Change Changed! — Understanding Logarithmic to Algorithmic Change
Of Note; this is part of the course:
Title: “Decide Wisely: A Guide to Choosing A Medical Specialty In The Post-Pandemic Digital Healthcare Era”
Section: Understanding Logarithmic to Algorithmic Change
To learn more about the course: Visit the Academy
The following is the transcript of the lecture:
Hi, this is Junaid, Founder of aineurocare.com. Glad that you have joined this course. The whole course is divided into three parts.
- Understanding the Changing world and its implications in Healthcare
- Work-Life Balance
- Future of Healthcare
Part 1 consists of 1 module with 9 lessons and this whole module is like a prelude, an appetizer for the whole course because this is sort of a conceptual mindset that you need to understand before starting this course. So, now, let’s move on to lesson 1:
Change is Changed — Understanding Logarithmic to Algorithmic Change
First, we need to understand that the change itself is rapidly changing and we’re not going to see the pace of change as slow as it is today. Due to the digital transformation, there’s going to be radically different healthcare soon and we can see this complete transformation already in many sectors like industry, finance, entertainment, and even in education.
The difference between Industry 4.0 & Healthcare 4.0:
Conceptually what we need to understand is how Industry 4.0 will transform the healthcare sector. Industry 4.0 is different from healthcare 4.0, and the real difference is that in an industry the main interactions are between machine to machine or human to machine. However, in healthcare, major interactions are between human to humans or even multidisciplinary teams. So the transformation takes a little longer and takes a little bit more effort because it’s a cultural change and not just a workflow change. Therefore, this transformation in medicine will take a little longer compared to other industries but will come for sure. And the question really is, how well are you prepared for it?
Challenges in Medical Education:
The two biggest challenges facing medical education are:
- Exponential Growth of Knowledge
Exponential Growth of Knowledge:
The growth of knowledge is increasing exponentially. It is said that medical knowledge is doubling every 73 days. But given that we have faster analysis, robust data, and the ability to churn out data significantly as compared to 10 years ago, there will be an explosion of medical knowledge.
Physicians need to learn the limitations of these new different techs and devices like HealthcareIOT, Artificial Intelligence, Blockchain, etc., to better understand and serve their patients.
This will lead to a reformation in healthcare and that’s already in shape. For example, nobody reimbursed telehealth before and only telestroke was reimbursed. But now there’s an openness from both Congress and Senate to completely reimburse telehealth at all levels, including federal and state. It’s a significant change and these reforms will completely digitize healthcare.
Data — The New Oil — Pinnacle of Financial Success:
If we look at history, the two major companies that were at the pinnacle of business were either energy or military and those two were considered the best investments in the last century. But now, there’s a complete shift towards data itself. Those companies with high-quality data are considered the pinnacle of business investment and we can see companies like Google, Facebook, Apple, Amazon, not just because of their technologies (which is important!), but also because they have a massive amount of data that is considered more valuable than gold and oil. For example, if we look at Tesla and examine why it’s highly valued, it’s because of the immense amount of data they collected from 10 billion miles of driving under their belt. That data in itself is so valuable that it will generate industry after industry. Hence, Tesla is not a car company but technically it’s a data company and that’s where the commercial value lies.
Artificial Intelligence enabler of disruptive technologies:
As the heading says, AI lies at the heart of all of this. It’s not possible to turn all this data into technologies directly that are usable and consumer-friendly. First, we need to analyze that data so that it turns into information, and information turns into knowledge and then knowledge turns into wisdom. Therefore, AI is at the heart of all of these disruptive technologies that we’re seeing.
Please make sure you follow the website: academy.aineurocare.com
All the slide references are available there for you to review and there will be updates that are no longer recorded but will be included within the notes for the course and show notes if it’s on YouTube