Effectiveness of a Decision Support System in Improving the Diagnosis and Screening Rate of Breast Cancer

NCT01336257 | Unknown

• 1 other identifier: HIBA00019
• Study Type: interventional
• Target: 2,200
• Locations: 1 country
• Sites: 1

Brief Summary

Clinical decision support has been shown to improve the performance of screening tests; however, few studies have documented direct clinical benefit resulting from the increased screening promoted by clinical decision support systems. The purpose of this study was to determine if a standards-based, sophisticated decision support system could not only promote additional breast cancer screening, but also detect significantly more breast cancer

Conditions

Breast Cancer

Keywords

Decision Support Techniques; Electronic Health Records; Reminder Systems; Early Detection of Cancer; Mammography; Women

Outcome Measures

Primary Outcomes (1)

• Number of participants with new Breast Neoplasms Diagnosis (Incident cases)

  New Breast Neoplasms Diagnosis (Incident cases from biopsy reports). Breast Neoplasms are stored in the institutional Clinical Data Repository. The diagnosis are automatically codified using a terminology server that use SNOMED-CT as reference terminology

  18 month

Secondary Outcomes (1)

• Number of patient with breast cancer screening due that received the order to perform the study (mammography)

  18 month

Study Arms (2)

Electronic Reminder

EXPERIMENTAL

alert from SEBASTIAN decision support system

Other: SEBASTIAN Clinical Decision Support System (CDSS)

control

NO INTERVENTION

Interventions

SEBASTIAN Clinical Decision Support System (CDSS) OTHER

SEBASTIAN is an example of a clinical decision support technology that supports the latest, service-based architectural approach to CDSS implementation. Developed at Duke University, SEBASTIAN is a clinical decision support Web service whose interface is now the basis of the HL7 Decision Support Service draft standard SEBASTIAN places a standardized interface in front of clinical decision support knowledge modules and makes only limited demands on how relevant patient data are collected or on how decision support inferences are communicated to end-users

Electronic Reminder

Eligibility Criteria

• Age: 50 Years - 69 Years
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Women between 50 and 69 years old

You may not qualify if:

• Breast Neoplasms
• Bilateral mastectomy
• Disabled Persons

Sponsors & Collaborators

• Hospital Italiano de Buenos Aires: lead
• Duke University: collaborator

Study Sites (1)

Hospital Italiano de Buenos Aires

Buenos Aires, Buenos Aires, 1209, Argentina

RECRUITING

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Study Officials

• Damian A Borbolla, MD

  Hospital Italiano de Buenos Aires

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD

Study Record Dates

• First Submitted: April 14, 2011
• First Posted: April 15, 2011
• Study Start: November 1, 2009
• Primary Completion: June 1, 2011
• Study Completion: June 1, 2012
• Last Updated: April 17, 2012

Record last verified: 2012-04

Locations

AR (1)