Effect of a Clinical Trial Alert System on Physician Participation in Trial Recruitment

Embí, Peter J.; Jain, Anil K.; Clark, Jeffrey L.; Bizjack, Susan; Hornung, Richard; Harris, C. Martin

doi:10.1001/archinte.165.19.2272

Cited by 168 publications

(148 citation statements)

References 28 publications

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“…The work in [12,13] presented a clinical trial alert system for a single clinical trial at a US academic healthcare system. The clinical trial was on diabetes.…”

Section: Related Workmentioning

confidence: 99%

“…MEANS is a tool which helps physicians to find eligible patients for their trials, in the case where a patient is found to be ineligible by MEANS, they would also have their case reviewed by a physician-investigator. From the results of the clinical trial alert system [13], we are encouraged to believe that many patients can be automatically ruled out in a timely manner. Depending on the acceptable time frame only about 20% would need further investigation.…”

Section: Additional Streamlining Of the Processmentioning

confidence: 99%

See 1 more Smart Citation

Complications in using automated methods to increase clinical trial accrual

Fefilatyev

Chen

Ivanovskiy

et al. 2010

IJBET

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“…The work in [12,13] presented a clinical trial alert system for a single clinical trial at a US academic healthcare system. The clinical trial was on diabetes.…”

Section: Related Workmentioning

confidence: 99%

Section: Additional Streamlining Of the Processmentioning

confidence: 99%

Complications in using automated methods to increase clinical trial accrual

Fefilatyev

Chen

Ivanovskiy

et al. 2010

IJBET

View full text Add to dashboard Cite

“…While some additional realworld uses of EHR's, such as integrated scheduling of research participant visits and sharing of real-time data on research progress, are likely to be limited by human research protection requirements, the four advantages listed in Table 1 still offer powerful tools for clinical translational research. While some researchers have used EHR resources in their work [23][24][25][26][27], such use of the EHR is in its infancy, and relatively little has been written about how to implement it effectively. Relevant questions that need to be addressed include: What are the challenges that need to be overcome (human, technological, organizational, and financial)?…”

Section: Introductionmentioning

confidence: 99%

Electronic health records as a tool for recruitment of participants' clinical effectiveness research: lessons learned from tobacco cessation

Fraser

Christiansen²,

Adsit³

et al. 2012

Behav. Med. Pract. Policy Res.

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Translating tobacco dependence treatments that are effective in research settings into real-world clinical settings remains challenging. Electronic health record (EHR) technology can facilitate this process. This paper describes the accomplishments and lessons learned from a translational team science (clinic/research) approach to the development of an EHR tool for participant recruitment and clinic engagement in tobacco cessation research. All team stakeholdersresearch, clinical, and IT-were engaged in the design and planning of the project. Results over the first 17 months of the study showed that over one half of all smokers, coming in for any type of clinic appointment, were offered participation in the study, a very high level of adherent use of the EHR. Study recruitment over this period was 1,071 individuals, over 12 % of smokers in the participating clinics. KEYWORDSElectronic health records, Recruitment, Tobacco cessation BACKGROUND While research advances have extended the effectiveness and reach of tobacco dependence treatment over the past two decades, the disjointed process for bringing laboratory advances into clinical practice has often resulted in interventions that yield diminished effects in real world use [1][2][3][4][5]. One approach to address this "translation gap" is to develop and test interventions in real world clinical settings whenever possible. However, research conducted in these settings poses challenges that can compromise internal validity (e.g., reduce the accurate assessment of outcomes) or render the intervention context unrepresentative of real world conditions (e.g., due to burdensome consent processes, confidentiality regulations, and assessment burdens). Despite these limitations, strategies are available that can foster enhanced translation. For instance, in the case of interventions designed for use in healthcare settings, research designs can enhance translation by leveraging existing clinic infrastructure and

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“…A key deterrent to participation is that matching patients to clinical trials is currently a manual, physician-driven process. Automating this process has shown some promising results in terms of increased patient referrals from physicians [2]. However, current efforts at automation require the development of custom applications.…”

Section: Introductionmentioning

confidence: 99%

Matching Patient Records to Clinical Trials Using Ontologies

et al. 2007

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Abstract. This paper describes a large case study that explores the applicability of ontology reasoning to problems in the medical domain. We investigate whether it is possible to use such reasoning to automate common clinical tasks that are currently labor intensive and error prone, and focus our case study on improving cohort selection for clinical trials. An obstacle to automating such clinical tasks is the need to bridge the semantic gulf between raw patient data, such as laboratory tests or specific medications, and the way a clinician interprets this data. Our key insight is that matching patients to clinical trials can be formulated as a problem of semantic retrieval. We describe the technical challenges to building a realistic case study, which include problems related to scalability, the integration of large ontologies, and dealing with noisy, inconsistent data. Our solution is based on the SNOMED CT R ontology, and scales to one year of patient records (approx. 240,000 patients).

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Effect of a Clinical Trial Alert System on Physician Participation in Trial Recruitment

Cited by 168 publications

References 28 publications

Complications in using automated methods to increase clinical trial accrual

Complications in using automated methods to increase clinical trial accrual

Electronic health records as a tool for recruitment of participants' clinical effectiveness research: lessons learned from tobacco cessation

Matching Patient Records to Clinical Trials Using Ontologies

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