More and more, consumers are demanding proactive, personalized, and preventive care, which is central to their needs. As WellCare becomes more prevalent across the industry, it poses a threat to your business. If patients can’t get WellCare, they may end up in the ER, which also poses a threat to the wallet. Want to take preventive care to the next level? Artificial intelligence (AI) can help you identify risks sooner, intervene faster, and provide better care for your patients. Sound good? Here’s how you can make this a reality at your organization.
Benefits of predictive analytics for preventative care
Artificial intelligence and machine learning (ML) have a wide range of possible applications; why use them to generate predictive analytics for preventive care?
Because predictive analytics can enhance your ability to provide high-quality, personalized, preventive care, which impacts patients, providers, and payers. Predictive analytics powered by AI and machine learning allows you to dig deeper into your data and discover risks you might not have been able to see before. With Lumiata’s solutions, for example, you can identify health risks and predict the onset of diseases at the patient or population level.
This enables you to intervene sooner, adjust care management as needed, and help keep your patients healthy while providing a positive patient experience. Proper preventive care also helps you avoid the need to provide costly treatment and helps keep patients out of hospitals, resulting in cost savings for patients, providers, and payers. Preventive care supported by predictive analytics is a win-win-win for all involved.
Does your data give you the insights needed to provide the best possible preventive care? Are you able to predict the onset of a disease, or predict a hospital admission before it happens? With Lumiata, you have the resources you need to generate predictive analytics to help you provide the care your patient’s demand.
How Lumiata uses AI and ML to make predictions
When using Lumiata products, you’ll start by gathering your data, including data regarding claims, behavioral health, eligibility, pharmacy, and more. Lumiata can use standard data with codes or unformatted data such as EHR and doctors’ notes. We then clean your data and prepare it for machine learning. With all of your data in one place, the data is transformed from raw data into Person360 records, which provide a historical view of each member’s encounter and claims history. We also enrich your data with our proprietary Lumiata Disease Codes, which help you make predictions about the onset or progression of a wide range of diseases. Additionally, we draw from millions of patient records, thousands of physician curation hours and millions of articles mined from PubMed.
Once your data is ready for machine learning and artificial intelligence, you can use Lumiata’s solutions to run pre-trained data models using missions of healthcare-specific features or create and run your own. The insights from these data models allow you to make predictions about the risks and needs of your patients. How likely is a hospital admission or readmission? What are the chances a patient will develop the disease within the next 12 months? Which patients are high-risk patients? Armed with predictive analytics, you can adjust care management plans to provide better care while managing risk and saving money.
Our products simplify your journey into healthcare AI and machine learning
Healthcare data is complex, full of challenges as well as potential benefits. Lumiata is the only AI company built from the ground up specifically for the healthcare industry. Our solutions simplify your journey into healthcare AI and ML and make it easier to predict clinical and financial events.
Lightning AI Model Builder
Using our Lightning AI Model Builder, you can train on enormous datasets and build high-performing data models from thousands of healthcare-specific, auto-generated machine learning features. This solution enables you to scale as your needs evolve and improve speed and ingenuity, all without being slowed down by clunky datasets, server issues, or lag. You can also innovate new machine learning features from a foundation of data enriched by our clinical IP, disease codes, and lab results.
Spectrum AI Model Catalog
Want to use ready-made healthcare ML models? Our Spectrum AI Model Catalog includes more than 100 pre-trained models that can be used as-is or customized based on your needs to help you solve real healthcare problems. Our financial model suite is 80% more accurate than the nearest competitors’ cost prediction models and our clinical suite is up to 65% more accurate than the leading carrier.
The Spectrum AI Model Catalog also enables you to leverage predictions to design and adjust care management plans based on patient and population risks. You can predict disease onset, hospitalizations, and the progression of chronic conditions, giving you powerful insights to help you determine how to provide the right care at the right time.
How you can use predictive analytics for preventative care
Artificial intelligence and machine learning transform your data into an even more valuable resource, one that can be used to make predictions about clinical and financial risks and events.
With help from Lumiata’s solutions, you can generate predictive analytics to help you see potential issues so you can address them as soon as possible. What does that look like in the real world?
You have better visibility into a patient’s risk factors and can predict that they’ll develop diabetes, for example, within the next 12 months. Armed with this information, you can adjust the patient’s care management plan and encourage them to take the appropriate steps to improve their health, potentially helping them avoid developing the disease and avoid needing more expensive treatment later on.
When you can identify risks and make predictions, you’re able to intervene sooner and provide better, more personalized care for your patients. This helps achieve better outcomes and provides a higher quality patient experience. It also helps prevent health issues from getting worse and helps reduce the need for more complex and costly treatments and procedures, which saves patients, providers, and payers money.
Predictions are also beneficial for telemedicine organizations, delivering insights to help providers make informed decisions and intervene earlier and remotely before critical in-person care is needed. Additionally, predicting high-cost patients can help in-person and remote organizations more accurately plan resource allocation and budgets.
See how Lumiata can support your personalized, preventive care initiatives
Ready to see how artificial intelligence and machine learning can make your data more valuable? Want to take advantage of predictive analytics to improve preventive care? Request a Lumiata demo today.