A Unit of Comparison for Local Council Budget Consultations, Based on Transparency Spending Data – ASCdays?

A few years ago, via the BBC Radio 4 & World Service programme More or Less (incidentally co-produced by the OU), I came across the notion of miciromorts (Contextualising the Chance of Something Happening – Micromorts), a one in a million chance of death that can be used as a unit of risk to compare various likelihoods of dying. Associated with this measure is David Spiegelhalter’s microlife, “30 minutes of your life expectancy”. The point behind the microlife measure is that it provides a way of comparing life threatening risks based on how much life is likely to be lost, on average, when exposed to such risks.

Life expectancy for a man aged 22 in the UK is currently about 79 years, which is an extra 57 years, or 20,800 days, or 500,000 hours, or 1 million half hours. So, a young man of 22 typically has 1,000,000 half-hours (57 years) ahead of him, the same as a 26 year-old woman. We define a microlife as the result of a chronic risk that reduces life, on average, by just one of the million half hours that they have left.

The idea of micromorts came to mind last night as I was reflecting on a public budget consultation held by the Isle of Wight Council yesterday (a day that also saw the Council’s Leader and Deputy Leader resign their positions). The Council needs to improve budgetary matters by £20 million over the next 3 years, starting with £7.5m in the next financial year. This can come through increasing funding, or cuts. By far the biggest chunk of expenditure by the council, as with all councils, is on adult social care (ASC) [community care statistics /via @jonpoole].

As with every year for the past however many years, I’ve had a vague resolution to do something with local council spending data, and never got very far. Early dabblings with the data that I’ve so far played with this year (and intend to continue…) reinforce the notion that ASC is expensive. Here’s a quick summary of the spending data items for October, 2016:

The spend for each of the directorates was as follows:

  • Adult Services:
    • total spend: £7,746,875.55 (48.33%% of total monthly spend)
    • capital: £395,900.06 (5.11% of directorate monthly spend)
    • revenue: £7,350,975.49 (94.89% of directorate monthly spend)
  • Chief Executive:
    • total spend: £501,021.32 (3.13%% of total monthly spend)
    • capital: £492,507.54 (98.30% of directorate monthly spend)
    • revenue: £8,513.78 (1.70% of directorate monthly spend)
  • Childrens Services:
    • total spend: £2,044,524.26 (12.76%% of total monthly spend)
    • capital: £243,675.08 (11.92% of directorate monthly spend)
    • revenue: £1,800,849.18 (88.08% of directorate monthly spend)
  • Place:
    • total spend: £4,924,117.40 (30.72%% of total monthly spend)
    • capital: £974,024.13 (19.78% of directorate monthly spend)
    • revenue: £3,950,093.27 (80.22% of directorate monthly spend)
  • Public Health:
    • total spend: £434,654.13 (2.71%% of total monthly spend)
    • revenue: £434,654.13 (100.00% of directorate monthly spend)
  • Regeneration:
    • total spend: £57.65 (0.00%% of total monthly spend)
    • revenue: £57.65 (100.00% of directorate monthly spend)
  • Resources:
    • total spend: £377,172.20 (2.35%% of total monthly spend)
    • capital: £20,367.87 (5.40% of directorate monthly spend)
    • revenue: £356,804.33 (94.60% of directorate monthly spend)

Cancelling out Adult Services revenue spend for a month would match the £7.5 million required to make up next year’s funds. That’s unlikely to happen, but it does perhaps hint at a possible unit of comparison when trying to make budget decisions, or at least, support budget consultations.

From my naive perspective, adult social care needs to support a certain number of people, a number that evolves (probably?) in line with demographics. One of the ways people exit care is by dying, though the service is set up to minimise harm and help prolong life. Folk may also be transiently cared for (that is, they enter the care system and then leave it). By looking at the amount spent on adult social care, we can come up with an average cost (mean, median?) per person per day of adult social care – ASCdays. We can reduce the total cost by reducing the amount of time folk spend in the system, either by shortening transient stays or postponing entry into the system.

So what I’ve started wondering is this: as one way of trying to make sense of transparency spending data, is there any use in casting it into equivalent units of ASCdays? If we use ASCday equivalent units, can we take a weak systems view and try to get a feel for whether a cut to a particular service (or improvement of another) can help us get a handle on the ASC expenditure – or whether it might cause problems down the line?

For example, suppose a week’s respite care costs the same as two weeks worth of ASCdays. If that week’s respite care keeps someone out of the adult care service for a month, we’re quids in. If cutting respite care saves 100 ASCdays of funding, but is likely to bring just one person into the care system 3 months early, we might start to doubt whether it will actually lead to any saving at all. (Longer tail saves complicate matters given councils need to balance a budget within a financial year. Spending money this year to save next year requires access to reserves – and confidence in your bet…)

For trying to make budget decisions, or helping engage citizens in budgetary consultations, costing things as per ASCday equivalents, and then trying to come up with some probabilities about the likelihood that a particular cut or expense will result in a certain number of people entering or leaving ASC sooner or later, may help you get a feel for the consequences for a particular action.

As to whether prior probabilities exist around whether cutting this service, or supporting that, are likely to impact on the adult care system, maybe data for that is out there, also?

Author: Tony Hirst

I'm a Senior Lecturer at The Open University, with an interest in #opendata policy and practice, as well as general web tinkering...

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