Lumiata Logo
Request demo

Solutions that address your most urgent challenges.

It’s time to move your AI initiatives forward.
Actuarial &
Underwriting
→
Care and Disease Management
→
COVID

→
Data Management
as a Service
→
Payment Integrity

→
Telemedicine

→

Actuarial & Underwriting

It’s time to build a data-enabled underwriting strategy

The nature of risk has changed. Is your data ready for the new era of underwriting?

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Identifying twice the number of high-cost members as our partner’s legacy tools
  • Reducing risk by $70M/year as compared to Wakely
  • Implementing solutions in under two months
Use Cases

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Increase competitiveness with precise cost and risk predictions
  • Boost risk assessment accuracy
  • Improve system reliability by detecting anomalies in the underwriting process
  • Slow market share erosion resulting from sub-optimal pricing
  • Identify high-cost group models to support underwriting
Lumiata Perspective

Like most insurance executives, Lumiata believes that intelligent technologies like machine learning will transform underwriting. We also believe that the payers who step into the world of machine learning today will be rewarded for years to come.

We’ve seen the possibilities first hand in our work with major payers and are continually investing in machine learning innovation for the underwriting space.

Care and Disease Management

Better care management starts with better use of data

Chronic and complex disease complicates every aspect of care. Your data can turn that around.

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Improved visibility into personas of Chronic Kidney Disease (CKD) patients through our Chronic Kidney Disease.
  • Onset Prediction and At-Home Patient Success Prediction.
  • Reduced risk and increased margins by minimizing clinic care.
  • Planning for future volume surges and increases in care demand.
Use Cases

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Leverage predictions to guide risk-based care management design
  • Improve care through the identification of high-risk patients
  • Support improved primary care through enhanced acute and chronic disease onset predictions
  • Identify at-risk patients earlier to reduce costs and improve outcomes
  • Review care utilization, health conditions, and prescription medications for any patient
  • Provide increased ability to optimize clinical resource allocation
  • Generate accurate predictions of over 20 diseases
  • Proactively identify patients likely to develop intervention-intensive conditions
  • Reduce hospital admissions with insights into disease-related complications
Lumiata Perspective

Care and disease management are fields of amazing opportunity — but in an era of an increasingly complex healthcare ecosystem, that opportunity will remain uncovered without strategic use of machine learning.

Lumiata’s approach to care and disease management prioritizes results through the prediction of undetected diseases – grouping data and shining a light on lurking health events and warning signs – enriching data for ML.

COVID

COVID changed everything… including your data

The next normal is here. Make sure your data tools are up to the tasks of a post-pandemic world.

At Lumiata, we’ve helped our partners address:

  • Cost-bloomers due to the pandemic
  • Covid cost peaks and valleys
  • Post-pandemic disease onset and progression predictions
Use Cases

For Payers:

  • Predicting pandemic-related impact on individual and group costs.
  • Forecasting hospitalization, ICU admissions, and re-admissions.
  • Calculating COVID-19 incidence by region or hospital system.

For Providers:

  • Enhancing clinical decision making by informing physicians of patient medical status.
  • Forecasting recurrence or resurgence of COVID-19 using epidemiological models.
  • Predicting hospitalizations, ICU admissions, and re-admissions
  • Calculating COVID-19 incidence by region, system, and community.
Lumiata Perspective

We believe that the pandemic changed the way healthcare should use data.
Our COVID-19 data set includes medical, mental health, and prescription drug claims through July 31, 2020 — improving your potential accuracy in managing COVID-19’s impact.

With our pioneering leadership in AI, strategic partnership with Blue Cross Blue Shield, and data asset of 120 million patients, we are happy to support our partners in leveraging ML and predictive analytics as they adapt to this new era in healthcare.

Data Management as a Service

Interoperability just got easier.

Getting your data interoperability-ready doesn’t have to be a chore.

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Getting their data right from the start.
  • Evolution from mediocre model performance to stellar performance and tangible results.
  • Making a smooth transition from ML to deep learning.
  • An up to 80% boost in accuracy of predictions over leading models.
Use Cases

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Data mapping and normalization for interoperability initiatives.
  • Episoding and member grouping.
  • Cross coding and disease tagging.
  • Improving healthcare data quality checks.
  • Generating Person360 records — longitudinal records of your patients that enable any user to easily access historic profiles though SQL queries, platform filters, or a Jupyter notebook.
Lumiata Perspective

Interoperability is increasingly fundamental to the function of healthcare organizations and relationships with other stakeholders. Effective data management is critical for organizations looking to keep up with the evolving needs of the industry.

Lumiata’s approach to data management prioritizes results through the prediction of undetected diseases – preparing it for ML in less time. We’ve spent over 60,000 hours creating a data model that transforms data into a structure that is understandable and usable to prime it for deploying effective machine learning models.

Payment Integrity

The new approach to payment integrity

Billing errors are far too common. Machine learning helps you catch them before you pay.

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Automating the claims review process
  • Identifying more suspicious claims
  • Increasing incremental savings opportunity
  • Reducing money paid to vendors
Use Cases

For Payers:

  • Identifying suspicious claims before they’re paid
  • Empowering your internal team to catch more suspicious claims
  • Sending fewer and lower-cost requests to vendors

For Providers:

  • Ensuring claims are paid the first time correctly
Lumiata Perspective

Incorrect claims cause problems for payers and providers. Our comprehensive payment integrity approach uses artificial intelligence and machine learning to catch more suspicious claims before they’re paid and before they reach vendors. We believe the typical overpayment identification potential to be 30-40%.

Telemedicine

Shining a light on the telemedicine of tomorrow

Telemedicine is reshaping healthcare as we know it. Is your data going to take you where you need to go?

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Reach out to at-risk patients before major health events.
  • Proactively alert physicians of at-risk patients.
  • Build telemedicine strategies that get ahead of patient needs and positively impact outcomes.
Use Cases

At Lumiata, we’ve helped our partners realize their desired outcomes including:

  • Informing integration of telemedicine and population health and care management initiatives.
  • Improving telemedicine strategy and operations through increased data precision.
  • Shaping business continuity plans that rely on remote care.
  • Intervening earlier and remotely before critical in-person care is needed.
  • Personalizing the patient telemedicine experience.
  • Preventing catastrophic events through remote interventions.
  • Better managing chronic disease regardless of location.
Lumiata Perspective

Telemedicine and telehealth will shape the future of care delivery and care outcomes in a way that providers and payers can’t afford to ignore. Exploring this opportunity will require a fresh approach to data that leverages the potential of machine learning (ML).

Lumiata’s approach to telemedicine unifies data sources – from EMRs to handwritten notes – enriching it for ML.