On the commensurability of efficiency

In this week’s round-up, I highlighted a recent paper in the journal Cambridge Quarterly of Healthcare Ethics. There are some interesting ideas presented regarding the challenge of decision-making at the individual patient level, and in particular a supposed trade-off between achieving efficiency and satisfying health need.

The gist of the argument is that these two ‘values’ are incommensurable in the sense that the comparative value of two choices is ambiguous where the achievement of efficiency and need satisfaction needs to be traded. In the journal round-up, I highlighted 2 criticisms. First, I suggested that efficiency and health need satisfaction are commensurable. Second, I suggested that the paper did not adequately tackle the special nature of microlevel decision-making. The author – Anders Herlitz – was gracious enough to respond to my comments with several tweets.

Here, I’d like to put forth my reasoning on the subject (albeit with an ignorance of the background literature on incommensurability and other matters of ethics).

Consider a machine gun

A machine gun is far more efficient than a pistol, right? Well, maybe. A machine gun can shoot more bullets than a pistol over a sustained period. Likewise, a doctor who can treat 50 patients per day is more efficient than a doctor who can treat 20 patients per day.

However, the premise of this entire discussion, as established by Herlitz, is values. Herlitz introduces efficiency as a value and not as some dispassionate indicator of return on input. When we are considering values – as we necessarily are when we are discussing decision-making and more generally ‘what matters’ – we cannot take the ‘more bullets’ approach to assessing efficiency.

That’s because ‘more bullets’ is not what we mean when we talk about the value of efficiency. The production function is fundamental to our understanding of efficiency as a value. Once values are introduced, it is plain to see that in the context of war (where value is attached to a greater number of deaths) a machine gun may very well be considered more efficient. However, bearing a machine gun is far less efficient than bearing a pistol in a civilian context because we value a situation that results in fewer deaths.

In this analogy, bullets are health care and deaths are (somewhat confusingly, I admit) health improvement. Treating more people is not better because we want to provide more health care, but because we want to improve people’s health (along with some other basket of values).

Efficiency only has value with respect to the outcome in whose terms it is defined, and is therefore always commensurable with that outcome. That is, the production function is an inherent and necessary component of an efficiency to which we attach value.

I believe that Herlitz’s idea of incommensurability could be a useful one. Different outcomes may well be incommensurable in the way described in the paper. But efficiency has no place in this discussion. The incommensurability Herlitz describes in his paper seems to be a simple conflict between utilitarianism and prioritarianism, though I don’t have the wherewithal to pursue that argument so I’ll leave it there!

Microlevel efficiency trade-offs

Having said all that, I do think there could be a special decision-making challenge regarding efficiency at the microlevel. And that might partly explain Herlitz’s suggestion that efficiency is incommensurable with other outcomes.

There could be an incommensurability between values that can be measured in their achievement at the individual level (e.g. health improvement) and values that aren’t measured with individual-level outcomes (e.g. prioritisation of more severe patients). Those two outcomes are incommensurable in the way Herlitz described, but the simple fact that we tend to think about the former as an efficiency argument and the latter as an equity argument is irrelevant. We could think about both in efficiency terms (for example, treating n patients of severity x is more efficient than treating n-1 patients of severity x, or n patients of severity x-1), we just don’t. The difficulty is that this equity argument is meaningless at the individual level because it relies on information about outcomes outside the microlevel. The real challenge at the microlevel, therefore, is to acknowledge scope for efficiency in all outcomes of value. The incommensurability that matters is between microlevel and higher-level assessments of value.

As an aside, I was surprised that the Rule of Rescue did not get a mention in the paper. This is a perfect example of a situation in which arguments that tend to be made on efficiency grounds are thrown out and another value (the duty to save an immediately endangered life) takes over. One doesn’t need to think very hard about how Rule of Rescue decision-making could be framed as efficient.

In short, efficiency is never incommensurable because it is never an end in itself. If you’re concerned with being more efficient for the sake of being more efficient then you are probably not making very efficient decisions.


You won’t believe what these NHS productivity statistics mean for health policy!

Newly published research from Chris Bojke and co-authors estimates productivity growth in the NHS from 1998/1999 to 2013/2014. Total output of the NHS comprises both the volume of various services and their quality while inputs are approximated by total expenditure. Growth in productivity is then calculated by comparing growth in output with growth in inputs. Their main results are shown in figure 1, reproduced from the paper. Over the fifteen year period total productivity growth was 4.1% and under the previous coalition government productivity growth averaged 1.6% per annum.

bokje fig 8

Figure 1. Inputs versus outputs for the NHS. (From Bojke et al. (2016) CC BY-NC 4.0)

Early on during the coalition government the NHS was set a productivity challenge to find around £50 billion of productivity savings by 2019/20. This was equivalent to an increase in productivity of around 5% per annum, which was completely unprecedented at the time. Compare figure 1 to figure 2, which shows the targets the government was imposing. The new productivity data show that the NHS has not and is unlikely to achieve anywhere near this figure. Indeed, one of the cornerstones of the government’s healthcare policy, a 7-day NHS, is unlikely to be cost-effective and may further reduce productivity growth despite attempts to reduce labour costs through changes to contracts.


Figure 2. Inputs and outputs for the NHS up to 2009, with the orange circles representing the coalition government’s goal. (From Appleby (2012))

When it comes to overall changes in productivity it is not possible to disentangle changes in efficiency, improvements in technology, and economies of scale. Generally, new technologies are both more expensive and provide greater benefits, but their effect on efficiency depends on whether they are more cost effective than what the NHS is currently achieving with its inputs. Some research suggests that the cost-effectiveness threshold for adoption of new technologies is too high potentially reducing efficiency. However, healthcare providers may have disinvested from the least cost-effective technologies as their budgets contract, improving efficiency.

It is widely acknowledged that there are shortfalls in staffing in the NHS. Guidelines for safe staff to patient ratios are frequently not met. Bojke et al. show that labour inputs to the NHS, which account for 42% of all inputs, hardly changed under the coalition government. Staff inputs are not considered in the same way as technologies; it is not known what the “cost-effectiveness” of a doctor is for example. Increasing labour inputs can improve patient safety, thereby reducing patient harm and length of stay, while also potentially improving the efficiency with which healthcare is provided as staff are complementary inputs with other healthcare capital. However, investment in labour, unlike capital goods, takes place in a broader political context as the current junior doctor’s strikes demonstrate. This may lead to a suboptimal policy choice about investment in and remuneration of labour, a so-called ‘government failure’.

The question of what is driving productivity growth still remains. Bojke et al. note that “output growth appears to be more closely related to lagged input growth than current input growth”. This may explain why productivity growth is observed to be positive when input growth is low. Observed productivity growth may therefore be an artifact of reductions to input growth, casting doubt on the sustainability of further productivity growth in the future under current policy.

Human capital, endogenous growth and hospital performance

In the health economics literature we often treat a hospital as a healthcare producing ‘firm’. We define cost-functions and perform efficiency analysis, for example. However, this sort of analysis is certainly hampered by the difficulty in measuring healthcare production. One of the inputs to a hospital production function is human capital and as such I was curious to learn whether theories of endogenous growth had been applied to increasing hospital productivity. Admittedly my literature search has been somewhat lacklustre but I have not yet found anything on this topic. So, here, I will explain why I think this could be an interesting area of exploration.

Human capital, being a somewhat fuzzy concept, is difficult to empirically examine. Even so, it is expected that a firm should perform better when its employees have more human capital. In a general sense, human capital can be gained through education, knowledge spill overs, or by learning-by-doing. In a hospital, staff with greater experience should produce more healthcare, which should translate as reduced mortality or reduced length of stay (Bartels et al (2011) did find this to be the case with nursing staff, for example).

Human capital is developed for specific tasks, not only in clinical procedures, but also in team organisation and functioning within a specific hospital and unit. Kim (1989) and others distinguish between intensive and extensive human capital:

The former is a stock of specialized knowledge and skills that improves worker productivity in a given production activity; the latter is a stock of general knowledge that renders the workers more adaptable to a variety of activities. Mohtadi and Kim (1992)

In this way the specialist is then more productive (and thus commands a higher wage) for the given set of tasks in which she specialises. Within the NHS there has been a drive for specialist nurses who practise a specific area of medicine, and indeed they are on a higher pay band than their generalist colleagues. Moreover, these nurse specialists lead to a demonstrable reduction in mortality (i.e. increased healthcare production) (see this example)

Becker and Murphy (1992) suggest that the degree of specialisation is determined at the equilibrium of the marginal return to specialised knowledge and marginal costs of coordinating specialists. This would explain why we don’t get specialisation to an extremely high degree, such as one nurse or doctor for every procedure.

The human capital generated in hospital units through experience can spill over. New members of the team can learn from older members; innovations in organisation can be shared. Thus, there should be a general accumulation of human capital over time, leading to increased productivity over time. This is endogenous growth.

It can be shown that hospital productivity has increased over time, and that there has been an increase in diversification of medical fields. The former may be explained by other theories of growth, and the latter by supply induced demand. Either way, I think it is an interesting hypothesis.

If you know of any literature on this or refute this idea, don’t hesitate to say so.