Hospital IT systems are replaced by intelligent agents called secretaries

Yesterday I spent the entire day observing three outpatient departments in ‘my’ case study hospital. I talked to the Orthopaedics, Surgery and Gynaecology outpatient departments and watched how surgeries are planned and organized. The night before I prepared the visit by looking at the facts and figures – the production data of 5 years, from 2013-2017 – of these three departments:

  • Orthopaedics has 6 operating people (operating orthopedists)
  • Surgery has 30 operating people (surgeons)
  • Gynaecology has 9 operating people (gynaecologist who do surgeries)

This all turned out to be fake information. There were 4 orthopedists, 11 surgeons and I don’t know how many operating gynaecologists, but it’s less than 7, because there are 7 gynaecologist who do not all do surgeries. How come the data were so misleading? I will explain with an example.

The 30 individual surgeons are coded in the data as follows: 00908, 00909, 00910, 00911, 00912, 00917, 00922, 00927, 00928, 00930, 00931, 00934, 00935, 01305, 05009, 42371, 509139, 509179, 509217, 509231, 509238, 509239, 509250, 509261, 509269, 509274, 509276, 509283, 509284.

I remembered that someone had said earlier that ’50’ codes were doctors-assistants (a doctor-assistant is a doctor who has completed his medical studies and is fully qualified, but not (yet) a medical specialist). So that leaves 13 people out in this case. I noted that some codes had a different structure than others: there are 12 009XX codes and some others such as 01305. And I found out that 42371 is actually a plastic surgeon.

For the other two medical specialities I did the same decoding of the data. For Gynaecology I could still not entirely work out the math. If there are 7 gynaecologist who not all do surgeries, then who are the 7 operators who have done a certain number of surgeries? That I will have to ask someone later in the process of this case study research.

OK. So the IT system does not really provide me with the right data. Well, the data are correct, probably, but they do not seem to provide the right information on the reality. I find it worrying, because many large strategic decisions are based on (high level) data.

This is nothing new for outpatient secretaries. They have realized for quite some time that the IT system is not perfect. They don’t really use the system for planning, just for registration. Although the IT system they use is provided by the market leader for hospital information systems in the Netherlands – Chipsoft, they do not use it for planning. All 7 secretaries I talked to independently stated that the system does not provide the overview they need to plan surgeries and that they have to bear in mind so many decision and control rules, that use prefer their own planning system. This system basically consists of their own brains and common sense. The tools they use look complety old-fashioned and obsolete. In fact, when they showed their folders, piles of A4 papers, paper diaries and whiteboards, they immediately started to apologize for their apparently middle aged methods. Some of these ‘tools’ had been used for over 20 years and were starting to fall apart. But, as they explained what the planning rules are that they use, their brains form a very advanced system. For example here are some of the rules they compile in their heads every day:

  • For a TEA carotis call the Intensive Care for a bed and arrange an EEG and plan vascular examination one day before the surgery takes place
  • For the combined PTA make an order for an X-ray
  • If there are multiple shoulder prosthesis surgeries, plan 3 days in between these
  • Doctors X, Y and Z are on a conference on dates A, B and C
  • Staff meetings for the upcoming months are on times X and Y so don’t plan surgeries then
  • There are only 2 instrument sets Y in the hospital so don’t plan 3 surgeries at the same time for which these are required
  • The Radiology starts at 8:30 each day so if an X-ray is required for surgery do not plan this before 9:00

In total it was said that there are about 70 rules and planning principles, but I believe this is just the tip of the iceberg. I have seen around 50 to 60 on paper documents, in emails, on walls and so on, but with each new person I talk to, new rules are added to my list. I haven’t heard them all, I am sure.

It seems a bit odd: the hospital has a state-of-the-art IT system but it does not suffice for more intelligent stuff. Secretaries do the thinking using tools that look unsophisticated, but what they actually do comes accross as very sophisticated, not in the least because they are an important coordination node in a very large network of agents. Often they have worked in the hospital for years (10 to 20 years) and their experience is priceless. The software, on the other hand, is actually unintelligent, I would even say stupid, but looks advanced. Maybe we are fooling ourselves when it comes to what or who is believed to be smart.

 

 

 

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Variation in Operating Room production; predictable or not?

If the demand for products or services are stable, then logistics is easy. In any household for example there are repetitive rythms, determined by meal times and working days. Meal times determine the moment that food supplies need to be in the house and working days could determine when there is time to buy these. Weekends differ from week days, and for someone working irregular hours the week pattern of activities could be different. Not every system has to be the same in order for it to be predictable. A variable rythm could be ‘nice’ in the sense that it repeats itself and has a certain flow, fitting for example with a natural life rythm.

I  believe a ‘nice’ rythm or flow is important for any person or system to be effective. So this would be important for an OR department as well. But what is the rythm of an OR department? And if we could define it, is it known to anyone working in the OR department? And do nursing departments or a sterilization unit know the rythm of the OR and do they adjust to this? Or does the OR adjust to the rythm of these ‘suppliers’ of patients and materials? Or do they each work in their own rythm, not matching the others?

First of all I therefore analysed whether the OR production data shows any patterns at all.

Looking at the weekly pattern of production, as shown below, there is variation. Each line represents production levels per week in a year. Each year has the same ups and downs in the production. These coincide with the school holidays in the Netherlands. The large dip, roughly between weeks 28 and 35, are the summer holidays. In the Netherlands regions do not all have the same school holidays and they shift every year. That is visible in weeks 7 to 10 for example: in this periode there is a recurring holiday, which takes place every year, but not always in the same week.

Blog productie patroon

Although the fact that there are ‘reduction weeks’ seems common use in the hospital world – at least I never heard anyone mentioning it as odd -, I find it remarkable that production varies based on school holidays. In contrary to for instance the education sector, demand for health care does not necessarily have a link with schools or children. The average age of patients in this OR is 54 years old. Do they want to be in surgery outside holiday periods? Or just before it? Or is (un)availability of staff the factor in this pattern?

Then there is a weekly pattern. In the figure below for each week day the total number of surgeries on a week day is presented, for 5 consecutive years: 2013 to 2017. Sunday is 1, Monday 2 etcetera. So in 2013 (blue column) the Tuesday was the day with the most surgeries and for 2017 (green column) this was Monday.

Blog productie weekpatroon

There are only emergency cases in the weekends (day 1 and 7). Friday appears to be a day with the least surgeries planned. Is that because one aims to have low occupancy rates in the nursing departments in the weekends? Is the expected length of stay a factor for planning surgeries on specific week days? Why is every year (or week) different?

This leads to several questions:

  • Is this year production pattern universal – in the sense that it is linked to national holidays for other hospitals as well? 
  • How could this production pattern be explained? Is patient demand or resource availability leading? 
  • Does this rythm serve a purpose (and if so, what purpose) or is it ‘just the way it is’?
  • How come that the variation in production changes for week days?

Please let me know by sending me a message what are your thoughts on this.

Blogging on scientific research

I am writing this blog for several reasons. First of all because I just like writing. Secondly I would like to share knowledge with people working in hospitals, with logistical or healthcare operations experts and basically anyone else who is interested in my research, including my friends and family who occassionally inform how my research is progressing. Thirdly I would like to experiment with sharing knowledge resulting from scientific research to a wide audience. Writing journal papers is one way to share knowledge. It is certainly valuable and very informative, also for myself, because of the peer review that comes with submitting journal papers. However, to share knowledge with the field, I believe journal papers are not sufficient. Journal papers are tough to read sometimes, especially when you are not familiar with academic writing.

This blog experiment is also meant to see whether this could be a way to share thoughts and ideas on the research itself. A common issue with case study research is that n = 1 (or, in my case 4 or 5). This raises a question like: are the things I see universal for hospitals or do the results only say something about the one hospital I have seen? In my experience, this last argument is used a lot in hospitals. I see a lot of similarities, but they are not always that obvious or they need to be made explicit.

Furthermore, my own experience, interpretation and maybe even personality could influence the outcomes. It is valuable to look at reality through more than one pair of eyes and by sharing my observations, I could perhaps put conclusions based on this, to the test. This is all the more necessary because I am an ‘external PhD candidate’, meaning I do the research in my own time, besides working as a consultant. I would like to see it as volunteery work rather than a hobby. A hobby would be merely for having fun – which is the basic motivation for doing this besides a full time job -, but I would like to think that it serves (some parts of) society.

The thing is: how do I reach the right audience? And how do I get these to respond, in these times of information overload and having questionnaires about every daily service you use?

In my next blog I will present some data from the case study research, asking explicit questions about these data. I will send an email to all Operating Room staff I know to respond to these questions and post the blog in Linkedin interest groups. Let’s see if this generates some feedback.