Cognizant’s Patient Health Insights Suite , hosted on AWS, is a multi-user analytics and insights platform for clinical and real-world evidence data, running a suite of interactive self-service applications for comprehensive visual, exploratory, and predictive/prescriptive analyses of patient care and health insights by means of advanced AI and machine learning algorithms. Using the generated insights, the interactive nature of the applications offers new possibilities to scientists, clinicians, and healthcare professional and service providers for knowledge-discovery, computer-assisted diagnosis, and automated decision support in context of Precision Health and P4* Medicine (*predictive, preventative, personalized, and participatory). Patient Health Insights Suite allows ingesting a broad range of clinical and real-world observational health data and is tested on open-access, synthetic, and randomized patient treatment data, electronic medical/health records, medical imaging data, laboratory test data, and physician notes with de-identified patient information. Its user applications were applied to and tested on a wide range of use cases and different disease areas, e.g., cardiovascular diseases (patient stratification, treatment adherence, switch prediction), diabetes mellitus and hypertension (co-medication interaction, adverse event detection, comorbidity prediction), breast cancer (patient stratification, risk prediction, treatment outcomes), lung cancer and tuberculosis (symptom detection and disease classification), diabetic retinopathy (disease classification). Patient Insights Suite can process any health condition captured with a diagnosis code (SNOWMED-CT or ICD 10) in the analyzed health data. That is, the insights generating functionalities of the user applications in Patient Insights Suite (by means of visual, exploratory, and predictive/prescriptive analyses of health data) are equally applicable to every health problem and disease of interest to the user. Patient Health Insights Suite is meant to improve Precision Health and P4 Medicine-related services via a suite of applications that can be used by scientists, clinicians, and healthcare professional for following purposes:

• Patient health feature analysis and stratification
• Cohort generation and comparative analysis
• Image recognition and disease classification
• Composite risk score and severity prediction
• Disease onset and progression prediction
• Treatment adherence and switch prediction
• Drug-disease and co-medication interactions
• Comorbidity and adverse event detection
• Treatment pathways and outcome prediction
• Concept: personalized treatment recommendation
• Geo-mapping and statistical care site profiling
• Managing and converting data in OMOP-CDM

It should be noted that the reliability of the generated insights depends on the achievable results of the used AI and machine learning algorithms within the applications. These results depend on the quality and quantity of the analyzed patient data, on the accuracy, relevance, validity, number of samples, completeness, and consistency of the captured health and medical information.