Optimization of electronic screening in clinical research practice

Garfield, Jared (2017) Optimization of electronic screening in clinical research practice. Master Essay, University of Pittsburgh.

	Microsoft Word Submitted Version Available under License : See the attached license file. Download (433kB)
	Plain Text (licence) Available under License : See the attached license file. Download (1kB)

Abstract

The problem that this essay addresses is that electronic platforms currently implemented across Allegheny Health Network (AHN) are not being optimized for clinical research subject identification and retention.The goals of my summer residency with the Allegheny Health Network Research Institute (“AHN Research Institute”) directed my master’s essay work. National best practices were a guideline to catalog existing subject recruitment practices and utilize new technologies to more efficiently identify and retain enrollees in clinical trials. The objectives of my work are three-pronged: 1) gauge the effectiveness of Epic as a screening tool before and after implementation of an “out of the box” clinical trials feasibility tool - SlicerDicer; 2) assess areas to improve subject/volunteer identification for recruitment within the EHR; and 3) analyze clinical research coordinator attitudes about Epic and CTMS as a whole. The study design is a pilot study, a pre-/post-interventional quantitative survey to measure research study coordinator perceptions of the observed interventions aimed to optimize electronic screening and other clinical research capabilities. Secondarily, qualitative responses were collected to help guide my recommendations and next steps to interventions post-implementation. The method of analysis was primarily quantitative with average scores calculated for each pre- and post-survey question with sporadic qualitative responses utilized when appropriate to supplement quantitative responses. Opinions concerning ease of screening, accurate identification of applicable study patients, and perception of Epic improved after introduction to SlicerDicer, while perception of time spent screening patients improved as well. Conclusions from the study are that SlicerDicer was effective in significantly positively shifting the attitudes of Allegheny Health Network clinical research coordinators regarding ease of screening and identifying applicable patients for research studies, while solidifying Epic’s standing as an effective electronic health record. This issue is of public health significance because optimizing recruitment methods to clinical trials will ultimately forge new medical frontiers: new interventions to surgery, investigational pharmaceuticals, implantable and wearable devices, biospecimen collection, and diagnostic technologies. While increasing patient accruals to these therapeutic areas will have a direct and largely positive impact on the future delivery of health care, resources remain scarce. Physician investigators’ time needs to be efficiently managed and the dedicated team of public health trained staff will be charged with developing and deploying the very resources and optimization methods outlined in this analysis.

---

Share

Citation/Export:	Select format... Citation - Text Citation - HTML Endnote BibTex Dublin Core OpenURL MARC (ISO 2709) METS MODS EP3 XML Reference Manager Refer
Social Networking:	Share |

---

Details

Item Type:	Other Thesis, Dissertation, or Long Paper (Master Essay)
Status:	Unpublished
Creators/Authors:	Creators Email Pitt Username ORCID Garfield, Jared jlg180@pitt.edu JLG180
Contributors:	Contribution Contributors Name Email Pitt Username ORCID Committee Chair Roberts, Mark S. mroberts@pitt.edu MROBERTS UNSPECIFIED Committee Member Fischer, Gary fischerg@upmc.edu UNSPECIFIED UNSPECIFIED Committee Member Bird, Kyle Kyle.Bird@ahn.org UNSPECIFIED UNSPECIFIED
Date:	2017
Date Type:	Publication
Publisher:	University of Pittsburgh
Institution:	University of Pittsburgh
Schools and Programs:	School of Public Health > Health Policy & Management
Degree:	MPH - Master of Public Health
Thesis Type:	Master Essay
Refereed:	Yes
Date Deposited:	17 Jul 2017 19:36
Last Modified:	01 Sep 2023 10:55
URI:	http://d-scholarship.pitt.edu/id/eprint/31177

---

Metrics

Monthly Views for the past 3 years

Plum Analytics

---

Actions (login required)

View Item