Public Perception of Using Predictive Analytics for Prevention and Early Intervention
PHE ePoster Library. Argyropoulou E. 09/12/19; 274504; 63
Ms. Effie Argyropoulou
Ms. Effie Argyropoulou
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Abstract
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Abstract Introduction
Islington is at the forefront of linking healthcare data with council held data to support prevention and early intervention. Currently, work includes exploring linking health and care data for an insight into the wider determinants of health and linking structured and unstructured data in care records to predict demand. Informing and involving the public in this work has been a key feature.MethodGiven the complexity of the concept, a pilot focus group (FG) was held with the NIHR-CLAHRC expert lay panel resulting in the approach being supplemented with an interactive card-sorting activity. Nine FGs were held across the two projects, with 44 total participants, including those from BAME group, Young Adults (16-24 years old) and Social Care Service Users (60 years+).
Results
Despite taking a more interactive approach, it was quite challenging to convey the complexities of different datasets and linkage to participants. Considerable time was spent ensuring participants were informed well enough to provide informed feedback. Participants were in favour of linking datasets for improving local services, with the benefits of a contextual view of residents to healthcare professionals a key theme. Concerns were raised around ensuring the accuracy of data, misrepresenting data and bias, as well as data privacy, especially amongst the older participants.
Conclusion
Ongoing engagement is needed with the local residents to keep them informed of developments in predictive analytics work. It is also recommended to develop guidelines for linked datasets and predictive analytics which adhere to ethical principles. External funding details Health FoundationNHS Digital
Abstract Introduction
Islington is at the forefront of linking healthcare data with council held data to support prevention and early intervention. Currently, work includes exploring linking health and care data for an insight into the wider determinants of health and linking structured and unstructured data in care records to predict demand. Informing and involving the public in this work has been a key feature.MethodGiven the complexity of the concept, a pilot focus group (FG) was held with the NIHR-CLAHRC expert lay panel resulting in the approach being supplemented with an interactive card-sorting activity. Nine FGs were held across the two projects, with 44 total participants, including those from BAME group, Young Adults (16-24 years old) and Social Care Service Users (60 years+).
Results
Despite taking a more interactive approach, it was quite challenging to convey the complexities of different datasets and linkage to participants. Considerable time was spent ensuring participants were informed well enough to provide informed feedback. Participants were in favour of linking datasets for improving local services, with the benefits of a contextual view of residents to healthcare professionals a key theme. Concerns were raised around ensuring the accuracy of data, misrepresenting data and bias, as well as data privacy, especially amongst the older participants.
Conclusion
Ongoing engagement is needed with the local residents to keep them informed of developments in predictive analytics work. It is also recommended to develop guidelines for linked datasets and predictive analytics which adhere to ethical principles. External funding details Health FoundationNHS Digital
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