Measurement methods

For data capture, following measurement methods will be used:

Primary outcome measurement will be performed using the Ada-App which will deliver a set of differential diagnoses to a given clinical case.²³ Based on an algorithmic questionnaire and machine learning technologies, the Ada chatbot assesses symptoms of the patient, similar to the anamnestic techniques and clinical reasoning of physicians. Patients’ data are integrated into an extensive knowledge base, which has been specifically designed by medical doctors by incorporating validated disease models and comprehensive medical literature. Then, differential diagnoses are generated and ranked in order considering two features: the probability, based on epidemiological data and the best match between the diagnosis and the given symptoms. Through AI-based methods and multiple feedback loops, the Ada knowledge base grows after each interaction and diagnostic ability improves continuously.

The occurrence of complications as secondary outcomes will be evaluated and analysed according to the CCI.³⁶ The CCI represents the standard assessment of postoperative morbidity and comprises all complications occurring during a patient’s course based on the Clavien-Dindo classification (CDC). Compared with the CDC, which ranks complications based on the severity of the therapeutic consequence and grades them in five levels, the CCI uses a formula to integrate all complications, ranging them from 0 (‘no complication’) to 100 (‘death’).³⁷ This advanced approach enables comparison of patients harbouring more than one complication and takes more subtle differences into consideration.

For assessment of comorbid diseases and frailty-associated risk in a surgical population, we will use the Charlson Comorbidity Index and the RAI-C score.