Healthcare

Healthcare is an industry in transition. Increasing pressure to deliver better care with lower costs is driving healthcare providers to invest in intelligent solutions that will inform their clinical, operational, and financial decisions. An AI-driven enterprise allows healthcare organizations to transform billions of data points into insights and predictions that improves quality of care and ultimately saves lives.

See how AI is transforming the healthcare industry.

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AI in Healthcare

Our mission is to help healthcare organizations, payers, and their partners use AI technology to help improve outcomes, streamline operations, identify financial risks, and retain their most valuable health consumers (patients, members, employees). DataRobot can work with you to turn your ever-increasing volumes of data into cutting edge insights and predictions that will drive cost saving clinical, operational, and financial decisions across your enterprise.

Payers

Be a leader in CAHPS, HEDIS, and Medicare Star quality ratings with superior healthcare analytics
Determine which members are at risk of leaving your health plan
Improve risk adjustment and capture the best target opportunities
Flag potential fraudulent claims
Build precise financial, actuarial, and underwriting models for cost of care, IBNR, MLR, large claims forecasting, and premium pricing models
Use analytics to understand member hospital inpatient length of stay and risk for readmission

Providers

Build more precise patient readmission risk models
Optimize your revenue cycle management and revenue prediction
Accurately forecast staffing needs with predictive analytics in healthcare
Actively manage your patient population health and accurately stratify your patient population risk
Use analytics to understand patient length of stay and patients at risk for hospital-acquired conditions
Be a leader in value-based healthcare

Vendors

Leverage predictive analytics to optimize your patient marketing campaigns, messaging, and call center operations
Increase renewals and reduce customer turnover while actively managing the efficiency of your sales force
Forecast product sales more accurately
Build more effective patient/customer messaging
Optimize your patient/customer messaging
Integrate AI-driven insights into clinical solutions, patient engagement applications, and healthcare operating systems
Be a leader in supply and demand chain planning with exceptional analytics

Payers
- Be a leader in CAHPS, HEDIS, and Medicare Star quality ratings with superior healthcare analytics
- Determine which members are at risk of leaving your health plan
- Improve risk adjustment and capture the best target opportunities
- Flag potential fraudulent claims
- Build precise financial, actuarial, and underwriting models for cost of care, IBNR, MLR, large claims forecasting, and premium pricing models
- Use analytics to understand member hospital inpatient length of stay and risk for readmission
Providers
- Build more precise patient readmission risk models
- Optimize your revenue cycle management and revenue prediction
- Accurately forecast staffing needs with predictive analytics in healthcare
- Actively manage your patient population health and accurately stratify your patient population risk
- Use analytics to understand patient length of stay and patients at risk for hospital-acquired conditions
- Be a leader in value-based healthcare
Vendors
- Leverage predictive analytics to optimize your patient marketing campaigns, messaging, and call center operations
- Increase renewals and reduce customer turnover while actively managing the efficiency of your sales force
- Forecast product sales more accurately
- Build more effective patient/customer messaging
- Optimize your patient/customer messaging
- Integrate AI-driven insights into clinical solutions, patient engagement applications, and healthcare operating systems
- Be a leader in supply and demand chain planning with exceptional analytics

High Value Use Cases In Healthcare

There are a multitude of clinical, operational, and financial risk use cases for healthcare organizations, payers, and providers. The potential to dramatically reduce the cost of care while improving the quality of care is game-changing and achievable through an enterprise end-to-end AI strategy.
Check out all Healthcare use cases

Reduce Readmissions

Patient readmission results in significant costs for payers, hospitals, and patients. Using DataRobot’s enterprise AI platform to predict and prevent hospital readmissions leads to more efficient use of scarce hospital resources while improving the overall quality of care that patients receive.
Accurate Predictions About ICU and ED Utilization

High costs and periodic scarcity of critical care resources are two key reasons why ICU operations must be improved. Using an enterprise AI platform to create models that more accurately predict which patients need and do not need intensive care and to anticipate optimum staffing levels represents an enormous cost saving opportunity for hospitals.
Determine which patients or members are less likely to adhere to prescribed drug regimens

Patients or members with chronic diseases who do not consistently take their medications lead to more than $100 billion in preventable costs annually. Using DataRobot to create models that identify the patients or members who are less likely to adhere to prescribed drug regimens and predict their behavioral drivers helps create the right intervention plan to increase medication adherence.
Identify Fraudulent Payment Activity

Healthcare fraud can be costly, but it is also too expensive and inefficient to investigate every suspicious claim. Using DataRobot’s enterprise AI platform, organizations build accurate predictive models to identify and prioritize the most likely fraudulent activity, allowing for more effective deployment of resources to investigate, and optimization of customer satisfaction.
Flag members or patients who are at risk for churn

Payers and providers lose money when members decline renewal with their health plan or when patients do not return to their facilities. Payers and providers can use DataRobot to incorporate patient retention risks into their organization’s workflow, leading to reductions in non-renewals and patients not returning for further treatments.
Alert providers to patients at risk for hospital-acquired conditions

Patients are more susceptible to bloodstream infections during hospital stays. This is a costly outcome that often leads to hospital readmissions. DataRobot can predict which patients are more likely to contract sepsis or CLABSI and automatically alert doctors to run additional diagnostics and testing.
Predict patient or member length of stay

One of the primary predictors of cost is length of stay. Longer stays not only place patients at higher risk of hospital-acquired conditions, but they also constrain hospital bed availability and physician time. DataRobot can help providers and payers predict the length of an inpatient stay, which creates greater scheduling flexibility, reduces costs, enables targeted interventions for at-risk patients, and helps organizations transform to value-based care.
Predict No-Shows

No-show patients are costly for providers and payers. can also be costly for patients because skipping medical appointments can lead to untreated medical conditions and adverse health outcomes. DataRobot can help predict which patients are most likely to be no-shows, equipping decision-makers with the information they need to rearrange schedules, craft interventions, and proactively engage patients. DataRobot can also aid in determining the probability of non-adherence and whether patients will respond to outreach efforts.

DataRobot Can Help:

Chief Medical Informatics Officers

Let DataRobot suggest the best model for each situation, saving your team time and effort trying and comparing every model. Use the enterprise AI platform to build many models at the same time it took to build one, increasing precision with more model granularity.
Chief Analytics Officers

With DataRobot’s enterprise AI platform, you acquire the productivity of a large data science team from a small one. Let DataRobot find the best models for you and use DataRobot’s simple deployment options to get them to market faster.
Business and Department Heads

Tap into the expertise within the data that your healthcare organization already has. Enable business analysts and data analysts without formal data science training to build and use sophisticated models.
Chief Digital Officers

Get models into production faster using DataRobot’s low-risk model deployment options, including code generation, deployment to Spark, and API-based deployment capability.
Chief Information Officers

The bottleneck in many healthcare organizations is no longer a lack of data, but rather plenty of data and not enough analytics staff to turn the data into insight. Democratize data science with DataRobot and watch the performance of your healthcare organization take off as the data analysis reveals opportunities for improvement.

In this webinar recording, Nathan from Symphony Post Acute Network discusses how DataRobot is transforming data science for challenges like hospital readmissions and patient falls. Find out why Nathan says, “DataRobot’s platform makes my work exciting, my job fun, and the results more accurate and timely -- it’s almost like magic!”

Nathan Patrick Taylor

CIO, Symphony Post Acute Network

We are using DataRobot to make some pretty huge decisions at Steward Health Care. It’s very much a part of our growth strategy. It’s uncharted territory for healthcare.

Erin Sullivan
Executive Director, Steward Health Care
Explainability is key in healthcare, and DataRobot's platform makes it easy for our clinicians to understand DataRobot's predictions and take action on those insights.

Nathan Patrick Taylor
CIO, Symphony Post Acute Network
We see DataRobot as a competitive advantage in healthcare. How else are you going to improve quality rates, or drive down medical costs, or reduce member churn, if not AI? It's an obvious choice.

Steve Prewitt
Chief Analytics Officer, HealthFirst