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

50 Years
69 Years
Open (Enrolling)
Breast Cancer

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Trial Information

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

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

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.

Inclusion Criteria:

- Women between 50 and 69 years old

Exclusion Criteria:

- Breast Neoplasms

- Bilateral mastectomy

- Disabled Persons

Type of Study:


Study Design:

Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Diagnostic

Outcome Measure:

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

Outcome Description:

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

Outcome Time Frame:

18 month

Safety Issue:


Principal Investigator

Damian A Borbolla, MD

Investigator Role:

Principal Investigator

Investigator Affiliation:

Hospital Italiano de Buenos Aires


Argentina: Human Research Bioethics Committee

Study ID:




Start Date:

November 2009

Completion Date:

June 2012

Related Keywords:

  • Breast Cancer
  • Decision Support Techniques
  • Electronic Health Records
  • Reminder Systems
  • Early Detection of Cancer
  • Mammography
  • Women
  • Breast Neoplasms