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Review
. 2012 Sep;85(3):363-77.
Epub 2012 Sep 25.

The future of medical diagnostics: large digitized databases

Wesley T Kerr  1 , Edward P Lau, Gwen E Owens, Aaron Trefler
Affiliations
Review

The future of medical diagnostics: large digitized databases

Wesley T Kerr et al. Yale J Biol Med. 2012 Sep.

Abstract

The electronic health record mandate within the American Recovery and Reinvestment Act of 2009 will have a far-reaching affect on medicine. In this article, we provide an in-depth analysis of how this mandate is expected to stimulate the production of large-scale, digitized databases of patient information. There is evidence to suggest that millions of patients and the National Institutes of Health will fully support the mining of such databases to better understand the process of diagnosing patients. This data mining likely will reaffirm and quantify known risk factors for many diagnoses. This quantification may be leveraged to further develop computer-aided diagnostic tools that weigh risk factors and provide decision support for health care providers. We expect that creation of these databases will stimulate the development of computer-aided diagnostic support tools that will become an integral part of modern medicine.

Keywords: computer-aided diagnostics; databases; electronic health record; machine learning.

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Figures

Figure 1
Figure 1
This figure illustrates the number of PubMed citations using each of the Mesh terms listed. Since 2002, the number of publications regarding computer-aided diagnostics has increased substantially. We are already seeing a commensurate increase in the number of publications regarding computerized medical record systems and electronic health records [1].
Figure 2
Figure 2
Even before the ARRA in 2009, the number of physicians utilizing EHR systems was increasing. There are already a substantial percent of physicians using electronic records. Consequentially, it is relatively inexpensive to combine and mine these EHR systems for high quality clinical information.
Figure 3
Figure 3
The creation and utilization of EHR databases is complex; however, each of the steps in the data and implementation stream are well defined. We expect that responsible researchers will be capable of tackling each of these steps to create unparalleled databases and develop high quality, clinically applicable CAD tools.
See this image and copyright information in PMC

References

    1. United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Ambulatory Medical Care Survey [Internet] 2009. Available from: http://www.cdc.gov/nchs/ahcd.htm .
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    1. Lunshof JE, Chadwick R, Vorhaus DB, Church GM. From genetic privacy to open consent. Nat Rev Genet. 2008;9(5):406–411. - PubMed
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    1. Hunter M, Smith RL, Hyslop W, Rosso OA, Gerlach R, Rostas JA. et al. The Australian EEG database. Clin EEG Neurosci. 2005;36(2):76–81. - PubMed

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