With the rapidly growing adoption of patient electronic health record systems (EHRs) due to Meaningful Use, and linkage of EHRs to research biorepositories, evaluating the suitability of EHR data for clinical and translational research is becoming ever more important, with ramifications for genomic and observational research, clinical trials, and comparative effectiveness studies. A key component for identifying patient cohorts in the EHR is to define inclusion and exclusion criteria that algorithmically select sets of patients based on stored clinical data. This process is commonly referred to, as ?EHR-driven phenotyping? is time-consuming and tedious due to the lack of a widely accepted and standards-based formal information model for defining phenotyping algorithms. To address this overall challenge, the proposed project will design, build and promote an open-access community infrastructure for standards-based development and sharing of phenotyping algorithms, as well as provide tools and resources for investigators, researchers and their informatics support staff to implement and execute the algorithms on native EHR data.

Public Health Relevance

The identification of patient cohorts for clinical and genomic research is a costly and time-consuming process. This bottleneck adversely affects public health by delaying research findings, and in some cases by making research costs prohibitively high. To address this issue, leveraging electronic health records (EHRs) for identifying patient cohorts has become an increasingly attractive option. This proposal will investigate and implement standards based approaches for computable phenotype identification from multiple EHRs.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM105688-08
Application #
9774075
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Brazhnik, Paul
Project Start
2017-09-01
Project End
2021-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
8
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Weill Medical College of Cornell University
Department
Other Health Professions
Type
Schools of Medicine
DUNS #
060217502
City
New York
State
NY
Country
United States
Zip Code
10065
Robinson, Jamie R; Denny, Joshua C; Roden, Dan M et al. (2018) Genome-wide and Phenome-wide Approaches to Understand Variable Drug Actions in Electronic Health Records. Clin Transl Sci 11:112-122
Sharma, Deepak Kumar; Peterson, Kevin Jerrold; Hong, Na et al. (2018) The D2Refine Platform for the Standardization of Clinical Research Study Data Dictionaries: Usability Study. JMIR Hum Factors 5:e10205
Kim, Min-Hyung; Banerjee, Samprit; Zhao, Yize et al. (2018) Association networks in a matched case-control design - Co-occurrence patterns of preexisting chronic medical conditions in patients with major depression versus their matched controls. J Biomed Inform 87:88-95
Morash, Maggie; Mitchell, Hannah; Yu, Anthony et al. (2018) CATCH-KB: Establishing a Pharmacogenomics Variant Repository for Chemotherapy-Induced Cardiotoxicity. AMIA Jt Summits Transl Sci Proc 2017:168-177
Lee, Kathleen; Weiskopf, Nicole; Pathak, Jyotishman (2017) A Framework for Data Quality Assessment in Clinical Research Datasets. AMIA Annu Symp Proc 2017:1080-1089
Jiang, Guoqian; Kiefer, Richard; Prud'hommeaux, Eric et al. (2017) Building Interoperable FHIR-Based Vocabulary Mapping Services: A Case Study of OHDSI Vocabularies and Mappings. Stud Health Technol Inform 245:1327
Upadhyaya, Sudhi G; Murphree Jr, Dennis H; Ngufor, Che G et al. (2017) Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility. Mayo Clin Proc Innov Qual Outcomes 1:100-110
Wang, Amy Y; Lancaster, William J; Wyatt, Matthew C et al. (2017) Classifying Clinical Trial Eligibility Criteria to Facilitate Phased Cohort Identification Using Clinical Data Repositories. AMIA Annu Symp Proc 2017:1754-1763
Jiang, Guoqian; Kiefer, Richard C; Sharma, Deepak K et al. (2017) A Consensus-Based Approach for Harmonizing the OHDSI Common Data Model with HL7 FHIR. Stud Health Technol Inform 245:887-891
Teixeira, Pedro L; Wei, Wei-Qi; Cronin, Robert M et al. (2017) Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals. J Am Med Inform Assoc 24:162-171

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