Electronic health record as a research tool: Frequency of exposure to targeted clinical problems and health care providers’ clinical proficiency

Wysocki, Tim; Diaz, Maria Carmen G.; Crutchfield, James H.; Franciosi, James P.; Werk, Lloyd N.

doi:10.1016/j.jbi.2017.04.016

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…Data missingness is a common problem in EHR-based research. (48)(49)(50)(51)(52)(53)(54)(55)(56)) This is particularly true in a tertiary referral center such as VUMC, where patients often receive routine clinical care at other institutions. We found that adding more stringent criteria for cases did improve our PPV, but did not greatly impact the clinical characteristics of the case sets identified (Table S4).…”

Section: Discussionmentioning

confidence: 99%

“…As previously mentioned, the use of EHR in biomedical research has inherent challenges due to inconsistent documentation, missing data, and inaccuracies. (48)(49)(50)(51)(52)(53)(54)(55)(56) Tertiary care EHR data often have sicker patients with denser clinical documentation and more complete data than other hospital settings. (56) COPD cases identified by our algorithm have more severe COPD based on FEV1 and FEV1/FVC measurements ( Figure S2).…”

Section: Discussionmentioning

confidence: 99%

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A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records

Martucci

Liu

Kerchberger

et al. 2019

Preprint

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Rationale. Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality in the United States. Electronic health records provide large-scale healthcare data for clinical research, but have been underutilized in COPD research due to challenges identifying these individuals, especially in the absence of pulmonary function testing data. Objectives.To develop an algorithm to electronically phenotype individuals with COPD at a large tertiary care center. Methods. We identified individuals over 45 years of age at last clinic visit within VanderbiltUniversity Medical Center electronic health records. We tested phenotyping algorithms using combinations of both structured and unstructured text and examined the clinical characteristics of the resulting case sets. Measurement and Main Results.A simple algorithm consisting of 3 International Classification of Disease codes for COPD achieved a sensitivity of 97.6%, a specificity of 76.0%, a positive predictive value of 57.1%, and a negative predictive value of 99.0%. A more complex algorithm consisting of both billing codes and a mention of oxygen on the problem list that achieved a positive predictive value of 86.5%. However, the association of known risk factors with chronic obstructive pulmonary disease was consistent in both algorithm sets, suggesting a simple codeonly algorithm may suffice for many research applications. Conclusions.Simple code-only phenotyping algorithms for chronic obstructive pulmonary disease can identify case populations with epidemiologic and genetic profiles consistent with published literature. Implementation of this phenotyping algorithm will expand opportunities for clinical research and pragmatic trials for COPD.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records

Martucci

Liu

Kerchberger

et al. 2019

Preprint

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“…Another mechanism for genetic discovery lies with the increasing use of electronic health records (EHRs). EHRs have become a more commonplace tool in genetics, allowing researchers to conduct studies on specific genetic conditions, including observational, epidemiological, descriptive, and comparative effectiveness studies, among others [6,7]. EHRs are also being used to recruit participants for research studies and clinical trials [8].…”

Section: Introductionmentioning

confidence: 99%

Ethical, Legal, and Social Issues Related to the Inclusion of Individuals With Intellectual Disabilities in Electronic Health Record Research: Scoping Review

et al. 2020

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Background Data from electronic health records (EHRs) are increasingly used in the field of genetic research to further precision medicine initiatives. However, many of these efforts exclude individuals with intellectual disabilities, which often stem from genetic conditions. To include this important subpopulation in EHR research, important ethical, legal, and social issues should be considered. Objective The goal of this study was to review prior research to better understand what ethical, legal, and social issues may need further investigation when considering the research use of EHRs for individuals with genetic conditions that may result in intellectual disability. This information will be valuable in developing methods and best practices for involving this group in research given they are considered a vulnerable population that may need special research protections. Methods We conducted a scoping review to examine issues related to the use of EHRs for research purposes and those more broadly associated with genetic research. The initial search yielded a total of 460 unique citations. We used an evaluative coding process to determine relevancy for inclusion. Results This approach resulted in 59 articles in the following areas: informed consent, privacy and security, return of results, and vulnerable populations. The review included several models of garnering informed consent in EHR or genetic research, including tiered or categorical, blanket or general, open, and opt-out models. Second, studies reported on patients’ concerns regarding the privacy and security of EHR or genetic data, such as who has access, type of data use in research, identifiability, and risks associated with privacy breach. The literature on return of research results using biospecimens examined the dissension in the field, particularly when sharing individualized genetic results. Finally, work involving vulnerable populations highlighted special considerations when conducting EHR or genetic research. Conclusions The results frame important questions for researchers to consider when designing EHR studies, which include individuals with intellectual disabilities, including appropriate safeguards and protections.

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Special issue on cognitive informatics methods for interactive clinical systems

Kannampallil

Patel

2017

Journal of Biomedical Informatics

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Electronic health record as a research tool: Frequency of exposure to targeted clinical problems and health care providers’ clinical proficiency

Cited by 4 publications

References 18 publications

A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records

A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records

Ethical, Legal, and Social Issues Related to the Inclusion of Individuals With Intellectual Disabilities in Electronic Health Record Research: Scoping Review

Special issue on cognitive informatics methods for interactive clinical systems

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