NEW AGE HEALTHCARE IS KNOCKING, LET’S BE FUTURE READY-Part2
By: Sanchez Bhattacharjee
Tags: Medicare, Healthcare, AI, Medical Devices, NLP

With the recent progress make in Diagnostic world with gene editing tools and AI/ML ever expanding toolsets big changes are in plate for modern healthcare . Please go through the first part of the article

So lets start with the exiting part of an introduce to the components needed to achieve this automated healtcare system .

100 ft view

How the system works under the hood to make this happen

WITH THE COMING FUTURE IS OF PRECISION BASED MEDICINE RATHER THEN INTUITIVE MEDICINE

There are 3 major chunks in which we

1. A Intelligent BOT

(A family friend/member who listens and advises)

The chat app starts with conversation asking about how are you feeling today gaining insights on how the patient feels and capturing as much data as possible with a list of queries and maybe information related data with it can fix the data then converted to a secured format and transferred securely using internet protocols.

only once it gets an input for further tests needed this will guide and suggest tests locations and booking slots , this takes to step 2 .

While informing patients about the disease and the cause of pregnancy the information will be processed by an extra layer of psychology and outputs the data in more soft and patient understandable format and suggest best practices to be followed based on patients lifestyle.

statistics : smartphone users

2. DIAGNOSTIC CHAIR/CLINIC (A Intelligent chair)

The whole idea of this is to convert all diagnostic inputs to digitize and then send digital signals to a centralised module to have a clear identification of the disease based on the learning Algorithm .

Some examples of LAB output digitisation already in industry

> Strand base blood sample digitiser

> Image based ophthalmology scans

> Insta ECG With the InstaECG, patients can receive the Cardiologist Certified ECG reports within 10 minutes.

> multiple diagnostic parameters like ECG, BP, Heart Rate, Auscultation, Oxygen Saturation & Temperature

> Urine and spags digitizer

> Radiology : Automated Image sampler and classifier already in lace

> dermatology : skin diseases identification by image with 95% accuracy

> oncology : Watson oncology with world database

> cardiology : Ex AI based predictions based only by looking as Eye(retinal images0)

Accuracy of the tests :

Digitised data producing instruments should be accurate and should be periodically calibrated are checked by third party vendors which gives a man’s new business opportunity the windows can take the maintenance and replacement of parts and handling of issues are complaints raised by the clinic attendant

This provides huge market for the maintenance and operations of the instruments and they can provide services based on demand and request raised

Calibration Layer:

The calibration people should certify the instrument as ok or not ok and they are completely another set of vendors approved by the government who can validate whether those instruments are working perfectly and then only we give a certificate of ok to them . Government can choose the validation process as per inspection guidelines decided by centralised unit in the government.

3. THIRD PILLAR (Computation and Decision making layer) HEART OF THE SYSTEM :

Below shows how the third pillar which is basically the brain of the system and it will detect and identify the disease and suggest a treatment course which the patient has to follow and App guide him through the process of treatment

The identification will be done from a centralised unit and can be kept as a block/sector level cliparts what is for disease identification and the second part is basically treatment identification the disease is defined based on the artificial intelligence for algorithms then the probable flow of treatment seeing the age and other factors are considered and same has been responded to the patient back.

Disease prediction Framework :

The prediction of the disease is done by a framework of centralised data and AI, ML algorithms which mine data based on the patient’s age , race and previous history .

The predicted results should be reliably accurate and all non certain predictions are sent for further physical evidence collection .

Currently there are several systems in work , and in progress in countries like Israel, US , and Taiwan .

Solution reference :

https://paperswithcode.com/task/disease-prediction

https://www.nature.com/articles/s41598-017-05778-z

This system should be a collection of all such relevant aggregation solutions.

Treatment Part :

The patient will get updated information about the treatment plan and medicines in the app and he can provide feedback on his current condition and help in the app itself based on that presented the system may decide whether this treatment is going ok only for the needs to go to a specialised clinic at to further check

4. SPECIALISED TREATMENT(ALL EXISTING HOSPITAL INFRASTRUCTURE )

Specialized treatment:

When a patient is identified with a specific kind of treatment , we have our existing hospitals set up as specialised units and can admit and treat the patient in need . Admission is given only when essentially required .

All the present system of hospital chains will work on this half with updated data about the treatment and patient condition . there is a dire need to automate the infrastructure

all communicable diseases , more robotics and automation should be there to replace the non essential human interaction .

5. CONSTANT MONITORING:

Wearable technologies can be innovative solutions for healthcare problems Some wearable technology applications are designed for prevention of diseases and maintenance of health, such as weight control and physical activity monitoring.

Wearable devices are also used for patient management and disease management. The wearable applications can directly impact clinical decision making. Some believe that wearable technologies could improve the quality of patient care while reducing the cost of care, such as patient rehabilitation outside of hospitals. These wearables are connected with the health app and provide updates and precaution to the patient .

COMPARISONS WITH CURRENT MEDICAL SYSTEM:

> FASTNESS iN DISEASE IDENTIFICATION:

The system will completely eliminate the need of visiting a doctor and go multiple Times and test to identify what disease he has by seeing the result of some lab test so the patient with this system can roughly the disease kind of in a few hours time and start with the course of the treatment also if you are sometime

> CONTAGIOUS DISEASE HANDLING (present covid scenario)

An early system alert based on Number if patients having similar scenarios . Handling the treatment in a contagious disease the treatment in a contagious disease is done with no touch of any human and that how’s the full system to be human free. This gives unlimited saving any chance of further communication of disease cause and treatment and isolation . Peoples and thus help in stopping the spread

> SAME QUALITY OF TREATMENT FOR ALL

Getting the services of best quality diagnosis and support throughout any part of the country including the most rural areas just had better internet connectivity and a working system of the disease identification module.

> REDUCED HOSPITALISATION:

Saving the hospital BED Load and only treating the patients in hospital or needs accountant monitoring and care so that the patient can get breast in glass treatment and if things needed then only move to hospital.

and many more

> SPEED OF DOCTORS GETTING READY AND ASSIST :

It will be very easy to scale and update and teh system can scale up or scale down according to load

and it will also assist as a doctor as it can handle 24 hrs of monitoring .

FUTURE READY SETUP

This kind of ecosystem of the equipments and technical systems that feed the patient in a easy and best possible way is a step ahead in future the patience will update the system with new data and new tu diseases that will make the system more accurate and the whole think and perform even better as the days goes by the system can be started as a pilot project and can work as an assistant for initial years of setup and when things mashup and its accuracy increases can slowly integrate and the healthcare as a whole .

Lets discuss on business aspects in Part 3(coming soon)