Starting case research

In the past weeks I have started my first case study research in a hospital. My main research question is of what elements the logistical system consists and how it functions. My focus is on the Operating Room department (OR) and all its supply  chain partners, varying from nursing departments to the central sterilization unit. I selected a relatively small hospital of which from earlier experience in my work my impression was that they were doing a good job in their daily business of running an OR. The idea behind this is that in a relatively small hospital, that is in a stable situation, we would then get to know the logistical system of any hospital.

First of all: how did I get the impression that this hospital was stable and functioning quite well? I got this impression from two consultancy jobs I did in the past years. When I ask people in this hospital for data, they deliver these. When you make appointments on meetings or actions, they show up or follow these up. This is not always the case in all hospitals. Many times hospitals cannot quickly find data on processes or performance. In this hospital, they seem to work together as a team and everyone I have ever spoken to in this hospital, knows how things are working or they tell you that they do not know and get the right person to answer the right question. For me, it had always been a pleasure to work with these people. So I asked them to work on this case study research together.

In the past month I have collected all production data from the past five years and over 40 documents on patient, material and staff planning. I am still in the middle of getting a grip on all these data, but, as first impressions are the best, I share some here.

Data are hard. They are hard to get; it makes you feel part of a scavenger hunt and being a girl scout. I started with the application controller, who gave me the production data, but after that I have walked around the OR talking to people who then showed me their paper lists, system overviews and information sheets that they use daily for preparing surgeries.

Data are also hard to interpret, as everything is coded. That is not to be secretive about it, but to limit the number of letters or words in systems or on lists. Names of medical specialties are are pretty easy to understand as three letters, but the other dozens of codes reveal (or rather hide) a world unknown. And the thing is, every group of employees uses its own codes. The OR planner uses different codes as the internal material staff. The people using the information systems talk in system codes, those who don’t use other jargon. You need an interpreter.

Further, there is a lot of data. The number of surgeries are large, the different kinds of surgeries are numerous and they have names that I cannot reproduce. Interestingly enough a seemingly easy question – how many surgeries does each medical specialty do per year- requires a lot of effort. I have worked on this for half a day and I still do not know. I need the interpreters and system experts to go along on my hunt for this, for not all surgeries have a medical specialty registered.

Almost every data set is filled with gaps. Some for good sensible reasons, some gaps are inexplicable. The inner circle – a few people on the OR – know why this is the case and how to interpret it. Where would be without these people, I wonder. We would be lost. Maybe we are already, because I have not met anyone yet who uses these data for strategic purposes. In fact, it appears there is no relation between the hospital budget and the number of surgeries planned or realized.

Recently one of the board members of the merging academic hospitals in Amsterdam stated that larger hospitals are necessary for transparency. Hmm, if for one OR it is quite a lot of work to find out how many surgeries per medical specialty there are on one OR department, then how transparent will two merging academic hospitals become?  I don’t think I would use the word transparency for current logistics. It is a mystery to most people.

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