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

Low-dose computed tomography is an effective but underused tool for identifying lung cancer

Lung cancer is the leading cause of cancer-related deaths in the United States among both men and women. 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). And while LDCT could reduce lung cancer deaths by about 20 percent, or more than 10,000 lives per year in the United States, its use is pretty abysmal; less than 10 percent of eligible patients are screened using LDCT every year.

Dr. Kensaku Kawamoto and a group of researchers from the University of Utah, the University of Michigan, and Intermountain Healthcare wanted to find a better way to integrate the potentially life-saving screening into clinical workflows. The team adapted a previously developed standalone shared decision-making tool for lung cancer screening called Decision Precision, which is available at https://screenlc.com. This clinical decision support (CDS) tool incorporates the USPSTF guidelines for LDCT screening and provides patient-specific information on the expected benefits and harms of screening, such as false positives that can result in unnecessary biopsies and possible complications. While standalone web-based CDS tools like Decision Precision 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. Further, even when these tools are developed within a specific organization’s electronic health record (EHR) system, they can be difficult to disseminate across different health systems and EHR platforms.

Decision Precision+ is a CDS SMART on FHIR app that improves lung cancer screening

In this followup study, the team adapted Decision Precision into a shareable tool that can be integrated into any EHR system that leverages standards-based interoperability. The new tool, Decision Precision+, is a SMART on Fast Healthcare Interoperability Resources (FHIR) app that 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 studied Decision Precision+ in conjunction with EHR prompts to consider lung cancer screening at University of Utah Health primary care clinics. Through this study, they found that rates of lung cancer screening orders and completion increased remarkably for eligible patients.

“We found that the DP+ and the EHR prompts had a pretty substantial impact. Our rate for screening orders for eligible patients as well as patients getting actually screened both increased over threefold. And in a clinical space, that's considered pretty substantial because we typically see a 5 to 10 percent increase. So, an over 300 percent increase is quite promising.”- Dr. Kensaku Kawamoto

Additional research is improving and scaling DP+

Decision Precision+ is now offered to healthcare organizations as a free tool that can be downloaded and used within any EHR system that supports the SMART on FHIR framework. Already, adoption of the CDS tool is in process with multiple healthcare systems. In addition, Dr. Kawamoto has received followup funding from AHRQ to further improve DP+ and promote real-world dissemination and implementation of the tool. The followup research is using a user-centered design approach to supplement DP+ with a patient-facing SMART on FHIR application called MyLungHealth. The app integrates with patient portals and can be used directly by patients so they can learn about lung cancer screening and review their individualized estimates of the benefits of screening. In addition, the researchers are studying how best to help other health systems implement these tools and developing self-service resources to assist with implementation. By doing so, this research will widely disseminate patient-centered tools to help improve lung cancer screening at scale and reduce lung cancer deaths.