Alga : a cancer patient profiling tool to improve physician-patient communication. an analysis in breast cancer patients

Background: Considerable improvement of communication between physicians and patients (pts) will need to occur as personalised medicine becomes the norm. An accurate profile of the pt’s cognitive and psychological status should help the physician shape his language and his messages to maximise the pt’s understanding of her management options. To this aim a computerized tool (ALGA questionnaire) has been created and validated. Methods: The validation process produced a questionnaire with 4 main factors: Health State Perception, Psychological, Psychosocial and Cognitive aspects. To test its ability to discriminate between healthy people and pts, ALGA has been administered to 50 newly diagnosed primary Breast Cancer (BC) pts prior to their first visit with the oncologist to discuss their adjuvant treatment, and to 50 healthy women (age range:20-60), using an iPad. Results: A multivariate analysis showed a significant difference between BC pts and healthy women relatively to the four aforementioned broad areas: Psychosocial (F(1,56)=13.42, p<.001), Cognitive (F(1,56)=6.53, p<.01), and Psychological Aspect (F(1,56)=2.77, p=.05). ALGA detected pts with higher levels of anxiety and depression. Pts tended to ruminate more than healthy subjects. Finally, pts showed higher level of positive Health State Perception, suggesting a dissociation between cancer illness and general health. Cognitive and Psychological aspects and Health State Perception interacted with participants’ level of education (respectively: F(1,56)=12.23, p<.001; F(1,56)=4.58, p<.05; F(1,56)=7.9, p<.05). Starting from this results a personal profile for each pt was created. Conclusions: The ALGA confirmed ability to discriminate between healthy people and BC pts, and is a good tool to create a personal pt’s profile with which physicians can empower patient with tailored knowledge. Starting from ALGA questionnaire, a smart environment is being implemented as a decision support infrastructure to help communication, interaction and information delivery process from doctor to patient, influencing patient’s quality of life and satisfaction