Earlier in Part I of this series, we reviewed the formation of an alliance between Amazon, Berkshire Hathaway and JPMorgan Chase in their bid to reduce healthcare costs. The move highlighted the intrinsic inefficiencies of the healthcare sector – for example, the American market – which are largely the result of a highly competitive but fragmented industry.

As Warren Buffett had pointed out that the "ballooning costs of healthcare act as a hungry tapeworm", the current inefficient market has prompted much innovation and entrepreneurship within the sector. Rapid changes and sweeping transformation become the hallmarks of today's healthcare – with profound consequences to patients. So, how is the industry evolving?

Less is more: Replacing volume with value

After the introduction of technological advancements into healthcare settings, doctors have been ordering more tests – although it is mainly due to patients insisting on them.

Back in the days, “we were told to first clinically examine the patient and record the medical history, and you must roughly know what the diagnosis is,” details Dr Ravindran R. Naidu, President of the Malaysian Medical Association (MMA), “then only tests are taken to investigate and confirm the diagnosis.”

“Today, tests are taken first, before a diagnosis is made,” he adds, suggesting that healthcare professionals could be over-reliant on technology.

Dr Ravindran R. Naidu, President of the Malaysian Medical Association (MMA), advises that doctors should not perform tests unnecessarily
Dr Ravindran R. Naidu, President of the Malaysian Medical Association (MMA), advises that doctors should not perform tests unnecessarily

However, the industry has witnessed the proliferation of the understanding that performing more tests does not mean better diagnoses – neither is dishing out more treatments helping patients recover faster. As such, the effort of reimbursing healthcare professionals based on patient outcomes – not the type of services – has been recently enforced in many countries.

As succinctly described by an article appearing on NEJM Catalyst, value-based healthcare rewards healthcare providers – hospitals and physicians – by "helping patients [to] improve their health, reduce the effects and incidence of chronic disease, and live healthier lives in an evidence-based way.”

Measuring “value” of healthcare in such a way is expected to benefit patients, providers and payers, alike. This achieves a more meaningful and practical outcome for both the patients and providers, while payers (such as health insurance companies) have more control over costs and reduce risks. Transforming from the fee-for-service to fee-for-value care model is not easy – but, it may be the best solution to reduce healthcare costs while improving the quality of care simultaneously.

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AI: Here to help, or take away jobs?

Despite the suggestion that healthcare professionals may be over-reliant on technology, experts believe AI will be able to help expedite diagnoses and identify treatments accurately.

Studies already demonstrate that AI is better at diagnosing lung cancers and heart diseases compared to doctors. A Stanford deep-learning algorithm has also outperformed radiologists in diagnosing pneumonia, based on chest X-ray images. As computing power increases exponentially in accordance with Moore's law, so does the ability of AI to analyse data and make accurate, actionable predictions.

Several prominent technology companies have already had their eyes on AI. Among them is Google, which launched its Deepmind Health project, in 2016. Working closely with the National Health Service (NHS) in the UK, the project aims to mine medical records for more efficient and quality health service.

Another tech giant, IBM, also launched the WatsonPaths project – in collaboration with the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University – to help physicians make better decisions based on data from electronic health records.

It is a “collection of cognitive-computing technologies that are combined and instantiated in different ways for each of the solutions,” said Watson research director Eric Brown, adding that Watson is a powerful engine that can revolutionise medicine.

Eric Brown, research director of IBM’s Watson, inside the physical system. He admits that Watson’s training is an arduous process and makes mistakes, but it is all part of machine learning.  Photo credit: Robyn Twomey, Fortune
Eric Brown, research director of IBM’s Watson, inside the physical system. He admits that Watson’s training is an arduous process and makes mistakes, but it is all part of machine learning. Photo credit: Robyn Twomey, Fortune

Despite it all, is AI in healthcare overhyped?

“I think it’s real and will continue to progress in many aspects of our lives and healthcare,” says Dr Fazilah bt Shaik Allaudin, Deputy Director of eHealth Planning Unit of the Planning Division at Malaysia’s Ministry of Health (MOH). “I have witnessed IBM-Watson myself and see the huge potential in cognitive computing.”

“But, the mind-set of the people using it, is the biggest challenge in implementing AI,” she details, reiterating the conservativeness of the healthcare industry.

While some suggest that AI will eventually replace human doctors and other allied health professionals, others are adamant that the real world human input will still be valuable. Human judgement and computer logic should work in a synergistic manner and must be perceived as complementary, not mutually exclusive, to each other.

Dr Fazillah bt Shaik Allaudin, Deputy Director of eHealth Planning Unit of the Planning Division at Malaysia’s Ministry of Health (MOH) hopes that the healthcare industry would be more open to accepting technological advances. Photo credit: Naja Najwa, Hacking Health KL
Dr Fazillah bt Shaik Allaudin, Deputy Director of eHealth Planning Unit of the Planning Division at Malaysia’s Ministry of Health (MOH) hopes that the healthcare industry would be more open to accepting technological advances. Photo credit: Naja Najwa, Hacking Health KL

The era of P-medicine

With the advent of big data and advanced data analytics, the sector is also increasingly reliance on "p-medicine" – personalised and precision medicine – for more targeted and effective treatment. The term "personalised" and "precision" are sometimes used interchangeably – although both carry a different meaning.

According to the paper authors, Shihab Sugeir and Stephen Naylor, the precision medicine model is based on the concept of “1-in-N” while personalised medicine uses the concept of “N-of-1”. Regardless of the technicality of both terms, the industry is quick to embrace p-medicine as the future of healthcare.

It remains to be seen, though, whether these new players in the healthcare market can effectively bring down costs and improve quality as a whole for the industry. Experts will continue to make speculations on new start-ups, mergers and acquisitions, or major movements within the industry.

It will be wise to keep a close eye on these businesses to see if they can really shake up the industry or fade into obscurity like many other failures before them. MIMS

In our final Part III of this series, we look into the future trends of the healthcare industry – and see if they are worth investing.


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https://www.sciencedirect.com/science/article/pii/S088394411731674X
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