DataRobot for Healthcare and Life Science
Transform Patient Outcomes, Care, and Operations with AI.
AI in Healthcare and Life Science
Amidst an aging global population and record healthcare system costs, DataRobot has helped the world’s largest payers, providers, pharmaceutical companies, and retail pharmacies improve both patients’ lives and the bottom line with AI.
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Reducing Costs with DataRobot at Steward Health
Steward Health Care, the largest for-profit private hospital operator in the United States, uses machine learning to make big decisions about staff and patients, reduce costs, and improve patient outcomes and experiences.
Challenges the Healthcare Industry Face with ML
Increasing Scrutiny and Regulatory Requirements of ML Models
Reporting requirements for models – including ones you didn’t build yourself – are leaving healthcare organizations struggling to quickly and effectively address new regulatory requirements.
Challenges Leveraging Complex Data to Address Health Problems
Endless permutations of patient profile and service delivery as well as data types collected make it difficult to discover meaningful patterns in complex medical and patient data.
Increasing Pace of AI Implementation from Competitors
Competitive pressures are increasing while cycle time is shrinking, increasing the pressure on R&D and operations.
Pressure to Reduce Operating Costs and Maximize Data Investment Impact
The sensitivity of patient care information and complexity of integrating it into key patient operations or applications has made the delivery of real-time, unbiased, and scalable AI-driven care challenging.
Why DataRobot for Healthcare?
Personalized Preventive Care
Factor in social determinants of health (SDOH) in ML models that will help you deliver personalized and preventative healthcare. With DataRobot, you can evaluate proxy variables, analyze insights about their influence on health outcomes, and detect disparate outcomes for protected classes with automated bias and fairness insights. Implement customizable bias mitigation on your models, and monitor bias and fairness measures with MLOps to help prevent the inequality of treatment while leveraging SDOH data.
Easily Handle Varied Healthcare Data to Drive Prescriptive Patient Outcomes
Quickly and easily discover meaningful patterns in complex medical and patient data.
DataRobot allows you to build population, cohort, or patient-level risk models using historical data with automated, time-aware feature engineering. Rapidly prototype models using multiple datasets such as patient data in EHRs, claims, or lab data, and deploy those insights into the hands of practitioners.
Proactively Address Regulatory Requirements
Provide your organization and regulators with transparent model explanations and assessments at the click of a button. Develop compliance documents for all of your models – even external ones developed outside of DataRobot – such as predictions from an EHR model or 3rd party model. With DataRobot data scientists, AI leaders and CIOs can quickly and consistently apply an algorithm risk assessment framework across all of models including automated model and deployment reporting.
Rigorous Protection for Healthcare Data
Tackle the most pressing use cases with your data and your team without worrying about managing the cloud infrastructure and exploding TCO. Deploy and monitor your infrastructure with our Single Tenant SaaS solution to ensure your data stays safe.
Strategic Integrations and Partners
See how our partners utilize DataRobot AI Platform to activate the full potential of healthcare solutions.
Related resources
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