AI Cloud for Healthcare

AI Cloud for Healthcare has the power to unlock true value from healthcare system data to optimize patient care, accelerate research in disease prevention and treatment, and accurately forecast staffing and operational needs, while optimizing payer operations — all which saves lives and improves the quality of care for all patients, regardless of socioeconomic status.

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AI in Healthcare

The ability to access and understand patient data and improve health outcomes is stronger than ever before. Stronger data-driven insights are critical for healthcare organizations across the board to confidently respond to the changing dynamics of the social determinants of health, staffing and operations, and disrupted care. AI Cloud for Healthcare gives the ability to harness data to optimize patient care, accelerate research in disease prevention and treatment, accurately forecast staffing and operational needs, optimize financial performance, and enable equitable service provision. The power of machine learning can transform consumer health.

DataRobot Customers Include 30% of the Top Global Healthcare Companies

See how AI Cloud for Healthcare is transforming the industry

AI Use Cases in Healthcare

In the wake of the global pandemic, supply chain disruptions, and tense economic environments around the world, the healthcare industry is facing unprecedented demand for patient and consumer health services alongside historically complex challenges. The healthcare industry needs to find new ways to address critical needs.

predict overpaid medical claims
Predict Overpaid Medical Claims (Fraud, Waste, Abuse)

Predict if a physician is submitting an overpaid claim based on historical data and the drugs they are prescribing.

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predict member or employer disenrollment
Predict Member or Employer Disenrollment

Reduce disenrollment, either on the member or employer level, by predicting ahead of time which are likely to churn.

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predict patient propensity to have certain diseases
Predict Patient Propensity to Have Certain Diseases

Supplement the existing medical diagnostic process to identify high risk patients that may be overlooked.

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predict suicide warning signs
Predict Suicide Warning Signs

Provide a supplementary assessment that helps prevent suicides and save lives by predicting ahead of time who is likely to commit suicide.

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reduce 30 day readmissions rate
Reduce 30-Day Readmissions Rate

Proactively reduce 30-day readmissions rate by predicting in advance which patients are likely to readmit and understanding the top reasons why

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reduce patient length of stay
Reduce Patient Length of Stay

Reduce patient length of stay (LOS) without sacrificing quality of care by understanding the barriers to a timely and effective discharge.

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forecast patient volume to improve staffing
Forecast Patient Volume to Improve Staffing

Census or patient admission forecasting helps healthcare providers optimize their staffing and resource needs.

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improve medical representatives performance
Improve Medical Representatives Performance (i.e. Sellers)

Improve medical rep performance by personalizing approach.

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predict patient nonadherence leakage in provider facilities
Predict Patient Nonadherence / Leakage in Provider Facilities

Foresee which patients are likely to churn before completing their course of care.

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predict churn for clinical trials
Predict Churn for Clinical Trials

Predict churn in order to improve the success rate of clinical trials.

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reduce avoidable returns
Forecast Daily Demand by Store

 Demand forecasting / sales forecasting with AI/ML helps reduce overstocks and out of stocks, helping you optimize your supply chain and working capital.

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identify members who will become high cost claimants
Forecast the Demand of New Products

Forecasting the demand of to-be-launched products enables retailers to optimize inventory, logistics, and working capital, and be better prepared to serve their customers.

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ucsf predicting patient outcomes using or data
Improve In-Store Product Assortment

Remove products predicted to perform poorly to leave a more targeted assortment for your customers.

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DataRobot AI Cloud Partner Ecosystem

See how our partners utilize DataRobot AI Cloud to activate the full potential of healthcare solutions.

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All Partners

demo

AI Cloud for Healthcare Demo: Predicting Hospital Readmissions

See how AI Cloud for Healthcare can be used to solve healthcare challenges such as decreasing the likelihood of patient readmission.

Frequently Asked Questions

  • How is AI used in healthcare?

    Using AI, healthcare organizations can develop and deploy breakthrough preventative treatments, improve medical procedures, and even design new pharmaceutical solutions. According to one global study, 78 percent of businesses, including the healthcare industry, use AI in at least one business unit.

  • What are examples of artificial intelligence in healthcare?

    Three significant areas of impact for AI in healthcare:

    • Social Determinants of Health (SDOH): Predict disease outbreak and spread
    • Staffing and retention: Predict which members (in any capacity, including staff) are at risk of churn and identify opportunities for retention
    • Disrupted care: Identify patients in need of preventative care
  • What are the upcoming tools of artificial intelligence in healthcare?

    Trends in the healthcare industry show AI being leveraged in the following areas:

    • Enhanced Operations
    • Clinical decision support
    • Predictive and prescriptive medicine
    • Funding of care (including payers)
    • Population health
  • What are the Benefits of AI in Healthcare?

    With trusted, explainable AI, healthcare providers can deliver high-impact business results that unify human intuition and machine intelligence to empower confident decision-making. As security, regulatory, and operational challenges keep on growing, stronger insights into data are critical for healthcare professionals to deliver quality patient care.

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