Almost by definition this requires a different kind of big data project to improve services and to highlight where integration is failing or leaving people behind.
The drivers to adoption of big data projects for social care might begin as just ensuring the organisation is paying lip service to government demands and complying with new regulations.
Cost savings and searching out fraud have led the push for some early projects both in the UK and the US
But to be truly successful a project must move to the second stage of taking a strategic approach and beginning to see the value that data mining and analysis can bring to the organisation.
This doesn’t just mean cost savings but the ability to improve and offer new services.
This means bringing together data on road gritting with delivery schedules for ‘meals-on-wheels’. It means linking up dental records with registers of at-risk children – kids not receiving regular dental checks are statistically more likely to be suffering other types of neglect or even abuse.
It means giving care givers in every part of the NHS access to the big picture without requiring patients to repeat the same information time and time again.
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Despite the potential benefits there are still big barriers to wider adoption of data sharing and analytics projects.
There are still sensitive issues of data protection around organisations sharing extremely personal and private information with other bodies. Too often data protection is used as a catch-all excuse for not even starting projects or giving out the most basic information. But organisations must tread carefully when setting legal parameters for such formal data sharing.
There are very different cultures in different areas of health and social care and there is often very real suspicion between organisations, even those which work together regularly.
There can be good technical reasons why timely data sharing is difficult too. But moves to open standards and cloud-based services, which are impacting all areas of the NHS, should reduce this problem.
The reality is that the biggest problems are very often human, not technical.
This HPE blog notes the three major requirements for an organisation to establish best practise big data analytics.
The organisation will need ‘commitment’ – there will be problems and plateaus to overcome which will all take time.
Good managers, doctors and social workers are not necessarily also good data analysts. Every organisation needs ‘competency’ – the skills to get the project up and running and providing useful, actionable results.
Finally it requires ‘culture’ to support the move. This means a culture which can deal with change, can deal with established practise being challenged by numbers, and has leaders who can help staff and business processes adapt to these rapid changes.
It is this area which can be the hardest to overcome. Showing the possible benefits on a small scale can help win over suspicious senior staff who might fear losing their decision making to machine-based analytics.
The best big data project must provide staff with the ability to do their jobs better and quicker.
Only after this can the advantages of data analysis go on to widen and deepen the kind of support services those staff can offer.
