Using clinical algorithms to identify psychosocial distress and other risk factors in cancer survivors.

Abstract

242 Background: Late effects, such as pain and fatigue, increase a cancer survivors' risk to psychosocial distress. Assessment and identification of distress and other risk factors can be integrated into survivorship care. Yet, clinical tools and processes needed to coordinate these efforts are severely limited. Here we describe the processes and metrics used to assess and document distress in the survivorship care plans (SCPs) of survivors diagnosed with colon and rectal cancers (CC and RC). Methods: Eligibility criteria for this longitudinal analysis included being: ≥ 18 years, diagnosed with a primary colon/rectal cancer, no evidence of disease ≥ 5 years, seen between 09/01/2011 - 8/31/2014, and alive at time of data abstraction. 117 survivors met these criteria and the first 50 sequential cases were included in this sub-analysis. Data were collected at Visits 1, 2, and 3 within specific time parameters. Data sources included the SCP, electronic medical records (EMRs), and CC/RC algorithms. Variables included demographic/clinical characteristics and standards of care (SOC) elements embedded in the algorithm related to distress, fatigue, pain, and social support. Compliance with SOC were measured using a “yes/no” response format. Results: Of 50 survivors, 58% were diagnosed with CC and 42% with RC. 52% were male, 64% Caucasian, 54% age 65-89 years, and 68% were 5-9 years from diagnosis. 52% of CC survivors were Stage IIIA-C or IV and 57% of RC were Stage 1-IIB. Documentation and metrics for each element indicated a total of 111 visits over the course of the analysis, 59% were CC and 42% RC. Provider's compliance rates (PCRs) were: distress (65%), fatigue (32%), pain (68%), and social support (46%). The pain element was not included in the CC algorithm. PCRs for each element varied by site. Evidence that providers followed algorithms' recommdendations to assess survivors current risk of distress was found in the EMRs, SCPs. Conclusions: We found cancer survivorship clinical algorithms and care plans can guide assessment, documentation, and monitoring of psychosocial assessment. Screening for risk factors to distress in cancer survivors can be done in real time and help identify at-risk survivors during their visit.