Unlocking data to inform public health policy and practice: A pilot study on utilising police data for linked population data research

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Amrita Bandyopadhyay
Sinead Brophy
Natasha Kennedy
Hope Jones
Julie Evans
Mark A Bellis
Benjamin Rowe
Irena Spasic
Cynthia L. Mcnerney
Simon Moore

Abstract

Objective
The UK Government increasingly emphasises a comprehensive, multi-agency approach to tackling crime. This pilot study explores the feasibility of integrating police data with routine health data to develop a holistic understanding of the predictors of domestic abuse (DA). 


Approach
The study encompasses three work-packages a) coding the narrative data from Domestic Abuse, Stalking and Harassment (DASH) risk assessment report from Public Protection Notifications (PPNs), which are information-sharing documents recording safeguarding concerns and shared with partner agencies b) exploring to identify what works to harmonise different software systems within police data-sharing approach, c) constructing a case study by linking PPN DASH data with routine health and administrative records. These efforts illustrate the potential of national data-sharing initiatives. 


Results


a) Text mining methods successfully identified and coded (with over 95% accuracy) 17 refereed/involved agencies from the PPN DASH data.  


b) Barriers to data sharing were attributed to a lack of clarity and consensus regarding appropriate information sharing, rather than technical obstacles. This barrier can be overcome by an unambiguous framework, endorsed at an elevated level, highlighting which data should be shared. 


c) The data-linkage study revealed that victims of DA had prior interactions with healthcare services before their initial PPN, and younger pregnant victims had higher risk of future healthcare emergency visits.  


Conclusion and Implication
Police and health data integration enhances evidence-based prevention and early identification of vulnerable individuals by both law enforcement and public health services.

Article Details

How to Cite
Bandyopadhyay, A., Brophy, S., Kennedy, N., Jones, H., Evans, J., Bellis, M. A., Rowe, B., Spasic, I., Mcnerney, C. L. and Moore, S. (2024) “Unlocking data to inform public health policy and practice: A pilot study on utilising police data for linked population data research”, International Journal of Population Data Science, 9(5). doi: 10.23889/ijpds.v9i5.2577.

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