Some Q and A about A and E Waiting Times

31 Jan

We don’t think that way, but field headers are a species of first-line documentation. We need to know what fields mean before we work with them, and quite apart from the brute operational need for fields to be headed at all (and header-less worksheets are out there to be found; I can think of a couple).

That is a none-too-arresting truism to be sure (most truisms aren’t too arresting), but when headers put understanding on hold, the truism suddenly matters. I’m thinking about the UK’s National Health Service Accident and Emergency (A&E) data on waiting times entrants to the Service’s emergency facilities endure before they’re attended to. It’s a perennially newsworthy concern, and some pretty current data are here:

 2015.01.25-AE-Timeseries4w3Rl

But before we think about those aforementioned headers some other, more standard spreadsheet considerations require a look, too. Begin with the oldest-to-newest sort ordering the Week Ending data in the Period field, a curiosity you may or not find nettling depending on the intentions you’re bringing to the sheet. If you’re doing nothing but reading the records you’d likely have opted for a recency-driven sort, in which the latest entries top the field; but if, on the other hand, you’re keen to mortar and pestle the data with a pivot table or some other analytical instrument you shouldn’t care at all, because you’ll be sorting as and when you wish. Note as well, of course, that those W/Es have seen to it that the presumptive dates filling the Period column are labels, a substantive devaluation that could and should have been forestalled. If you run a Find for W/E[space] and Replace with nothing, you should be able to recover the data’s rightful quantitative standing (though be prepared for some issues if your Dates and Times honor the U.S. month-first protocol). And when that rework does its job you can rename the field Week Ending.

Moreover, if you are going to pivot table the data set, you need to do something about the blank row 18 – namely, by deleting it – and treat the grand-totalling row 17 to much the same. Again, you don’t want 17’s totals uncorking a double-count all over your tables. And the merged superordinate headings in 15 have to go the way of 17 and 18, or else your pivot tables won’t go at all (just delete the entries; the row can be left alone).

And now for my opening pronouncement. Perhaps it’s me, but I experienced more than a jot of difficulty in my strivings to understand whence the percentages in columns M and N came. You see how the two metrics are meant to be differentiated: one conveys the percentage of all A& E patients attended (that verb probably requires scrutiny) in four hours or less, the other the fraction of type 1 incidents seen within that time (Type 1 denotes  “A consultant led 24 hour service with full resuscitation facilities and designated accommodation for the reception of accident and emergency patients”, we’re informed here).

The problem – to which my obtuseness is probably central – is in the clarity of the headers’ implied instructions to divide this field by that field.  What field, that is, denominates the Percentage in 4 hours or less (type 1) data?  That datum in cell M18, for example, reports 95.6%, and after a round of head scratching I returned my fingers to the keyboard and at last prevailed with this triumphant formulation:

=1-I18/E18

Considered in field terms, I divided

Type 1 Departments – Major A&E/Type 1 Departments – Major A& E

Subtract that result from 1 and you do get 95.6%, in single-decimal terms. But you got it – I seem to have divided two fields by the same name, and in fact I have. Of course they’re topping different columns, but…I wouldn’t have done that, quite apart from my early inclination to think about dividing I18 by H18, or Total Attendances.  That 95.6% then needs to be understood as confining itself to Type 1 on both sides of the divisor, and not all attendances.

And now – now – that other percentage, the 96.9% in N18, reads more sensibly:

=1-L18/H18

Or,

1-Percentage in 4 hours or less (all)/Total attendances

(remember that L18 counts attendances that took longer than four hours, and so the division computers the greater-than-four-hour data, which need to be subtracted from 1, or 100%, in order to develop the less-than-four-hour percentage). But I might have also replaced Total with All, so that the adjective reads identically across those two fields. Why should we have to wonder about the difference between Total and All?

Another point: the merged-cell heading in I15, A&E attendances > 4 hours from arrival to admission, transfer or discharge, seems to point to patient receptions in excess of four hours; but the percentage recounted above computes attendances of four hours or less. But as I said, maybe it’s me.

A concluding recommendation, even as no one asked me for it: click anywhere in M and N and see 10-or-so decimal points congesting its column. Might not all confusion have been allayed if the actual formulas occasioning the M and N results have been left in their places, instead of the hard-coded replacements that we’re seeing? We’d then know exactly what was divided by what, to the relief of all those bloggers confessing their obtuseness in shameless public view.

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