Using Electronic Health Record (EHR) Best Practice Alert (BPA) to Improve RBC Transfusion Practices and Adherence to the Guidelines

Sroujieh, Laila; Monroy, Daniel; Warren, Edward

doi:10.1016/j.chest.2016.08.691

Cited by 3 publications

(1 citation statement)

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“…Federman et al [53], 2017; Goehler et al [54], 2019; Horton et al [55], 2018; Howell et al [56], 2014; Klang et al [57], 2021; Li et al [58], 2020; Lindholm et al [59], 2010; Melnick et al [60], 2022; Milne Adult et al [61], 2020; Mitchell et al [62], 2022; Mulhem et al [63], 2020; Park et al [64], 2021; Ritchey et al [65], 2016; Rose et al [66], 2018; Ryan et al [67], 2021; Shelley et al [68], 2017; Sroujieh et al [69], 2016; Toscos et al [70], 2020; Toscos et al [71], 2020; Willis et al [72], 2022 Del Fiol et al [73], 2020; DeLozier [74], 2021; Jones et al [75], 2022; Jose et al [76], 2020; Keizur et al [77], 2022; Kolb et al [78], 2016; Lilih et al [79], 2017; Nikolic et al [80], 2017; Ray et al [81], 2018; Adult and pediatric Shelden et al [82], 2021; Siff and Emerman [83], 2016; Sonstein et al [84], 2014; Straub et al [85], 2013; Stutz et al [86], 2018; Tham et al [87], 2016; Wendel et al [88], 2023; Zorn et al [89], 2022 Tsai et al [90], 2015 Not specified Goldberg et al [91], 2016; Hojat et al [92], 2020; Simon et al [93], 2023; Tham et al…”

Section: Clinical Decision Supportmentioning

confidence: 99%

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Chishtie,

Sapiro,

Wiebe

et al. 2023

J Med Internet Res

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Background Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research. Objective The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences. Methods We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results. Results We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized. Conclusions The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

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Section: Clinical Decision Supportmentioning

confidence: 99%

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Chishtie,

Sapiro,

Wiebe

et al. 2023

J Med Internet Res

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Electronic Health Record Phenotypes for Identifying Patients with Late-Stage Disease: a Method for Research and Clinical Application

et al. 2019

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BACKGROUND: Systematic identification of patients allows researchers and clinicians to test new models of care delivery. EHR phenotypes-structured algorithms based on clinical indicators from EHRs-can aid in such identification. OBJECTIVE: To develop EHR phenotypes to identify decedents with stage 4 solid-tumor cancer or stage 4-5 chronic kidney disease (CKD). DESIGN: We developed two EHR phenotypes. Each phenotype included International Classification of Diseases (ICD)-9 and ICD-10 codes. We used natural language processing (NLP) to further specify stage 4 cancer, and lab values for CKD. SUBJECTS: Decedents with cancer or CKD who had been admitted to an academic medical center in the last 6 months of life and died August 26, 2017-December 31, 2017. MAIN MEASURE: We calculated positive predictive values (PPV), false discovery rates (FDR), false negative rates (FNR), and sensitivity. Phenotypes were validated by a comparison with manual chart review. We also compared the EHR phenotype results to those admitted to the oncology and nephrology inpatient services. KEY RESULTS: The EHR phenotypes identified 271 decedents with cancer, of whom 186 had stage 4 disease; of 192 decedents with CKD, 89 had stage 4-5 disease. The EHR phenotype for stage 4 cancer had a PPV of 68.6%, FDR of 31.4%, FNR of 0.5%, and 99.5% sensitivity. The EHR phenotype for stage 4-5 CKD had a PPV of 46.4%, FDR of 53.7%, FNR of 0.0%, and 100% sensitivity. CONCLUSIONS: EHR phenotypes efficiently identified patients who died with late-stage cancer or CKD. Future EHR phenotypes can prioritize specificity over sensitivity, and incorporate stratification of high-and low-palliative care need. EHR phenotypes are a promising method for identifying patients for research and clinical purposes, including equitable distribution of specialty palliative care.

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Abnormal Vital Sign Recognition and Provider Notification in the Pediatric Emergency Department

Valentino¹,

Campos²,

Acker³

et al. 2020

Journal of Pediatric Health Care

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Using Electronic Health Record (EHR) Best Practice Alert (BPA) to Improve RBC Transfusion Practices and Adherence to the Guidelines

Cited by 3 publications

References 0 publications

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Electronic Health Record Phenotypes for Identifying Patients with Late-Stage Disease: a Method for Research and Clinical Application

Abnormal Vital Sign Recognition and Provider Notification in the Pediatric Emergency Department

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