Artificial Intelligence to manage municipal home care better

Toni Codina on 11 October 2022

Artificial Intelligence tool that enables more preventive, proactive and efficient management of municipal home care services.

The algorithm uses the data history of each citizen and an assessment of their functional status by social services professionals according to the ICF index (International Classification of Functioning, Disability and Health). From patterns it identifies people at high risk of having extensive future needs, determines the potential for improvement with appropriate interventions, identifies which individuals and efforts are most likely to provide lasting improvement, and triggers concrete preventive measures to stop or delay the need for home care services.

At the same time, it is a support tool for municipal social professionals, as it helps them to better measure the efforts invested for each situation, to direct key resources where they can be most useful, to reduce time spent on unnecessary administrative tasks, or to reduce stress caused by the risk of making incorrect or too late decisions regarding the intervention or response needed by each person.

Characteristics of innovation

Lab, Aging, Bank of innovations, Disability, Information and planning, New technological tool, Personalization of the service, Prediction and prevention

Localization

Helsingborg, Sweden

Partners / Funders

Ensolutions

Genesis

Helsingborg’s local social services did not have sufficient resources and staff to work proactively with all inhabitants. Moreover, due to demographic developments, more and more people are in need of care and treatment, with resources not increasing at the same rate.

That is why the City Council promoted this initiative, with the aim of gaining efficiency, saving resources, and being able to dedicate them to offering a more personalised and preventive care system.

És per això que l’ajuntament de la ciutat va impulsar aquesta iniciativa, amb l’objectiu de guanyar eficiència, estalviar recursos, i poder-los dedicar a oferir un sistema de cures més personalitzades i preventives.

Level of implementation

During the autumn of 2021 the solution was developed with the participation of the social professionals of the municipality, in the winter of the same year it was tested, and during the year 2022 it has started to be implemented in all municipal social services.

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One View, a predictive and preventative homelessness system

Toni Codina on 7 September 2022

Predictive system that allows social services to anticipate, prevent and reduce homelessness in the territory.

The One View system analyses the data set related to services for adults, children and homeless people. The analytical model includes data on income, benefits and schools, and obtains a comprehensive overview of citizens and households in the territory in order to identify existing risk situations that may lead to homelessness in the near future.

One View enables this preventive approach by using advanced analytical models to identify people at risk, with the aim of detecting potential problems 6 to 9 months before a crisis. In addition, the service provides long-term monitoring, so that social services can also evaluate the effectiveness of the interventions put in place, and adjust them. The specialised software provides robust information governance and security, with strict protocols that determine access levels.

The service enables the district to achieve three objectives. The first is to improve the quality of life of residents by providing the necessary contact and assistance when needed. Secondly, a prevention of evolving needs with better informed and targeted interventions. In other words, social service professionals in the district have a unique view that allows them to select the most appropriate and effective course of action in each case. Finally, it contributes to the management of the demand for social and housing services, generating savings due to the combination of improved interventions and predictive information to identify at-risk situations.