scholarly journals Using an electronic medical record (EMR) to conduct clinical trials: Salford Lung Study feasibility

Author(s):  
Hanaa F Elkhenini ◽  
Kourtney J Davis ◽  
Norman D Stein ◽  
John P New ◽  
Mark R Delderfield ◽  
...  
2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6626-6626
Author(s):  
J. W. Goldwein ◽  
M. Van Der Pas ◽  
L. Tis ◽  
R. Nickens ◽  
R. Comis

6626 Background: One reason for the low numbers of patients entered on cancer clinical trials is the difficulty and inconvenience encountered in determining whether patients are eligible. The introduction of electronic medical record (EMR) systems in cancer facilities provides a means by which clinical parameters may be electronically collected and compared against clinical trial eligibility criteria, with the potential to facilitate eligibility determination. We hereby describe a widely utilized EMR system interfaced to a caBIG-certified searchable clinical trials database which facilitates eligibility determination. Materials and Methods: MOSAIQ is a widely utilized oncology- specific EMR system that is operational in radiation and medical oncology facilities world-wide. During the routine course of patient care, clinical trial eligibility parameters such as diagnosis, stage, age, and performance status are entered into defined data fields within the EMR. Trialcheck is an independently maintained caBIG bronze level certified database that lists thousands of clinical trials from Cooperative Groups, NCI/PDQ, the pharmaceutical industry and trials being conducted exclusively at particular oncology facilities. TrialCheck registrants can screen trials for patient eligibility as well as filter and track the status of trials that have been activated at their facility. In addition, a real-time, secure Internet interface between MOSAIQ and TrialCheck extracts eligibility parameters from a patient record, sends that information to TrialCheck, and returns a listing of matched clinical trials. Results: In a test screen of 4 MOSAIQ EMR patients against 257 TrialCheck clinical trials, the system matched a patient with Stage IV breast cancer to 7 available trials in less 2 seconds, a patient with Stage IIIB colon cancer to 3 trials in 5 seconds, a Stage IV prostate cancer to 5 trials in 4.4 seconds, and a patient with stage II esophageal cancer to 2 trials in 3.7 seconds. Conclusion: This product demonstrates a novel and innovative solution to one of the problems inherent in the clinical trial registration process in an efficient, reliable and secure manner. No significant financial relationships to disclose.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3008-3008
Author(s):  
Sudip Bhandari ◽  
Charles Lagor ◽  
Judith Mueller ◽  
Warren Whyte ◽  
Samuel Heilbroner

Abstract Background: Black patients are underrepresented in multiple myeloma (MM) clinical trials. Despite the promise of Real-World Data (RWD), little research exists on RWD's usage to address this health disparity. In collaboration with a large pharmaceutical partner, we used RWD from commercial datasets (ConcertAI's Electronic Medical Record and claims datasets) aimed at identifying sites with a large Black patient population. We recommended including these sites in a recent clinical trial of Chimeric Antigen Receptor T cell (CAR-T) therapy for MM patients. Methods: We used the following criteria to identify promising sites: (1) high Black patient density, (2) access to a CAR-T accredited parent organization within 100 miles, (3) a hematologist/oncologist who treats MM patients, and (4) a history of treating MM patients with a Proteasome Inhibitor (PI) and Lenalidomide (Len) in the first line of therapy. For (1), sites were ranked using the lower 95% confidence interval for the percent of Black MM patients at the site. For (4), only sites with at least five MM patients who received PI and Len were included. Our data sources were: ConcertAI's Electronic Medical Record (EMR) and claims datasets to link each patient to a site, and Google maps API to identify the CAR-T center nearest each oncology site. The patients in our data sets were not identifiable, and our research was conducted in compliance with the Health Insurance Portability and Accountability Act. After having identified and filtered promising sites, we curated individual candidates in the order of Black patient density. The purpose of curation was to validate a final list of sites. Results: We identified 17 promising clinical trial sites affiliated with 16 healthcare systems in the mid-west, mid-Atlantic, southeastern, and southwestern regions of the United States (table 1). Our RWD captured an average of 141 MM patients (range: 6-791) who were treated at the 17 sites from 2015-2020. Thirty-nine percent of the patients were Black (range: 13-67%). This percentage was three times the recruitment rate of black patients in MM trials in the US (13%). On average, the sites were 44 miles driving distance (range: 0.8-96 miles) from the closest CAR-T center, had eight hematology/medical oncology specialists on staff (range: 1-17), and had previous interventional trial experience (13 sites had experience with MM trials). All of the identified sites were community-based sites, and none of the sites were previously identified by our pharmaceutical partner. Conclusions: We demonstrated that RWD can be leveraged to identify clinical trial sites with a high potential for Black patient recruitment, thereby addressing a known health disparity problem within multiple myeloma (MM) clinical trials. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.


2015 ◽  
Vol 145 (10) ◽  
pp. 452-457
Author(s):  
Antonio J. Carcas ◽  
Francisco Abad Santos ◽  
Luis Sánchez Perruca ◽  
Rafael Dal-Ré

JAMIA Open ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Kelly Claire Simon ◽  
Samuel Tideman ◽  
Laura Hillman ◽  
Rebekah Lai ◽  
Raman Jathar ◽  
...  

AbstractObjectivesTo demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design.MethodsWe have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician’s typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI).ResultsWe are successfully collecting structured data, in the context of the providers’ clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun.DiscussionThis proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design.ConclusionThe demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.


2020 ◽  
pp. 174077452095696
Author(s):  
Hailey N Miller ◽  
Jeanne Charleston ◽  
Beiwen Wu ◽  
Kelly Gleason ◽  
Karen White ◽  
...  

Background/aims: Electronic-based recruitment methods are increasingly utilized in clinical trials to recruit and enroll research participants. The cost-effectiveness of electronic-based methods and impact on sample generalizability is unknown. We compared recruitment yields, cost-effectiveness, and demographic characteristics across several electronic and traditional recruitment methods. Methods: We analyzed data from the diet gout trial recruitment campaign. The diet gout trial was a randomized, controlled, cross-over trial that examined the effects of a dietary approaches to stop hypertension (DASH)–like diet on uric acid levels in adults with gout. We used four electronic medical record and four non-electronic medical record–based recruitment methods to identify and recruit potentially eligible participants. We calculated the response rate, screening visit completion rate, and randomization rate for each method. We also determined cost per response, the screening, and randomization for each method. Finally, we compared the demographic characteristics among individuals who completed the screening visit by recruitment method. Results: Of the 294 adults who responded to the recruitment campaign, 51% were identified from electronic medical record–based methods. Patient portal messaging, an electronic medical record–based method, resulted in the highest response rate (4%), screening visit completion rate (37%), and randomization rate (21%) among these eight methods. Electronic medical record–based methods ($60) were more cost-effective per response than non-electronic medical record–based methods ($107). Electronic-based methods, including patient portal messaging and Facebook, had the highest proportion of White individuals screened (52% and 60%). Direct mail to non-active patient portal increased enrollment of traditionally under-represented groups, including both women and African Americans. Conclusion: An electronic medical record–based recruitment strategy that utilized the electronic medical record for participant identification and postal mailing for participant outreach was cost-effective and increased participation of under-represented groups. This hybrid strategy represents a promising approach to improve the timely execution and broad generalizability of future clinical trials.


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