Accuracy of identifying hospital acquired venous thromboembolism by administrative coding: implications for big data and machine learning research
Big data analytics research using heterogeneous electronic health record (EHR) data
requires accurate identification of disease phenotype cases and controls. Overreliance on …
requires accurate identification of disease phenotype cases and controls. Overreliance on …
[HTML][HTML] Evaluation of clinical text segmentation to facilitate cohort retrieval
Objective: Secondary use of electronic health record (EHR) data is enabled by accurate and
complete retrieval of the relevant patient cohort, which requires searching both structured …
complete retrieval of the relevant patient cohort, which requires searching both structured …
[HTML][HTML] Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare
Background Diagnostic codes are commonly used as inputs for clinical prediction models, to
create labels for prediction tasks, and to identify cohorts for multicenter network studies …
create labels for prediction tasks, and to identify cohorts for multicenter network studies …
A computable phenotype improves cohort ascertainment in a pediatric pulmonary hypertension registry
Objectives To compare registry and electronic health record (EHR) data mining approaches
for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort …
for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort …
PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data
Objectives This study proposes a novel P rior knowledge guided I ntegrated likelihood E
stimation (PIE) method to correct bias in estimations of associations due to misclassification …
stimation (PIE) method to correct bias in estimations of associations due to misclassification …
Workflow differences affect data accuracy in oncologic EHRs: a first step toward detangling the diagnosis data babel
F Diaz-Garelli, R Strowd, VL Lawson… - JCO Clinical Cancer …, 2020 - ascopubs.org
PURPOSE Diagnosis (DX) information is key to clinical data reuse, yet accessible structured
DX data often lack accuracy. Previous research hints at workflow differences in cancer DX …
DX data often lack accuracy. Previous research hints at workflow differences in cancer DX …
[HTML][HTML] An independently validated, portable algorithm for the rapid identification of COPD patients using electronic health records
Electronic health records (EHR) provide an unprecedented opportunity to conduct large,
cost-efficient, population-based studies. However, the studies of heterogeneous diseases …
cost-efficient, population-based studies. However, the studies of heterogeneous diseases …
[HTML][HTML] Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research
Abstract The All of Us Research Program was designed to enable broad-based precision
medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is …
medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is …
Parkinson's disease diagnosis codes are insufficiently accurate for electronic health record research and differ by race
EJ Hill, J Sharma, B Wissel, RP Sawyer, M Jiang… - Parkinsonism & Related …, 2023 - Elsevier
Background There are no evidence-based guidelines for data cleaning of electronic health
record (EHR) databases in Parkinson's disease (PD). Previous filtering criteria have …
record (EHR) databases in Parkinson's disease (PD). Previous filtering criteria have …
Automated phenotyping tool for identifying developmental language disorder cases in health systems data (APT-DLD): A new research algorithm for deployment in …
Purpose Data mining algorithms using electronic health records (EHRs) are useful in large-
scale population-wide studies to classify etiology and comorbidities. Here, we apply this …
scale population-wide studies to classify etiology and comorbidities. Here, we apply this …