A common refrain when cutting resources is that the impacts can be mediated by improving cost effectiveness through better targeting. But can it be done?
Creating a view of all care based on people is the first essential step, according to Tower Hamlets public health professionals. The ability to do this is transforming the way providers are thinking about services.
Having truly joined up data has a host of benefits such as improved efficiency, accounting, planning at a local level, service design and targeting. More importantly it also leads to better outcomes.
The changes are driven not only by the relentless squeeze on resources but also other policy developments such as the race to set up health and wellbeing boards in every local authority and the emerging localism agenda.
The London borough of Tower Hamlets has led the way in integrating information for use in health and care using a partnership approach across the council and health economy, with professional support from ourselves. It has created a comprehensive database by joining together administrative data sets such as the GP register, the local land and property gazetteer and the school pupil census. This has been further enhanced with local service data at address level such as social care and hospital admissions.
The actionable intelligence created is helping to re-shape both the commissioning and delivery of local services in the borough. For example, it is informing GP networks at local level by identifying and quantifying socially isolated risk groups and their effect on health costs.
According to Somen Banerjee, Tower Hamlets' director of public health, "it enables us to put a cost on local health inequalities and provides the evidence base for different and more innovative interventions and delivery structures".
A good example of its use is in the identification of higher cost users of hospital care in the population aged 65 and over. They are divided into eight groups, depending on whether or not they qualify for three risk factors: living alone, being aged 75 and over and receiving benefits.
Looking at the average annual cost of hospital admissions for each of the eight resulting groups shows that with none of these risk factors the average admission cost is £551 per person, compared to £1,193 for individuals who are in all three risk groups. Further analysis shows that costs per person increase by £393 for those aged 75 or over, an additional £157 for those receiving benefits and by £91 for those living alone.
The data can also be mapped for each risk group, allowing it to be analysed for gaps and local variations. One example has identified older people's homes in Tower Hamlets and the resulting GP access blackspots. Tower Hamlets has the lowest take up of free eye tests in London, and yet eye testing is important for detecting early signs of diseases such as glaucoma or macular degeneration.
The data showed that older people were strongly deterred from travelling even short distances to regular eye test providers. With the addition of more flexible eye testing arrangements at home or in GP surgeries, take up would significantly improve.
Tower Hamlets has similarly analysed health visiting, community nursing, cancer screening, non-elective admissions, adult social care and other services using joined up data.
Such analysis and mapping can help fine tune direct investment and provision locally, and few would argue against better intelligence enabling improved targeting of scarce resources. However to achieve this, the crucial message is you that you need to combine your data assets.
Source:
guardian.co.uk
Creating a view of all care based on people is the first essential step, according to Tower Hamlets public health professionals. The ability to do this is transforming the way providers are thinking about services.
Having truly joined up data has a host of benefits such as improved efficiency, accounting, planning at a local level, service design and targeting. More importantly it also leads to better outcomes.
The changes are driven not only by the relentless squeeze on resources but also other policy developments such as the race to set up health and wellbeing boards in every local authority and the emerging localism agenda.
The London borough of Tower Hamlets has led the way in integrating information for use in health and care using a partnership approach across the council and health economy, with professional support from ourselves. It has created a comprehensive database by joining together administrative data sets such as the GP register, the local land and property gazetteer and the school pupil census. This has been further enhanced with local service data at address level such as social care and hospital admissions.
The actionable intelligence created is helping to re-shape both the commissioning and delivery of local services in the borough. For example, it is informing GP networks at local level by identifying and quantifying socially isolated risk groups and their effect on health costs.
According to Somen Banerjee, Tower Hamlets' director of public health, "it enables us to put a cost on local health inequalities and provides the evidence base for different and more innovative interventions and delivery structures".
A good example of its use is in the identification of higher cost users of hospital care in the population aged 65 and over. They are divided into eight groups, depending on whether or not they qualify for three risk factors: living alone, being aged 75 and over and receiving benefits.
Looking at the average annual cost of hospital admissions for each of the eight resulting groups shows that with none of these risk factors the average admission cost is £551 per person, compared to £1,193 for individuals who are in all three risk groups. Further analysis shows that costs per person increase by £393 for those aged 75 or over, an additional £157 for those receiving benefits and by £91 for those living alone.
The data can also be mapped for each risk group, allowing it to be analysed for gaps and local variations. One example has identified older people's homes in Tower Hamlets and the resulting GP access blackspots. Tower Hamlets has the lowest take up of free eye tests in London, and yet eye testing is important for detecting early signs of diseases such as glaucoma or macular degeneration.
The data showed that older people were strongly deterred from travelling even short distances to regular eye test providers. With the addition of more flexible eye testing arrangements at home or in GP surgeries, take up would significantly improve.
Tower Hamlets has similarly analysed health visiting, community nursing, cancer screening, non-elective admissions, adult social care and other services using joined up data.
Such analysis and mapping can help fine tune direct investment and provision locally, and few would argue against better intelligence enabling improved targeting of scarce resources. However to achieve this, the crucial message is you that you need to combine your data assets.
Source:
guardian.co.uk
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