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

The recruitment status of this study is unknown. The completion date has passed and the status has not been verified in more than two years.
Verified April 2012 by Hospital Italiano de Buenos Aires.
Recruitment status was:  Recruiting
Duke University
Information provided by (Responsible Party):
Damian Borbolla, Hospital Italiano de Buenos Aires Identifier:
First received: April 14, 2011
Last updated: April 13, 2012
Last verified: April 2012

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

Condition Intervention
Breast Cancer
Other: SEBASTIAN Clinical Decision Support System (CDSS)

Study Type: Interventional
Study Design: Allocation: Randomized
Intervention Model: Single Group Assignment
Masking: Open Label
Primary Purpose: Diagnostic
Official Title: Effectiveness of a Decision Support System in Improving the Diagnosis and Screening Rate of Breast Cancer

Resource links provided by NLM:

Further study details as provided by Hospital Italiano de Buenos Aires:

Primary Outcome Measures:
  • Number of participants with new Breast Neoplasms Diagnosis (Incident cases) [ Time Frame: 18 month ]
    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

Secondary Outcome Measures:
  • Number of patient with breast cancer screening due that received the order to perform the study (mammography) [ Time Frame: 18 month ]
    Number of patient with breast cancer screening due that received the order to perform the study (mammography). This information will be record through the clinical data repository every time that a provider order a screening test to each of the patients involve in the study

Estimated Enrollment: 2200
Study Start Date: November 2009
Estimated Study Completion Date: June 2012
Primary Completion Date: June 2011 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
Experimental: Electronic Reminder
alert from SEBASTIAN decision support system
Other: SEBASTIAN Clinical Decision Support System (CDSS)
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
No Intervention: control

Detailed Description:

Breast cancer is the most common female cancer. In the United States, the second most common cause of cancer death in women, and the main cause of death in women ages 45 to 55 years old. The U.S. Preventive Services Task Force recommends screening mammography, with or without clinical breast examination, every one to two years among women aged 50 to 69 years old.

Recent research has shown that health care delivered in industrialized nations often falls short of optimal, evidence based care. US adults receive only about half of recommended care. To address these deficiencies in care, health-care organizations are increasingly turning to clinical decision support systems. A clinical decision-support system is any computer program designed to help health-care professionals to make clinical decisions. In a sense, any computer system that deals with clinical data or knowledge is intended to provide decision support.

Examples include manual or computer based systems that attach care reminders to the charts of patients needing specific preventive care services and computerized physician order entry systems that provide patient-specific recommendations as part of the order entry process. Such systems have been shown to improve prescribing practices, reduce serious medication errors, enhance the delivery of preventive care services, and improve adherence to recommended care standards.

The aim of this study is to show the efficacy of a decision-support system as a strategy for improving the performance of the mammography care process and the detection of significantly more breast cancer.


Ages Eligible for Study:   50 Years to 69 Years   (Adult, Senior)
Sexes Eligible for Study:   Female
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  • Women between 50 and 69 years old

Exclusion Criteria:

  • Breast Neoplasms
  • Bilateral mastectomy
  • Disabled Persons
  Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its identifier: NCT01336257

Hospital Italiano de Buenos Aires Recruiting
Buenos Aires, Argentina, 1209
Contact: Ana M Gomez, MD    541149590200 ext 5398   
Sponsors and Collaborators
Hospital Italiano de Buenos Aires
Duke University
Principal Investigator: Damian A Borbolla, MD Hospital Italiano de Buenos Aires
  More Information

Responsible Party: Damian Borbolla, MD, Hospital Italiano de Buenos Aires Identifier: NCT01336257     History of Changes
Other Study ID Numbers: HIBA00019
Study First Received: April 14, 2011
Last Updated: April 13, 2012

Keywords provided by Hospital Italiano de Buenos Aires:
Decision Support Techniques
Electronic Health Records
Reminder Systems
Early Detection of Cancer

Additional relevant MeSH terms:
Breast Neoplasms
Neoplasms by Site
Breast Diseases
Skin Diseases processed this record on May 22, 2017