R.D. Bell1,2,3,4, J.E. Williams3,4, R.C. Jacobs1,2,3,4, J. Howlett3, L.A. Szczygiel3,4, M.A. Byrnes3,4, D.D. Odell3,4 1Feinberg School Of Medicine – Northwestern University, Surgery, Chicago, IL, USA 2Feinberg School Of Medicine – Northwestern University, Northwestern Quality Improvement, Research, And Education In Surgery (NQUIRES), Chicago, IL, USA 3University Of Michigan, Center For Healthcare Outcomes And Policy, Ann Arbor, MI, USA 4University Of Michigan, Surgery, Ann Arbor, MI, USA
Introduction:
Lung cancer surveillance post-surgery has become more common with earlier-stage disease detection. This process usually involves chest CTs, assessing physical and respiratory function, and promoting smoking cessation. However, adherence to these guidelines is low, particularly among minority, rural, and low-income populations. This project seeks to improve adherence through a patient-centered remote surveillance approach using telehealth and patient-reported outcomes (PROs).
Methods:
Using the Consolidated Framework for Implementation Research (CFIR) and Exploration, Preparation, Implementation, Sustainment (EPIS) frameworks, a model for developing and testing a Decision Aid for a Remote Telehealth User-Reported Cancer Surveillance (RETURNS) Program was constructed. User-centered design (UCD) principles will be employed to develop/test this model. The framework aims to develop and test the decision aid.
Results:
Data collection is ongoing. Results from Phase 1 are crucial for creating and optimizing the Decision Aid. Subsequent phases will test/refine the Decision Aid, evaluating its impact on surveillance adherence, patient and clinician satisfaction, and reduction of disparities.
In Phase 1, initial qualitative interviews with surgeons have shown that remote surveillance is acceptable, though there are concerns about patient access to technology and using PROs to make health decisions. This phase focuses on assessing barriers and facilitators for remote surveillance among patients, caregivers, and clinicians at five diverse hospitals. Data from these assessments will inform the design and optimization of a user-centered Decision Aid to select appropriate patients for remote surveillance, ensuring the program meets diverse end-user needs.
Phase 2 employs UCD and implementation science principles to develop and optimize the Decision Aid. This aid will guide patient selection for remote surveillance, considering factors such as travel barriers, clinical status, and patient preferences. The optimized workflow will facilitate remote PRO collection, asynchronous CT review, and telehealth visits, aiming to improve patient and clinician satisfaction.
Phase 3 will evaluate the effectiveness of the remote surveillance program through a pragmatic hybrid trial across five thoracic surgery clinics. The trial will assess adherence to surveillance guidelines, early detection of recurrence, disparities in surveillance, patient and clinician satisfaction, and cost-effectiveness compared to standard practice.
Conclusion:
This project integrates remote surveillance with PROs and telehealth to enhance lung cancer surveillance adherence, reduce disparities, and improve care quality for survivors, with an emphasis on shared decision-making.