Research co-design in health: a rapid overview of reviews

Curated on Posted on by Stefaan Verhulst

Paper by Peter Slattery, Alexander K. Saeri & Peter Bragge: “Billions of dollars are lost annually in health research that fails to create meaningful benefits for patients. Engaging in research co-design – the meaningful involvement of end-users in research – may help address this research waste. This rapid overview of reviews addressed three related questions, namely (1) what approaches to research co-design exist in health settings? (2) What activities do these research co-design approaches involve? (3) What do we know about the effectiveness of existing research co-design approaches? The review focused on the study planning phase of research, defined as the point up to which the research question and study design are finalised….

A total of 26 records (reporting on 23 reviews) met the inclusion criteria. Reviews varied widely in their application of ‘research co-design’ and their application contexts, scope and theoretical foci. The research co-design approaches identified involved interactions with end-users outside of study planning, such as recruitment and dissemination. Activities involved in research co-design included focus groups, interviews and surveys. The effectiveness of research co-design has rarely been evaluated empirically or experimentally; however, qualitative exploration has described the positive and negative outcomes associated with co-design. The research provided many recommendations for conducting research co-design, including training participating end-users in research skills, having regular communication between researchers and end-users, setting clear end-user expectations, and assigning set roles to all parties involved in co-design…

Research co-design appears to be widely used but seldom described or evaluated in detail. Though it has rarely been tested empirically or experimentally, existing research suggests that it can benefit researchers, practitioners, research processes and research outcomes. Realising the potential of research co-design may require the development of clearer and more consistent terminology, better reporting of the activities involved and better evaluation….(More)”.

Change of heart: how algorithms could revolutionise organ donations

Curated on Posted on by Stefaan Verhulst

Tej Kohli at TheNewEconomy: “Artificial intelligence (AI) and biotechnology are both on an exponential growth trajectory, with the potential to improve how we experience our lives and even to extend life itself. But few have considered how these two frontier technologies could be brought together symbiotically to tackle global health and environmental challenges…

For example, combination technologies could tackle a global health issue such as organ donation. According to the World Health Organisation, an average of around 100,800 solid organ transplants were performed each year as of 2008. Yet, in the US, there are nearly 113,000 people waiting for a life-saving organ transplant, while thousands of good organs are discarded each year. For years, those in need of a kidney transplant had limited options: they either had to find a willing and biologically viable living donor, or wait for a viable deceased donor to show up in their local hospital.

But with enough patients and willing donors, big data and AI make it possible to facilitate far more matches than this one-to-one system allows, through a system of paired kidney donation. Patients can now procure a donor who is not a biological fit and still receive a kidney, because AI can match donors to recipients across a massive array of patient-donor relationships. In fact, a single person who steps forward to donate a kidney – to a loved one or even to a stranger – can set off a domino effect that saves dozens of lives by resolving the missing link in a long chain of pairings….

The moral and ethical implications of today’s frontier technologies are far-reaching. Fundamental questions have not been adequately addressed. How will algorithms weigh the needs of poor and wealthy patients? Should a donor organ be sent to a distant patient – potentially one in a different country – with a low rejection risk or to a nearby patient whose rejection risk is only slightly higher?

These are important questions, but I believe we should get combination technologies up and working, and then decide on the appropriate controls. The matching power of AI means that eight lives could be saved by just one deceased organ donor; innovations in biotechnology could ensure that organs are never wasted. The faster these technologies advance, the more lives we can save…(More)”.

How does participating in a deliberative citizens panel on healthcare priority setting influence the views of participants?

Curated on Posted on by Stefaan Verhulst

Paper by Vivian Reckers-Droog et al: “A deliberative citizens panel was held to obtain insight into criteria considered relevant for healthcare priority setting in the Netherlands. Our aim was to examine whether and how panel participation influenced participants’ views on this topic. Participants (n = 24) deliberated on eight reimbursement cases in September and October, 2017. Using Q methodology, we identified three distinct viewpoints before (T0) and after (T1) panel participation. At T0, viewpoint 1 emphasised that access to healthcare is a right and that prioritisation should be based solely on patients’ needs. Viewpoint 2 acknowledged scarcity of resources and emphasised the importance of treatment-related health gains. Viewpoint 3 focused on helping those in need, favouring younger patients, patients with a family, and treating diseases that heavily burden the families of patients. At T1, viewpoint 1 had become less opposed to prioritisation and more considerate of costs. Viewpoint 2 supported out-of-pocket payments more strongly. A new viewpoint 3 emerged that emphasised the importance of cost-effectiveness and that prioritisation should consider patient characteristics, such as their age. Participants’ views partly remained stable, specifically regarding equal access and prioritisation based on need and health gains. Notable changes concerned increased support for prioritisation, consideration of costs, and cost-effectiveness. Further research into the effects of deliberative methods is required to better understand how they may contribute to the legitimacy of and public support for allocation decisions in healthcare….(More)”.

An AI Epidemiologist Sent the First Warnings of the Wuhan Virus

Curated on Posted on by Stefaan Verhulst

Eric Niiler at Wired: “On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors’ exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31.

BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan.

Speed matters during an outbreak, and tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters. But public health officials at WHO and the CDC have to rely on these very same health officials for their own disease monitoring. So maybe an AI can get there faster. “We know that governments may not be relied upon to provide information in a timely fashion,” says Kamran Khan, BlueDot’s founder and CEO. “We can pick up news of possible outbreaks, little murmurs or forums or blogs of indications of some kind of unusual events going on.”…

The firm isn’t the first to look for an end-run around public health officials, but they are hoping to do better than Google Flu Trends, which was euthanized after underestimating the severity of the 2013 flu season by 140 percent. BlueDot successfully predicted the location of the Zika outbreak in South Florida in a publication in the British medical journal The Lancet….(More)”.

Barriers to Working With National Health Service England’s Open Data

Curated on Posted on by Stefaan Verhulst

Paper by Ben Goldacre and Seb Bacon: “Open data is information made freely available to third parties in structured formats without restrictive licensing conditions, permitting commercial and noncommercial organizations to innovate. In the context of National Health Service (NHS) data, this is intended to improve patient outcomes and efficiency. EBM DataLab is a research group with a focus on online tools which turn our research findings into actionable monthly outputs. We regularly import and process more than 15 different NHS open datasets to deliver OpenPrescribing.net, one of the most high-impact use cases for NHS England’s open data, with over 15,000 unique users each month. In this paper, we have described the many breaches of best practices around NHS open data that we have encountered. Examples include datasets that repeatedly change location without warning or forwarding; datasets that are needlessly behind a “CAPTCHA” and so cannot be automatically downloaded; longitudinal datasets that change their structure without warning or documentation; near-duplicate datasets with unexplained differences; datasets that are impossible to locate, and thus may or may not exist; poor or absent documentation; and withholding of data for dubious reasons. We propose new open ways of working that will support better analytics for all users of the NHS. These include better curation, better documentation, and systems for better dialogue with technical teams….(More)”.

Hospitals Give Tech Giants Access to Detailed Medical Records

Curated on Posted on by Stefaan Verhulst

Melanie Evans at the Wall Street Journal: “Hospitals have granted Microsoft Corp., International Business Machines and Amazon.com Inc. the ability to access identifiable patient information under deals to crunch millions of health records, the latest examples of hospitals’ growing influence in the data economy.

The breadth of access wasn’t always spelled out by hospitals and tech giants when the deals were struck.

The scope of data sharing in these and other recently reported agreements reveals a powerful new role that hospitals play—as brokers to technology companies racing into the $3 trillion health-care sector. Rapid digitization of health records and privacy laws enabling companies to swap patient data have positioned hospitals as a primary arbiter of how such sensitive data is shared. 

“Hospitals are massive containers of patient data,” said Lisa Bari, a consultant and former lead for health information technology for the Centers for Medicare and Medicaid Services Innovation Center. 

Hospitals can share patient data as long as they follow federal privacy laws, which contain limited consumer protections, she said. “The data belongs to whoever has it.”…

Digitizing patients’ medical histories, laboratory results and diagnoses has created a booming market in which tech giants are looking to store and crunch data, with potential for groundbreaking discoveries and lucrative products.

There is no indication of wrongdoing in the deals. Officials at the companies and hospitals say they have safeguards to protect patients. Hospitals control data, with privacy training and close tracking of tech employees with access, they said. Health data can’t be combined independently with other data by tech companies….(More)”.

Social media firms 'should hand over data amid suicide risk'

Curated on Posted on by Stefaan Verhulst

Denis Campbell at the Guardian: “Social media firms such as Facebook and Instagram should be forced to hand over data about who their users are and why they use the sites to reduce suicide among children and young people, psychiatrists have said.

The call from the Royal College of Psychiatrists comes as ministers finalise plans to crack down on issues caused by people viewing unsavoury material and messages online.

The college, which represents the UK’s 18,000 psychiatrists, wants the government to make social media platforms hand over the data to academics so that they can study what sort of content users are viewing.

“We will never understand the risks and benefits of social media use unless the likes of Twitter, Facebook and Instagram share their data with researchers,” said Dr Bernadka Dubicka, chair of the college’s child and adolescent mental health faculty. “Their research will help shine a light on how young people are interacting with social media, not just how much time they spend online.”

Data passed to academics would show the type of material viewed and how long users were spending on such platforms but would be anonymous, the college said.

The government plans to set up a new online safety regulator and the college says it should be given the power to compel firms to hand over data. It is also calling for the forthcoming 2% “turnover tax” on social media companies’ income to be extended so that it includes their turnover internationally, not from just the UK.

“Self-regulation is not working. It is time for government to step up and take decisive action to hold social media companies to account for escalating harmful content to vulnerable children and young people,” said Dubicka.

The college’s demands come amid growing concern that young people are being harmed by material that, for example, encourages self-harm, suicide and eating disorders. They are included in a new position statement on technology use and the mental health of children and young people.

NHS England challenged firms to hand over the sort of information that the college is suggesting. Claire Murdoch, its national director for mental health, said that action was needed “to rein in potentially misleading or harmful online content and behaviours”.

She said: “If these tech giants really want to be a force for good, put a premium on users’ wellbeing and take their responsibilities seriously, then they should do all they can to help researchers better understand how they operate and the risks posed. Until then, they cannot confidently say whether the good outweighs the bad.”

The demands have also been backed by Ian Russell, who has become a campaigner against social media harm since his 14-year-old daughter Molly killed herself in November 2017….(More)”.

The future is intelligent: Harnessing the potential of artificial intelligence in Africa

Curated on Posted on by Stefaan Verhulst

Youssef Travaly and Kevin Muvunyi at Brookings: “…AI in particular presents countless avenues for both the public and private sectors to optimize solutions to the most crucial problems facing the continent today, especially for struggling industries. For example, in health care, AI solutions can help scarce personnel and facilities do more with less by speeding initial processing, triage, diagnosis, and post-care follow up. Furthermore, AI-based pharmacogenomics applications, which focus on the likely response of an individual to therapeutic drugs based on certain genetic markers, can be used to tailor treatments. Considering the genetic diversity found on the African continent, it is highly likely that the application of these technologies in Africa will result in considerable advancement in medical treatment on a global level.

In agriculture, Abdoulaye Baniré Diallo, co-founder and chief scientific officer of the AI startup My Intelligent Machines, is working with advanced algorithms and machine learning methods to leverage genomic precision in livestock production models. With genomic precision, it is possible to build intelligent breeding programs that minimize the ecological footprint, address changing consumer demands, and contribute to the well-being of people and animals alike through the selection of good genetic characteristics at an early stage of the livestock production process. These are just a few examples that illustrate the transformative potential of AI technology in Africa.

However, a number of structural challenges undermine rapid adoption and implementation of AI on the continent. Inadequate basic and digital infrastructure seriously erodes efforts to activate AI-powered solutions as it reduces crucial connectivity. (For more on strategies to improve Africa’s digital infrastructure, see the viewpoint on page 67 of the full report). A lack of flexible and dynamic regulatory systems also frustrates the growth of a digital ecosystem that favors AI technology, especially as tech leaders want to scale across borders. Furthermore, lack of relevant technical skills, particularly for young people, is a growing threat. This skills gap means that those who would have otherwise been at the forefront of building AI are left out, preventing the continent from harnessing the full potential of transformative technologies and industries.

Similarly, the lack of adequate investments in research and development is an important obstacle. Africa must develop innovative financial instruments and public-private partnerships to fund human capital development, including a focus on industrial research and innovation hubs that bridge the gap between higher education institutions and the private sector to ensure the transition of AI products from lab to market….(More)”.

Paging Dr. Google: How the Tech Giant Is Laying Claim to Health Data

Curated on Posted on by Stefaan Verhulst

Wall Street Journal: “Roughly a year ago, Google offered health-data company Cerner Corp.an unusually rich proposal.

Cerner was interviewing Silicon Valley giants to pick a storage provider for 250 million health records, one of the largest collections of U.S. patient data. Google dispatched former chief executive Eric Schmidt to personally pitch Cerner over several phone calls and offered around $250 million in discounts and incentives, people familiar with the matter say. 

Google had a bigger goal in pushing for the deal than dollars and cents: a way to expand its effort to collect, analyze and aggregate health data on millions of Americans. Google representatives were vague in answering questions about how Cerner’s data would be used, making the health-care company’s executives wary, the people say. Eventually, Cerner struck a storage deal with Amazon.com Inc. instead.

The failed Cerner deal reveals an emerging challenge to Google’s move into health care: gaining the trust of health care partners and the public. So far, that has hardly slowed the search giant.

Google has struck partnerships with some of the country’s largest hospital systems and most-renowned health-care providers, many of them vast in scope and few of their details previously reported. In just a few years, the company has achieved the ability to view or analyze tens of millions of patient health records in at least three-quarters of U.S. states, according to a Wall Street Journal analysis of contractual agreements. 

In certain instances, the deals allow Google to access personally identifiable health information without the knowledge of patients or doctors. The company can review complete health records, including names, dates of birth, medications and other ailments, according to people familiar with the deals.

The prospect of tech giants’ amassing huge troves of health records has raised concerns among lawmakers, patients and doctors, who fear such intimate data could be used without individuals’ knowledge or permission, or in ways they might not anticipate. 

Google is developing a search tool, similar to its flagship search engine, in which patient information is stored, collated and analyzed by the company’s engineers, on its own servers. The portal is designed for use by doctors and nurses, and eventually perhaps patients themselves, though some Google staffers would have access sooner. 

Google executives and some health systems say that detailed data sharing has the potential to improve health outcomes. Large troves of data help fuel algorithms Google is creating to detect lung cancer, eye disease and kidney injuries. Hospital executives have long sought better electronic record systems to reduce error rates and cut down on paperwork….

Legally, the information gathered by Google can be used for purposes beyond diagnosing illnesses, under laws enacted during the dial-up era. U.S. federal privacy laws make it possible for health-care providers, with little or no input from patients, to share data with certain outside companies. That applies to partners, like Google, with significant presences outside health care. The company says its intentions in health are unconnected with its advertising business, which depends largely on data it has collected on users of its many services, including email and maps.

Medical information is perhaps the last bounty of personal data yet to be scooped up by technology companies. The health data-gathering efforts of other tech giants such as Amazon and International Business Machines Corp. face skepticism from physician and patient advocates. But Google’s push in particular has set off alarm bells in the industry, including over privacy concerns. U.S. senators, as well as health-industry executives, are questioning Google’s expansion and its potential for commercializing personal data….(More)”.

Towards adaptive governance in big data health research: implementing regulatory principles

Curated on Posted on by Stefaan Verhulst

Chapter by Alessandro Blasimme and Effy Vayena: “While data-enabled health care systems are in their infancy, biomedical research is rapidly adopting the big data paradigm. Digital epidemiology for example, already employs data generated outside the public health care system – that is, data generated without the intent of using them for epidemiological research – to understand and prevent patterns of diseases in populations (Salathé 2018)(Salathé 2018). Precision medicine – pooling together genomic, environmental and lifestyle data – also represents a prominent example of how data integration can drive both fundamental and translational research in important medical domains such as oncology (D. C. Collins et al. 2017). All of this requires the collection, storage, analysis and distribution of massive amounts of personal information as well as the use of state-of-the art data analytics tools to uncover healthand disease related patterns.


The realization of the potential of big data in health evokes a necessary commitment to a sense of “continuity” articulated in three distinct ways: a) from data generation to use (as in the data enabled learning health care ); b) from research to clinical practice e.g. discovery of new mutations in the context of diagnostics; c) from strictly speaking health data (Vayena and Gasser 2016) e.g. clinical records, to less so e.g. tweets used in digital epidemiology. These continuities face the challenge of regulatory and governance approaches that were designed for clear data taxonomies, for a less blurred boundary between research and clinical practice, and for rules that focused mostly on data generation and less on their eventual and multiple uses.

The result is significant uncertainty about how responsible use of such large amounts of sensitive personal data could be fostered. In this chapter we focus on the uncertainties surrounding the use of biomedical big data in the context of health research. Are new criteria needed to review biomedical big data research projects? Do current mechanisms, such as informed consent, offer sufficient protection to research participants’ autonomy and privacy in this new context? Do existing oversight mechanisms ensure transparency and accountability in data access and sharing? What monitoring tools are available to assess how personal data are used over time? Is the equitable distribution of benefits accruing from such data uses considered, or can it be ensured? How is the public being involved – if at all – with decisions about creating and using large data
repositories for research purposes? What is the role that IT (information technology) players, and especially big ones, acquire in research? And what regulatory instruments do we have to ensure that such players do not undermine the independence of research?…(More)”.