Exploring the Tipping Point of Explosive Growth in the Medical Industry — Value Chain Analysis
This article suggests that the tipping point has already begun to occur and explores innovative developments in the healthcare service value chain. It starts with technological innovations such as RPA and AI, combined with platform business models, leading to disruptive innovation with sustaining innovation as a supplement.
Then, it will enter an era of institutionalized reform, promoting sustaining innovation based on value-based solutions.
What is worth noting is that AI technology permeates the entire healthcare service value chain, and a certain company’s monument is used here to illustrate the ultimate goal of all technologies.
Theoretical Basis
The theoretical basis of this article is mainly based on Clayton Christensen’s Innovator’s Prescription and Scott Galloway’s Post Corona, From Crisis to Opportunity theory. In addition, Scott Galloway’s book, The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google, inspired the author to use a value chain framework to analyze industry development.
Value Based Solution
The initial basis of this article’s thinking is based on Clayton Christensen’s Innovator’s Prescription theory, exploring the following topics.
At that time and in that context, although there were mature platform business models, there were not enough technological capabilities to drive disruptive innovation. In addition, the article’s thinking mainly focuses on domain thinking within the healthcare circle, exploring how to promote a Value Based System to achieve the goal of reducing unnecessary medical waste through the healthcare system and service model under the national health insurance scheme.
As time passed, it became clear that this was a slow journey, characterized by incremental innovation.
Finding a Way out for life
However, in the past five years, with the maturity of AI technology and the arrival of RPA technology, as well as mature platform business models for reference, disruptive innovation with incremental innovation as a supplement has solved the biggest pain point of healthcare services — the huge non-value-added costs, such as complex administrative tasks, outdated systems that cannot integrate information, and excessive use of expensive medical procedures.
Finally, utilizing such innovations, healthcare services have been able to significantly reduce costs and return to reasonable value.
Based on current observations, AI plays a similar role in the current healthcare industry revolution as early industrial automation, shifting tasks that used to require a large workforce, such as image interpretation, to machines, thus significantly reducing labor costs and improving the quality consistency and output per unit of time.
The development in this stage mainly aims to address the low efficiency, high cost, and limited quality of the current healthcare system.
In contrast to the value-based solution mentioned in the previous article (system section), the biggest difference is that the primary goal of AI in healthcare is to reduce unnecessary, non-value-added expenses, and bring the original care back to a reasonable price.
The value-based solution, on the other hand, focuses on effectively addressing the medical problem within the professional scope of the healthcare industry and avoiding unnecessary waste of medical resources.
For example, in the treatment of asthma, if a doctor introduces an electronic asthma diary solution that enables parents to record their child’s peak flow values daily and reminds them to take medication on time, the doctor can prescribe medication based on the asthma diary’s record, ultimately reducing the child’s use of steroid medications and achieving the goal of curing the patient and reducing unnecessary medication waste.
Observing the development of innovation through the framework of the healthcare service value chain.
From the concept of product differentiation in Scott Galloway’s book “The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google,” the author gained the following inspiration: differentiation is not just about selling physical products. It can occur in any link of the product or service value chain and can create value through addition or subtraction.
This article uses a simplified healthcare service value chain (consisting of administration, triage, diagnosis, and treatment) to observe the development of innovation.
According to observation, the development roles of different innovations from the perspective of the medical service value chain can be described by the following analogy:
In the past: Buying an iPhone 3G online costed $599 plus $34.95 for shipping.
Now: With the use of Amazon or Uber’s delivery, and the implementation of group buying systems, an iPhone 3G can be purchased for $499 with free shipping.
This is a subtractive approach, cutting out the hassle or unnecessary expenses, and starting a reform that focuses on disruptive innovation with sustaining innovation as a supplement.
On the other hand, the introduction of a value-based solution can be viewed as follows:
In the past: Buying an iPhone 3G online costed $599 plus $34.95 for shipping.
With the implementation of value-based solutions, the development is similar to the following:
Now: With the introduction of high-performance chips, an iPhone SE can be purchased for $599 plus $34.95 for shipping.
This is an additive approach, creating value and focusing on sustaining innovation as the main reform.
Therefore, this also shows that the trend in the future will be:
Future:
With the use of Amazon or Uber’s delivery, and the implementation of group buying systems, a high-performance chip iPhone SE can be purchased for $499 with free shipping.
Summary
The healthcare industry has reached a tipping point in terms of growth, and innovation in healthcare services will be driven by disruptive innovation with support from sustaining innovation through the introduction of RPA, AI, and platform business models. The ultimate goal is to achieve value-based solutions, which will involve a gradual and incremental transformation process that may be affected by changes in healthcare policies.
AI’s role in healthcare services will also evolve from significantly reducing operating costs to creating additional value through the Benjamin product effect. Given the diverse range of subcategories and customer segments in the healthcare industry, it is unlikely that there will be a one-size-fits-all solution for value-based solutions. Instead, solutions will be tailored to specific areas of service content.
In the future, platform businesses are expected to provide one-stop-shop services, and value-based solutions may resemble a specialty counter in a department store, attached to the platform’s development.
Others: AI, High-level Digital Workforce
As far as I can tell, any industry that cannot leverage AI in the next decade is bound to have limited growth potential or even be eliminated.
Now, in response to the evolution of AI, organizations are incorporating the role of AI in their product development, company management, quality control, and regulatory affairs planning, and treating AI as high-level digital workforce (because it can be continuously trained and evolved), and designing relevant supporting systems in the organization.
For example, I have somes to develop a regulatory review AI software (similar to an AI that reads contracts, but not as complex, and the basic version can be achieved through RPA), and is continuously researching it.
Currently, I see a suitable development approach and theoretically believe it can be executed.
In this type of company, I would first introduce a product development control software. The first step is to use AI to assist in checking the design input to track the product development process. In addition, the AI will learn from each complaint record and provide feedback to the design input. When tracking the product development process, the AI can generate stage risk management reports and check whether the corresponding safety test reports have been achieved.
Finally, the labeling required for the product, such as the manual, box, label, and other documents, will be proposed for operational design, and the labeling will be read by the machine to inform the regulatory interpretation result, which will be decided by the regulatory authority.
This system can greatly reduce the regulatory personnel’s review time, and even save most of the time for generating technical data. Even inexperienced personnel with logical thinking can quickly get into the job.
The significant amount of manpower cost/time that can be saved, and more importantly, the significant reduction in the probability of making mistakes, can enable regulatory personnel to use the saved time to improve processes or tackle high-difficulty products.
This organization will require an AI manager responsible for the system’s introduction, integration with relevant departments, and making the insights from process improvement part of AI training.
This is only a small part, and the research and development capabilities can be vast. This will be similar to the current computation simulation team, using AI to develop products and significantly add value to product functionality.
At this point, the company’s COO must have an integrated plan for such high-level digital manpower like AI to maximize the impact.
Therefore, when the development of an organization becomes a complex of humans and AI, compared to an organization that relies solely on manpower, it is self-evident who can survive in the market.
Finally, I would like to use a monument that often moves me. This monument was donated by my company’s number one competitor, Omron. The original picture is as follows.
Due to the effects of time and wear, I have personally used image processing to enhance the image as follows.
he text reads: “Let machines do what machines can do, and humans should engage in more creative work.”
Isn’t that the essence of AI?
Postscript:
04/15/2023: Regarding the AI assisting regulatory review, I had preseneted my requirements to ChatGPT, and it offers me the python code and related OpenCV package. Thus, I don’t need to hire any consultant and can proceed in my way.
