Differences in cancer pain are profound and uniquely harmful among some cancer survivors as they may undermine their already limited ability to access, tolerate, and/or receive treatment for their cancer. Differences relate to poor care, needless persistence and intense pain, as well as the over- and under-prescribing of opioids. Multi-modal pain care (MMPC), a robustly validated, safer, and more effective alternative to a solely medication-based approach has proven challenging to implement broadly, and virtually impossible in resource limited and isolated settings. The factors that impede delivery of MMPC; provider bias, patients’ reluctance to report pain, and lack of patient-centered MMPC options, also mediate differences making them key targets for improvement. The Collaborative Care Model (CCM) provides a well-established and validated framework that can neutralize factors that perpetuate differences, guide MMPC delivery, and improve pain detection and treatment. However, as currently configured the CCM’s single symptom emphasis needs to be modified to address the multi-level drivers of pain. Our team has developed and tested CCM iterations that integrate elements of team-based care (TBC) to improve the CCM’s monitoring of patients’ needs, as well as to accommodate MMPC’s multi-disciplinary care requirements. In addition, we have leveraged electronic health records (EHRs) to enable care teams to link symptomatic cancer patients with MMPC providers and resources. Our prior research deploying CCM-TBC hybrid interventions with patient-and-care team-centered EHR-reengineering has also significantly improved patient symptom reporting and deployment of MMPC. These efforts, while fruitful, have also shown us that a broader EHR retrofitting is required to address the breadth of patients’ needs and the requirements of real-world clinical workflows. This experience suggests that a flexible, modular CCM-TBC hybrid system, supported by EHR enablement, can deliver high fidelity MMPC in a manner that improves care and pain symptom experiences at multiple levels among cancer survivors. We plan to evaluate the effectiveness of this approach in a clinical trial entitled “Advancing Safe, Comprehensive, Digitally-Enabled Cancer Pain managemeNT (ASCENT).” More specifically, we will partner with our community stakeholders during an initial, 1-year R61 development phase to refine a patient-centered version of our CCM-TBC hybrid that addresses the needs and preferences of cancer survivors most susceptible to poor pain outcomes (Aim 1). After confirming the functionality of the intervention’s components, we plan to transition to a 4-year R33 execution phase with a 2-arm, parallel group randomized clinical trial. This trial (Aim 2) will be conducted in 4 semi-autonomous Health Care Systems and is designed to assess whether our tailored/personalized CCM-TBC hybrid intervention improves pain outcomes relative to usual care among 578 survivors susceptible to poor pain outcomes. Primary (pain) and secondary (mood, sleep, physical function, work status, and healthcare utilization) outcomes will be assessed at 0, 3, and 6 months. All data, excepting patient reported outcome measures, will be extracted from the EHR for main effects, as well as exploratory mediator and machine learning analyses; the latter to identify characteristics associated with positive responses. Aim 3 will evaluate implementation strategies to support multistakeholder adoption and use of intervention components.
