, T. B., & Martin, L. J. (2016) · Frontiers in Genetics · doi:10.3389/fgene.2016.00022 · Cited by 106 · see citing works
Self-citationErdmann, A., Rehmann-Sutter, C., & Bozzaro, C. (2021) · BMC Medical Ethics · doi:10.1186/s12910-021-00682-8 · Cited by 86 · see citing works
- Authors
- Petersen, K. E., Prows, C. A., Martin, L. J., & Maglo, K. N.
- Affiliations
- University of Cincinnati (US)
- Venue
- Public Health Genomics
- Publisher
- S. Karger AG
- Published
- 2014
- Volume
- 17
- Issue
- 4
- Pages
- 209-220
- ISSN
- 1422-2795 (ISSN-L)
- 1662-4246
- 1662-8063
- OpenAlex
- W2032451354
- Cited by
- 26
- References
- 5
- Citations by year
- 2026: 1 · 2025: 1 · 2022: 8 · 2021: 2 · 2020: 3 · 2019: 3 · 2018: 2 · 2017: 4 · 2016: 2
- FWCI
- 1.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Public Health Genomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UL1TR000077)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- personalized medicine, physician perceptions, racial and ethnic disparities, health equity, implementation barriers, cost of genetic testing, gene therapy, genetic information, family history (medicine), drug-drug interaction alerts, biomarkers, children's hospitals
- MeSH terms
- Adult, Ethnicity, Female, Genetic Testing, Health Services Accessibility, Humans, Male, Middle Aged, Physicians, Surveys and Questionnaires, Referral and Consultation, United States, Healthcare Disparities, Precision Medicine
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