The aim is the population stratification in relation to the risk of hospitalization due to preventable causes and death through the RiskER algorithm.
Risker addresses the need of early identification of the population at risk of adverse health outcomes to allow targeted preventive interventions, occurring more frequently especially in an ageing population due to chronic disease.
The risk prediction model where the algorithm is grounded was estimated in Emilia-Romagna (involving almost 4 million people), exploiting the data on the use of health services (SDO, ADI, PS), data on pharmaceuticals (AFT FED) and demographic data relating to age, gender and geolocation in the same year.
In Campania, Risker has already been implemented for Salerno province, using available dataflows. A multidisciplinary group of experts, including clinicians, IT, administrative and social professionals have been working together. GPs have been involved to validate the findings of the stratification in Campania, and are now setting up the organizational model to facilitate the personalised interventions on the population at risk.
The model is being scaled up progressively.
Salerno local health agency is currently developing the organizational and administrative models to integrate the risk strata with interventions in terms of anticipatory care, health promotion and disease prevention, for which also a cost estimate is being carried out according to the methodology of time-driven Activity Based Costing.
So far 90.000 Euro have been invested so far, also to involve GPs and economists in the set up of the local implementation model.
Evidence of success
Avoided acute events for citizens at high risk. The algorithm stratified 920.000 citizens > 14 aa. Very high-risk patients identified were 12.700; high-risk were 26.000. 150 subjects at high-very high risk have been involved in the assessment. This approach can potentially avoid acute events for high-very high-risk citizens. The expected social impact is an improvement of the quality of life of the citizens reached by the proactive interventions reducing the risk of adverse health outcomes.
- The identification of the data strings in the context of Campania dataflows.
- The need to validate the strata in collaboration with the GPs.
- The organization of data extraction to feed the algorithm at regional level, that implied the involvement of the managers of the dataflows.
Potential for learning or transfer
Has this good practice been adopted in other regions around the country or beyond?
The good practice is fully implemented in Emilia Romagna, In Campania is between a pilot programme and an extended program. There is a plan to extend it through a regional project. Other Italian regions are involved in the scale up.
Has this good practice implemented as a pilot programme or as an extended programme? In case it is a pilot programme, is there any plan for a wider implementation?
It is is being currently implemented as a large-scale pilot.
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