The first rule of support…

I had a classic ‘parent’ experience this week.

My son played a basketball game and at one point made a desperate dive to stop the ball leaving the court and keep it in play. As a consequence he hit the wall hard, and as we were driving home he complained of pain in his chest, and pain breathing.

Yep, you guessed it, every parent’s favourite place was just about to be graced with my presence.

So off we troop to the local hospital – which shall remain nameless, to protect the innocent – and settle in for a wait.

Now, as anyone who has visited casualty can attest, it’s rarely a speedy process. And before I receive any complaints, I am fully aware of:

  1. How hard working most hospital staff are
  2. What a great job they do
  3. How under-paid they are
  4. How great it is to have a public health system

So this is not a shot at receiving slow service or having to wait.

It is, however, a shot at a poor user experience that could easily have been fixed.

First, let’s jump to the end of the story. We waited just over five hours, and were seen by a doctor who gave my son a physical examination, told us that x-rays weren’t possible as there were no staff in, and then sent us home with some concerns allayed – it waspossibly fractured, but probably wasn’t in danger of puncturing a lung. Good news.

But let’s rewind a little. Five hours earlier I walked in, explained the situation to reception, explained it again to a triage nurse, and was then told to take a seat and wait. Knowing that my primary concern was that the ribs may be broken, there was an immediate failure point here in terms of user experience – and in terms of plain-old customer support. Both reception and the triage nurse could easily have explained that there were no radiology staff on, and let me know my options (which were simple – go home and come back tomorrow, go to a larger hospital that did have 24 hour coverage, or stay and get a brief physical exam instead). Unfortunately neither staff member felt this was necessary. In fact, I could just as easily have gone home and called a 24 hour radio doctor from the comfort of my armchair, who could have dispensed the same examination and guidance.

Next, and most important as far as I am concerned, was a failure to communicate any information during the five hour wait. We all know it’s going to take some time when you hit casualty, and we all know that more serious cases go first. My son had a possible fractured rib, but during our time there we saw a potential overdose, an older man with a bleeding head, another with a smashed face from a fall, a diabetic lady struggling not to enter diabetic shock, and one small child with a fish-hook (prawn still attached) embedded in his skull. Most of those were seen before us despite arriving after, and that’s perfectly understandable. Fish-hook boy left us quietly giggling thanks to the prawn bouncing round his noggin, but that’s another story.

My issue here is that there was no way to predict or timeframe the wait.

After three hours waiting I asked reception – explaining that I knew they were busy and just wanted some information – where we were standing in terms of a queue. At that point they told me there were two people in front of us. How long, roughly, I asked?

“We can’t tell you.”

Just an idea, a guesstimate maybe?

“We can’t tell you.”

I asked again at 4 hours, and got the same response. At 4.5 hours I was ready to walk away and come back tomorrow, especially given that it was nearing midnight, but for my son it had become a competition and he wasn’t going to be beaten – we’d stay till the sun rose, if necessary. So I asked again. “You’re next” was the answer this time. 45 minutes later we were in, 5 minutes after that we were on our way home.

Now I understand it’s impossible to put accurate figures on times. Doctors surgeries have the same problem, despite 15 minute appointment times. One customer might take three minutes, the next half an hour. So accurate timing is impossible.

Equally though, average timing must be relatively easy to calculate.

The ideal solution from a customer perspective would be for a complex calculation. Work out how many doctors are working, how long each patient takes on average, if necessary even by time of day/day of the week, and calculate how long your wait might be.

Failing that, a simpler calculation – just average time taken times patients in the queue. it could even be roughed out to hour blocks – estimated waiting time 2 hours, 3 hours, etc. Just think how much frustration that would save.

And failing that, some form of ticketing or numbering system to tell you who’s ahead. Hospitals grade patients on arrival, so have those split into queues and displayed, provide a ticket. So if I’m in the least risky category I can see my queue numbers going down and work out for myself when I might get seen.

And failing all of that, the hospital could easily have told me that I had options and sent me on my way, before I tied up a massively overworked doctor five hours later on a relatively pointless examination.

The first rule of good UX is feedback – and the first rule of good support is the same, feedback and set expectation. It’s a simple rule, really.