Saturday, 22 June 2013

Waiting times in A&E

The UK's National Health Service seems to have been constantly in the news in recent months for the wrong reasons. One issue has been waiting times at Accident and Emergency Departments. The government's target is to treat 95% of patients at A&E departments within 4 hours. Whether or not the target is met has become a general indicator of pressure within the NHS. Recently the government missed the target. But, how useful are such targets?
      Let us look at a hypothetical A&E department at 6pm on the 2nd July 2013. The waiting room is full of people. To be efficient we need to work out the benefit of treating each patient and compare that to the cost. The benefits and costs are shown in the diagram below. To illustrate how the benefit side works we can pick out two of the patients: David has had a heart attack and needs treatment or he will die, while Brian has sprained his ankle playing football. The benefit of treating David far exceeds that of treating Brian. On the cost side we recognize the capacity constraint in the department. The department can treat Q patients at any one time without much cost, but cannot realistically treat more than that. Who should the hospital treat? Clearly they should treat David and leave Brian waiting.
      Fast forward one hour. David is now in intensive care and Brian is still waiting. A new set of patients has arrived. Amongst these new patients is John who was in car accident and has serious injuries. Again, the benefit of treating John far exceeds that of treating Brian and so Brian is going to be left waiting a bit longer.
      Its now 10pm and Brian has been waiting four hours. The benefit and cost trade-off, however, has not changed. David and John have been treated but many new patients have arrived in more need of treatment than Brian. For example, Sarah has just arrived after a fall that caused serious head injuries. Who should the hospital treat? On any ethical and moral grounds they should treat Sarah. There are, however, 'strategic' or 'management' incentives to treat Brian in order to meet the target. Essentially, the benefit of treating Brian becomes artificially higher due to the target.
         One would hope that decisions are made on medical grounds. Unfortunately, however, we have evidence that sometimes they are not. Serious problems, for example, were uncovered at Stafford Hospital. An inquiry into the poor standard of care found a management culture that put targets ahead of patient care. Receptionists were left deciding who to treat in A&E. Brian might get treated ahead of Sarah. 
       Our hypothetical example illustrates the way that targets can distort incentives.They provide an incentive for the department to treat Brian ahead of more needy patients. And things work the other way too: why did Brian turn up at A&E with a sprained ankle? The promise of being treated in under four hours may have been a deciding factor. Which is why increasing the capacity of A&E is not necessarily the answer to the problem.
        This is not to say that targets are not a good thing. Performance measures and indicators are clearly essential to motivate performance. It is, however, necessary to be careful how targets are used. Setting a target that can be artificially met is not good - it is easy for a hospital to meet the waiting time target by sacrificing patient care. Setting a target that makes no sense is also not good - On neither efficiency or equity grounds do we want a hospital treating Brian ahead of Sarah. Undue focus on one target is also not a good thing - a mix of targets avoids distorting incentives in one particular way. Such nuances are, though, difficult to sell to a public audience that likes simple black and white tests of whether the NHS is performing up to standard.

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