Implementing USPSTF Recommendations for Breast Cancer Screening and Prevention by Integrating Clinical Decision Support Tools with the Electronic Health Record (Oregon)

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Integrating patient-generated breast cancer risk information with patients’ electronic health records will enhance decision support for clinicians and patients and improve screening and preventive services for patients at risk.

Project Details - Ongoing


Breast cancer is the most common cancer among women in the United States excluding nonmelanoma skin cancer. While clinical recommendations for breast cancer screening and prevention are contingent on age and risk factors, tools to determine eligibility are not widely used in clinical practice. This research develops a method to integrate clinical tools with electronic health records (EHR) to improve breast cancer screening and prevention. The project uses a previously piloted risk tool and clinical decision aid, MammoScreen, developed by the research team that features a web-based application for women ages 40-74. MammoScreen provides individual guidance for patients facing decisions about mammography screening and genetic counseling in accordance with the U.S. Preventive Services Task Force (USPSTF) recommendations. Women enter their personal risk factor data through the application, information is then processed through validated risk algorithms, and clinic-approved messages for next steps are returned to patients based on their personal risk profiles and stated preferences. The decision aid provides numerous informational modules to the user. These include descriptions of types of breast cancer and risk factors using text and pictographs, explanations of mammography procedures and the screening experience, and priority-setting questions that educate users on the benefits and harms of screening. Pilot studies of MammoScreen showed that it was an effective tool for women to identify their individual risks for breast cancer and engage in shared decision making with their clinicians. However, pilot studies also revealed that the web-based application faced interoperability limitations because no risk assessment tools currently available exchange data with a patient’s EHR. Direct integration with the EHR has the potential to provide patient-personalized decision support for both patients and clinicians and, in turn, improve quality of care for women who are at increased risk for breast cancer.

This research will use secure health data methodologies to allow the exchange of data between MammoScreen and the EHR. Patient data from the EHR will be pulled into the tool so that women will not have to enter existing data. Women will be able to identify incorrect and outdated information pulled into the tool, and corrections will be tracked. The resulting risk category (above average risk or average risk) and breast symptoms identified with MammoScreen will then be stored in the EHR for clinician review to guide appropriate care.

The specific aims of the research are as follows:

  • Implement standards-based, safe, secure, interoperable integration of MammoScreen with the EHR. 
  • Evaluate MammoScreen acceptance by patients and clinicians to identify and remove potential barriers to use. 
  • Evaluate use of EHR-integrated MammoScreen by clinicians and patients across age groups and measure clinical outcomes. 

To integrate the informative data from the web-based application of MammoScreen into clinical practice, the research team will use SMART (Substitutable Medical Applications, Reusable Technologies) on FHIR (Fast Healthcare Interoperability Resources) standards, allowing the exchange of data between the external MammoScreen application with the designated EHR. The integration will allow clinicians access to the patient-personalized data and clinical decision support in the MammoScreen application directly from the EHR. The research team will track the acceptance of the MammoScreen data, using analytics from both entities to monitor the uptake in application utilization by patients and information used by clinicians in the EHR. A multi-team implementation strategy will allow for a staggered rollout of the integration among different clinicians, permitting the researchers to observe the baseline breast cancer risk documentation compared to application data from the integration of MammoScreen and the EHR. The research team will measure the use of MammoScreen among patients, observing the application adoption rate among women.

The MammoScreen integration will demonstrate the capability of successful data exchange between decision support applications and EHR systems. Additionally, this research will provide patient and clinical support for prevention decision making at point of care. Research findings from this study will further inform the implementation and use of health information technology applications as a tool to improve the transfer of new evidence into practice and to improve data interoperability across healthcare settings.