This is development work, internal to the AIF Allocations Team (Analysis and Insight for Finance), to calculate various populations for use in allocations. Exploration / Training - to try out new techniques, code and training for personal/team development.
To develop methodologies for calculating approprate calculations for allocations, using RAP principles
How to optimise production of populations
NHS England is responsible for determining allocations of financial resources to Integrated Care Boards (ICBs). Total annual budgets given to ICBs cover the majority of NHS spending. The allocations process uses a statistical formula to make geographic distribution fair and objective, so that it more clearly reflects local healthcare need and helps to reduce health inequalities. Allocations models have been developed for the services commissioned directly by the ICBs - Core Services (Acute & General, Community, Mental Health, Prescribing and Maternity) and for Primary Care (General Practice). The work of the Allocations team is set out by an independent advisory group, ACRA.
Health populations based on GP practice registrations are published monthly (or quarterly for lower level data, such as by single-year age AND LSOA of residence) usually by 5-year age-group. ACRA determined to address issues of seasonality in the data (particularly for university and seaside areas), so we calculate the most recent 12 month average value for each GP practice present during that year, as the base year for each allocations round. Growth rates from ONS SNPPs at LAD level are used to calculate populations for all the years included in the allocation, which could be one, or several.
GP registered populations are the basis for ICB population 'fair share' of the money available in the NHS, along with adjustments for need. Accurate calculations for estimated populations gives each ICB the best chance of a fair allocation. This process was previously calculated in Excel/Access, currently in Stata and also mirrored in R (as a means of QA). We have been transparent by publiching our methods in the Allocations Technical Guide. It is hoped to make the R calculations more robust and modular, following RAP principles.
We can only use the most recent available data. Since the census, population projections have not been published, so sometime we have to use data which is old or not optimal. Recent projections were simply the national projection with no regional variation, so the fastest and slowest growing populations may not be accurately reflected.
The calculations include 12-month averages by sex and 5-year age group for allocations, mapping to administrative geographies, application of ONS growth rates, lsoa of patient residence from MPI to track growth of digital-first practices, some of the need models, including age-specific groups for dental and public health (vaccs/imms)