Ken Gibb's 'Brick by Brick'

Housing, academia, the economy, culture and public policy

Month: March, 2017

Prevention and Predictive Analytics

 

I was at a What Works Scotland seminar this morning, the latest in our joint events with NHS Health Scotland on the Economics of Prevention. Papers and slides and a summary of discussion groups will be posted at the WWS website. We heard papers from Heather McCauley on the use of predictive analytics in New Zealand, on modelling the burden of disease by Diane Stockton and using agent-based models to consider informal care and obesity by Eric Silverman. They were followed by Ian Marr who summed up, drawing on his first-hand knowledge of social impact bonds and the social impact partnership model he has been developing.

A key aspect of preventative thinking, from Derek Wanless to Campbell Christie and beyond, is the issue of understanding where the most public service spending goes and therefore targeting spending, as far as one can, to those people and needs that will otherwise generate disproportionate public cost e.g. early year intervention to prevent what would otherwise lead to, in high likelihood,  negative future outcomes such as less good education and employment outcomes, poorer health and or episodes involving the justice system. A key issue is also how to manage the disinvestment that goes with a shift to prevention.

While it was fascinating to hear Eric Silverman tall about these simulation model as safe playgrounds of policy experimentation without consequences (unlike piloting, for instance), I want to talk  primarily about Heather’s exposition of preventative predictive analytics in New Zealand. She told us about the evolution of the programme, how it works and provided detail in terms of policy spheres such as welfare benefits and children in care.

The three big lessons and challenges that arose for me were as follows:

  • Moving government to think and act in terms of the lifetime costs (on an actuarial basis) rather than the annual cash costs of a high need individual, household or client;
  • Using statistical/econometric methods to uncover the probabilities that signify the high need households and individuals – the diagnosis of where lifetime costs are very high and therefore where large potential savings can be made; and
  • Designing the optimal mix of practice and policies that allow case managers to maximise the effectiveness of intensive interventions (what works?).

All three are difficult – the third, perhaps the most challenging. Let’s look at each in a little more detail.

Heather described the need for culture change to take on the lifetime cost approach. She pointed out that New Zealand has a culture of seeking the best possible value for the public dollar and so the shift from short term to a longer, multi-parliamentary term perspective, can be made and perhaps done so more readily than in the UK or Scotland. Many of us might be comfortable with the idea of focusing on the lifetime savings made by preventing someone falling into the negative outcomes suggested above – but it does require current governments spending money now and postponing benefits to future governments.  Heather provided the example of using a helicopter to transfer a spinal injuries patient from an accident site immediately to hospital with potential long term savings in reduced future health care costs. Lifetime benefits considerably outweigh upfront (helicopter usage) costs.

Second, the New Zealand benefit figures suggest that much of their employability spend goes to job seekers who are a small proportion of the total client group compared to the higher and persistent incidence of for example those on disability benefits and lone parent benefits. They cost more in lifetime terms and represent longer term need. Modelling under certain conditions offers, to different degrees in different policy areas, a reasonable basis to diagnose where highest need is concentrated and where benefits might be maximised by effective targeted interventions. But as was stressed in the presentation, these models produce probabilities and associations; they are not causal and indeed there is a fascinating question about understanding why some highly at risk groups remain resiliently unaffected in future years – what can we learn from their resilience?

Heather rightly recognises the suspicions and criticisms open to these sorts of approaches (often relating to big data and predictive algorithms): bias, non-discretionary model creating discriminatory or arbitrary outcomes, perverse incentives, moral hazard and discrimination like cream-skimming of the cheapest easiest candidates in areas like the work programme.  Transparent models (all on line from the New Zealand government) and independent scrutiny of the models, their assumptions and how they work ‘under the hood’, is essential, as is always seeking to improve the model and to reduce negative aspects of models.

Finally, there is the classic what works question – assuming that the modelling has indicated who and where the highest need target group resides, what are the suite of policy tools and interventions that best reduce the lifetime cost and make those savings because negative future outcomes are significantly reduced? How do we assemble good practice, policies, and effective case management in the variety of policy areas likely to be developed? A sector by sector repository and on-going discussion about these tailored responses is essential.

Predictive analytics has well founded criticisms but as in so many areas, this is one where continued independent scrutiny, a commitment to transparency and a willingness to continuously improve modelling, can provide valuable prevention benefits but there I can be no guarantee that this will be so. Furthermore, there is the small question of then designing the appropriate mix of policy responses aimed at those in most need

 

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Returning to the Start: Housing and Public Health

 

Housing intervention by the state started with public health challenges. Public health approaches today have much to say about the structural determinants of health inequality, spatial inequities and connections to key sites and drivers of these inequalities. Housing is of course centrally implicated both in terms of physical and mental health, but also in relation to the broader wellbeing of individuals, families and communities. Housing conditions, fuel poverty, unaffordability, all manners of indicators of unmet need are relevant.

The Scottish Public Health Network have just published a new report: Foundations for Well-being: reconnecting public health and housing. A Practical guide to Improving health and reducing inequalities (lead author Emily Tweed). It sets out to be a ‘best practice resource’ to guide the Scottish housing and public health sectors to improve health and reduce inequalities through good housing. It is well worth a look.

The report is a primer that sets out the context facing the different professional communities, provides useful links to data and policy resources and provides recommendations for good practice and development for both. The big health themes touched on by housing include well-being, ageing, inequality and poverty, health and care integration, community empowerment and climate change. What is helpful as an educational and professional resource is that the report provides a basic grounding or primer for either group, sets out a long list of statistics and other policy and practice connections as well as key practice pointers.  There are also useful diagrams and boxed case studies.

The report (section 2 and appendices) has a nice discussion of the complex multi-dimensional relationship between housing and health (also see a recent review of housing and health inequalities by NHS Health Scotland ). These dimensions include:

  • Bi-directional – while housing may influence health the opposite is also true with health issues constraining locational choices and housing design as well as impacting on financial constraints and employability.
  • Context-specific – impacts and strength of these connections will vary across different populations (and sub-groups), eras and places.
  • Direct and indirect dimensions – where indirect effects can include for instance burdensome housing costs reducing access to other health-benefitting activities.

As the authors say (p.15): “acknowledging these complexities helps add nuance to our understanding, but does not undermine the central fact that housing can be a powerful determinant of health and wellbeing, and of inequalities in their distribution across the population”.

Section 5 is an excellent compendium of resources for housing and public health. Just one example worth following up – a very useful public health oriented report from Wales on the prevention case for housing investment . The final section looks at opportunities for joint working, initiatives that might be taken to link data in housing and health (potentially very powerful) and specific priorities like the private rented sector and strategic joint planning around for instance health and care integration.

I would not pretend to have any background in public health other than reading about it in a housing context and occasionally debating these causality questions with colleagues. More recently through What Works Scotland and through public health colleagues in the University and beyond I have become more engaged with these important inequalities questions. A report like this one is a great practical way into these questions for researchers, students, practitioners and policy facing professionals alike. Well done.

 

Rent Reform and the Too difficult Box

 

Over the last 20 years, I have worked on at least five discrete projects about rents and rent-setting. This has included studies funded by governments and by individual providers in Scotland and Northern Ireland. A feature of this experience has been on the one hand that precious little reform of how rents are set followed on from this work (score zero for ‘impact’), but at the same time, it has been a learning curve. In this post, I want to reflect on these lessons.

First,  we are primarily interested in the pricing of social housing. By that we mean the level of the average rent, the way that rents are distributed around that average reflecting variations in, or differentiating the, quality of the stock, and, how we uprate rents each year. A fourth theme is whether these principles can be established not just for one provider but across a housing system (e.g. all social landlords), be that a local authority, a region or even a country. A fifth theme is whether rents should be consistent across the entire stock or whether pooling would not extend to separate well-defined schemes and new developments? Most of the following discussion assumes complete pooling (e.g. with a premium applied to new build should it be required).

Second, this desire to look at rents may arise because of policy seeking to remove anomalies and put rents on a more coherent basis than current perception or evidence would suggest. It may also arise because of the actions of a single landlord (e.g. taking over another landlord’s stock), it may be due to external policy challenge such as welfare reform or the sense that competitive threat makes its necessary to review the rents. It may also reflect asset management strategies and the use to which rental income is put. There could conceivably also be internal pressures from board members or tenant groups, or indeed staff groups, to address perceived shortcomings. However, we should not underestimate the ability of these groups alongside other stakeholders like lenders or the regulator – to resist or dilute rent reform proposals.

Third, what are the key principles involved? One would be consistency – that rents are differentiated on a rational and credible basis e.g. bigger properties, more space and more amenity command higher rents and do so in a coherent way. A second would be affordability (a thorny issue in its own right) but typically about securing low cost housing for low income households, especially those just above HB ceilings, often in low wage work. A third point would concern viability – does the rent allow development to take place and does it support the ongoing operational delivery of housing services thereafter?

Many readers will recognise longstanding problems of archaic rent structures lost in the mists of time, of anomalies in rent levels comparing similar properties from different landlords and inconsistencies within a given landlord’s portfolio when looking at different areas, vintages of stock and other similar problems. There is also often the sense that rent systems may be past their prime and are slipping into entropic disorder accelerating over time.  These discrepancies can be brought to light particularly during periods of new development, when stock transfers or mergers take place and when the external policy environment sheds perhaps too much light on the way rents are done.

So how to reform? I worked with one landlord who initially wanted to bring the full weight of evidence and analysis through a sophisticated formula rent. The stakeholders I mentioned earlier thought not and subsequently a much simpler model based really only on size and property type became the favoured option. Others lose their zeal for reform when they see that, as in England in the 2000s. shifting to a national formula rent (complete with local average rent convergence across landlords) requires long term adjustment over 10-15 years and also implementing protection measures for those losing out in the form of damping to lessen year-on-year effects. While the English model was relatively complex – such a process of transition and convergence could be devised for much simpler internally consistent models. But a big lesson from the English experience for me has been the unwillingness of Governments to see these sorts of policies through. The simplicity of a national formula rent, for all its problems (e.g. the financial pressure it put on landlords who had to slow down planned rent increase), fell apart after a change of Government and their desire to set off on different paths for non-market housing and required rents for new models. This was then followed up by statutory rent cuts to save on housing benefit – massively expensive for social landlords who in good faith planned reinvestment (as well as  just trying to retain the resource levels of  their landlord operations).

Geography is interesting concerning policy trajectories over rents. Alongside the English experience since 2000, Northern Ireland’s social sector appears to have had quite a lot of discretion though in fact almost all social landlords base their rents on some version of sorts of the dominant (Housing Executive) landlord’s rent points policy from the 1980s.  Again, this has gradually become less recognizable over time (and average rents remain lower for Housing Executive properties). In Scotland, on the other hand, despite earlier research studies examining the merits of a more national system of rent-setting, there has been absolutely no interest from those who would champion rent reform. And as a result, Scotland probably has the least coherent and comparable rents in the social sector across the UK. Yet no-one gets that excited about it, other than in terms of the starting rents required for new build, and the impact of LHA caps on rents and rental income received.

So, does viable, affordable and consistent pricing of rents matter? At one level, of course it does. But more broadly, surely it still makes sense for tenants to be able to make rational, informed judgements about price and quality both within a landlord’s stock and between different landlords? Arguably the growth and encroachment of private renting into the non-market housing sphere is another reason for more not less transparency. But if the regulator is tolerably happy with the situation, if tenants are not too despondent about annual rent increase (outside of England), and if providers are up to their necks in operations and crises, unless the policy environment forces it on them – rent reform is not going to be coming anytime soon. Like so many public policy reform questions, the rationality and benefits of rent restructuring are outweighed by their time, resource and political costs (and it is of course a nontrivial process) – but like council tax reform, not making the necessary change will only in due course make things worse.