Model building in Bournemouth saves lives

NO, not sandcastles, although if it could be said to improve your health then the 2010 annual meeting of UKPHA* (“Confronting the Public Health Crisis”) would have offered it in Bournemouth (alongside Nordic walking, Tai chi, handclapping exercises (I kid you not!) cycling and vegetarian food (see my colleague's blog  Wot no conference bag?).

NO what I am referring to is the result of one man’s persistence with an idea whose time has finally come (thanks to the credit crunch & the need to ensure you are working cost effectively in the field of public health).

Prof. Malcolm Whitfield (Sheffield Hallam University) and his team have created the Sheffield Health Effectiveness Framework (SHEFTOOL) which enables cities and primary care trusts (PCTs)  to identify the health benefits for their particular populations if they reduce specific risk factors for disease (using one of 7 different groups or “domains” of health intervention). It can tell you which intervention will have the most health impact, what risk factors are affected & by how much, work out how much it would cost and how much money they would ultimately save their health budget having to deal with the clinical consequences of disease. All before you have invested a penny.

It was created by identifying health intervention/ risk factor studies from world literature & using the data therein to create algorithms for each type of intervention, quantifying  for each, various known risk factors such as body mass index, blood cholesterol, blood pressure, smoking, alcohol consumption. Interventions by definition are intended to prevent diseases occurring or prevent transmission, and are not about treatment after you have been diagnosed, so treatment data is not included in the model. 

So far, the model (tool) has to be adapted by the researchers for each city or PCT, using population data supplied by the client (eg number, ethnicity, disease prevalence) but where there are gaps they can use national data. However, funding is currently being sought to create software which will enable each customer to input their local data, which will speed the process and reduce the initial cost outlay to the PCT/city (currently running at £8000 per PCT).

The tool was developed as part of the EU-funded DECIPHEr project and "Four Healthy Cities" participate: Helsingborg, Sheffield, Turku and Udine.

So how does it work for the user? Read on…

( *UKPHA=UK Public Health Association; **DECIPHEr=Developing an Evidence-Based Approach to City Level Public Health Planning and Investment in Europe)

Select an intervention domain e.g. smoking or maybe a 5-a-day fruit program, plug in the number of people you’d like to target, the age group, ethnicity (if its relevant to your area, they will build this into your version of the model), then how many people you expect to stick with the programme, PRESS the Button ( so to speak) and it will give you details of the various risk factors affected & by how much, the delivery costs and the clinical costs saved. In addition to seeing the return on your investment in terms of health impact & financial costs saved,  it can also tell you what to do in different parts of your city,  how to reduce demand on services, and  you can use it as a training device to show the impact of decisions, particularly the ones which unexpectedly impact health.

This model is seen as the way forward for local authorities and PCTS, in cashstrapped times, to justify particular health intervention programmes for their local population and patients … as you can identify hotspots in a city, a ward even a street. With it you could focus on the highest risk groups, using multiple interventions, to maximise the health impact in a particular hotspot, and then expand it to the rest of the city.

So far Birmingham and Liverpool are using this model, and 14 PCTS in the UK have also had their populations modelled…the PCTS are using the results to focus or retain resources supplied by their local authority.

There are apparently similar but more limited programs being developed in the UK by NICE, IDEAs and by at least one PCT: the SHEFTOOL model generated much interest as its potential for universally improving delivery of public health was clear.

Two final thoughts:

  • SHEFTOOL (or DECIPHER prediction tool as its known in Europe) uses data from world literature: I can’t think of a better source of relevant observational studies than our Global Health and I’ve included some in the reference list below.
  • Sandcastle building actually is a good way to de-stress so could possibly improve your mental health….as long as you don’t enter a competition

REFERENCES

  1. Effects of the DASH diet alone and in combination with exercise and weight loss on blood pressure and cardiovascular biomarkers in men and women with high blood pressure: the ENCORE study. Archives of Internal Medicine, 2010, 170, 2, 126-135

  2. Analysis on causes of death and burden of diseases among residents of Yunnan's Surveillance-spots in 2007. Journal Modern Preventive Medicine 2009 Vol. 36 No. 22 pp. 4343-4344, 4346

  3. Tobacco-use psychosocial risk profiles of girls and boys in urban India: implications for gender-specific tobacco intervention development. Nicotine & Tobacco Research, 2010, 12, 1, 29-36

  4. Population-wide changes in reported lifestyle are associated with redistribution of adipose tissue. Scandinavian Journal of Public Health, 2009, 37, 5, 545-553

  5. Blood pressure is lower in children and adolescents with a low-saturated-fat diet since infancy: the Special Turku Coronary Risk Factor Intervention Project. Hypertension ( Dallas), 2009, 53, 6, 918-92

  6. Risk factors of type 2 diabetes among Korean adults: the 2001 Korean national health and nutrition examination survey. Nutrition Research and Practice, 2009, 3, 4, 286-294 (FULLTEXT available through Global Health)

  7. HIV/AIDS interventions in Bangladesh: what can application of a social exclusion framework tell us? Journal of Health, Population and Nutrition, 2009, 27, 4, 587-597 (FULLTEXT available through Global Health)

 

 

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