EIP on AHA Repository

Population risk stratification: deployment of stratification methods in the Basque Country

Keywords: Chronic Diseases, Data Analysis, Disease Risk, Risk Stratification
Basque Ministry of Health


Digital solution and service (e.g. application/digital health portal/platform/AI based system/etc.)
Short description
Within the Basque Country healthcare system, a customized version of the Adjusted Clinical Groups (ACG) Predictive Model is used for risk stratification (RS). The aim of the risk stratification is mainly case finding; RS is deployed to stratify the entire population of the Basque Country being by next year’ healthcare cost. Then population is classified in four groups according to the presence or not of a chronic disease, with a special focus on the 95th percentile of chronic population. To stratify by use of healthcare resources allows identifying and selecting target populations that may benefit from specific programs of action. The RS model is based on diagnoses, socio-demographic data, pharmacy data, prior health care utilization, and socio-economic data. Currently work is being carried out to develop mechanisms to perform a periodic evaluation and optimization of the RS model, and to improve the tool enabling data collection in a more regular basis.
Impact on the health system’s capacity and resilience (e.g., health and care efficiency, continuity of care)
The best practices and lessons learnt from the implementation and deployment of a RS in the Basque Country are supposed to serve as examples for the development of programs for managing multi-morbidity among complex frail older citizens, and to help policy makers and stakeholder to design, plan, deploy and validate RS in other regions. A high-quality operational plan establishing the agenda and the strategic goals and objectives for the years to come is needed. Having trained people qualified in RS is necessary. The clinicians’ commitment is a sine qua non requirement. If we can assure the commitment of innovators and early adopters, the remaining organizations will follow in their steps. The communication, not only of RS, but also of what it is aiming for, is a key element of its feasibility. If the clinicians do not see the point of RS, it would be really difficult to implement. Since the clinical group consists of different profiles, it is vital to have a multidisciplinary team leading the RS deployment: each and every one of the professional profiles involved is important. Besides, having appropriate ICT has been identified as crucial. Care intervention includes case finding and selecting the target population allows one to focus efforts on the people that can make the best of the programmes designed for chronic patients. A process of continuous improvement that, on the one hand, includes the quality assessment and improvement process and, on the other hand, the pathway definition and implementation, always helps to produce feasible interventions
The practice/case/tool is “on the market” and integrated in routine use. There is proven market impact in terms of job creation/spin-off creation or other company growth
Geographical scope
Basque Country
Submitted in other database or repository of digital health resources that is publicly available
https://futurium.ec.europa.eu/en/active-and-healthy-living-digital-world/library/eip-aha-repository-innovative-practices, EIPonAHA Repository of innovative practices

Additional information

to clinicians / care practitioners
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
to patients / citizens
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Primary target patient group (age)
May be used across all patient ages
Addressed prevention area(s)
Health screenings
Ready to be transferred to
Ready for transfer, but the practice has not been transferred yet.