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The real future of healthcare is cultural change, not just AI and other technology



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“It actually is quite easy to be a futurist with regards to where are we going with health,” says Dr Ron Grenfell, director of health and biosecurity at CSIRO.

“It takes 15+ years to get evidence into practice,” he told the Commonwealth Bank’s Future of Health conference in Sydney last week. The “inertia of the system” will hold back the adoption of a lot of technology that’s being pitched as the future of health.

That, in your writer’s view, is one of the two big conceptual challenges at the heart of so many discussions of the digital transformation of healthcare. Vendors are pitching technologies like AI and chatbots to reduce the workload of humans, yet the healthcare sector is way behind the pace.

Dr Kevin Cheng is founder of Australian healthcare provider Osana. They use cloud communications provider 8×8 for their own needs, and use cloud-based medical records, but they run into the usual problems when communicating with other providers.

“I tried really hard not to buy a fax machine for our startup, but we failed,” Cheng said during a roundtable in Sydney last week, to much knowing laughter.

“When I talk to allied health and specialists, we’re often crossing IT barriers. It’s hard to get people on the phone to talk, so we’re very transactional … the other clinician could be sitting in a room next door, but we’re literally writing letters to each other and not talking,” he said.

Cheng believes Australia is lagging behind other high-tech nations. GPs in the US are now doing many of their consultations virtually, he said, whereas in Australian that generally only happens in remote locations.

“We’re having to create our own scorecards and dashboards in our own datasets, because there’s no reporting analytics that is on the market that fits our workflows,” Cheng said.

Phil Kernick, co-founder and chief technology officer of information security firm CQR Consulting, confirmed that belief.

“Nowadays doctors use computers for everything, and it doesn’t matter which industry you’re in, these are run badly. They’re run inefficiently. They’re run insecurely,” he said.

When it was “just” data, that didn’t matter so much. But software is now integrated into diagnostic and therapeutic devices, and if vendors are to be believed, AI will soon be taking control.

See: AI and the NHS: How artificial intelligence will change everything for patients and doctors

“I have a real concern that as everything moves to technology, and when we get into AI and machine learning something, we stop understanding how the technology works,” Kernick said.

We’re building systems that have a “very shaky foundation, and there are no regulations around this,” he said.

“If you look at the Therapeutic Goods Act, you look at how we regulate medical equipment, there are no software security standards. The information page actually says we take a risk-based approach, and use the same risk-based and safety-first approach to all systems, whether they include software or not. I mean, that’s just waffle. It doesn’t mean anything.”

Making patients the actual focus of healthcare

Cheng says that Orana’s strategy is to put the patient’s health at the centre of their business, focusing on prevention and outcomes, rather than the transactional fee-for-service treatment model.

“Patients are going to be consumers, so they’re our customers, and that means that we need to practice in a different way. We want to be partners with patients in their health and well-being,” he said, and data and apps will be part of that.

Dr Bertalan Mesko, director of The Medical Futurist Institute, says that the healthcare sector could and should go much further.

“By 2050 the most important change will be that patients will become the point of care,” he told the CommBank conference from Budapest. Not just becoming more engaged, or “empowered”, but the actual point of care and service delivery, using their own apps and devices to gather data, rather than travelling to medical facilities for diagnostic tests.

This isn’t so much a technological revolution, according to Mesko, but a cultural revolution. In your writer’s view, that’s the second big conceptual challenge.

“Since Hippocrates, for 2000 years, medicine has been quite straightforward. Medical professionals know everything, and they let patients come to them for help, they tell them what to do, and patients go home, and either they comply with what they were told or not. Usually half of them do, and half them don’t. That’s quite a bad success rate,” Mesko said.

Medical knowledge, and even the patient’s own data, were held in the medical professionals’ “ivory tower,” he said. But that’s changing.

See: VR, AR and the NHS: How virtual and augmented reality will change healthcare

“With crowdsourcing and crowdfunding, with Amazon and social media, with open access to medical papers, and all of these online communities out there, now patients can get access to the same resources,” Mesko said.

“The hierarchy of the doctor-patient relationship is transforming into an equal partnership.”

And sometimes patients race way ahead of their doctors. Diabetes patients, for example, have combined a continuous glucose monitor, an insulin pump, and a small computer such as a Raspberry Pi, to create what is in effect a do-it-yourself pancreas.

“Many of us have no medical or engineering training and we work on improvements in the evening or at the weekend, for free,” Dana Lewis, founder of the Open Artificial Pancreas System project, told the The Guardian in July.

“Commercial devices similar to ours are now being trialled and gradually coming on to the market: we’re happy to be helping companies to speed up development. The most important thing is that people don’t have to wait,” she said.

Governments and regulators “seem to be pretty terrified about these developments and technologies”, Mesko said.

“When patients find out that there’s a solution technologically for their health problem, they will not wait for regulators to come up with a solution. They will make those solutions themselves,” he said.

“It’s possible for a government to come up with a digital health policy — not just a healthcare policy or a health IT policy, those are different things — a digital health policy that focuses on the cultural aspects of the changes technologies initiate.”

It’s the Terminator scenario forever

This is not to say that the technology isn’t important. AI-powered chatbots can take care of routing patient interactions, for example, leaving the clinicians more time for managing and patient’s health.

According to Murray Brozinsky, chief strategy officer of Conversa Health, the company’s chatbots have saved Northwell Health some $3,400 per patient when they’ve been used to help manage patients after a hip or knee replacement surgery.

Rather than having a clinician call a patient every week to see how they’re doing, a chatbot can check in daily, or whenever the patient has a question. Using what Brozinsky prefers to call “augmented intelligence” any problems can be escalated more quickly.

Mesko, like many other medtech boosters, thinks AI will be the key technological change between now and 2050, but he says it’s important to be clear about what than means.

Artificial narrow intelligence is what we have now, in everything from a car’s braking system or Amazon’s recommendation engine.

Read: IoT and the NHS: Why the Internet of Things will create a healthcare revolution

Artificial general intelligence would mean having one algorithm with the cognitive ability of one human.

“We are far away from that,” Mesko said.

“And then we would have artificial superintelligence, meaning one algorithm would have the cognitive power of humanity, basically meaning that we are doomed. It’s the ‘Terminator’ scenario forever.”

“So I think we have to draw a line under which point it would be great to develop AI. It will be just before reaching artificial general intelligence.”

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Managing Vulnerabilities in a Cloud Native World



This free 1-hour webinar from GigaOm Research brings together experts in Cloud Native Vulnerability Management, featuring analyst Iben Rodriguez and special guest from Palo Alto Networks, John Morello. The discussion will focus on optimizing cloud security posture and integration with enterprise tool sets.

We will review platforms delivering Security Posture Management and Workload Protection for Microservice based and Hybrid Cloud Workloads.

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Register now to join GigaOm and Palo Alto Networks for this free expert webinar.

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Security Tools Help Bring Dev and Security Teams Together



Software development teams are increasingly focused on identifying and mitigating any issues as quickly and completely as possible. This relates not only to software quality but also software security. Different organizations are at different levels when it comes to having their development teams and security teams working in concert, but the simple fact remains that there are far more developers out there than security engineers.

Those factors are leading organizations to consider security tooling and automation to proactively discover and resolve any software security issues throughout the development process. In the recent report, “GigaOm Radar for Developer Security Tools,” Shea Stewart examines a roundup of security tools aimed at software development teams.

Stewart identified three critical criteria to bear in mind when evaluating developer security tools. These include:

  • Vendors providing tools to improve application security can and should also enhance an organization’s overall security posture.
  • The prevailing “shift-left” mindset doesn’t necessarily mean the responsibility for reducing risk should shift to development, but instead focusing on security earlier in the process and continuing to do so throughout the development process will reduce risk and the need for extensive rework.
  • Security throughout the entire software development lifecycle (SDLC) is critical for any organization focused on reducing risk.

Figure 1. How Cybersecurity Applies Across Each Stage of the Software Development Lifecycle *Note: This report focuses only on the Developer Security Tooling area

Individual vendors have made varying levels of progress and innovation toward enhancing developer security. Following several acquisitions, Red Hat, Palo Alto Networks, and Rapid7 have all added tooling for developer security to their platforms. Stewart sees a couple of the smaller vendors like JFrog and Sonatype as continuing to innovate to remain ahead of the market.

Vendors delving into this category and moving deeper into “DevSecOps” all seem to be taking different approaches to their enhanced security tooling. While they are involving security in every aspect of the development process, some tend to be moving more quickly to match the pace of the SDLC. Others are trying to shore up existing platforms by adding functionality through acquisition. Both infrastructure and software developers are now sharing toolsets and processes, so these development security tools must account for the requirements of both groups.

While none of the 12 vendors evaluated in this report can provide comprehensive security throughout the entire SDLC, they all have their particular strengths and areas of focus. It is therefore incumbent upon the organization to fully and accurately assess its SDLC, involve the development and security teams, and match the unique requirements with the functionality provided by these tools. Even if it involves using more than one at different points throughout the process, focus on striking a balance between stringent security and simplifying the development process.

Read more: Key Criteria for Evaluating Developer Security Tools, and the Gigaom Radar for Developer Security Tool Companies.

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Key Criteria for Evaluating User and Entity Behavior Analytics (UEBA)



Cybersecurity is a multidisciplinary practice that not only grows in complexity annually but evolves nearly as quickly. A survey of the security landscape today would reveal concerns ranging from the classic compromised servers to the relatively new DevSecOps practices aimed at securing the rapid deployment of new code and infrastructure. However, some things remain constant no matter how much change is introduced. While technology evolves and complexity varies, there is almost always a human component in
risks presented to an organization.

User Behavior Analysis (UBA) was designed to analyze the actions of users in an organization and attempt to identify normal and abnormal behaviors. From this analysis, malicious or risky behaviors can be detected. UBA solutions identify events that are not detectable using other methods because, unlike classic security tools (an IDS or SIEM for example), UBA does not simply pattern match or apply rule sets to data to identify security events. Instead, it looks for any and all deviations from baseline user activity.

As technology advanced and evolved, and the scope of what is connected to the network grew, the need to analyze entities other than users emerged. In response, entity analysis has been added to UBA to create UEBA or User and Entity Behavior Analysis. The strategy remains the same, but the scope of analysis has expanded to include entities involving things like daemons, processes, infrastructure, and so on.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

The post Key Criteria for Evaluating User and Entity Behavior Analytics (UEBA) appeared first on Gigaom.

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