Using a lay patient navigator to improve care of newly diagnosed underserved patients: An application of the Cognitive-Social Health Information-Processing (C-SHIP) model

Patient navigation has become an important component of quality cancer care, especially for underserved populations. Guided by the cognitive-social health information processing (C-SHIP) model, this demonstration project implemented a theory-driven, bilingual (English-Spanish) patient navigation program in an urban healthcare setting.

Newly diagnosed cancer patients from five sites (breast, cervical, colorectal, prostate, and lung) were recruited, established a baseline and followed to assess their satisfaction and intervention impact on the C-SHIP variables (cognition, expectancy, goals and values, affects, and self-regulatory strategies). Relying on a community-based participatory research principle, a non-clinical navigator model was used to address patient issues and needs. Paired t-tests with Bonferroni adjustments were used to examine the changes in C-SHIP variables and patient's satisfaction over time.

A total of 44 patients enrolled, consented and completed the baseline assessment. Approximately 63% of the patients recruited earned less than $15,000 per year, nearly 82% were women, 82% were African American, and 25% spoke Spanish and had their assessments translated in Spanish. Both affect and self-regulatory scores significantly improved from baseline to 4-weeks. The increase in mean satisfaction scores from 4-weeks to 12-weeks was also significant.

The results of the demonstration project suggest a positive impact on patient satisfaction and the psychosocial load on the patient regarding their cancer diagnosis. Future and larger-scale patient navigation studies should consider the psychosocial impact of cancer on patients and tailor these interventions accordingly.