Other Titles

Strategies for Early Diagnosis and Treatment of Patients with Ovarian Cancer: A Quality Assurance Project Proposing a Clinical Decision Support System to Advance Health Equity in Ovarian Cancer Care [Title Slide]

Abstract

Background/Purpose: Ovarian cancer remains the leading cause of death among gynecologic malignancies, largely due to delayed diagnosis. Rural clinics face unique challenges, including limited access to specialists and diagnostic tools. This DNP quality assurance project aimed to evaluate and improve providers’ strategies for the timely diagnosis and treatment of ovarian cancer within a rural gynecology clinic serving women at increased risk for delayed detection and mortality.

Methods/Design: Using Avedis Donabedian’s structure-process-outcome framework, a retrospective chart review assessed adherence to evidence-based diagnostic and treatment practices. Findings informed the implementation of a Clinical Decision Support System (CDSS) integrated into provider workflows. Educational sessions, standardized algorithms, and audit-feedback cycles promoted provider engagement and fidelity to guidelines.

Results/Findings: Post-implementation data demonstrated improved timeliness of diagnostic testing, earlier stage identification, and reduced treatment initiation delays. Provider compliance with guideline-based care increased markedly. Qualitative feedback revealed greater confidence in managing nonspecific ovarian cancer symptoms, leading to more consistent referrals and improved continuity of care.

Implications for Practice/Education/Research: The CDSS intervention supported earlier diagnosis, improved provider decision-making, and advanced equity in women’s cancer care—especially among Black and rural populations disproportionately affected by late detection. Findings underscore the value of decision-support tools and interprofessional collaboration in promoting quality and safety outcomes consistent with the AACN 2021 Essentials domains of Systems-Based Practice and Quality & Safety. This project provides a scalable model for national and global application in women’s health equity initiatives.

Notes

Presenter notes available in attached slide deck. To see the notes in Adobe Acrobat, go to Tools > Comment or look at your Layers Panel. If the notes were saved as comments or layers, you can toggle them visible. 

Reference list attached as separate file.

Description

This DNP quality assurance project implemented a clinical decision support system (CDSS) to improve timely diagnosis and treatment of ovarian cancer in a rural gynecology clinic. Guided by Donabedian’s framework, the intervention enhanced provider adherence to evidence-based algorithms, increased early detection, and reduced diagnostic delays, advancing health equity among underserved women.

Author Details

Petrina N. Harrison, DNP, APRN, AGCNS-BC, CIC

Sigma Membership

Gamma Kappa

Type

Presentation

Format Type

Text-based Document

Study Design/Type

Quality Improvement

Research Approach

Other

Keywords:

Ovarian Cancer, Clinical Decision Support System, Donabedian Framework, Health Equity

Conference Name

37th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Toronto, Ontario, Canada

Conference Year

2026

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

Date of Issue

2026-07-24

Click above link to access the slide deck.

Additional Files

References.pdf (100 kB)

Share

COinS
 

Strategies for Early Diagnosis and Treatment of Patients with Ovarian Cancer

Toronto, Ontario, Canada

Background/Purpose: Ovarian cancer remains the leading cause of death among gynecologic malignancies, largely due to delayed diagnosis. Rural clinics face unique challenges, including limited access to specialists and diagnostic tools. This DNP quality assurance project aimed to evaluate and improve providers’ strategies for the timely diagnosis and treatment of ovarian cancer within a rural gynecology clinic serving women at increased risk for delayed detection and mortality.

Methods/Design: Using Avedis Donabedian’s structure-process-outcome framework, a retrospective chart review assessed adherence to evidence-based diagnostic and treatment practices. Findings informed the implementation of a Clinical Decision Support System (CDSS) integrated into provider workflows. Educational sessions, standardized algorithms, and audit-feedback cycles promoted provider engagement and fidelity to guidelines.

Results/Findings: Post-implementation data demonstrated improved timeliness of diagnostic testing, earlier stage identification, and reduced treatment initiation delays. Provider compliance with guideline-based care increased markedly. Qualitative feedback revealed greater confidence in managing nonspecific ovarian cancer symptoms, leading to more consistent referrals and improved continuity of care.

Implications for Practice/Education/Research: The CDSS intervention supported earlier diagnosis, improved provider decision-making, and advanced equity in women’s cancer care—especially among Black and rural populations disproportionately affected by late detection. Findings underscore the value of decision-support tools and interprofessional collaboration in promoting quality and safety outcomes consistent with the AACN 2021 Essentials domains of Systems-Based Practice and Quality & Safety. This project provides a scalable model for national and global application in women’s health equity initiatives.