Summary

I want to know how my health is, specifically, what I can do for better health, and I want to “know what I don’t know” about my health – and I don’t want to randomly run to different doctors and find out what and how myself.

It is a service with elements of medicine and IT

• medicine part
  • periodic blood sampling, etc., and quantitative examination => a bunch of numbers (how much iron, potassium, .., but also more complex data from hematology, diabetology, etc.)
  • preventive examination for specific diseases, see indications below

• IT part (applications)
  • storage and analysis of data from samplings, based on which the application gives alerts (this logic developed in cooperation with doctors) what I can ignore and what I shouldn’t and how to positively influence the numbers (eat more of this or that, …) – and of course I can see the trend, and in an extreme case what examination to do to be sure (if the numbers indicate a possible disease)
  • a list of all possible diseases that I can get, with an indication of the risk for me specifically (based on age, etc., and the data from the samples), and an indication of whether I have been tested for the given disease (~ green, I am OK), or when should I go again if needed regularly (~ orange, warning) or not at all (~ red, should go)
  • the application plans for the user when and where to go for sampling and examination – cooperation with a network of doctors

SWOT analysis

Strengths

the target group could be represented by people who are willing to pay for not having to think, but just listen to the application

Weaknesses

the Service will not be inexpensive for end users to operate; economy of scale will not work for services (? subscriptions ?) that are not paid for by the insurance company; implementing data upload and analysis logic will be expensive

Opportunities

The IT part is absolutely universal, almost identical logic will work everywhere in the world (quantities and units differ at most)

Threats

obtaining and processing such data leading to non-trivial recommendations is complex, e.g. if the method of examination will change over time, there will be other quantities, etc., or the data will be ‘chaotic’

Business model

• the user pays the operator for the service (periodically)
• the user pays doctors only for procedures not covered by the insurance company (specified in the application)
• actively participating doctors are paid by the operator: for example, if they help set up a model according to which the documents that the user receives from them are interpreted
• doctors who do not participate in it are not paid, and therefore the operator has to solve it “manually”, i.e. the user uploads scanned documents from the doctor and someone from the operator has to unlock the data manually

Ad data sensitivity and the legal side which is often a topic in this area:

• only the user has access to the data in the application; access, allowing the participating doctor to upload data to the application, or to view it, is a one-time action subject to the explicit consent of the user
• data security, including possible external audits, and compliance with GDPR, etc. is standard