Long Live the Human Network Effect


Julia Hobsbawm at Strategy + Business: “Picture the scene. The eyes of the world are on the Tham Luang cave system in Thailand, near the border with Myanmar. Trapped on a rock ledge deep inside is the Wild Boars soccer team of 12 boys and their coach, who had ventured into the caves about two weeks earlier. It is monsoon season. Water is rising and oxygen levels are falling. Not all of the boys can even swim. Time is running out.

Elon Musk proposes building a “kid-sized submarine” to assist the rescue effort. Musk’s solution is politely declined by Thai authorities as “not practical.” In fact, by the time Musk’s sub arrives, most of the boys are already out, alive. One of the most audacious, moving, complex, and successful rescue operations in history relied not on a single technology or hero but on the collaboration of many people, working together in a spontaneous network.

This web of connections came together organically and quickly, unassisted by algorithms, in a unique collaboration led by humans. It was a stunning example of what physicist Albert-László Barabási calls “scale-free networks”: networks that reproduce exponentially by their very nature. The exact same network effects that can be lethal in spreading a virus can be productive — beautiful, even — in creating a web of diverse human skills quickly. Networks, as Barabási puts it, “are everywhere. You just have to look for them.”…

Networks that come together like this and use technology, community, and communications in a timely manner are an example of what the U.N. calls its “leave no one behind” strategy for achieving sustainable development goals. I consider it an example of social health in action: They are the kinds of collaborations that help us live full and productive lives. And in business, there is an exciting opportunity to harness social health and the power of networks to help solve problems.

This kind of social health network, perhaps unsurprisingly, is very visible in innovations in the healthcare sector. A digital health community called The Mighty, for example, is a forum to find information about rare illnesses and connect people facing similar challenges, so that they might learn from the experiences of others. It now has 90 million engagements on its website per month and a new member joins every 20 seconds….(More)”.

Making NHS data work for everyone


Reform: This report looks at the access and use of NHS data by private sector companies for research or product and service development purposes….

The private sector is an important partner to the NHS and plays a crucial role in the development of healthcare technologies that use data collected by hospitals or GP practices. It provides the skills and know-how to develop data-driven tools which can be used to improve patient care. However, this is not a one-sided exchange as the NHS makes the data available to build these tools and offers medical expertise to make sense of the data. This is known as the “value exchange”. Our research uncovered that there is a lack of clarity over what a fair value exchange looks like. This lack of clarity in conjunction with the lack of national guidance on the types of partnerships that could be developed has led to a patchwork on the ground….

Knowing what the “value exchange” is between patients, the NHS and industry allows for a more informed conversation about what constitutes a fair partnership when there is access to data to create a product or service

WHAT NEEDS TO CHANGE?

  1. Engage with the public
  2. A national strategy
  3. Access to good quality data
  4. Commercial and legal skills…(More)

Using insights from behavioral economics to nudge individuals towards healthier choices when eating out


Paper by Stéphane Bergeron, Maurice Doyon, Laure Saulais and JoAnne Labrecque: “Using a controlled experiment in a restaurant with naturally occurring clients, this study investigates how nudging can be used to design menus that guide consumers to make healthier choices. It examines the use of default options, focusing specifically on two types of defaults that can be found when ordering food in a restaurant: automatic and standard defaults. Both types of defaults significantly affected choices, but did not adversely impact the satisfaction of individual choices. The results suggest that menu design could effectively use non-informational strategies such as nudging to promote healthier individual choices without restricting the offer or reducing satisfaction….(More)”.

These patients are sharing their data to improve healthcare standards


Article by John McKenna: “We’ve all heard about donating blood, but how about donating data?

Chronic non-communicable diseases (NCDs) like diabetes, heart disease and epilepsy are predicted by the World Health Organization to account for 57% of all disease by 2020.

Heart disease and stroke are the world’s biggest killers.

This has led some experts to call NCDs the “greatest challenge to global health”.

Could data provide the answer?

Today over 600,000 patients from around the world share data on more than 2,800 chronic diseases to improve research and treatment of their conditions.

People who join the PatientsLikeMe online community share information on everything from their medication and treatment plans to their emotional struggles.

Many of the participants say that it is hugely beneficial just to know there is someone else out there going through similar experiences.

But through its use of data, the platform also has the potential for far more wide-ranging benefits to help improve the quality of life for patients with chronic conditions.

Give data, get data

PatientsLikeMe is one of a swathe of emerging data platforms in the healthcare sector helping provide a range of tech solutions to health problems, including speeding up the process of clinical trials using Real Time Data Analysis or using blockchain to enable the secure sharing of patient data.

Its philosophy is “give data, get data”. In practice it means that every patient using the website has access to an array of crowd-sourced information from the wider community, such as common medication side-effects, and patterns in sufferers’ symptoms and behaviour….(More)”.

Giving Voice to Patients: Developing a Discussion Method to Involve Patients in Translational Research


Paper by Marianne Boenink, Lieke van der Scheer, Elisa Garcia and Simone van der Burg in NanoEthics: “Biomedical research policy in recent years has often tried to make such research more ‘translational’, aiming to facilitate the transfer of insights from research and development (R&D) to health care for the benefit of future users. Involving patients in deliberations about and design of biomedical research may increase the quality of R&D and of resulting innovations and thus contribute to translation. However, patient involvement in biomedical research is not an easy feat. This paper discusses the development of a method for involving patients in (translational) biomedical research aiming to address its main challenges.

After reviewing the potential challenges of patient involvement, we formulate three requirements for any method to meaningfully involve patients in (translational) biomedical research. It should enable patients (1) to put forward their experiential knowledge, (2) to develop a rich view of what an envisioned innovation might look like and do, and (3) to connect their experiential knowledge with the envisioned innovation. We then describe how we developed the card-based discussion method ‘Voice of patients’, and discuss to what extent the method, when used in four focus groups, satisfied these requirements. We conclude that the method is quite successful in mobilising patients’ experiential knowledge, in stimulating their imaginaries of the innovation under discussion and to some extent also in connecting these two. More work is needed to translate patients’ considerations into recommendations relevant to researchers’ activities. It also seems wise to broaden the audience for patients’ considerations to other actors working on a specific innovation….(More)”

Blockchain systems are tracking food safety and origins


Nir Kshetri at The Conversation: “When a Chinese consumer buys a package labeled “Australian beef,” there’s only a 50-50 chance the meat inside is, in fact, Australian beef. It could just as easily contain rat, dog, horse or camel meat – or a mixture of them all. It’s gross and dangerous, but also costly.

Fraud in the global food industry is a multi-billion-dollar problem that has lingered for years, duping consumers and even making them ill. Food manufacturers around the world are concerned – as many as 39 percent of them are worried that their products could be easily counterfeited, and 40 percent say food fraud is hard to detect.

In researching blockchain for more than three years, I have become convinced that this technology’s potential to prevent fraud and strengthen security could fight agricultural fraud and improve food safety. Many companies agree, and are already running various tests, including tracking wine from grape to bottle and even following individual coffee beans through international trade.

Tracing food items

An early trial of a blockchain system to track food from farm to consumer was in 2016, when Walmart collected information about pork being raised in China, where consumers are rightly skeptical about sellers’ claims of what their food is and where it’s from. Employees at a pork farm scanned images of farm inspection reports and livestock health certificates, storing them in a secure online database where the records could not be deleted or modified – only added to.

As the animals moved from farm to slaughter to processing, packaging and then to stores, the drivers of the freight trucks played a key role. At each step, they would collect documents detailing the shipment, storage temperature and other inspections and safety reports, and official stamps as authorities reviewed them – just as they did normally. In Walmart’s test, however, the drivers would photograph those documents and upload them to the blockchain-based database. The company controlled the computers running the database, but government agencies’ systems could also be involved, to further ensure data integrity.

As the pork was packaged for sale, a sticker was put on each container, displaying a smartphone-readable code that would link to that meat’s record on the blockchain. Consumers could scan the code right in the store and assure themselves that they were buying exactly what they thought they were. More recent advances in the technology of the stickers themselves have made them more secure and counterfeitresistant.

Walmart did similar tests on mangoes imported to the U.S. from Latin America. The company found that it took only 2.2 seconds for consumers to find out an individual fruit’s weight, variety, growing location, time it was harvested, date it passed through U.S. customs, when and where it was sliced, which cold-storage facility the sliced mango was held in and for how long it waited before being delivered to a store….(More)”.

Startup Offers To Sequence Your Genome Free Of Charge, Then Let You Profit From It


Richard Harris at NPR: “A startup genetics company says it’s now offering to sequence your entire genome at no cost to you. In fact, you would own the data and may even be able to make money off it.

Nebula Genomics, created by the prominent Harvard geneticist George Church and his lab colleagues, seeks to upend the usual way genomic information is owned.

Today, companies like 23andMe make some of their money by scanning your genetic patterns and then selling that information to drug companies for use in research. (You choose whether to opt in.)

Church says his new enterprise leaves ownership and control of the data in an individual’s hands. And the genomic analysis Nebula will perform is much more detailed than what 23andMe and similar companies offer.

Nebula will do a full genome sequence, rather than a snapshot of key gene variants. That wider range of genetic information would makes the data more appealing to biologists and biotech and pharmaceutical companies….

Church’s approach is part of a trend that’s pushing back against the multibillion-dollar industry to buy and sell medical information. Right now, companies reap those profits and control the data.

“Patients should have the right to decide for themselves whether they want to share their medical data, and, if so, with whom,” Adam Tanner, at Harvard’s Institute for Quantitative Social Science, says in an email. “Efforts to empower people to fine-tune the fate of their medical information are a step in the right direction.” Tanner, author of a book on the subject of the trade in medical data, isn’t involved in Nebula.

The current system is “very paternalistic,” Church says. He aims to give people complete control over who gets access to their data, and let individuals decide whether or not to sell the information, and to whom.

“In this case, everything is private information, stored on your computer or a computer you designate,” Church says. It can be encrypted so nobody can read it, even you, if that’s what you want.

Drug companies interested in studying, say, diabetes patients would ask Nebula to identify people in their system who have the disease. Nebula would then identify those individuals by launching an encrypted search of participants.

People who have indicated they’re interested in selling their genetic data to a company would then be given the option of granting access to the information, along with medical data that person has designated.

Other companies are also springing up to help people control — and potentially profit from — their medical data. EncrypGen lets people offer up their genetic data, though customers have to provide their own DNA sequence. Hu-manity.co is also trying to establish a system in which people can sell their medical data to pharmaceutical companies….(More)”.

You can’t characterize human nature if studies overlook 85 percent of people on Earth


Daniel Hruschka at the Conversation: “Over the last century, behavioral researchers have revealed the biases and prejudices that shape how people see the world and the carrots and sticks that influence our daily actions. Their discoveries have filled psychology textbooks and inspired generations of students. They’ve also informed how businesses manage their employees, how educators develop new curricula and how political campaigns persuade and motivate voters.

But a growing body of research has raised concerns that many of these discoveries suffer from severe biases of their own. Specifically, the vast majority of what we know about human psychology and behavior comes from studies conducted with a narrow slice of humanity – college students, middle-class respondents living near universities and highly educated residents of wealthy, industrialized and democratic nations.

Blue countries represent the locations of 93 percent of studies published in Psychological Science in 2017. Dark blue is U.S., blue is Anglophone colonies with a European descent majority, light blue is western Europe. Regions sized by population.

To illustrate the extent of this bias, consider that more than 90 percent of studies recently published in psychological science’s flagship journal come from countries representing less than 15 percent of the world’s population.

If people thought and behaved in basically the same ways worldwide, selective attention to these typical participants would not be a problem. Unfortunately, in those rare cases where researchers have reached out to a broader range of humanity, they frequently find that the “usual suspects” most often included as participants in psychology studies are actually outliers. They stand apart from the vast majority of humanity in things like how they divvy up windfalls with strangers, how they reason about moral dilemmas and how they perceive optical illusions.

Given that these typical participants are often outliers, many scholars now describe them and the findings associated with them using the acronym WEIRD, for Western, educated, industrialized, rich and democratic.

WEIRD isn’t universal

Because so little research has been conducted outside this narrow set of typical participants, anthropologists like me cannot be sure how pervasive or consequential the problem is. A growing body of case studies suggests, though, that assuming such typical participants are the norm worldwide is not only scientifically suspect but can also have practical consequences….(More)”.

Why Doctors Hate Their Computers


Atul Gawande at the New Yorker: “….More than ninety per cent of American hospitals have been computerized during the past decade, and more than half of Americans have their health information in the Epic system. Seventy thousand employees of Partners HealthCare—spread across twelve hospitals and hundreds of clinics in New England—were going to have to adopt the new software. I was in the first wave of implementation, along with eighteen thousand other doctors, nurses, pharmacists, lab techs, administrators, and the like.

The surgeons at the training session ranged in age from thirty to seventy, I estimated—about sixty per cent male, and one hundred per cent irritated at having to be there instead of seeing patients. Our trainer looked younger than any of us, maybe a few years out of college, with an early-Justin Bieber wave cut, a blue button-down shirt, and chinos. Gazing out at his sullen audience, he seemed unperturbed. I learned during the next few sessions that each instructor had developed his or her own way of dealing with the hostile rabble. One was encouraging and parental, another unsmiling and efficient. Justin Bieber took the driver’s-ed approach: You don’t want to be here; I don’t want to be here; let’s just make the best of it.

I did fine with the initial exercises, like looking up patients’ names and emergency contacts. When it came to viewing test results, though, things got complicated. There was a column of thirteen tabs on the left side of my screen, crowded with nearly identical terms: “chart review,” “results review,” “review flowsheet.” We hadn’t even started learning how to enter information, and the fields revealed by each tab came with their own tools and nuances.

But I wasn’t worried. I’d spent my life absorbing changes in computer technology, and I knew that if I pushed through the learning curve I’d eventually be doing some pretty cool things. In 1978, when I was an eighth grader in Ohio, I built my own one-kilobyte computer from a mail-order kit, learned to program in basic, and was soon playing the arcade game Pong on our black-and-white television set. The next year, I got a Commodore 64 from RadioShack and became the first kid in my school to turn in a computer-printed essay (and, shortly thereafter, the first to ask for an extension “because the computer ate my homework”). As my Epic training began, I expected my patience to be rewarded in the same way.

My hospital had, over the years, computerized many records and processes, but the new system would give us one platform for doing almost everything health professionals needed—recording and communicating our medical observations, sending prescriptions to a patient’s pharmacy, ordering tests and scans, viewing results, scheduling surgery, sending insurance bills. With Epic, paper lab-order slips, vital-signs charts, and hospital-ward records would disappear. We’d be greener, faster, better.

But three years later I’ve come to feel that a system that promised to increase my mastery over my work has, instead, increased my work’s mastery over me. I’m not the only one. A 2016 study found that physicians spent about two hours doing computer work for every hour spent face to face with a patient—whatever the brand of medical software. In the examination room, physicians devoted half of their patient time facing the screen to do electronic tasks. And these tasks were spilling over after hours. The University of Wisconsin found that the average workday for its family physicians had grown to eleven and a half hours. The result has been epidemic levels of burnout among clinicians. Forty per cent screen positive for depression, and seven per cent report suicidal thinking—almost double the rate of the general working population.

Something’s gone terribly wrong. Doctors are among the most technology-avid people in society; computerization has simplified tasks in many industries. Yet somehow we’ve reached a point where people in the medical profession actively, viscerally, volubly hate their computers….(More)”.

Better Ways to Communicate Hospital Data to Physicians


Scott FalkJohn Cherf and Julie Schulz at the Harvard Business Review: “We recently conducted an in-depth study at Lumere to gain insight into physicians’ perceptions of clinical variation and the factors influencing their choices of drugs and devices. Based on a survey of 276 physicians, our study results show that it’s necessary to consistently and frequently share cost data and clinical evidence with physicians, regardless of whether they’re affiliated with or directly employed by a hospital….

There are multiple explanations as to why health system administrators have been slow to share data with physicians. The two most common challenges are difficulty obtaining accurate, clinically meaningful data and lack of knowledge among administrators about communicating data.

When it comes to obtaining accurate, meaningful data, the reality is that many health systems do not know where to start. Between disparate data-collection systems, varied physician needs, and an overwhelming array of available clinical evidence, it can be daunting to try to develop a robust, yet streamlined, approach.

As for the second problem, many administrators have simply not been trained to effectively communicate data. Health system leaders tend to be more comfortable talking about costs, but physicians generally focus on clinical outcomes. As a result, physicians frequently have follow-up questions that administrators interpret as pushback. It is important to understand what physicians need.

Determine the appropriate amount and type of data to share. Using evidence and data can foster respectful debate, provide honest education, and ultimately align teams.

Physicians are driven by their desire to improve patient outcomes and therefore want the total picture. This includes access to published evidence to help choose cost-effective drug and device alternatives without hurting outcomes. Health system administrators need to provide clinicians with access to a wide range of data (not only data about costs). Ensuring that physicians have a strong voice in determining which data to share will help create alignment and trust. A more nuanced value-based approach that accounts for important clinical and patient-centered outcomes (e.g., length of stay, post-operative recovery profile) combined with cost data may be the most effective solution.

While physicians generally report wanting more cost data, not all physicians have the experience and training to appropriately incorporate it into their decision making. Surveyed physicians who have had exposure to a range of cost data, data highlighting clinical variation, and practice guidelines generally found cost data more influential in their selection of drugs and devices, regardless of whether they shared in savings under value-based care models. This was particularly true for more veteran physicians and those with private-practice experience who have had greater exposure to managing cost information.

Health systems can play a key role in helping physicians use cost and quality data to make cost-effective decisions. We recommend that health systems identify a centralized data/analytics department that includes representatives of both quality-improvement teams and technology/informatics to own the process of streamlining, analyzing, and disseminating data.

Compare data based on contemporary evidence-based guidelines. Physicians would like to incorporate reliable data into their decision-making when selecting drugs and devices. In our survey, 54% of respondents reported that it was either “extremely important” or “very important” that hospitals use peer-reviewed literature and clinical evidence to support the selection of medical devices. Further, 56% of respondents said it was “extremely important” or “very important” that physicians be involved in using data to develop clinical protocols, guidelines, and best practices….(More)”.