A new study by Western Sydney University researchers has found that a short 15–20 minute discussion between a local endocrinologist and general practitioner (GP) in Sydney's south west is improving the care of people with complex type 2 diabetes.

Published in the International Journal of Integrated Care, the three-year study is the first evaluation of "patient-free" diabetes case conferencing—a model where, with the patient's consent, an endocrinologist visits a GP practice, alongside a practice nurse or diabetes educator, to collaborate on the care of patients to develop a joint management plan for the patient.

The study found blood glucose (HbA1c), blood pressure, weight, as well as other cardiovascular risk factors all improved following the three-year trial involving more than 600 patients with type 2 diabetes from 40 general practices across south western Sydney.

Blood glucose results substantially improved between 2017 and 2020, with more than a third (37%) of patients within the target range compared with just one in five (20%) before the program.

In addition, more than three quarters (77%) of patients were recording systolic blood pressure within the target range on follow-up, compared with less than half of patients (47%) in 2017.

Co-author Professor David Simmons, Head of Endocrinology at Campbelltown Hospital and from the University's School of Medicine said the study found the model made a significant contribution to diabetes management in primary care settings.

"Diabetes is a significant health issue in south western Sydney and it is critical we work together to find more effective, integrated and streamlined ways to manage patients and Strengthen outcomes," said Professor Simmons.

"The findings from this study show how a collaborative discussion between a GP and endocrinologist where the patient is not present, can be one of the most effective integrated diabetes care interventions.

"This can allow the GP to continue to care for the patient in the practice, avoiding the need to see an endocrinologist in person. The collaboration also helps build the GP's expertise in managing their other complex patients and the endocrinologist learns more about the patient from the GP which facilitates truly patient-centered care."

The findings add to the evidence suggesting that case conferencing programs can help close the gaps in service provision such as barriers between different settings, Strengthen the patient experience by accommodating more complex cases in primary care and reduce duplication of care.

Co-author Ms. Reetu Zarora, a Ph.D. student at Western Sydney University, highlighted how the model of care doesn't just save time and resources in primary care settings but also has a positive impact more broadly on the health system.

"This is a real win-win-win for patients, GPs and the health system: patients get specialist input into their care without any extra time or cost, GPs can continue to manage their patients using their extra knowledge, and the health system has less demand on hospital clinics, potentially reducing and preventing hospitalizations in people with complex diabetes compared with usual care. This should reduce diabetes-related health issues," said Ms. Zarora.

"In addition, the case conferencing model through the study was shown to be suitable in both urban and rural settings where a number of participating practices support large multi-ethnic populations with varying socioeconomic status.

"This points to the potential for broader applications of the model of care including in regions with resource restraints and diverse populations."

Thirty percent of Americans are overweight. There are many influences on overeating including genetic predispositions, overweight friends, and family. The good news is these influences can't force you to overeat since your actions come from your thinking and you can change your thinking.

In most (but by no means all) cases, being overweight results most directly from eating too much no matter what influences surround this problem. The simple (even if only partial) solution involves eating fewer calories. The difficult aspect involves putting this into practice.

Steps in overcoming obesity

Step 1. Apply the Problem Separation Technique (PST). Ask yourself: do I have an emotional problem such as anxiety, stress, guilt, or depression about my practical problem of eating too many calories?

Step 2. If the answer is yes, then determine if you have a secondary disturbance: a secondary disturbance means you're disturbing yourself about disturbing yourself. To put it another way, when your primary disturbance lies in your eating, Secondary disturbance means making yourself disturbed about eating too much and about gaining too much weight. Here's how it may manifest: suppose you notice you're eating more than is desirable. Primary disturbance: You tell yourself, "I must satisfy my craving for food right now and eat, I can't stand feeling deprived." Secondary disturbance: then as you are compulsively eating you think, "I must stop eating." You have a must about a must! Disturbing yourself about your problem doesn't help and only makes you feel worse. The demand often here is something like "I must not overeat." Demanding this of yourself is unrealistic, doesn't help, and only tends to make matters worse. A more realistic view would be something like, "I prefer not to overeat but clearly there's no law of the universe stating I must not. If I do, I do, I'll try to eat less next time."

Step 3. Remind yourself that you can accept yourself and still enjoy life and be productive with the extra pounds. Then why lose the weight? Because your life can be even better, satisfying, and more healthful without carrying around the extra pounds.

Step 4. Recognize eating too much and eating unhealthy food is a choice. You can choose to eat the ice cream or choose not to. You can choose to stop eating when you've had enough or choose to continue eating. You're not compelled to eat even though it may feel like you are and have no control. If you're skeptical imagine this: you are about to feast on your favorite ice cream. Someone shows up with a gun pointed at your head and threatens: "if you eat the ice cream I'll shoot." Clearly you decide to skip the ice cream.

Step 5. Go for unconditional self-acceptance (USA). You accept yourself unconditionally whether you overeat or you stay on your diet. Refuse to rate your total self based on the rating of your behavior. Whether you diet successfully or unsuccessfully you're still the same imperfect human who acts imperfectly. You always have been and you always will be.

Step 6. Go for unconditional life acceptance (ULA). You accept your life unconditionally with its frustrations, discomforts, and difficulties.

Practice implementing the above steps regularly. It's hard, but hard doesn't mean impossible. The good news: overeating is a choice. You can choose to stay on a reasonable eating regimen or choose not to. It's up to you!

For brands hunting for customer insights to drive decision-making, Strengthen customer experience (CX), and ultimately spur growth, market research has long been part of the toolkit.

Whether it’s actually helpful or not is another question. In a typical market research project, brands invest (often heavily) in conducting research that amounts to a one-time snapshot of existing customer sentiment and, perhaps, competitors’ prevailing differentiators. While this research can yield useful insights, it usually fails to recognize the wants of potential customers, or adequately correlate data that reveals exactly why customers are with competitors.

Brands can easily miss the forest for the trees when relying on traditional market research. They get bogged down in addressing complaints while missing out on the fundamental reasons for why a customer chooses one brand over another. At the same time, market research projects are prohibitively expensive to repeat with regularity, and offer limited insights that begin to go stale from the moment research is completed. 

Some marketers instead leverage social listening platforms for more continuous analysis of customer behavior (and customer engagement with specific features or brand offers). This strategy can collect useful customer reviews and feedback, and tends to be much more affordable than commissioning one-off market research studies.

However, this approach still leaves marketers blind to competitive activity and the adjustments that are best poised to win over those potential customers. Social listening platforms also require largely manual processes to sift insights from firehouse data. Talented data analyst teams doing this time-consuming work may very well identify correlations across that data, but that talent doesn’t come cheap. The shortcomings of both traditional market research and social listening platforms mean that rich opportunities to meaningfully and agilely Strengthen customer experiences regularly go undiscovered. 

The answer to legacy market research and incomplete social listening platforms—as it is across the broader technology landscape — might very well be artificial intelligence (AI) and automation.

With AI deployed to round up continual marketing insights from the right data sources, brands can remove the guesswork from researching and correlating relevant customer experience data. AI-driven automation addresses the biggest limitations of traditional market research head-on: transforming the cost, cadence, and quality of insights collected. Marketers that would otherwise budget out expensive research projects periodically — and adjust their customer-facing practices only that often — should be seeking real-time, always-on insights that show clear correlations.

If traditional market research is like deciphering meaning from a still photograph taken at one moment in time, bringing AI and automation into this marketing practice is like allowing brands to leverage a continuous live video feed of shifts in customer needs and sentiment. Smart use of AI also curbs the need for expensive data teams, enabling marketers and business managers to directly implement insight-based improvements.

Simply put, analyzing customer sentiment data with AI reaches beyond the human capacity for recognizing correlations and customer trends. By collecting continuous marketing intelligence — including customer feedback across social media, review sites, surveys, service interactions and other touchpoints — a smart, AI-driven approach enables brands to be far more responsive and confident in aligning business practices with what customers actually want. Deploying an AI-centric strategy can then also perform the same analysis on competing businesses to discover useful insights, such as identifying practices that win those competitors’ positive customer sentiment and may be worthwhile to emulate.

For example, a hospitality business that implements AI-based customer sentiment data analysis might find that a direct competitor’s customers make many positive mentions calling out the hotel’s high-quality breakfast options. Automated analysis would then present this actionable insight as an easily digestible key takeaway: by investing in a breakfast menu that matches or exceeds the quality of that competitor’s, the brand has a likely path to a more satisfying customer experience, improved ratings, and long-term customer and revenue growth.

In the same way, a coffee chain might discover that competitors are winning positive customer sentiment for their variety of alternative milk options, and adapt their offerings to capitalize on that clear opportunity.

When harnessed correctly, small findings like these hidden within noisy data can nevertheless transform a brand’s competitiveness in their market. 

Stas Tushinksiy is the CEO at Instreamatic.

Keeping employees safe and healthy at work is the foundation of our profession. When someone is injured at work, the impact may create a ripple effect on their life. It can be difficult to quantify or understand the impact of an injury on workplace culture and on the injured person’s life outside of work.

Perhaps they can no longer do the things they love to do outside of work. Maybe they can no longer perform their job as well as they used to. It’s quite possible that a workplace injury can put an employee’s life on hold while they heal, recover and try to bounce back. Sadly, injuries sometimes have permanent ramifications.

In 2021, more than 2.6 million recordable injuries were reported by private industry in the United States alone. Nearly a third of those were due to overexertion. Manual ergonomic assessments are our traditional tool to reduce overexertion injuries. These are, unfortunately, time consuming and limited in scope. The inherent limitations make injury prevention challenging and cost prohibitive to deploy at scale.

Thankfully, technology has advanced in the coaching and assessment realms to the extent that new horizons for safety improvement are within reach.

The Problem with Traditional Ergonomic Assessments

When was the last time you had someone closely watch the work you were doing? What if they were taking notes on a tablet, making measurements of your movements and even taking photos or videos of your work? Do you think that you might try a bit harder or do things “the right way?”

Let’s say we conduct an ergonomic assessment on the first shift operator who happens to be a 5’10” male. Our calculations and hazard assessment is based on his interaction with the workstation, tools and process. What if the second shift operator is a 5’2” female? How might the operation present different risks for these two individuals?

These two basic illustrations highlight some of the challenges that we have faced since the beginnings of our profession:

• How might the risks change if we used a bigger data set instead of a moment in time?
• How might we efficiently understand the way multiple employees within a job role are performing the tasks?

Up until now, the best solutions to these challenges require significant time and effort. This means that ergonomic assessments are cost prohibitive for most organizations to leverage at scale.

But what if there’s another way?

Technology as a Tool for Proactive Injury Prevention

One new solution harnesses artificial intelligence (AI) to identify and quantify ergonomic risks in near real time. It automates measurement of an employee’s movements, the frequency at which they occur and identifies hazards exceeding preset thresholds. Imagine a visual, second-by-second angle of movement evaluation without having to use a protractor or make an educated guess. Videos from app-based AI technology allow safety professionals to gather big picture data over a longer period of time.

This solution enables safety professionals to scale their efforts across multiple facilities and locations without requiring as much travel and time away from home. We can cost-effectively collect ergonomic data from a group of employees for two weeks. We can also easily assess different employees performing the same job. Once this data is collected, it can be used in other ways as well—identifying trainers, best practices and improving standards of work.

What about Overexertion Injuries?

Imagine having an athletic trainer at an employee’s side coaching them into better body mechanics consistently over the course of several weeks. Do you think they would learn safer ways to perform their job duties?

While this type of on-the-job coaching might be an ideal way to reduce injuries, it is not a feasible solution for most companies to deploy at scale. There is no substitute for human interaction, but wearable devices are a game changer in this space! They can measure movements and provide real-time feedback to employees when high-risk movements such as bending, twisting, overhead reaching, or open arm push and pull are performed.

For safety professionals, the data collected from wearable devices provides a great opportunity to make our interactions with employees and supervisors more effective by the insights it can provide. A dashboard displays data for each employee wearing a device. Employees and managers can view the frequency of each type of hazard, where these hazards are happening (e.g., department, job roles) and pinpoint quickly where the risks of injuries are the greatest.

The Root Cause

While technology is opening new horizons of possibility to Strengthen the safety of our operations at greater scale and lower cost, it is, ultimately, just another tool in the safety arsenal. Technology alone is not going to solve problems. People need to identify and address the root cause of the problem. We all have a role to play, from safety professionals and managers to employees and executives with the power to approve spending and investment in engineering controls.

There is only so much time in a day, and safety professionals never have a shortage of priorities. The use of technology can be invaluable, making ergonomic assessments much less time-consuming, more interactive with employees and truly a proactive measure.

Envision a future where we routinely Strengthen culture and employee perception by giving employees the power to change the way they work for the better. How might a more collaborative approach impact morale and retention? Well, that’s a conversation for next time!

Heather Chapman is principal of Paradigm Safety and U.S. account manager of Soter Analytics. Her presentation on “Advancing Injury Prevention through AI and Wearable Technology” was delivered at EHS Today’s Safety Leadership Conference 2022.

The protein STAT5 has long been an appealing target against cancer, but after decades of research it was consigned to the "undruggable" category. Now, University of Michigan Rogel Cancer Center researchers have found success with a new approach.

By tapping into a cellular garbage disposal function, researchers found they could eliminate STAT5 from cell cultures and mice, setting the stage for potential development as a cancer treatment.

STAT5 plays a key role in how some blood cancers develop and progress. But efforts to identify a small molecule inhibitor to block STAT5 have been stymied. Previous research efforts have found it challenging to design a drug to bind to STAT5 with a high-affinity, a measure of how well they fit together. Even when a compound was found to bind with the protein, it may not make its way into cell and tissue. It's also difficult to find a compound that inhibits STAT5 only without affecting any of the other STAT proteins.

Shaomeng Wang, Ph.D., Warner-Lambert/Parke-Davis Professor in Medicine and professor of medicine, pharmacology and medicinal chemistry at the University of Michigan, had another idea.

His lab has been working on a new drug development approach targeting protein degradation. This is a naturally occurring function within cells to get rid of unwanted protein. Think of it as the garbage disposal: When a protein is no longer needed to keep a body healthy, this mechanism removes the unwanted or damaged protein from the cell.

Using this approach, Wang's lab identified a protein degrader, AK-2292, that targets and removes STAT5. The compound was highly specific to STAT5 with no effect on other STAT proteins. It was effectively taken up by both cell lines and mouse models and was found to stop cell growth in cell lines of human chronic myeloid leukemia (CML) and to induce tumor regression in mouse models of CML. Results are published in Nature Chemical Biology.

The protein degrader works by eliminating STAT5 proteins from tumor cells and tissues, unlike a small molecule inhibitor that would traditionally be designed to bind with the protein and interfere with its function.

"We've overcome some of the major issues that were barriers for scientists to target STAT5," Wang said. "People have worked in this field for the last 20 years, and there are no small molecules targeting STAT5 going into clinical development. This study shows us STAT5 can be targeted through a protein degradation approach. It's a new, exciting direction for developing a potential drug molecule targeting STAT5 for the treatment of cancers in which this protein plays a major role."

"This compound gives us a very solid foundation to do further optimization to identify a compound that we eventually can advance into clinical development," Wang added.

Wang's lab has been investigating protein degraders for several years and has a number of degraders in advanced preclinical development studies, which they hope will lead to clinical trials for the treatment of cancer in people.

Ongoing market volatility has left many investors grasping for an investment lifeline to help them stay afloat amidst stormy economic conditions. Conventional approaches to long-term investments follow the 60/40 model (opens in new tab), which allocates 60% of your portfolio to stocks and 40% to bonds. But that strategy may no longer produce your desired results, as both asset classes have performed under their historical averages during the last two decades.

Bond yields historically had an inverse relationship with the stock market to help offset loss. But in 2022, inflation and other global economic factors caused both bonds and stocks to fall. Anyone relying on the 60/40 model is likely finding themselves in deep water. Modern market conditions require a fresh approach to long-term investing in order to properly protect your retirement savings.

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