Rational, aims, and objectives: Understanding of barriers and successes associated with the implementation of electronic patient self-reported measures (ePSRMs) within clinical settings are limited and have not been pursued utilizing implementation science frameworks. This qualitative study is designed to assess staff perceptions of an ePSRM implementation. Methods:The study took place in an academic hospital's Consultation Liaison Psychiatry practice. Qualitative interviews were conducted with the staff and clinicians from the practice. Participants were directly involved with the implementation and use of the ePSRM system within the Psychiatry practice. Interviews were structured around the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework. Results:Participants reported increased patient engagement as well as efficiency and time savings. The intervention was perceived to be more challenging for older patients. Facilitators include communicating the ePSRM to patients prior to the care visit, having enough trained staff or super-users who can assist with technical problems, and having a shorter questionnaire. Conclusions:Overall, assessment of the ePSRM implementation was positive. Staff and clinicians indicated benefits in time, effectiveness, and improvements in patient treatment. Results indicate that defining how the system would fit within the clinical workflow was key, as was a flexible and user-friendly technology platform. The ePSRM implementation was dependent upon clinical involvement and interest in adoption, while barriers were associated with technical challenges as well as some patient difficulties, such as cognitive impairment. The use of the RE-AIM framework is valuable as it allows for systematic assessment of the implementation and identifies areas in that implementation has succeeded or is lacking.

Background: Individualized postoperative survival calculators for patients with cancer can be an aid for predicting prognosis and clinical decision making, such as the use of adjuvant chemotherapy. The aim of this study was to compare existing survival calculators for colon cancer and determine their performance using an independent cohort of patients. Methods: A retrospective analysis of a multi-site institutional experience was performed on patients diagnosed with stage II-III colon cancer between January 2012 and March 2013. Patient survival rates were estimated using Roswell Park Comprehensive Cancer Center (RPCCC), Memorial Sloan Kettering Cancer Center (MSKCC), and MD Anderson Cancer Center (MDACC) calculators. These calculators vary in the number and breadth of variables that are included. The agreement between selected models was obtained through a scatter plot matrix and related intra-class correlation coefficient (ICC). Calculators' performances were compared using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC) values. Results: After the application of inclusion and exclusion criteria, a total of 97 patients were included in the analysis. Survival data were available for all patients. Median follow-up was 57.6 months, and the overall 5-year survival rate was 0.74 (95% CI: 0.64-0.82). Overall, the different calculators tended to predict survival similarly (ICC =0.017). However, there was variation among calculator performance with the RPCCC calculator showing the highest performance (AUC =0.913), followed by the MSKCC calculator (AUC =0.803), and the MDACC calculator (AUC =0.644). Conclusions: Prognostic models incorporating a more comprehensive amount of patient and tumor specific variables may provide a more accurate estimate of individual patient survival rates. These tools can be an actual aid in the clinical practice, allowing physicians to personalize treatment and follow-up for patients with colon cancer.