Bioanalysis for precision medicine

Human genetic variation may lead to different responses from patients who are subjected to the same treatments. The efficacy and potency of a drug may vary because of genetic differences among individuals. In comparison to the ‘one-size-fits all’ treatment (or same treatment for all patients who have similar diseases), precision medicine (PM) has become an important strategy to identify improved diagnostic and targeted therapeutic treatment. In the future, PM may also inform personalized gene therapy treatments. As there are approximately 19,000– 20,000 human protein-coding genes [1], and possibly hundreds of those genes may harbor variations contributing to human illness; hence, it is essential to develop gene-based PM. Gene therapies have already found clinical successes in the treatment of several noncancer diseases, such as severe combined immunodeficiency-X1, hemophilia B and blindness caused by retinitis pigmentosa. Many high mortality diseases including cancers and heart failure have not yet been successfully treated by gene therapies alone. Thus, gene therapy holds promise as an ideal and potentially effective strategy for cancer treatment by incorporating proteomic, lipidomic and metabolomic methodologies.

The full article can be downloaded below.  

Estimating Implicit and Explicit Gender Bias Among Health Care Professionals and Surgeons

The main contribution of this work is an initial estimate of the extent of implicit gender bias within health care. Future research could examine implications of implicit gender biases on gender inequality and discrimination. Other research already provides some interventions for addressing gender bias regardless of whether it comes from implicit bias or other sources. For example, increasing transparency of hiring and promotion policies, considering diversity as a performance metric for organizations, and promoting flexible leave all serve to increase the success of female physicians and trainees. Further documentation of implicit associations and other potential psychological obstacles to women’s success will be important for determining the most effective interventions to reduce gender inequality. It is important to also intentionally study the effects of bias on individuals who hold more than one minority identity, such as black or Hispanic women. Such research will benefit current medical students who will become our physicians tomorrow.

The full article can be downloaded below.  

Doctors Slow To Adopt Tech Tools That Might Save Patients Money On Drugs

When Mary Kay Gilbert saw her doctor in May for a skin infection on her leg, she wasn't surprised to receive a prescription for an antibiotic cream.

But Gilbert, 54, a nurse and health consultant, was shocked when her physician clicked on the desktop computer and told Gilbert the medicine would cost $30 on her Blue Cross and Blue Shield plan.

"I was like, 'Wow — that's pretty cool that you know that information,' " she recalled telling the doctor in Edina, Minn.

Allina Health, the large Minnesota-based hospital network Gilbert's doctor belongs to, is one of a growing number of health systems and insurers providing real-time drug pricing information to physicians so they can help patients avoid "sticker shock" at the pharmacy.

The pricing tool, which is embedded in each participating physician's electronic health records and prescribing system, shows how much patients can expect to pay out of pocket, based on their insurance and the pharmacy they choose.

It also allows the doctor to find a cheaper alternative, when possible, and start the process of getting authorization for a drug, if the insurer requires that.

The full Forbes article can be viewed at this link.  

More than just friends: in-home use and design recommendations for sensing socially assistive robots (SARs) by older adults with depression

As healthcare turns its focus to preventative community-based interventions, there is increasing interest in using in-home technology to support this goal. This study evaluates the design and use of socially assistive robots (SARs) and sensors as in-home therapeutic support for older adults with depression. The seal-like SAR Paro, along with onboard and wearable sensors, was placed in the homes of 10 older adults diagnosed with clinical depression for one month. Design workshops were conducted before and after the in-home implementation with participating older adults and clinical care staff members. Workshops showed older adults and clinicians saw several potential uses for robots and sensors to support in-home depression care. Long-term in-home use of the robot allowed researchers and participants to situate desired robot features in specific practices and experiences of daily life, and some user requests for functionality changed due to extended use. Sensor data showed that participants’ attitudes toward and intention to use the robot were strongly correlated with particular Circadian patterns (afternoon and evening) of robot use. Sensor data also showed that those without pets interacted with Paro significantly more than those with pets, and survey data showed they had more positive attitudes toward the SAR. Companionship, while a desired capability, emerged as insufficient to engage many older adults in long-term use of SARs in their home.

The full article can be downloaded below.  

What’s Powering Artificial Intelligence?

To scale artificial intelligence (AI) and machine learning (ML), hardware and software developers must enable AI/ML performance across a vast array of devices. This requires balancing the need for functionality alongside security, affordability, complexity and general compute needs. Fortunately, there’s a solution hiding in plain sight.

The full Arm whitepaper can be downloaded below.  

Comparison of healthcare professionals’ motivations for using different online learning materials

Online learning is increasingly prevalent throughout all stages of medical education. There is little published literature exploring what motivates healthcare professionals to engage with different types of e-learning content. Learner motivations must be understood in order to design effective educational solutions and to optimize the overall online learning experience.

This article aims to examine engagement, satisfaction, and motivations of healthcare professionals using OPENPediatrics, an open-access medical e-learning platform.

We use a retrospective analysis of online survey data. Users were asked to report engagement and satisfaction with the platform, as well as to select motivations for using different types of content on the site: Courses, Simulators, and World Shared Practice Forum videos.

The majority of respondents were physicians and nurses in North America and Europe. Overall satisfaction with the platform was high. Most frequently cited motivations for using Courses and Simulators were: learn basic and in-depth information around topics, and learn how to deliver safer or more effective patient care. For World Shared Practice Forum videos, most commonly cited motivations were: learn in-depth information about a topic, learn the latest advances or developments in an area, and learn how to deliver safer or more effective patient care.

We appreciated both commonalities and differences in learning motivations among clinicians accessing different kinds of medical e-learning content. Respondents were consistently motivated to learn in order to deliver safer or more effective patient care, but they reported using different types of educational content depending on whether they were learning basic information versus updating or changing their knowledge.

The full article can be downloaded below.  

‘Engagement’ of patients and healthcare professionals in regulatory pharmacovigilance: establishing a conceptual and methodological framework

Engagement of patients and healthcare professionals is increasingly considered as fundamental to pharmacovigilance and risk minimisation activities. Few empirical studies of engagement exist and a lack of explicit conceptualisations impedes effective measurement, research and the development of evidence-based engagement interventions.

This article (1) develops a widely applicable conceptualisation, (2) considers various methodological challenges to researching engagement, proposing some solutions, and (3) outlines a basis for converting the conceptualisation into specific measures and indicators of engagement among stakeholders. 

We synthesise social science work on risk governance and public understandings of science with insights from studies in the pharmacovigilance field.

This leads us to define engagement as an ongoing process of knowledge exchange among stakeholders, with the adoption of this knowledge as the outcome which may feed back into engagement processes over time. We conceptualise this process via three dimensions; breadth, depth and texture. In addressing challenges to capturing each dimension, we emphasise the importance of combining survey approaches with qualitative studies and secondary data on medicines use, prescribing, adverse reaction reporting and health outcomes. A framework for evaluating engagement intervention processes and outcomes is proposed. Alongside measuring engagement via breadth and depth, we highlight the need to research the engagement process through attentiveness to texture— what engagement feels like, what it means to people, and how this shapes motivations based on values, emotions, trust and rationales.

 Capturing all three dimensions of engagement is vital to develop valid understandings of what works and why, thus informing engagement interventions of patients and healthcare professionals to given regulatory pharmacovigilance scenarios.

The full article can be downloaded below.  

Social and juristic challenges of artificial intelligence

Artificial intelligence is becoming seamlessly integrated into our everyday lives, augmenting our knowledge and capabilities in driving, avoiding traffic, finding friends, choosing the perfect movie, and even cooking a healthier meal. It also has a significant impact on many aspects of society and industry, ranging from scientific discovery, healthcare and medical diagnostics to smart cities, transport and sustainability. Within this 21st century ‘man meets machine’ reality unfolding, several social and juristic challenges emerge for which we are poorly prepared. We here review social dilemmas where individual interests are at odds with the interests of others, and where artificial intelligence might have a particularly hard time making the right decision. An example thereof is the well-known social dilemma of autonomous vehicles. We also review juristic challenges, with a focus on torts that are at least partly or seemingly due to artificial intelligence, resulting in the claimant suffering a loss or harm. Here the challenge is to determine who is legally liable, and to what extent. We conclude with an outlook and with a short set of guidelines for constructively mitigating described challenges.

The full article can be downloaded below.  

How Conversational Artificial Intelligence Is Providing Companionship To The Elderly

Looking to address the challenges of elderly loneliness, Accenture has developed a solution that uses conversational AI to let people capture memorable stories for future generations while providing companionship. Powered by Google Voice Assistant, Memory Lane initiates conversations by asking someone who is lonely to tell their life story. This is then turned into a physical book and podcast.

The full Forbes article can be viewed at this link.  

How Do You Measure Quality in Health Care?

As someone who leads an integrated health care delivery system, this is a question I frequently find myself asking.

The obvious answer, of course, is to develop measurements based on treatment protocols. Of which we have plenty. It seems these days that we have a measurement and documentation requirement for just about everything. In fact, quality measurement in health care has become an industry unto itself. Hospitals and health care systems across the country pay a lot of money to have their quality of care scrutinized and, hopefully, lauded, by a number of companies that charge them for such assessments. In many cases, those assessments are valuable.

Nevertheless, I began to think about the value of measurement after exchanging some emails with my friend and college mentor, Deborah Stone. Deborah is a professor at Brandeis University’s Heller School for Social Policy and Management who’s been doing a lot of thinking lately about counting, measurement, and statistic and the ways in which numbers are used to distort and distract from reality. In a lecture she recently gave to the American Political Science Association, Deborah announced to her audience, “Numbers are figments of our imagination, fictions really, no more true than poems or drawings. In this sense, all statistics are lies.”

I’m not sure I’m willing to go as far as Deborah, who’s quite a provocative thinker, but she did make me wonder whether our current health quality measures are offering the right information and, moreover, whether everything valuable in health care can be easily measured. At some level, I suspect, things that are important are not always quantifiable. For example, even if my facilities are spotless and my clinical staff is expert at avoiding preventable infections, does that mean they’re good at explaining diagnoses to their patients? Do they know how to communicate effectively and sympathetically when delivering bad news? Do they return patient calls at night? In today’s health care climate, physicians are often required to see a specific number of patients each day. But how effective are our measurements if a physician misses that quota because she devoted extra time to a single patient who really needed the extra attention and care?

The full Forbes article can be viewed at this link.