Tempus Next
Intelligence

Clinical intelligence solutions for oncology life sciences.

AI-powered clinical intelligence

Tempus Next Intelligence for oncology life sciences is an AI-powered platform that leverages unstructured and structured data, allowing life sciences companies access to a near-real time, granular, de-identified view of patient journey data.

 

Access comprehensive and actionable insights from a continually growing dataset, empowering teams to monitor guideline adherence, identify and quantify care gaps, and make data-driven decisions to accelerate oncology programs.

Next Intelligence Actionable Insights

Transform complex, real-world data into actionable insights

 

AI-powered platform designed to surface deep insights from multi-modal and longitudinal patient data, extracting relevant clinical data to contextualize demographic, clinical, health system, and geographic details around care gap occurrence.

Flowchart for diagnosing and staging Non-Small Cell Lung Cancer (NSCLC) patients.Flowchart for diagnosing and staging Non-Small Cell Lung Cancer (NSCLC) patients.

Access a dynamic view of the patient journey

 

Dynamic and granular view of testing, treatment adherence, and care gaps, providing insight into the state of guideline-directed precision medicine and gaining an unbiased understanding of patient journeys.

A digital dashboard presenting data insights through various bar charts, a donut chart, and a funnel chart.A digital dashboard presenting data insights through various bar charts, a donut chart, and a funnel chart.

Advance equitable access to care

 

Next Intelligence helps improve timely and accurate diagnostics, procedures and therapies for patients, regardless of socioeconomic status. This analysis helps identify testing disparities and specific barriers to support health equity research.

Line graph comparing days to clinical follow-up for rural and urban populations over time.Line graph comparing days to clinical follow-up for rural and urban populations over time.

Figure: In this study, black patients saw a larger decrease in average time from index echo to follow up (120 vs 64 days) compared to white patients (57 to 36 days), showing the improvement in black patients’ time to follow up towards the average seen in white patients’ (narrowing the gap).

 

Horde G, Sotelo M, D’Amico A, et al. Use of an echocardiographic-based, artificial intelligence system to improve racial disparities in care of patients with valvular heart disease. European Heart Journal – Cardiovascular Imaging. 2023;24(Suppl 1):38.3.

Resources

This is AI-enabled precision medicine

This is the future of healthcare.