Decision Precision+: Increasing Lung Cancer Screening for At-Risk Patients

Widely disseminating a CDS tool that supports individualized shared decision making for lung cancer screening is expected to increase appropriate screening and save lives.

Principal Investigator: Kawamoto, Kensaku

Organization: University of Utah

Research Profile: Scalable Decision Support and Shared Decision Making for Lung Cancer Screening

Funded Amount: $1,184,380

An effective, but underused screening for identifying early stage lung cancer

Lung cancer is the leading cause of cancer-related death in the United States. Screening for lung cancer using low-dose computed tomography (LDCT) is effective in early detection of lung cancer among individuals with a history of heavy smoking and is recommended by the U.S. Preventive Services Task Force (USPSTF). Yet, less than 5 percent of eligible patients are screened using LDCT every year. Increasing use of LDCT for at-risk patients could prevent as many as 10,000 lung cancer deaths annually. However, the decision to screen requires a risk-benefit discussion between patients and their physicians, as false positives can result in unnecessary biopsies and possible complications. Dr. Kensaku Kawamoto and a group of researchers from the University of Utah, the University of Michigan, and Intermountain Healthcare are examining ways to integrate this life-saving screening into clinical workflow.

CDS can improve lung cancer screenings

Study co-investigators Tanner Caverly and Angie Fagerlin previously led the development of a standalone shared decision making tool for lung cancer screening called Decision Precision. This CDS tool incorporates the USPSTF guidelines for LDCT screening and provides patient-specific information on the expected benefits and harms of screening. When used in eight Veterans Health Administration medical centers, decision-making improved about LDCT screenings among at-risk patients. While standalone, web-based CDS tools may enable clinicians to more easily personalize screening, they are also limited by a lack of workflow integration and often require duplicate data entry, thus increasing provider burden and limiting the tool’s usefulness.

The data is there [in the EHR]. We need to figure out how to intelligently mine the data to get the right information to providers at the points of care for shared decision making with patients.”

– Dr. Kawamoto

Integrating and scaling an effective CDS tool into clinical workflow

Dr. Kawamoto and his colleagues are adapting Decision Precision into a shareable tool that can be integrated into any EHR system. This new tool, Decision Precision+, pulls data from the EHR to enable providers to have an individualized risk-benefit discussion with at-risk patients on whether lung cancer screening is right for them. The team’s goal is for patients and their providers to engage in informed, shared decision making regarding this potentially lifesaving test. Dr. Kawamoto and his colleagues feel strongly about sharing and scaling effective CDS. The team plans to integrate Decision Precision+ into multiple EHR systems and make the tool available to other health systems.