Problem: Lung cancer is the leading cause of cancer deaths, and lung cancer screening through low-dose CT scans could save more lives than breast cancer screening. However, only about 5% of eligible Americans are screened each year. An important reason for this lack of appropriate screening is that lung cancer screening requires the review of patient-specific benefit and risk information using a decision aid, but such shared decision making is cumbersome without effective decision support tools integrated with the EHR.
Solution: Decision Precision+ is an EHR-integrated decision aid that provides individualized benefit and risk information using state-of-the art risk models from the National Cancer Institute. It is seamlessly integrated with the EHR and enables high-quality shared decision making in busy clinical settings. After deployment at University of Utah Health, the rate of lung cancer screening increased significantly (manuscript in process).
Decision Precision+ is a SMART on FHIR applications that pulls in a wide range of relevant data from the EHR and provides patient-specific guidance on benefits and risks. The tool uses the U.S. Preventive Services Task Force guidelines to determine which patients should be considered for lung cancer screening, then uses lung cancer risk and life expectancy models from the National Cancer Institute (https://dceg.cancer.gov/tools/risk-assessment/lcrisks) to provide patient-specific benefit and risk information. Further guidance on whether screening has high net benefit or is preference sensitive is provided based on work published by Caverly et al. in the Annals of Internal Medicine.
A stand-alone version of the tool, known as Decision Precision, is available to all at https://screenlc.com/. The EHR-integrated version of the tool is also being made available for free through EHR app stores.
The initial development of the standalone Decision Precision tool was funded by the Veterans Administration, with the work led by Dr. Tanner Caverly and Dr. Angie Fagerlin. The subsequent conversion of the tool into the EHR-integrated Decision Precision+ tool was funded by the Agency for Healthcare Research and Quality (R18 HS026198), with the work led by Dr. Kensaku Kawamoto,.
A screenshot of Decision Precision+ is provided below:
FHIR Resources used
Decision Precision+ uses the following FHIR resources:
- Family Member History
Utah Biomedical Informatics Team
Charlene Weir, PhD, RN, FACMI – Professor and Lead of Sociotechnical Expertise Core, Evaluation Director of ReImagine EHR
Claude Nanjo, MPH, MAAS – Senior Clinical Informaticist
Douglas Martin, MD – Senior Clinical Informaticist
Guilherme Del Fiol, MD, PhD, FACMI, Associate Professor and Vice Chair for Research, Research Director of ReImagine EHR
Isaac Warner – Research Assistant
Kensaku (Ken) Kawamoto, MD, PhD, MHS, FACMI, FAMIA – Project PI, Associate CMIO, Associate Professor and Vice Chair for Clinical Research, Director of ReImagine EHR
Phillip Warner, MS – Senior Software Design Engineer
Polina Kukhareva, PhD, MPH – Senior Clinical Informaticist
Salvador Rodriguez, PhD – Software Design Engineer
Teresa Taft, PhD – Operational Director, Sociotechnical Expertise Core
Other University of Utah Collaborators
Angie Fagerlin, PhD – Professor and Chair, Dept. of Population Health Sciences
Chakravarthy Reddy, MBBS – Associate Professor of Pulmonology
Michael Flynn, MD – Community Clinics Associate Medical Director for Research and Clinical Innovation
Rachel Hess, MD, MS – Professor and Chief, Division of Health System Innovation and Research
Yue Zhang, PhD – Associate Professor of Biostatistics
University of Michigan
Tanner Caverly, MD, MPH – Assistant Professor of Learning Health Sciences and Internal Medicine
Pallavi Ranade-Kharkar, MS, PhD, FAMIA – Director of Research Informatics and Precision Health Systems
NY Langone Health
Devin Mann, MD, MS – Senior Director of Informatics and Innovation
Bryn Rhodes – Chief Technology Officer