My first journal paper now available open access

My first journal paper of my PhD research was published last November. It was my first scientific paper ever. Although I have written many reports and papers over the past 20 years, writing a scientific paper was something else. It was a team effort of all authors. It was peer reviewed twice. It took a time: 1,5 year from first submission to publication.  This week I received an offer from the publisher to make it open access (for free). Good news, now people can now actually read it!

You can read or download it on the website of SAGE: https://journals.sagepub.com/doi/10.1177/0951484818813488. If this link does not work, then search on ‘Identifying logistical parameters in hospitals’ or copy DOI code 10.1177/0951484818813488 into the internet search engine.

This paper is about the logistical parameters that are used in research on hospital logistics. The aim of this research was to see what logistical parameters are mentioned in international literature. I was particularly interested to see which parameters were mentioned in relation to hospital strategy, because in my experience logistics and hospital strategy did not seem to go together (see an earlier blog).

To put it bluntly I hardly found anything on logistical parameters in relation to hospital strategy and on the operational level I found, well, maybe I should say, too many logistical parameters. There were 106 in total.

What are some practical lessons to be drawn from this paper?

Local and global logistical parameters 

One of the reviewers of the paper commented that it would be very useful to be able to draw some kind of framework from this, in order to present decision makers with a useful tool for controlling hospital logistics. That would be extremely useful indeed, I agree, but how on earth would that be possible? Not only did we find 106 logistical parameters, they were mentioned in the context of 92 very different subsystems of the hospital. I think we have to distinguish between local parameters – relevant in a particular context or department – and global parameters that have a hospital wide relevance and impact. It is related to the issue of the right ratio between integration and differentiation in a hospital (see this blog).

Define logistical parameters that are relevant for the context 

Another thing that struck me is that logistical parameters were not defined clearly (or not at all) in several papers. Throughput time and lead time for example seem to be used as interchangeable words, but are they really the same? So a first step towards any framework would be to define what is meant with these logistical parameters. A next step would be what norms are useful: when does waiting time become a bad thing? This can be valued in different ways in different contexts, subsystems or even situations. Frameworks therefore need some kind of standards, but also need to be flexible, that is: using different standards for different situations. Standards will have to be developed in the hospital practice and there needs to be a debate about them between the different agents in the hospital.

Find the relation between logistical parameters

It is important to relate logistical parameters to one another. We all understand that if there is no waiting patient in the holding, the utilization of the surgeon in the Operating Room will be low. So utilization and waiting time are related. That is easy. With 106 parameters this leads to a very complex model. But I believe it is essential for hospital management.

Optimization or balancing 

Most people want to optimize, to achieve the best possible result. In the over 1000 research papers that I read, in the individual studies researchers tried to optimize one or maybe two parameters. However, this optimization of one logistical parameter can lead to undesired effects for other parameters. It’s not just that we have to know how parameters influence each other, perhaps we need to balance parameters. I am not really sure yet how this should work, but it would mean something like getting all parameters at their most feasible optimum, in relation to each other.

 

 

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