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Extracting Primary Open-Angle Glaucoma from Electronic Medical Records for Genetic Association Studies.

Restrepo NA, Farber-Eger E, Goodloe R, Haines JL, Crawford DC - PLoS ONE (2015)

Bottom Line: Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies.As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies.The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center's biorepository linked to a de-identified version of the EMR (EAGLE BioVU).

View Article: PubMed Central - PubMed

Affiliation: Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America.

ABSTRACT
Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies. As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies. The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center's biorepository linked to a de-identified version of the EMR (EAGLE BioVU). Here we develop and deploy an algorithm utilizing data mining techniques to identify primary open-angle glaucoma (POAG) in African Americans from EAGLE BioVU for genetic association studies. The algorithm described here was designed using a combination of diagnostic codes, current procedural terminology billing codes, and free text searches to identify POAG status in situations where gold-standard digital photography cannot be accessed. The case algorithm identified 267 potential POAG subjects but underperformed after manual review with a positive predictive value of 51.6% and an accuracy of 76.3%. The control algorithm identified controls with a negative predictive value of 98.3%. Although the case algorithm requires more downstream manual review for use in large-scale studies, it provides a basis by which to extract a specific clinical subtype of glaucoma from EMRs in the absence of digital photographs.

No MeSH data available.


Related in: MedlinePlus

Histogram plots of the distribution of cup-to-disk (CDR) ratios of POAG cases from the Synthetic Derivative.Distribution of CDR for the right eyes (A) and the left eyes (B) of POAG cases from numbers that were manually extracted from the SD.
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pone.0127817.g003: Histogram plots of the distribution of cup-to-disk (CDR) ratios of POAG cases from the Synthetic Derivative.Distribution of CDR for the right eyes (A) and the left eyes (B) of POAG cases from numbers that were manually extracted from the SD.

Mentions: A total of 132 POAG case records were positive for a CDR key word phrase, and all were manually reviewed for CDR. Only 9 of the 132 records (7%) were missing a measure for CDR. The median values for CDR in this study are 0.7 (SD 0.22) in the right eyes and 0.7 (SD 0.23) in the left eyes (Fig 3).


Extracting Primary Open-Angle Glaucoma from Electronic Medical Records for Genetic Association Studies.

Restrepo NA, Farber-Eger E, Goodloe R, Haines JL, Crawford DC - PLoS ONE (2015)

Histogram plots of the distribution of cup-to-disk (CDR) ratios of POAG cases from the Synthetic Derivative.Distribution of CDR for the right eyes (A) and the left eyes (B) of POAG cases from numbers that were manually extracted from the SD.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4465698&req=5

pone.0127817.g003: Histogram plots of the distribution of cup-to-disk (CDR) ratios of POAG cases from the Synthetic Derivative.Distribution of CDR for the right eyes (A) and the left eyes (B) of POAG cases from numbers that were manually extracted from the SD.
Mentions: A total of 132 POAG case records were positive for a CDR key word phrase, and all were manually reviewed for CDR. Only 9 of the 132 records (7%) were missing a measure for CDR. The median values for CDR in this study are 0.7 (SD 0.22) in the right eyes and 0.7 (SD 0.23) in the left eyes (Fig 3).

Bottom Line: Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies.As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies.The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center's biorepository linked to a de-identified version of the EMR (EAGLE BioVU).

View Article: PubMed Central - PubMed

Affiliation: Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America.

ABSTRACT
Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies. As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies. The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center's biorepository linked to a de-identified version of the EMR (EAGLE BioVU). Here we develop and deploy an algorithm utilizing data mining techniques to identify primary open-angle glaucoma (POAG) in African Americans from EAGLE BioVU for genetic association studies. The algorithm described here was designed using a combination of diagnostic codes, current procedural terminology billing codes, and free text searches to identify POAG status in situations where gold-standard digital photography cannot be accessed. The case algorithm identified 267 potential POAG subjects but underperformed after manual review with a positive predictive value of 51.6% and an accuracy of 76.3%. The control algorithm identified controls with a negative predictive value of 98.3%. Although the case algorithm requires more downstream manual review for use in large-scale studies, it provides a basis by which to extract a specific clinical subtype of glaucoma from EMRs in the absence of digital photographs.

No MeSH data available.


Related in: MedlinePlus