06Jun

You’ve just been tapped to lead a development team on a new project. It’s a sign of the company’s confidence in you and the opportunity you’ve been wanting for a while.

Now that you’re back at a workstation, reality is setting in. What do you need to get your team on board and rowing together?

In a word, it’s leadership. And that has far less to do with your coding skills than your ability to communicate, motivate and collaborate. Your team will look to you for guidance in setting priorities, advocating for them up the food chain, and working with them to solve problems.

“In today’s world,” says The Ohio State Engineer Magazine, “It is essential for an engineer to possess strong communication skills; it is the biggest determiner of success in the modern engineer’s professional career.” This goes double for project leads and managers.

Clear communication starts with knowing the details of the project, defining the end goals clearly, assigning roles and setting expectations. Clarity is essential, so even when you see nodding heads, don’t assume everyone understands. Ask for discussion. A diplomatic way of ensuring your team understands what needs to be done is ask if the process and goals are realistic; does anyone see any potential problems. Invite pushback on the timeline.

Besides uncovering misunderstandings or communication gaps, you’ll demonstrate your openness to disagreement and differing points of view. Creating an environment of psychological safety is the single most important component of team success, according to Google, which exhaustively studied team leadership.

Slack blog post describes how a team lead creates psychological safety:

  1. An empathetic approach – “Strive to read your teammates. Are they content, stressed out or struggling?… Aiming to empathize with their point of view is key to gaining their trust.”
  2. Practice active listening – This means listening to understand what the person is saying rather than thinking of how we will respond.
  3. Avoid finger pointing – Constructive feedback is helpful. But blaming does nothing good. When problems arise — and they always do — focus on how to solve them. Involving the team in finding solutions is often a smart way to find creative ways to resolve problems.
  4. Be humble – When you make a mistake, admit it. When you’ve been short with someone, apologize. Say “please” and “thank you” often.

Image by Free-Photos from Pixabay

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Jun 6, 2023

How COVID Is Changing Clinical Trials

Amidst all the uncertainty about a COVID vaccine, at least this one thing is certain: it is changing how clinical trials are conducted.

Instead of taking years to move apotential vaccine from laboratory to trial, the US’s Operation Warp Speed has moved two of six prospective COVID vaccines into Phase 3 recruitment in under six months. Two more are expected to begin Phase 3 recruitment this month.

In the United Kingdom, a different type of clinical trial showed it is possible to enroll 12,000 patients, test several different existing treatment candidates and have the first significant results in fewer than 100 days.

Even given the substantial differences between the government-run health care system of the UK and the private, decentralized US system, there are lessons – “ideas,” Nicole Mather calls them in an article for the journal Nature – researchers here can apply to accelerate trials.

Describing how the UK’s RECOVERY trial went from concept to first, actionable results in such a short time, Mather identifies five differences with traditional trials:

  1. The trial protocol took only 20 pages to detail the design, and data and regulatory requirements. It was flexible enough to allow trial arms to be stopped or added.
  2. It got approvals in 9 days, versus the typical 30-60.
  3. Recruitment paperwork was simplified.
  4. Data collection and processing was accelerated through the UK’s DigiTrials hub, which provides centralized support for clinical trials.
  5. Results were quickly made public.

Though the RECOVERY program has its critics – objections center on releasing results without first being peer-reviewed and structural issues – Mather says it shows how a centralized health data system and a streamlined design and approval process can accelerate the timeline.

“We’ve gone so far towards managing risk that we’ve created layers of bureaucracy that absorb time and money, and, paradoxically, increase the risk that beneficial treatments are not tested,” she writes.

That view is echoed by Martin Landray, deputy chief investigator of RECOVERY, who said the way the National Institute for Health Research cut red tape was “fabulous.” “Many academic and commercial trials have accumulated so much extra baggage over the years, such as long case report forms and 10 page patient consent forms,” he said in an interview with The BMJ.

Digital entry for the RECOVERY trial made consent and subsequent data collection quick and simple, The BMJ article reports.

Leveraging data systems is an important lesson, says Mather, who is life-sciences lead at IBM Services in London, which was a partner in the DigiTrials project. Because of the UK’s National Health System, much information was already available for trial study patients, simplifying the participation process.

That would be a much greater challenge in the US because of its private medical system, although the strong push over the last decade to digitize medical records is making the portability of patient data easier.

The UK RECOVERY program has given momentum to accelerating clinical trial processes. To build on it, says Landray, “We now need to apply the lessons from this approach to other major health challenges such as heart disease, cancer, arthritis, and mental health.”

Photo by JC Gellidon on Unsplash

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Jun 6, 2023

AI Could Be the Answer to Alarm Fatigue

Patient monitoring technology has proven both a boon and, in some ways, a burden to medical science.

Automatic sensors can detect heart fluctuations, sounding an alarm that will bring staff running. Other sensors monitor respiration, brain activity, temperature and multiple other critical factors, alerting professionals when help is needed.

However, these monitors can be so sensitive they send alerts for even minor departures from preset norms. A busy surgical unit can be a noisy place with alarms going off so frequently for little reason that they become part of the background ambiance, causing what medical professionals call “alarm fatigue.”

In one large study, nurses in a busy urban hospital were bombarded by an average of 187 alarms per bed each day. Of the 2,558,760 alarms recorded during the month-long study, most – up to 95% — were false or of little consequence.

So serious is alarm fatigue that in 2013 The Joint Commission issued a Sentinel Event Alert warned about the potential for desensitization. “In response to this constant barrage of noise, clinicians may turn down the volume of the alarm, turn it off, or adjust the alarm settings outside the limits that are safe and appropriate for the patient – all of which can have serious, often fatal, consequences.”

Still listed as one of the “Top 10 Health Technology Hazards” by the Emergency Care Research Institute, there is hope that yet another technological advance may hold the solution to too many alarms.

At Johns Hopkins, the health system’s alarms committee has been using and testing a number of techniques for quieting unnecessary alarms. Among these is the use of algorithms to decide when to sound an alarm, to whom and when and how to escalate the situation.

A more extensive use of artificial intelligence was discussed last fall in the Journal of Medical Internet Research. Researchers tested their AI algorithms against the recorded data from 32 surgical patients in Australia. Their technology reduced the total number of alarms by 99.3%.

Although it was not used in an actual clinical environment, “The experimental results strongly suggest that this reasoning algorithm is a useful strategy for avoiding alarm fatigue,” they wrote.

Using artificial intelligence to decide when and how to sound an alarm is still in the future. But, notes The Medical Futurist, “With time, AI solutions will be incorporated in patient monitors as a built-in “smart alarm system” throughout hospital units.”

Image by Bokskapet

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