A Journey to Pathology 3.0: Take a Walk on a Supply Side

We use data models to contextualise and plan every day. They are all just abstract representations of the "real world" and estimates of operational or financial situations. As such, they are all wrong. The only question is, "How much?"

More precise models incorporate more nuances and levels of complexity, but for some conversations, ballparking suffices. For example, suppose I know the work amounts to "x" Direct Clinical Care Programmed Activities (DCC)–equivalents. In that case, I will multiply "x" by 1.5 to estimate the number of whole-time pathologists required to do the job. Factor 1.5 accounts for Supporting Professional Activities (SPA) and 42 working weeks per year, according to the United Kingdom National Health Service standard. A colleague with Consultant job planning experience will know that there are several assumptions in the calculation, but the number will be a reasonably good approximation. The RCPath Guidelines provide a reporting productivity ballpark. We can approximate that the preparation, delivery, and follow-up of multidisciplinary team meetings (MDTs) take twice their length.

Let's use urological pathology, a specialty I have never practised, as an example. Considering the projected increase in demand very conservatively, I estimate that our service will require no less than five whole-time equivalents. Urological pathology is only one of 11 specialties in our histopathology portfolio. Since we all know the realities of the pathology job market, you do not need me to QED this calculation or extrapolate it to the whole system level. At the end of the day, this is about supply and demand. This is about the growing gap between demand and capacity.

Many will disagree with my maths, and I will be as happy as Larry to be proven wrong. However, I do not accept that pathologists can be magicked to work more productively. As usual, productivity is one of those management words that conceals as much as it illuminates. The current productivity levels reflect the current state of technology and the environment. If we want to increase productivity, we need to work on both. Productivity improvement is never a technological project; it is a transformational programme enabled by technology and organisational development.

Of course, there is a scope for productivity improvement, maybe even quick wins, before we even start talking about AI and start running before we can walk. How about simple interventions that can use the existing technology to enable prioritisation, improve communication, and cut interruptions or waste time on menial things? I cannot quantify how much time we can save if we have electronic requests with relevant information, appropriate prioritisation and precise target dates, internal electronic requests for additional procedures, smart forms to streamline reporting and compliance and better case allocation. How about streamlined, short MDTs with no chasing and disruption during reporting hours, etc.? None of it is high-tech, but I bet there is a bit in there.

Before we start reaping the benefits of digital and computational pathology, shall we also look into our reporting datasets and decide what is essential for patient management and what may be nice to have? I do not advocate shrinkflation of pathology; we do not sell chocolate bars, but pathologists will have to reign in the pseudocomplexity creep themselves. There is no one else to do it for them. Sorting technology is less unpleasant, isn't it? It may require conversations about money but does not require difficult conversations of another kind.

See you next week.

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