scholarly journals Validation of Colorectal Cancer Screening in the Electronic Health Record for Identifying Patients Due for Screening in a Pragmatic Trial

2016 ◽  
Vol 3 (3) ◽  
pp. 180
Author(s):  
Amanda F Petrik ◽  
Bev Green ◽  
William Vollmer ◽  
Thuy Let ◽  
Barbara Bachman ◽  
...  
2019 ◽  
Vol 156 (6) ◽  
pp. S-1075-S-1076
Author(s):  
Vivek Rudrapatna ◽  
Benjamin Glicksberg ◽  
Patrick Avila ◽  
Emily Harding-Theobald ◽  
Connie Wang ◽  
...  

2019 ◽  
Vol 23 (4) ◽  
pp. 253-258 ◽  
Author(s):  
Deanna Teoh ◽  
Rachel I. Vogel ◽  
Adam Langer ◽  
Jinai Bharucha ◽  
Melissa A. Geller ◽  
...  

2022 ◽  
pp. 0272989X2110699
Author(s):  
Louise B. Russell ◽  
Qian Huang ◽  
Yuqing Lin ◽  
Laurie A. Norton ◽  
Jingsan Zhu ◽  
...  

Introduction. Pragmatic clinical trials test interventions in patients representative of real-world medical practice and reduce data collection costs by using data recorded in the electronic health record (EHR) during usual care. We describe our experience using the EHR to measure the primary outcome of a pragmatic trial, hospital readmissions, and important clinical covariates. Methods. The trial enrolled patients recently discharged from the hospital for treatment of heart failure to test whether automated daily monitoring integrated into the EHR could reduce readmissions. The study team used data from the EHR and several data systems that drew on the EHR, supplemented by the hospital admissions files of three states. Results. Almost three-quarters of enrollees’ readmissions over the 12-mo trial period were captured by the EHRs of the study hospitals. State data, which took 7 mo to more than 2 y from first contact to receipt of first data, provided the remaining one-quarter. Considerable expertise was required to resolve differences between the 2 data sources. Common covariates used in trial analyses, such as weight and body mass index during the index hospital stay, were available for >97% of enrollees from the EHR. Ejection fraction, obtained from echocardiograms, was available for only 47.6% of enrollees within the 6-mo window that would likely be expected in a traditional trial. Discussion. In this trial, patient characteristics and outcomes were collected from existing EHR systems, but, as usual for EHRs, they could not be standardized for date or method of measurement and required substantial time and expertise to collect and curate. Hospital admissions, the primary trial outcome, required additional effort to locate and use supplementary sources of data. Highlights Electronic health records are not a single system but a series of overlapping and legacy systems that require time and expertise to use efficiently. Commonly measured patient characteristics such as weight and body mass index are relatively easy to locate for most trial enrollees but less common characteristics, like ejection fraction, are not. Acquiring essential supplementary data—in this trial, state data on hospital admission—can be a lengthy and difficult process.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15557-e15557
Author(s):  
Sarah C. Markt ◽  
Benjamin Booker ◽  
Wyatt Bensken ◽  
Fredrick R Schumacher ◽  
Johnie Rose ◽  
...  

e15557 Background: Oncology has greatly benefited from the use of clinical genomics to aid diagnostic and treatment decisions. To inform targeted therapy, standard practice dictates molecular testing of metastatic colorectal cancer (mCRC) tumors through genomic testing (GT), including molecular biomarker, single gene, or next-generation sequencing (NGS). While persisting disparities in CRC screening, treatment, and outcomes have been well described, little is known about differences in GT for mCRC. Using all-payer electronic health record-derived de-identified data from a real-world database generated from routine clinical care across the U.S., we identified combinations of demographic and clinical characteristics, rather than individual factors, associated with GT. Methods: This study used the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database. During the study period, the de-identified data originated from approximately 280 US cancer clinics (̃800 sites of care). Our study population included 26,524 patients with mCRC during the years 2013-2020. We evaluated documentation of receipt of GT (individual biomarker or NGS) measured within one year of diagnosis of metastatic disease, by demographic (age, sex, and race/ethnicity), payer type, de novo metastatic cancer (vs. progression to metastatic disease), tumor site (colon vs. rectum), Eastern Cooperative Oncology Group (ECOG) performance status, and year of diagnosis. We identified Elixhauser comorbid conditions from ICD codes, and grouped them by count (0-4, 5+). We conducted Classification and Regression Tree (CART) analysis, a machine learning approach to identify combinations of demographic and clinical characteristics associated with receipt of GT. Results: Nearly 83% had documented GT, 90% of whom did so within 6 months of diagnosis. The largest group of patients with GT at 90% consisted of individuals with colon cancer, 64 years of age or younger, 0-4 comorbidities, and an ECOG score of 0 or 1 (n = 2,004). Conversely, the lowest rates of GT ( < 60%) were observed among women 75 years of age or older, despite having 0-4 comorbidities (n = 1,314). In this group of patients, GT was higher among those with ECOG score of 1 than among those with high ECOG scores (66% and 54%, respectively). On the other hand, 71% of patients 75 years of age or older with 5+ comorbidities and high ECOG scores received GT. Conclusions: Considerable variations exist in GT across subgroups of the population. Additional analysis is warranted to characterize young and healthy patients who did not receive GT, and those who did get tested despite their older age and compromised health status. Future analyses will investigate whether documentation of receipt of GT is associated with treatment decisions and outcomes.


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