A pre-implementation examination of barriers and facilitators of an electronic prospective surveillance model for cancer rehabilitation: a qualitative study

• Main Authors: Christian J. Lopez (Author), Jennifer M. Jones (Author), Kristin L. Campbell (Author), Jackie L. Bender (Author), Gillian Strudwick (Author), David M. Langelier (Author), Tony Reiman (Author), Jonathan Greenland (Author), Sarah E. Neil-Sztramko (Author)
• Format: Book
• Published: BMC, 2024-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12913-023-10445-3; 1472-6963
• Keywords: Implementation; Rehabilitation; Cancer survivorship; Cancer care delivery; Prospective surveillance model; Patient-reported outcomes; Public aspects of medicine; RA1-1270
• Source: BMC Health Services Research, Vol 24, Iss 1, Pp 1-13 (2024)

Abstract Background An electronic Prospective Surveillance Model (ePSM) uses patient-reported outcomes to monitor symptoms along the cancer pathway for timely identification and treatment. Randomized controlled trials show that ePSMs can effectively manage treatment-related adverse effects. However, an understanding of optimal approaches for implementing these systems into routine cancer care is limited. This study aimed to identify barriers and facilitators prior to the implementation of an ePSM to inform the selection of implementation strategies. Methods A qualitative study using virtual focus groups and individual interviews was conducted with cancer survivors, oncology healthcare providers, and clinic leadership across four cancer centres in Canada. The Consolidated Framework for Implementation Research (CFIR) guided the interviews and analysis of barriers and facilitators based on five domains (intervention characteristics, individual characteristics, inner setting, outer setting, and process). Results We conducted 13 focus groups and nine individual interviews with 13 patient participants and 56 clinic staff. Of the 39 CFIR constructs, 18 were identified as relevant determinants to the implementation. The adaptability, relative advantage, and complexity of an ePSM emerged as key intervention-level factors that could influence implementation. Knowledge of the system was important at the individual level. Within the inner setting, major determinants were the potential fit of an ePSM with clinical workflows (compatibility) and the resources that could be dedicated to the implementation effort (readiness for implementation). In the outer setting, meeting the needs of patients and the availability of rehabilitation supports were key determinants. Engaging various stakeholders was critical at the process level. Conclusions Improving the implementation of ePSMs in routine cancer care has the potential to facilitate early identification and management of treatment-related adverse effects, thereby improving quality of life. This study provides insight into important factors that may influence the implementation of an ePSM, which can be used to select appropriate implementation strategies to address these factors.