Literature DB >> 34465180

Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS.

Lisa Bastarache1.   

Abstract

Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases) codes that can be used to rapidly define the case/control status of thousands of clinically meaningful diseases and conditions. Phecodes were originally developed to conduct phenome-wide association studies to scan for phenotypic associations with common genetic variants. Since then, phecodes have been used to support a wide range of EHR-based phenotyping methods, including the phenotype risk score. This review aims to comprehensively describe the development, validation, and applications of phecodes and suggest some future directions for phecodes and high-throughput phenotyping.

Entities:  

Keywords:  Mendelian genetics; electronic health record; genomics; phecodes; phenome-wide association study (PheWAS); phenotype risk score; phenotype risk score (PheRS); phenotyping

Mesh:

Year:  2021        PMID: 34465180      PMCID: PMC9307256          DOI: 10.1146/annurev-biodatasci-122320-112352

Source DB:  PubMed          Journal:  Annu Rev Biomed Data Sci        ISSN: 2574-3414


  95 in total

1.  Use of the International Classification of Diseases (ICD-9-CM) to identify hospitalizations for mechanical low back problems in administrative databases.

Authors:  D C Cherkin; R A Deyo; E Volinn; J D Loeser
Journal:  Spine (Phila Pa 1976)       Date:  1992-07       Impact factor: 3.468

2.  Inaccuracy of ICD-9 Codes for Chronic Kidney Disease: A Study from Two Practice-based Research Networks (PBRNs).

Authors:  Charlotte W Cipparone; Matthew Withiam-Leitch; Kim S Kimminau; Chet H Fox; Ranjit Singh; Linda Kahn
Journal:  J Am Board Fam Med       Date:  2015 Sep-Oct       Impact factor: 2.657

3.  Accuracy in recorded diagnoses.

Authors:  S F Jencks
Journal:  JAMA       Date:  1992 Apr 22-29       Impact factor: 56.272

4.  Contrasting Association Results between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes.

Authors:  Joseph B Leader; Sarah A Pendergrass; Anurag Verma; David J Carey; Dustin N Hartzel; Marylyn D Ritchie; H Lester Kirchner
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

5.  Representation of EHR data for predictive modeling: a comparison between UMLS and other terminologies.

Authors:  Laila Rasmy; Firat Tiryaki; Yujia Zhou; Yang Xiang; Cui Tao; Hua Xu; Degui Zhi
Journal:  J Am Med Inform Assoc       Date:  2020-10-01       Impact factor: 4.497

6.  Improving the phenotype risk score as a scalable approach to identifying patients with Mendelian disease.

Authors:  Lisa Bastarache; Jacob J Hughey; Jeffrey A Goldstein; Julie A Bastraache; Satya Das; Neil Charles Zaki; Chenjie Zeng; Leigh Anne Tang; Dan M Roden; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2019-12-01       Impact factor: 4.497

Review 7.  Beyond the simplicity of Mendelian inheritance.

Authors:  Joseph Schacherer
Journal:  C R Biol       Date:  2016-06-22       Impact factor: 1.583

8.  Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.

Authors:  Joshua C Denny; Lisa Bastarache; Marylyn D Ritchie; Robert J Carroll; Raquel Zink; Jonathan D Mosley; Julie R Field; Jill M Pulley; Andrea H Ramirez; Erica Bowton; Melissa A Basford; David S Carrell; Peggy L Peissig; Abel N Kho; Jennifer A Pacheco; Luke V Rasmussen; David R Crosslin; Paul K Crane; Jyotishman Pathak; Suzette J Bielinski; Sarah A Pendergrass; Hua Xu; Lucia A Hindorff; Rongling Li; Teri A Manolio; Christopher G Chute; Rex L Chisholm; Eric B Larson; Gail P Jarvik; Murray H Brilliant; Catherine A McCarty; Iftikhar J Kullo; Jonathan L Haines; Dana C Crawford; Daniel R Masys; Dan M Roden
Journal:  Nat Biotechnol       Date:  2013-12       Impact factor: 54.908

9.  Phenome-based approach identifies RIC1-linked Mendelian syndrome through zebrafish models, biobank associations and clinical studies.

Authors:  Eric R Gamazon; David B Melville; Nisha Patel; Gokhan Unlu; Xinzi Qi; Amy R Rushing; Mais Hashem; Abdullah Al-Faifi; Rui Chen; Bingshan Li; Nancy J Cox; Fowzan S Alkuraya; Ela W Knapik
Journal:  Nat Med       Date:  2020-01-13       Impact factor: 53.440

10.  A short history of the genome-wide association study: where we were and where we are going.

Authors:  Shiro Ikegawa
Journal:  Genomics Inform       Date:  2012-12-31
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1.  New Insights into Clinical and Mechanistic Heterogeneity of the Acute Respiratory Distress Syndrome: Summary of the Aspen Lung Conference 2021.

Authors:  Thomas R Martin; Rachel L Zemans; Lorraine B Ware; Eric P Schmidt; David W H Riches; Lisa Bastarache; Carolyn S Calfee; Tushar J Desai; Susanne Herold; Catherine L Hough; Mark R Looney; Michael A Matthay; Nuala Meyer; Samir M Parikh; Troy Stevens; B Taylor Thompson
Journal:  Am J Respir Cell Mol Biol       Date:  2022-09       Impact factor: 7.748

Review 2.  Computational analysis of neurodevelopmental phenotypes: Harmonization empowers clinical discovery.

Authors:  David Lewis-Smith; Shridhar Parthasarathy; Julie Xian; Michael C Kaufman; Shiva Ganesan; Peter D Galer; Rhys H Thomas; Ingo Helbig
Journal:  Hum Mutat       Date:  2022-05-22       Impact factor: 4.700

3.  Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases.

Authors:  Chenjie Zeng; Lisa A Bastarache; Ran Tao; Eric Venner; Scott Hebbring; Justin D Andujar; Sarah T Bland; David R Crosslin; Siddharth Pratap; Ayorinde Cooley; Jennifer A Pacheco; Kurt D Christensen; Emma Perez; Carrie L Blout Zawatsky; Leora Witkowski; Hana Zouk; Chunhua Weng; Kathleen A Leppig; Patrick M A Sleiman; Hakon Hakonarson; Marc S Williams; Yuan Luo; Gail P Jarvik; Robert C Green; Wendy K Chung; Ali G Gharavi; Niall J Lennon; Heidi L Rehm; Richard A Gibbs; Josh F Peterson; Dan M Roden; Georgia L Wiesner; Joshua C Denny
Journal:  JAMA Oncol       Date:  2022-06-01       Impact factor: 33.006

4.  Developing real-world evidence from real-world data: Transforming raw data into analytical datasets.

Authors:  Lisa Bastarache; Jeffrey S Brown; James J Cimino; David A Dorr; Peter J Embi; Philip R O Payne; Adam B Wilcox; Mark G Weiner
Journal:  Learn Health Syst       Date:  2021-10-14

5.  Scanning the medical phenome to identify new diagnoses after recovery from COVID-19 in a US cohort.

Authors:  V Eric Kerchberger; Josh F Peterson; Wei-Qi Wei
Journal:  J Am Med Inform Assoc       Date:  2022-08-25       Impact factor: 7.942

  5 in total

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