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Deliver AI-powered solutions for your healthcare organization today, transforming billions of data points into insights and predictions that drive down costs, ultimately helping to save lives.

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AI in Healthcare

Healthcare data is growing exponentially. DataRobot can work with you to help turn the troves of data found in electronic medical records, diagnostic data, and medical claims information into cutting-edge insights and predictions tailored to your healthcare application.

Pagadoras

Pagadoras

  • Be a leader in CAHPS, HEDIS and Medicare Star quality ratings with superior analytics
  • Determine which members are at risk for leaving the 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
Prestadoras

Prestadoras

  • Build more precise patient readmission risk models
  • Optimize your revenue cycle management and revenue prediction
  • Accurately forecast staffing needs
  • 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 care
Healthcare Vendors

Healthcare Vendors

  • Leverage precision analytics to optimize your patient marketing campaigns, messaging, and call center operations
  • Increase renewals and reduce customer turnover while actively managing your sales force effectiveness
  • Forecast product sales more accurately
  • Build more effective patient/customer messaging
  • Optimize your target marketing
  • Be a leader in supply and demand chain planning with exceptional analytics

High Value Use Cases In Healthcare

The healthcare industry has a multitude of AI and machine learning applications it can use to improve the quality of care, reduce costs, and streamline operations. Payers, providers, healthcare vendors (i.e., medical device/supplies companies, pharmacies, MSOs, dental, vision, and public sector) can use actionable insights from automated machine learning to reduce costs while maximizing revenue, improving patient/member outcomes, and optimizing operations throughout the industry. Healthcare organizations that adapt their businesses to take full advantage of AI and machine learning will dominate their markets.

Reduce Readmissions

Patient readmission leads to significant costs for the payer, hospital, and patient alike. Using DataRobot’s automated machine learning 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.

Make accurate predictions about ICU and ED utilization

High costs and periodic scarcity of critical care resources are two key reasons why ICU utilization must be improved. Using automated machine learning to more accurately predict which patients need and do not need intensive care represents enormous cost savings for hospitals. This also assists hospitals in anticipating staffing needs for these units.

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 to predict the behavioral drivers for those patients or members helps create the right intervention plan to increase medication adherence.

Identify potentially fraudulent payment activity

Fraudulent claims are costly, but it is too expensive and inefficient to investigate every claim. Using DataRobot’s automated machine learning platform, organizations build accurate predictive models to identify and prioritize likely fraudulent activity, allowing for more effective deployment of resources 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 the 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 appointments are costly for providers and payers, but they can also be costly for patients because skipping medical appointments can lead to untreated medical conditions and adverse health outcomes. DataRobot can help predict these 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.

A DataRobot Pode Ajudar Com:

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 automated machine learning to build many models at the same time it took to build one, increasing precision with more model granularity.

Chief Analytics Officers

With automated machine learning, 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 reveals opportunities and improvements.

 
Nathan Patrick Taylor
Nathan Patrick Taylor
CIO, Symphony Post Acute Network
Na gravação deste webinar, Nathan da Rede Symphony Post Acute fala como a DataRobot está transformando a ciência de dados para desafios como readmissões em hospitais e quedas de pacientes. Descubra porque Nathan diz, “A plataforma DataRobot torna meu trabalho estimulante, meu emprego mais motivador, e os resultados são mais precisos e no tempo certo -- é quase mágica!”

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