Category Archives: Emerging technologies

Trusting Digital Health Technologies: Why Global Standards Are A Must

An editorial by Maria Palombini, director, healthcare and life sciences global practice lead, IEEE Standards Association, highlights that the clinical trials ‘industry’ needs to adopt the currently available and evolving digital tools that are integral to modernize and streamline the process of validating and discovering new treatment options and bring new drugs to market.

Clinical trials are not modernizing fast enough due, in part, to lagging global standards.

The need to digitally transformation the approach to patient recruitment and engagement, study design protocols, and overall trial management is mandatory. On a regular basis, shocking numbers are publicized as to the rising cost of evaluating and bringing a new drug to market, the declining rates of enrollment and patient retention, and the extended length of overall trials. “While these numbers often stir up emotions and debate, they are often undervalued as a symptom of the main problem: Clinical trials are not modernizing fast enough due, in part, to lagging global standards.”

Decentralized clinical trials (DCT) compels clinical operations to become more digitalized. 

Digitalization encompasses much more than electronic data capture and electronic data management systems. Digitalizing the entire process enables the use of the many exciting technologies in the digital health toolkit, including artificial intelligence (AI), machine learning (ML), blockchain/distributed ledger technologies (DLT), digital therapeutics, wearables, the Internet of Things (IoTs), biosensors, and many more. These following digital technologies present the opportunity to optimize the clinical trial management process from study design through review:

  • Wearables and sensors minimize, and potentially eliminate, the need for some patients to visit sites. Their continuous monitoring capability provides troves of data that can be further mined and used to improve clinical study design, protocols, recruitment, and more.
  • Digital therapeutics in the form of a smartphone app can be used to encourage patient adherence (i.e., medication reminders) or make participant feedback collections for eCOAs (electronic clinical outcome assessments) more efficient and effective.
  • Software as a Medical Device (SaMD) includes fixed or adaptive algorithms used for multiple purposes, including prescreening, screening, adjunctive clinical diagnosis, clinical diagnosis, medical monitoring for adverse events, and more.
  • AI/ML Artificial Intelligence and Machine Learning can be used throughout most steps of DCTs or modernized trials with the ability to predict patient retention rates, better analyze and implement participant feedback to reflect the patient’s perspective, better identify and target patient populations for recruitment, filter unstructured data from multiple patient record sources to gather insights, and more.

Can these technologies be trusted?

Some of these technologies are relatively new to a legacy process, which begs the inevitable question: Can they be trusted? How are they validated? Will they work the way they are intended? There are many technical and ethical considerations that clinical trial management teams need to understand and negotiate when applying these technologies to their processes while asking patients to use and trust them. This conundrum of trust in digital technologies can be the very obstacle to deciding whether a component or the entire trial will be decentralized.

Patients Are Ready, But Are Clinicians?

While trust can be the cornerstone of clinicians’ concerns, patients are seemingly ready to embrace more digital components.  A survey by Deloitte, reveal that 92% of clinical trial patients believe that improving experiences (such as through innovative technologies) should be a top priority for the healthcare industry. Patients are embracing digitalization quickly, and a great example is the growing wearables market: 

  • The number of connected wearable devices has increased dramatically since 2019.  The number of devices is forecast to reach more than 1 billion in 2022. (
  • It is estimated that there are over 52,400 healthcare and medical apps currently available on the Apple App Store.
  • According to Statistica, we are now nearly a decade into the Zettabyte Era, with the amount of health care data and information created, captured, copied, and consumed worldwide in 2020 was 64.2 zettabytes and projected to be 120 zettabytes in 2023.

At this rate of use, it can be argued that patients are ready for it. The growing use of digital technologies such as wearables, digital therapeutics, and other biosensors by patients provide benefits that were never available before to patients to participate in their wellness/health process.

However, scientists and clinicians are not engineers or technical gurus.

Therefore, how do they effectively evaluate what and which technologies should be used and trusted? The answer is not so simple. The process will take some time to learn from trial and error. However, it also will require communities of multidisciplinary experts including clinical professionals and patients to get involved with development of global industry technical standards to address these uncertainties in the application and/or technology itself.

Looking at the world of health sensors and wearable devices, there has been more development in global technical standards to mitigate concerns of data transfer and portability and open sharing of mobile health. However, more development is still needed in the space of cybersecurity, patient privacy, data governance, validating algorithms, data integration, and more.

In addition, technical standards very important. “On any given day, internet users trust that a mobile device will connect to Wi-Fi. The global technical standard helps enable seamless connectivity anywhere in the world. Wouldn’t it be just as great to have the same approach when digital technology is integrated into the clinical research process?”


[Reimagining clinical trials in the age of the digital patient (pdf)]

NICE’s Early Value Assessment for Medtech

The explosion in digital health products has left National Health Service commissioners in the UK wondering how they can possibly sift out what works and what provides maximum benefit for the service and for patients.

The Early Value Assessment for Medtech will offer a rapid assessment of digital products, devices and diagnostics for clinical effectiveness and value for money. The goal of this new approach is that the service and patients will be able to benefit sooner.

Early Value Assessment is being designed to draw in the most promising and impactful medical technologies where the evidence base is still emerging, starting with digital products, in areas where there is greatest need.  Whether its empowering patients to better manage their own health and seek clinical advice, reducing admissions and waiting lists or supporting clinicians and other front-line staff to provide better quality care this new program will help to alleviate system pressures as the NHS recovers from the COVID pandemic.

In this accelerated approach, the first two pilot digital health topics will begin their early value assessments this month (June) with a view to publishing findings in October. This is much faster than a full NICE Medtech evaluation meaning benefits will be realized sooner, while companies generate more evidence required for a full NICE evaluation at a later stage.  

The first two pilots are digital apps for depression and anxiety in children and others will quickly follow in adult mental health, early cancer diagnosis, cardiovascular disease and other areas that support elective recovery following the pandemic.

In this ‘fast-track’ approach, NICE is working closely with NHS England and all its system partners to help develop commercial and data collection arrangements to support the technologies that go through early value assessment in adoption and scaling and to make this new program of work deliver on the potential of digital health for patients.

Source: NHS Blog

Don’t Blame Social Media for the Decrease In Face-to-Face Interaction.

An new article in Current Opinion in Psychology reviews the best available evidence to debunk the “social displacement hypothesis” that holds that use of mobile and social media is the cause of decreased face-to-face (FtF) interaction. Lead author Jeffrey Hall, PhD has uncovered a worrisome trend: In the United States, Great Britain and Australia, there has been a steady, uniform decline in FtF time that began well before the rise of social media. This new analysis shows the decline continued through the stay-at-home orders and social distancing of the COVID-19 pandemic.

Dr. Hall, a professor of communication studies and director of the Relationships and Technology Lab at the University of Kansas, and his co-author, Dong Liu of Renmin University in China, take on that notion in a new paper titled “Social media use, social displacement, and well-being” 

The ‘social displacement hypothesis’ is probably the most well-known, long-lasting explanation that blames the new technologies (especially texting and social media) for usurping everyone’s time away from person-to-person contact. Hall states that “the best available evidence suggests that it’s just not so.”

Hall took data on FtF time from the U.S. Department of Labor’s annual American Time Use Survey and from similar governmental studies in Australia and Great Britain between 1995 and 2021 and plotted them on a single chart. Interestingly, all three lines decline over time at a similar rate.

According to Hall,  “it’s the case that social media rates of consumption have grown across demographic groups and across the world. Yes, it’s the case that face-to-face time has declined. However, it’s not the case it takes from face-to-face time.”

If the evidence doesn’t support the social displacement theory, then where is the time for increased social media use coming from?

The paper highlights that there has been a transformation of where people are putting their attention. While it is true that TikTok and YouTube are increasingly popular outlets for watching streaming content, Hall suggests social media time is most likely borrowing from time spent watching TV, which, for decades, has been a major place where Americans spend their time. “Social-media time is also borrowing from time at work or doing household chores” Hall said.

Similar Data In 3 Countries

The paper reports a new analysis showing that FtF time has declined across three countries in a similar fashion. “The fact that the UK data track U.S. data so tightly despite using slightly different methods in different years, is surprising,” Hall said. This international trend of reduced time in face-to-face communication may reflect growing rates of loneliness.

Hall’s analysis shows that these trends of declining face-to-face communication existed well before the pandemic, and the pandemic may have exacerbated some of them. When people had some time back because they weren’t commuting to work or able to go out as much, they didn’t turn to face-to-face communication. “What’s discouraging about that,” Hall notes, “is even when people have time, they don’t seem to use it in a way that promotes their social health.” Noting the widespread evidence that FtF socialization is beneficial to well-being, “we’re not on the right path to being able to reclaim that face-to-face time,” said Hall, “at least in these three nations.”

Why is FtF time declining?

“The best available evidence suggests face-to-face is in competition with hours spent at work and commuting,” Hall says. In other words, people who work longer spend more of their leisure time alone. During the pandemic, when people got that time back from commuting, “they still spent it working virtually,” Hall said. “They didn’t spend it socializing with each other.”

And, Hall says, friendship and social media are not enemies: “Social media can be used in many friendship-promoting ways, especially now that many people use messaging programs supported by social media platforms.” As the paper claims, “social people are active both online and offline.”   

“It seems we live in a society that privileges working and media consumption over everything else,” Hall said. “The decline in face-to-face time is a matter of priority and a matter of availability. And we are neither prioritizing face to face time, nor are we available to do so.”

Source: Hall JA, Lui D. Social media use, social displacement, and well-being. Current Opinion in Psychology. Volume 46, August 2022, 101339

Americans Cautious About Advances in Artificial Intelligence and Human Enhancement Technologies

A new Pew Research Center survey finds that Americans believe that AI and human enhancements via technology have the potential to improve daily life and human abilities. Yet public views are also cautiously defined by 1) the context of how these technologies would be used, 2) what constraints would be in place and 3) who would stand to benefit – or lose – if these advances become widespread.

Public caution is mostly centered around concerns about privacy, autonomy, unintended consequences and the amount of change these developments might mean for humans and society.

This survey looks at a broad arc of scientific and technological developments – some in use now, some still emerging. Three highlight the burgeoning array of AI applications: the use of facial recognition technology by police, the use of algorithms by social media companies to find false information on their sites and the development of driverless passenger vehicles.

Another three are often described as types of human enhancements, revolve around developments tied to the convergence of AI, biotechnology, nanotechnology and other fields. They raise the possibility of dramatic changes to human abilities in the future: computer chip implants in the brain to advance people’s cognitive skills, gene editing to greatly reduce a baby’s risk of developing serious diseases or health conditions, and robotic exoskeletons with a built-in AI system to greatly increase strength for lifting in manual labor jobs.

Americans are far more positive than negative about the widespread use of facial recognition technology by police to monitor crowds and look for people who may have committed a crime: 46% of U.S. adults think this would be a good idea for society, while 27% think this would be a bad idea and another 27% are unsure.

By narrower margins, more describe the use of computer algorithms by social media companies to find false information on their sites as a good rather than bad idea for society (38% vs. 31%), and the pattern is similar for the use of robotic exoskeletons with a built-in AI system to increase strength for manual labor jobs (33% vs. 24%).

The survey of 10,260 U.S. adults was conducted between Nov. 1 and 7, 2021. There are five key themes that run through people’s answers on these questions.

  1. Americans’ judgments about the potential impact of this set of applications are varied and, for portions of the public, marked by uncertainty. [Link to graphic]
  2. Less than half of the public believes these technologies would improve things over the way they are now. [Link to graphic]
  3. Americans see a need for higher standards to assess the safety of technologies on the horizon than are currently used. [Link to graphic]
  4. There are sharp partisan divisions when people think about possible government regulation of these new and developing technologies.
  5. There are mitigating steps people say would make these AI and human enhancement developments more acceptable. [Link to graphic]

Source: Pew Research

AI and Human Enhancement: Americans’ Openness Is Tempered by a Range of Concerns