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Case Study 2 - Strategic Population Health Planning
BIRMINGHAM AND BLACK COUNTRY STRATEGIC HEALTH AUTHORITY

To meet future strategic planning needs the Birmingham and Black Country Strategic Health Authority identified that it would need strategic planning systems which:

• Routinely identify and describe healthcare resource usage for their populations (describe by geography, age/gender, and demographics), identifying areas where low access coincides with measured need.  Although many organisations have carried out such needs analyses, they tend – given thecurrent disposition of information and systems within the NHS – to be a major exercise, so that there is seldom a current and rich picture of usage for more than a handful of the main disease groups.
• Describe trends in resource usage by disease groups.  This relies on a more sophisticated approach to episode grouping across healthcare sectors than has previously been applied in the NHS.
• Enable quantified prediction on future resource usage at a macro level to support allocation decisions. As a minimum, such systems should allow modelling assumptions on the major drivers of cost changes - demographic change, prescribing inflation, new drugs, changes in provision, etc. – to be modelled more systematically than they are currently.
• Drive investment planning by identifying those service interventions which are likely to have the greatest cost-benefit impact on population health.
• Allow better evaluation of proposals for capital development.  It is currently difficult to link the health improvement agenda to capital development, and discussion of population health issues in business casesis often an add-on without clear links to the logic of the scheme. We believe that the application of disease group profiling to integrated health records presents an opportunity to create this linkage.   In particular, it should allow more precise modelling of the impact of major developments on patterns of resource usage and ultimately the development of return on investment measures which weight cost changes, quality improvements and outcomes.
• Track the use of treatment protocols and care pathways at individual patient level.  This will allow commissioners and clinicians to monitor adherence to agreed pathways and standards of care, and facilitate audit of change of sub-optimal care paths.
• To facilitate a focus on high-resource use disease groups, incorporating actuarial methods to flag for clinicians individual patients who may be at risk of a major heath event (e.g. a long stay in hospital or a move to supportedaccommodation) and who may benefit from early intervention. In particular,we would wish to test a particular hypothesis: that we can improve the quality of patient care and reduce the cost of care for a specified range of chronicdiseases by using predictive tools to encourage preventative intervention at an early stage.
• Track policy interventions and service reconfigurations, in particular to allow monitoring of policies to shift care to primary care settings.
• Profile practitioner patterns of care as an aid to the performance management of primary care.
• Using the knowledge base to inform patient choice.
• Facilitate development of the commissioning function: just as there is to be diversity in the healthcare provider environment, it is not unreasonableto suggest that similar diversity might be allowed to evolve in the commissioner function, and that three-star health economies with a track record of financial stability and earned autonomy might be encouraged to develop different approaches to planning.

• The PCT were able to supply data to UHC for 50,000 registered Walsall patients.  The data exchange process proved difficult, particularly for primary care systems, and automating the routine capture of primary care data would need to be a key part of any extension of the project.
• UHC were able to load the data.  The US and the UK use different coding systems and a degree of “lowest common-denominator” mapping was required to allow the UHC episode grouper to work.
• UHC were able to identify those gaps in the data which had the greatest impact on the power of the software.  If extended, the project would have an initial data quality phase to address some of these issues.