South by South West (SXSW) is the leading conference on creativity and innovation, so it’s no wonder that health tech had a striking presence this year. Sessions created and presented by experts explored topics like artificial intelligence, 3D printing, big data, compassion and reducing the impact of pandemics – posing some big questions about the role of health tech and future of the industry throughout the process.
It’s easy to get lost in a sea of experiences (and tacos), but it was important to me to capture the biggest health tech questions I heard asked and answered (or kind of), and the questions they left me with. I hope that if you couldn’t attend in person this year, you find value in these quick bites!
Question #1: Can health tech increase compassion?
When compassion is defined as the quality of care provided to a patient, including their role as an informed participant in the decision-making process, there’s a strong argument that yes, technology today can increase compassion. David Ring, MD, PhD, Dell Medical School at The University of Texas at Austin, spoke on the opportunity for technology and expertise to optimize hope and peace of mind for the patient – unlike certain online symptom search tools that can provide inaccurate and frightening diagnostics suggestions.
In this case, compassion isn’t related to emotion, but the quality of care provided.
He highlighted how websites and digital tools can help patients better understand their condition, the options available to them and how these align with their personal values, which can lead to a more informed and better discussion with their provider about the best treatment approach. Ring also noted that remote video consultation can increase access to healthcare providers and that coverage and reimbursement is evolving to include these resources. With the use of this technology, he noted providers must be careful in how they correct misinformation and misperception to ensure patients feel listened to.
Ring’s take – separating compassion from emotion – surprised me and in the days following SXSW left my reflecting on my own experiences as a health tech consumer. I’d argue that quality of care should be incorporated into our view of compassion, but we’re losing something if we ignore emotion.
Or maybe emotion should be considered part of quality of care? As an uncoordinated, yet avid hiker, I find myself visiting the doctor or urgent care with remarkable frequency. Over the years, certain tasks have been taken over by machines. A receptionist now barely glances up to direct me to the machine to check in for my appointment. While I appreciate the efficiency, a machine won’t see my limp and swollen ankle and start looking for crutches like a person would – which leaves me wondering, what is the right balance and how do we automate and expedite simple processes without sacrificing the personal touch of interacting with another human?
Question #2: What’s the deal with artificial intelligence – has it cured cancer yet?
Artificial intelligence has been a buzz word in health tech lately, but has it delivered on lofty promises to transform the treatment and ultimately cure disease?
Not just yet. James Scott, PhD, McCombs School of Business at The University of Texas at Austin, presented the idea that artificial intelligence is actually an old concept used for problem-solving dating back to at least 1696 – of course, not in the form we understand it today.
Interestingly, he argued that the relentless focus on AI as something new is unhealthy, inaccurate and alienates “neophobes,” or those who are hesitant to the “new” – myself, admittedly one of them. It’s important that we focus on the continuity, rather than the disruption, as artificial intelligence really presents an opportunity to do the same tasks better, faster and more efficient.
A couple of the more interesting questions asked and answered related to AI:
- When will AI run countries? They always have. They’re called laws.
- How has this narrative played out? The focus on the new distracts us from reality and has polarized views on AI and data. In the middle is a failure to recognize there is an incredible amount of low hanging fruit to do simple things better, including data science.
- What’s an example in health care? An anonymized patient Joe has Type 2 diabetes and heart failure. At every medical interaction between having a stroke in his 40s and his death at age 62 of kidney disease, Joe’s glomerular filtration rate (GFR) is measured. A scatter plot of his GFR over time – a “cutting edge 19th century invention,” according to Scott could have indicated Joe’s risk for kidney disease and allowed doctors to intervene earlier – but the existing medical data system failed this simple task.
- Can AI moderate a debate? No – or at least not in the panel I attended. There was, however, AI that provided real-time analytics for the debate by tracking speaker emotions, accuracy and breadth of topics covered, which was pretty interesting.
AI in healthcare isn’t going away. If reframing it as an extension of an age-old problem-solving tool helps us embrace it’s ability to drive efficiency in the healthcare ecosystem, I’m all for it. Of course, that’s not to say there aren’t concerns and risks related to the data that AI requires.
Question #3: What is the role of data in health care and will it be our savior or ender?
Big data was a key topic across a multitude of sessions – from a debate on whether it’s inherently good or bad to a discussion on preventing the Cambridge Analytica of healthcare data and a review of its use in the fight against the opioid epidemic to its potential in disease detection.
The theme that rang true across topics and perspectives? With health data, there is great potential for high impact insight but also risk for misuse. One panelist stated, “even seemingly insignificant data can lead to significant inferences about our health.”
A few of the more interesting positive applications for data in healthcare included:
Insight: Conversations are the catalyst for changing culture – and data can provide meaningful insight to drive the conversation. Example: opioid prescribing
- A review of opioid prescription use data by Intermountain Health showed that patients only take about half of their prescribed opioids. Intermountain Health used the data to develop an opioid prescribing dashboard, which allows their physician network to compare their prescribing patterns to their colleagues’. Ultimately, there was a 40% reduction in acute opioid prescribing.
Insight: In each century, we see a driving force that comprehensively changes the public health landscape: sanitation in the 19th century; vaccines and antibiotics in the 20th century; data will be this force in the 21st century. Two examples:
- In disease detection, there’s room for automation and algorithms to improve disease surveillance, allowing public health professionals to do more with data, and do it more creatively.
- In developed countries, we have enormous data available – too much, in fact. From electronic health records to social media posts and wearable trackers, it’s a puzzle for data scientists to determine what is the right data to store and analyze. In less developed countries, the looming question is how to collect the data.
Insight: When it comes to our health data, there’s plenty to be concerned about – but three key areas that emerged include:
- Inequalities and biases: There are inequalities in the gathering of data, meaning data sets are biased – so resulting diagnostics might not lead to generalizations or conclusions, or products might not work in under-represented populations.
- Discrimination: People are worried about getting labeled with something that will adversely affect their ability to obtain life insurance, loans, fair insurance premiums. Unlikely players are starting to track health data, like credit rating agencies and colleges.
- Control and manipulation of data – for example, to extract higher prices from users based on location or search history.
The promise of healthcare data is to figure out how it can be used to benefit the health of people and put guardrails in place to minimize risks. As always with data, there are more questions than there are answers. But, asking the right question is the first step – and I was relieved to hear the questions posed and considered by industry leaders in a session specifically on protecting our healthcare data (side note: this incredible all-female panel spoke on the topic on International Women’s Day – a coincidence that was celebrated).
Question #4: Is SXSW worth it for the healthcare/health tech professional?
SXSW is a big investment to attend. It’s an investment in money, time, and in some sense one’s own sanity. It’s easy to wonder whether it’s worth attending, particularly in the health tech space where there’s no shortage of inspiring conferences.
I hope you found value in the questions and answers I’ve shared, and that they’ve inspired you to think differently about the potential and future for health technology.
Personally, I left Austin excited, inspired and grateful for the opportunity to attend SXSW. It was a remarkable experience. While I enjoyed my fair share of queso, virtual/automated reality and puppies, and waited in line to listen to Senator Elizabeth Warren speak – what impacted me most was the breadth, depth and variety of health-related sessions at a conference known for celebrity sightings, music and brand experiences.
One panelist stated, “Technology and innovation aren’t the ultimate end for us. The ultimate end should be human flourishing both on the individual level and global, community population level. There should be moral limits to tech, innovation and markets. We may need to slow down or invest in ensuring morals develop at the same pace.”
I think if for nothing else than to explore the broader context of the work we do in health tech, to connect our world of data, efficiency and innovation to our broader purpose and the culture that will accept or reject our efforts, #SXSW is a valuable and unparalleled experience.
This article was originally published by Caroline Hoffman, Account Supervisor, as a 4-part series on LinkedIn: Compassion Asked and Answered; AI Asked and Answered; Data Asked and Answered; Health Tech Asked and Answered.