Healthcare
Consistently deliver optimal patient care experiences, powered by efficient behind-the-scenes operations.
Why AI Now?
Data is transforming healthcare as we know it, creating better patient outcomes while reducing costs. Healthcare providers that are taking advantage of the vast quantity of data are differentiating themselves now and leading the industry to the future. Precision medicine can be tailored to each patient’s exact needs. Connected devices improve operations and spark new business models and clinical approaches. Remote treatment can take advantage of predictive diagnostics to lower costs, accelerate patient treatment and improve patient satisfaction. At the same time, regulatory compliance requires careful navigation of complex data issues. As the healthcare ecosystem innovates, so too do the opportunities to combat fraud, waste and abuse (FWA). RapidMiner empowers healthcare companies to keep ahead of these changes, ensure optimal care experiences for patients and create efficient operations behind-the-scenes.
Healthcare Industry Use Cases
Drive Revenue
- Provide precision care with personalized treatment and healthier outcomes
- Discover new treatments and identify the right patient candidate profiles for each treatment
Cut Costs
- Optimize operations to deliver the best possible care at the lowest cost
- Leverage connected devices for more patient insight and innovative treatment models
Avoid Risks
- Identify signs of fraud, waste & abuse (FWA) early and take preventive measures
- Improve patient safety through better determination of treatment criteria and risk factors
Highlighted RapidMiner Impact
A provider used text analytics of patient comments to identify service problems and made improvements that boosted patient satisfaction levels.
A hospital made care recommendations using predictive models combining patient history with current diagnostics to improve outcomes.
A surgical center analyzed selected treatments and patients’ physical status to predict the optimal post-surgical care and speed recovery.
An insurer analyzed readmission data to determine root causes and took steps that reduced return visits to providers.
A provider significantly improved accuracy and speed of early sepsis identification, reducing false positives and triaging to focus on urgent cases, while slashing costs.
A major hospital operator used regional and seasonal illness and incident patterns to predict and optimize staffing for its distributed care centers.
An insurer improved its ability to predict prescription fraud by identifying new, indicative patterns such as unreasonable distance from doctor to pharmacy.
A provider can now better predict potential medication safety issues, such as detecting unnecessary or excessive opioid prescriptions for particular treatments.
What Our Customers Say
“Easy to use data science tool. Straight forward tool with good functionality and walkthrough tutorials with easy to understand examples.”
– Director of Data research and Analytics in the Healthcare Industry