Health Risk Quantification
Making health measurable and understandable on an individual basis is our core mission.
Over the past nine years, dacadoo has become a leading provider of Health Scoring technology. The robust dacadoo Risk Engine is based on over 300 million person-years of clinical data. It was developed in collaboration with a professor and former scientist at the MIT in Boston.
Our technology fills in the gaps and makes sense out of very limited health and lifestyle data. It can also translate huge amounts of data that are fed continuously into the Risk Engine via the dacadoo Health Engagement Platform or other tracking sources.
Models based on clinical research
Work with limited data
Our risk-based model can be used in two different ways:
Measure & understand health
Normalised by age & gender
Target: Insurers & Providers
Accelerated UW & dynamic pricing
Mortality & morbidity risks
Imputations for missing data
The dacadoo Health Score is a number between 0 and 1,000 representing overall health. It increases or decreases in near real-time, depending on how a user’s mental and physical health, nutrition, activity, sleep, self-control and mindfulness data change over time.
The score is normalized by age and gender to support comparison and benchmarking. The ability for users to compare themselves with people of a different age and gender is one of the key reasons why we opted for a score, as opposed to an age-related indicator.
The dacadoo Health Score can be accessed in different ways:
The dacadoo Health Score is integral to the dacadoo Health Engagement Platform. It can be licensed as part of a white label version or by accessing the functionalities of the platform via RESTful APIs.
The dacadoo Risk Engine is designed for reinsurers, insurers and providers.
With limited self-reported data, the Risk Engine calculates mortality and morbidity risks and provides full data sets with 100 data points for each record. It does this by imputing estimated values for all missing data. For example, if only age, gender, height and weight of a person are provided, the engine will impute 96 missing data points, including blood values and other bio-metric data.
The dacadoo Risk Engine works with as little as four data points (age, gender, height and weight) and can work with up to 100.
All-cause (*) mortality
(*) excluding death from accidents, infectious diseases, and self-inflicted death
Morbidity / Disease Risks
Type II diabetes mellitus
Index of Metabolic Dysfunction
The dacadoo Risk Engine is regularly updated, new models are being added and existing models refined. Various additional morbidity models are currently under development. It is accessible via a stateless RESTful API and works as a calculator, without storing any data.
Use Case for Accelerated Underwriting
The dacadoo Risk Engine produces full data sets for each person by imputing values for all missing data inputs.
The output of the dacadoo Risk Engine can support the pricing and underwriting engine of insurers & reinsurers to facilitate fluid-less online underwriting and increase the amount of Straight-Through-Processing (STP).
Use Case for Dynamic Pricing
To enable flexible premium pricing as part of a Pay-As-You-Live (PAYL) product offering, customer health related data needs to be continuously updated.
We combine our Risk Engine with our award-winning Health Engagement Platform. This helps users to actively manage their health by tracking body, mind and lifestyle data in a playful way.