Desiderata for computable representations of electronic health records-driven phenotype algorithms.
BACKGROUND
Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).


METHODS
A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.


RESULTS
We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.


CONCLUSIONS
A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Huan
H
Mo
Center for Biomedical Research Informatics, NorthShore University HealthSystem, Evanston, IL, USA.
William K
WK
Thompson
Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Luke V
LV
Rasmussen
Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jennifer A
JA
Pacheco
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Guoqian
G
Jiang
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Richard
R
Kiefer
Department of Information Systems, University of Maryland, Baltimore County, Baltimore, MD, USA.
Qian
Q
Zhu
Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jie
J
Xu
Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Enid
E
Montague
Group Health Research Institute, Seattle, WA, USA.
David S
DS
Carrell
Division of Biomedical Informatics, Cincinnati Children's Hospital, Cincinnati, OH, USA.
Todd
T
Lingren
Center for Applied Genomics, the Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Frank D
FD
Mentch
Division of Biomedical Informatics, Cincinnati Children's Hospital, Cincinnati, OH, USA.
Yizhao
Y
Ni
Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Firas H
FH
Wehbe
Marshfield Clinic Research Foundation, Marshfield Clinic, Marshfield, WI, USA.
Peggy L
PL
Peissig
Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Stellenbosch, Cape Town, South Africa.
Gerard
G
Tromp
Group Health Research Institute, Seattle, WA, USA.
Eric B
EB
Larson
Division of General Internal Medicine, Johns Hopkins University, Baltimore, MD, USA.
Christopher G
CG
Chute
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.
Jyotishman
J
Pathak
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA Department of Medicine, Vanderbilt University, Nashville, TN, USA josh.denny@vanderbilt.edu.
Joshua C
JC
Denny
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Peter
P
Speltz
Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Abel N
AN
Kho
Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Gail P
GP
Jarvik
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Cosmin A
CA
Bejan
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Marc S
MS
Williams
The Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, USA.
Kenneth
K
Borthwick
Marshfield Clinic Research Foundation, Marshfield Clinic, Marshfield, WI, USA.
Terrie E
TE
Kitchner
Department of Medicine, Vanderbilt University, Nashville, TN, USA Department of Pharmacology, Vanderbilt University, Nashville, TN, USA.
Dan M
DM
Roden
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Paul A
PA
Harris
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D057286:Electronic Health Records; D006801:Humans; D010641:Phenotype
computable representation; data models; electronic health records; phenotype algorithms; phenotype standardization