Better data, better knowledge, better society: Developing an ideal homelessness data system drawing on lessons from global practice
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Abstract
The aim of this paper is to set out the principles of an ideal data system. Good data is crucial to effective policy and practice development in all social policy spheres and this is a particular challenge in the context of homelessness policy. Policy makers, practitioners and researchers have been highly critical of the current state of homelessness data across the globe, with concerns largely focused on the incompleteness of the data. Most research has narrowly focused on the strengths and weaknesses of different data collection techniques, such as Point-In-Time counts. However, good data does not only derive from the data collection method - consideration must also be given to the wider data system, including how data are generated, reported, analysed, and crucially, how they are made accessible and to who.
The evidence base for the paper is a desk-based review of 49 data collection systems from 8 countries, including systems in health and social care settings—where data are being increasingly used to drive more effective care. The different systems are synthesised to generate 8 areas of design, being: data architecture, governance, data quality, ethical and legal, privacy/security, data access, and importantly, purpose. Drawing these elements together, the paper concludes that data collection should adopt a common data standard shared across the sector, enabling inter-organisational information sharing and improving collaboration; reporting to local and central government must not be one-sided, instead data providers should receive some tangible benefit for their engagement; the focus of analysis needs to shift from statistics toward evaluation into the effectiveness of interventions; and access must be available to a range of sector actors, including service providers and academia. Importantly, the paper also concludes that in delivering the ideal system, care must be taken not to interrupt the delivery of effective homelessness interventions.
The aim of this paper is to set out the principles of an ideal data system. Good data is crucial to effective policy and practice development in all social policy spheres and this is a particular challenge in the context of homelessness policy. Policy makers, practitioners and researchers have been highly critical of the current state of homelessness data across the globe, with concerns largely focused on the incompleteness of the data. Most research has narrowly focused on the strengths and weaknesses of different data collection techniques, such as Point-In-Time counts. However, good data does not only derive from the data collection method - consideration must also be given to the wider data system, including how data are generated, reported, analysed, and crucially, how they are made accessible and to who.
The evidence base for the paper is a desk-based review of 49 data collection systems from 8 countries, including systems in health and social care settings—where data are being increasingly used to drive more effective care. The different systems are synthesised to generate 8 areas of design, being: data architecture, governance, data quality, ethical and legal, privacy/security, data access, and importantly, purpose. Drawing these elements together, the paper concludes that data collection should adopt a common data standard shared across the sector, enabling inter-organisational information sharing and improving collaboration; reporting to local and central government must not be one-sided, instead data providers should receive some tangible benefit for their engagement; the focus of analysis needs to shift from statistics toward evaluation into the effectiveness of interventions; and access must be available to a range of sector actors, including service providers and academia. Importantly, the paper also concludes that in delivering the ideal system, care must be taken not to interrupt the delivery of effective homelessness interventions.
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