About the doctor and Digital Transformation


Last week I had to take a day off to take my son to the hospital for a little surgery. While he was recovering from the treatment, I got to talk to his doctor. We shared some thoughts and came to talk about both our professional careers. When I told about analytics, the doctor picked up on it and mentioned his daily struggle to find his way into to wealth of prepared reports the hospital provides him. I mentioned I understood: "the adoption issues that regularly seen within business analytics, are often caused by the huge amount of offered reports that are strongly alike, highly unrecognizable from a visualization stance, and often named and stored at the highest "secret" places and thus unfindable". Of course I couldn't resist and started explaining him what he should say to the hospital's BICC team in order to get things bettered (I'll explain in a separate blog).

Later that day when my son was ready to go back home, we had to wait for the doctor to get some prescription. The patient before us was talking to the doctor; he had a rack with electronics equipped. When it was our turn, of course I asked after the rack and what the electronics did. The doctor explained it was a device that allows him to monitor the patient's breathing from distance. The device is an implantable reciver and injector, that is in the patients body. It is also connected to a reservoir containing medical fluids and medicines.

This patient suffered from serious asthma and real-time monitoring of his breathing is necessary for the doctor and patient to immediately act with medicines if the situation requires. Wow, brilliant technique and based upon Iot data-interaction. Lenz and I were lucky the doctor explained a bit about it, and what it allowed him and the patient to do with it.

Asthma diagnosed

As said the patient is diagnosed with a very serious level of asthma causing infrequent breathing and life threatening behavior when not treated well. Treatment for this patient is on various levels:

  • fluid - injected - medicine to stabilize breathing and treat the asthma

  • adjusted diet depending on the breathing and condition of the heart

  • if breathing is destabilized for a longer period, the patient temporarily relocates to other countries with high mountains. The thin air helps getting the breathing back to normal

The device works against a predictive analytics model that calculates when breathing starts deviating from this patient normal breathing rhythm. Only (!) when this starts happening the device is starting to alert to doctor. The doctor receives these alerts via a personalized patient-dashboard on his mobile device. The dashboard indicates deviation, current breathing, location of the patient, and the condition of the air where the patient is located. The schedule of the medicine is also indicated since this patient has a permanent infusion that automatically injects the medicine when the patients condition requires (see picture).

Monitor and interact

I asked the doctor what he can do to follow up on the treatment using the Iot tranceiver/injector. The doctor has following capabilities using various analytics components:

  • he has permanent and real-time insights on breathing, heartbeat and medicine usage

  • at any moment in time the doctor can influence the usage schedule of medicine injection. The patient can do this only in certain cases. Adjustments are always send to the doctor

  • any moment heartbeat, breathing or medicine deviate from what is set as "normal", both the doctor as the patient are informed so the doctor can adjust medicine injection. The "normal" state is permanently monitored via a self-learning predictive analytics model. The model gets better with time. If treatments work well in certain conditions, this is "translated" into the model.

  • If the patient's condition (heartbeat, breathing etc) trends to go down, the doctor is informed so he can liaise with the patient and consider temporarily relocation to better climats

  • alerts for both the doctor as the patient when either the medicine tends to run down or the quality of the medicine gets below a certain treshold level

  • given the patient can use the remote device that is connected to his tranceiver to key in his meals, the doctor has clear insights on what diet treats well and which one doesn't. If the doctor wants to simulate and explore other diets, he can take all the patients Iot data into a self-service BI component and blend that data with the alternative diet data. The doctor uses a similar technique when he wants to combine the patients data with data from similar treatments in the rest of the world. The hospital where the doctor works buys treatment data on an annual schedule as reference and source for study

  • the outcome of the permanently running self-learning predictive model is shared towards other patients. This allows the hospital to better the overall treatment of asthma patients; things learnt with one patient can be reused with another

The above is just a summary. What the doctor told me is really impressive. It brings tremendous value add to the quality level of asthma treating for both this patient, the doctor and hospital, but also to other patients. It saves both the doctor and patient plenty of time since the number of appointments they had together decreased dramatically. The Iot application behind is a good example of an Industry Specific IoT application (see this blog for all the details).

Interoperability

Asking what could be improved, the doctor pointed at scientific research to better the predictive models. Now it was my turn to tease him a bit, challenging him to think "broader" than just straightforward healthcare. Two coffees later, after explaining what Interoperability of IoT Applications means, we came up with the following list:

  • Wheater conditions greatly affect the condition of this patient. Some conditions are really good, some specific ones are bad and the patient better avoids being in these conditions. If the current IoT application could be connected to the wheather forecast, the patient can plan and act-upon expected bad conditions. It would keep his permanent condition way more stable and as such help his health

  • Though the current IoT application is connected to the hospitals core system - so the patient files can be automatically followed up - it is not connected to the systems of Social Security. If this could be done, the usage of medicine (covered in this patients social security package) can automatically be cross-charged to them saving time and administrative work

  • an asthma's patient worst nightmare is smog or air conditions that are contaminated. With the Smart City concept, many cities start measuring and distributing these air conditions. If the patient's IoT application could be connected to thes Smart City applications, he could avoid these unplesant situations. Unfortunately our city is not yet a Smart City, but the idea is great

I left the hospital with a very positive feeling. This is great technology and a very nice example of where Digital Transformation brings us. Everybody benefits in this specific case and that's what Digital Transformation is all about.

Ah, by the way, my son Lenz is fully recovered and healthy as one can be !

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