- English
- Українська
- Русский
Healthcare and pharma industry
How medical institutions can win from a using machine learning? And why it`s crucial to bring evaluation along the patient recovery stage.
Data Science born in science laboratories where only very narrow science community could use it properly.
Now due to such methods as ML doctors, patients, and pharma industry can cover their unsolved targets.
In this fight for understanding each other, all the participants would benefit.
Doctors would like to have more definite answers our of this and eliminate all the noise of the complaints
Patient treatment progress monitoring
What task was resolved?
Doctors usually treat patients based on outdated description about their manner of self-treatment. This type of getting information can cause serious damage because a sickness could transform into a chronic disease.
Sometimes for relatives that seems the best variant is to put a patient to the hospital for all day keeping.
Challenges:
Being the "people of science" doctors would love to see all the facts to draw up the right conclusions. On the other hand, a sick person usually can`t understand what is important to write down about his treatment and what is not.
That`s why we`ve tested a range of formats that people would eager to fill frequently. We tried text formats (like social communication in facebook), photos (like Instagram), but none of them were suitable for all parients. As we know, the most people that are needed in treatment - these are the older people. And they need a more delicate and more human manner of communication.
Still, the doctors would like to have more definite answers out of this and eliminate all the noise of the complaints.
Did you feel the loop here?
How all of that was done?
We managed to break this circle by the means of ML technology. That`s a so-called medical assistant.
Firstly, a doctor creates an online web-forms with questions and some variants of answers, indicate the delays between next questions or the whole poll and assign a range of patients to it.
A patient gets one questions at a time, can make an answer about his temperature, pressure, weight, type of bad food that seduced him today or ask something to the doctor as well. All would go smoothly, as a life-changing of thoughts.
More than chat-bot - is analyzing personalized trigger within each clinic and medical institution about particular segments of patients.
Results:
Our methodology could be easily set up within any medical institution.
Doctors could spend their precious time to professional conferences, writing articles and preparing innovative treatment methodologies.
While patients get a 24 hours/ per day discussions about their life, manner of living and proper treatment.
How to avoid situations when patients being damaged by treatment? Or keep away pharma companies from being sued?
Side effects detection in drugs
What task was resolved?
Pharmaceutical industry struggles to bring new medicines into the world. Decades are invested into R&D stage, many years are put into the marketing and product certification. Unfortunately, side effects could happen due to various reasons.
That`s crucial as for the society, as for corporate segment to get the notification about this fact as soon as possible.
Challenges:
Discussion between patient and doctor can form a solid basis for understanding the cause of the disease and how the treatment is working.
Still, this open conversations is hard to reach, especially if a patient comes to a doctor to resolve his problem quickly and effectively.
How all of that was done?
A web and mobile App with questionnaires handle all the missions that we have. Patients were eager to answer some quick questions during their day, rather than remember all of that during the doctors' appointments.
Results
The whole statistics about the facts of drugs misuse can be stored separately and anonymously send to the doctor and medical representative immediately.
Next stage (like a side effect formalization) can be made within our system, that keeps patients info safe and protected.
Doctors were amazed how fast and convenient this process became
Early diagnosis of diseases
What task was resolved?
There is a bunch of people that got some strong disease but didn`t realize that yet.
If a person would like to live more and make his life more filled, so he needs to know the fact about his sickness and struggle with it on an early stage.
Challenges:
Unfortunately, not all of us understand the crucial needs of early diagnosis.
Still, there is a particular group of risk for a certain disease.
That`s why cooperation between different business segment could take place.
Firstly, doctors were frustrated what technology would help them to do that.
How all of that was done?
We managed to do that with a help of communication tool that provides cheat sheets for medical assistants and doctors to speak quickly, effectively and write down all the answers in a flash speed.
And finally, when they used this tool, so they were amazed how fast and convenient this process became.
Results
Doctors eventually remembered, that all their efforts are about people`s lifetime on this planet. And their assistants get a perfect professional lesson how new technologies could rescue lives and extend lifespan.
Medical representatives can become a scientific advisors
Communication between doctors and medical representatives
What task was resolved?
Highly professional doctors have plenty of patients to speak with, work with and a lot of examinations or operations to do.
Medical representatives could become their scientific advisors in the world of drugs and prescriptions.
Still, there is a lack of tools that could easily provide that sort of high-conversation level for articles exchange, discussions and interactive graphics.
Challenges:
The main aspect that put in a corner some deeper discussions and argumentations - is the absence of data within a particular part of science investigation (sometimes it`s about the local level of data that is much more relevant to the doctors' reality).
How all of that was done?
We helped doctors to see medical representatives as their fare colleagues, that could help them to gather scientific research for some certain narrow question in order to get material for the international article.
Results
World science needs a new type of methodologies, attitudes, and drugs. Revolutionary inventions could be made by the step-by-step method. Mutual science article formation between medical institutions, doctors and pharmaceutical companies can become an assertive step towards saving billions of lives.
