HIStalk Interviews Chakri Toleti, CEO, Care.ai

Chakri Toleti is founder and CEO of Care.ai of Orlando, FL.

Tell me about yourself and the company.

This is my fourth gig in the healthcare space. My brother Raj and I have done business together, and this is my own project. I started the business three and a half years ago to bring ambient intelligence to healthcare.

I don’t have a pure technology background or healthcare background. I worked for Disney Ideas, then went to film school. That has nothing to do with any of this stuff, but I always was intrigued with other industries and how they adopt technology to bring process automation and efficiencies to deliver consistent, better solutions. That is my background and my passion.

Looking at healthcare, many processes can be efficiently automated to impact the care delivery process itself. I looked at ambient intelligence and felt that there is a significant gap in healthcare. I saw the transformation that was happening even in your home, like a smart home, the ability to get control of what’s going on in real time. That was the genesis of Care ai.

How will your business change as new types of health-related sensors are developed?

The technology has evolved dramatically. We can deploy high compute engines like GPUs in a smaller form factor with less power consumption. We have several provisional patents in terms of how to scale and do edge computing in a much more efficient way in the healthcare setting. We can roll out across tens of thousands of rooms without bringing the network down. We are really good at being able to get the appropriate data, clean data, to run these AI models on the edge.

If you want to draw parallels, look at Nuance’s 10- or 15-year-old technology with Dragon. When you have enterprises like Google, Microsoft, and Amazon spending billions of dollars on NLP-based workflows, that has become commoditized dramatically. Amazing large language models are being deployed in enterprise settings to be able to deliver the same kind of results, and much better results, for a fraction of the cost. That’s the transformation that is happening.

What we’ve built is bringing these operational clinical workflows together, building a scalable command center, and shifting the paradigm of what clinical data capture or operational data capture will look like in healthcare.

A lot of the old-school monitoring in the ICU went beyond sensor-based instrument alarms and instead involved an experienced clinician asking questions or observing the patient. Can value be added by analyzing audio and visual information?

That’s exactly what we do. Imagine a Tesla car sitting in a room. That’s what we’ve built — inferencing, audio-visual, three-dimensional volumetric data to give you a lot more information of what’s going on, how many people are in the room, how long did they stay there, did the patient eat food, how long have they been sleeping in the same position. All the environmental data, coupled with the data capture of every action that’s happening, is the fundamental difference that we are enabling to truly build a smart patient room.

I wake up every day from the dream that I’m going to kill the EMR. EMRs are the most antiquated way of data capture. They are required, but were built for a specific purpose 10, 15, or 20 years ago with an archaic way of data capture. It would be unthinkable if workers in an Amazon warehouse had to stop and input information about everything that they are doing. Yet we take the most talented and expensive resources in healthcare and make them do data entry in a crappy interface with all these clicks, forms, and flows in a complex form of data capture. All it is doing is generating a bill.

Obviously the clinical data is important, but we all know that every unit in every health system has skewed dark data. If you look at the respiratory rate, it is magically the same, 14 or something, in every unit. It’s like muscle memory. It gets worsen as you go through the ecosystem. Post-acute reimbursement is completely based on data capture. They have something called ADLs, activities of daily living. They have to capture all of that, and it’s a manual process.

Some hospitals have created command centers and are interested in remote patient monitoring. What will the hospital of the future look like given the opportunity to separate the services from the hardware capabilities of the room or having people enter the room regularly?

An accelerator for us is that the staffing shortage and the staffing crisis is elevating the need for solutions like these that can give the bedside care teams the scale that they need. Also, they have to think outside the box. The EMR cannot be the universe of every way of capturing information. Every health system recognizes that, and that’s why we are getting traction.

Also, the technology has become democratized, in that the cost to deploy these solutions is fractional. If you go to most of these organizations, they are still moving computers-on-wheels from older companies from one room to another, paying $10,000 or $30,000 per cart. For a fraction of that cost, we can wire up a true smart patient room that gives you real-time visibility into operational and clinical workflows with the ability to analyze audio, video, three-dimensional volumetric data visualization and capture of that information with super high accuracy.

How will AI change the way we think about healthcare software and how technology is developed or deployed?

It will be a once in a generation change in terms of how you look at delivering care. There are two sides to it. One is innovation, drug discovery and all the other aspects of AI. But when it comes to the four walls of operations of a hospital or post-acute facility itself, real-time AI will fundamentally change how we monitor and how we deliver care in an efficient way and at higher standards of quality. If you look at generative AI and all the innovation that is happening at an accelerated rate, healthcare will have a huge impact on that.

When we talk about AI in a healthcare setting, people talk about taking a few algorithms and applying them to the dataset that we have. That is good, and you need it. But a lot of the data is dark data. It’s skewed. How did we capture that information? Is it accurate? You have to go back and look at how you bring true, clean data into the system. 

Imagine a self-driving car. They send out these cars, capture real-time information about the roads, then teach the neural nets to look for the most efficient way of driving. More and more you will see those kind of implementations and adoption of AI into healthcare in a different way. It could be a radiology or a CT scan that’s happening in real time. The ability for it to recalibrate itself using AI to get more accurate scans will also be a part of the entire ecosystem. Rather than just, hey, I’ve scanned, so let’s apply AI to identify abnormalities. There are different aspects of AI that have not fully been leveraged in healthcare settings.

How should a mid-sized healthcare technology company look at incorporating large language models that are changing so quickly?

We should be looking at a problem and then seeing if applying AI to that problem will solve it. Does it even require AI? Once you have identified a problem like nursing shortages — we have a virtual nursing infrastructure — but then how do you look at AI being more integrated into the platform? Understanding the workflows within healthcare and using the frameworks with the right set of data to impact that workflow. That work will be a key way for these organizations to succeed. 

Cerner or Epic were designed before a lot of these innovations happened. For example, for controlled substances, two people have to sign off in the room, logged into the EHR on the same computer. That was designed like 10 years ago. There’s no way for one person to be virtually beaming in and one person in the room. EMRs don’t have the ability to do it. They would have to re-architect everything in the new way of doing things. That would be a big lift for them. 

Newer companies have an advantage to look at a clean slate and say, what’s the most effective way in today’s technology landscape to implement the most effective solution for that problem? If they truly understand what real-time AI can do, then the sky’s the limit to transform healthcare.

You started the company right before the pandemic began. What is different now about starting, running, and selling a digital health company?

I would strike out the last one. If someone is building something with the objective of selling it, then that’s the wrong way of going about it. You have to solve a problem, and whatever the outcome is, it will be good, whether you sell the company or stay with it. 

The landscape has dramatically changed. For us, we had an advantage in that we started the business when the pandemic hit, which propelled and accelerated our growth. I don’t think I could repeat the same kind of growth again in my career. We were at that inflection point.

Also, health systems have changed their thought process. The pandemic exposed the weaknesses that are inherent in the care delivery system and processes. That is in the forefront of the leaders in these health systems for them to solve. They are much more open to new, innovative companies, so it’s a great time to bring innovative technologies to these institutions that are more open to newer ideas and newer companies to innovate for them. They know that the status quo has a lot of weaknesses that are built into their systems today. It’s a great time if you have the right solution to help them be more efficient and deliver the same or higher standards of care.

What will be key to the company’s strategy in the next three or four years?

It will be extremely important to understand the impact of AI and how it will change the client’s businesses. If companies don’t look at new ways to solve problems, be nimble about it, and adapt aggressively, it will be tough in a dynamic environment. The technology landscape is changing at a much faster pace than we’ve ever seen in our careers. They have to be at the same speed as what the technology is changing. ChatGPT 3.5 versus ChatGPT 4 or Bard are coming up at lightning speed, and startups and new companies that are trying to go to market need to have the same agility.

Readers Write: Cutting Through the Hype: Navigating AI in Healthcare

Cutting Through the Hype: Navigating AI in Healthcare
By Michael Burke

Michael Burke, MBA is founder and CEO of Copient Health of Atlanta, GA.

First, a confession. Our company leverages machine learning in our operating room utilization software solution. As such, we stand to benefit from the AI hype machine that is running at full speed. But I promise you, the intent of this paper is not self-promotion; it’s to help you distinguish true AI value from mere marketing hype.

Understanding the categories of AI, and a little about how each tool set works, is essential. However, wading into the weeds a bit is an unfortunate requirement of doing this.

The Basics of AI: What Healthcare Executives Should Know

Before delving into the nuances of true versus misleading AI claims, let’s first understand some fundamental AI categories relevant to healthcare. The items below aren’t a comprehensive list, but they do capture some of the most common and important categories you’ll see:

Machine Learning (ML)

Machine learning is a branch of AI that uses specific algorithms to analyze and learn from large amounts of data. This “training” process, and subsequent testing, results in a model that can make predictions or decisions without being explicitly programmed to perform the task.

Training methods of different ML algorithms include:

• Supervised learning. Supervised learning is like teaching a child with the help of a teacher. The teacher knows the correct answers and provides guidance, and the child learns from this guidance. An example of supervised learning in healthcare could be predicting whether a tumor is malignant or benign based on a set of labeled tumor data. In this case, the “teacher” is a labeled dataset where each tumor is classified as either malignant or benign. The ML model is trained on this data and can then predict whether a new, unlabeled tumor is malignant or benign based on what it has learned.
• Unsupervised learning. Unsupervised learning is like a child learning through exploration without guidance from a teacher. The child learns about the world by observing and interacting with their environment. An example of unsupervised learning in healthcare could be patient segmentation, where healthcare providers group patients into different categories based on their health data. There are no pre-labeled categories here; the ML model must learn to identify patterns and structure in the patient data to determine how best to group the patients. For instance, an unsupervised learning algorithm could analyze patient data to identify clusters of patients with similar health characteristics, which might correspond to different risk groups or disease subtypes.
• Semi-supervised learning. Semi-supervised learning is a combination of supervised and unsupervised learning. The model learns from a combination of labeled and unlabeled data. A semi-supervised learning example could be if a hospital had a large amount of patient data, but only a small portion of the data is labeled. Perhaps only a small set of the patients’ records include a diagnosis for a certain disease. The ML model can use the small amount of labeled data to learn about the characteristics of patients with that disease and then apply this learning to the large amount of unlabeled data to predict which of those patients might have the disease.
• Reinforcement learning. Reinforcement learning is more like teaching a dog to perform a new trick. You don’t tell the dog explicitly what to do. Instead, the dog tries different actions, and you give it a treat (a reward) when it performs the action you want, like sitting or rolling over. Over time, the dog learns which actions will earn it a treat and starts performing those actions more frequently. In a healthcare context, consider a machine learning model that is trying to optimize treatment plans for patients with chronic conditions. To compare to our dog training explanation, the ML model is the dog, the different treatment plans are the actions the dog tries, and the patient health outcomes are the rewards. The model tries different treatment plans (actions) and observes improvements in patient health (the reward). Over time, the ML model learns which treatment plans lead to better patient health outcomes, much like the dog learns which actions earn it treats.

ML excels at tasks where patterns and structures can be discerned from data, such as prediction (predicting hospital readmission rates based on patient data), classification (classifying skin lesions as benign or malignant based on image data), and clustering (segmenting patients into different risk groups based on their health data).

Deep Learning (DL)

Think of deep learning as a team of detectives working on a case. Each detective looks at a part of the evidence and makes their own observations. They pass their findings to a senior detective, who then makes more complex observations based on the initial detectives’ findings. This goes on until the chief detective (the final layer of the network) makes a decision based on all these observations.

In the world of AI, each ‘detective’ is a layer in an artificial neural network. Each layer looks at some aspect of the data and passes on its findings to the next layer. This allows the network to learn from simple features at lower layers to more complex features at higher layers.

Let’s translate this into a healthcare example. Consider a deep learning model analyzing an MRI scan to detect a tumor. The initial layers might look for basic features like edges or colors. The next layers might recognize more complex patterns like shapes or textures. And the higher layers might identify the specific features of a tumor. Just like our detective team, each layer contributes to the final decision, allowing the model to accurately identify whether a tumor is present.

Deep learning excels at tasks involving unstructured data such as images, audio, and text. For instance, deep learning algorithms can analyze MRI images to detect tumors, listen to a patient’s speech to diagnose mental health conditions or analyze electronic health records to predict patient outcomes.

Natural Language Processing (NLP)

Natural language processing (NLP) involves the interaction between computers and human (natural) languages. This technology allows computers to understand, interpret, and generate human language in a valuable way. At its core, NLP involves machine learning to automatically learn rules by analyzing a set of examples and making a decision based on them. This decision could be understanding sentiment, translating languages, or converting speech to text.

In the healthcare sector, NLP can be used to interpret clinical documentation, analyze patient feedback, or enable natural language user interfaces (e.g., chatbots for patient engagement).

Generative AI

Generative AI involves creating new, previously unseen content. Think of it like an AI artist that creates new works based on styles it has learned from. Generative AI is not limited to any particular type of content and can generate images, text, music, and other types of data.

In healthcare, generative AI could be used to create synthetic patient data that can be used for research or training purposes without compromising patient privacy. For instance, a generative model could be trained on real patient data and then generate new data that maintains the statistical properties of the original data (like the distribution of different diseases or the average patient age) but does not correspond to any real individual patient. This synthetic data can then be freely used without worrying about privacy violations.

Computer Vision

Computer vision is like teaching a computer to ‘see’ and interpret visual data in the way humans do. This technology is extremely versatile, being used in everything from self-driving cars to facial recognition software.

In healthcare, computer vision is often used in medical imaging to detect diseases and conditions. For example, computer vision algorithms can be used to analyze X-rays, MRIs, or CT scans to detect tumors, fractures, or other abnormalities. It’s also used in telemedicine solutions, where computer vision algorithms can help monitor patients and detect abnormalities or changes in their condition. Computer vision is also used in robotics.

Knowledge Representation and Reasoning

Imagine AI as a detective solving a complex case. To do this, it needs  a vast amount of knowledge about the world, along with the ability to reason with this knowledge to draw conclusions. That’s what knowledge representation and reasoning AI do.

In the healthcare domain, such AI can be used in clinical decision support systems to aid physicians in diagnosing diseases. The AI system has access to a vast amount of medical knowledge and can reason with this knowledge to provide suggestions to physicians.

It’s hard to decide where to draw the lines when categorizing types of AI. For instance, that the problem of tumor detection often involves computer vision as part of a series of machine learning models that feed together into a deep learning network. Additionally, a field like robotics is sometimes considered its own AI category and other times considered an application that uses specific categories of AI. I’m confident that people smarter than me will sometimes disagree with my categorization choices.

Identifying Genuine AI: A Guide to Avoiding the Hype

While understanding AI categories is a good starting point, the key to discerning genuine AI applications in healthcare software lies in recognizing when these technologies add real value to a process or outcome. And remember: AI, at its core, should aid decision-making, not replace it.

It’s easy for marketing campaigns to dress up their solutions with the AI label, but there are several ways in which the reality may fall short of the hype.

The AI Imposter: Recognizing Automation Dressed Up as AI

AI, including ML, DL, and NLP, learns and improves from data over time, enabling complex decision-making that is generalizable and extends beyond predefined rules. In contrast, rules-based automation, though beneficial in certain contexts, lacks this level of complexity and adaptability.

Consider, for example, a software solution that sends alerts when patient vitals reach certain thresholds. This represents a rules-based automation system, not AI. A genuine AI solution might continuously analyze patient data, learn from it, predict potential health risks before they become critical, and even suggest personalized treatment plans. This shouldn’t imply that a solution that leverages AI is necessarily better than a rules-based automation solution. However, beware of vendors dressing up automation as AI to take advantage of the hype as a rationale to increase price.

The Overkill: Unnecessary AI Implementations

Some solutions may incorporate AI where it’s unnecessary, serving more as a marketing tool than a feature that adds value to the end user. An example could be an element of a software solution that matches tasks to individuals based on skills. It might use an unnecessarily complex ML categorization algorithm where a simple lookup table would have sufficed.

The Overstatement: Claiming Unrealistic AI Capabilities

Some vendors may oversell what their AI can achieve. While AI can indeed help predict patient outcomes, claiming perfect accuracy is unrealistic and potentially misleading. Also, prediction accuracy in machine learning is a moving target as training data sets change over time, sometimes in response to the ML-based intervention itself.

Downplaying the need for quality data can lead to overstating anticipated results. AI systems are only as good as the data they’re trained on. If a solution downplays the importance of data quality, quantity, or diversity, be skeptical.

The Overlook: Ignoring the Need for Human Oversight

True AI applications in healthcare are designed to support and enhance human decision-making, not replace it. If a solution suggests that its AI can replace human judgment entirely, it’s likely overhyped. It could also be dangerous.

Conclusion

While Copient Health indeed benefits from the AI boom, we urge discernment when it comes to AI in healthcare. Understanding the basics and recognizing when AI genuinely adds value is critical. The future of healthcare is undeniably intertwined with AI. With a robust grasp of the subject, you’ll be primed to guide your organization into a more efficient, patient-focused era.

Curbside Consult with Dr. Jayne 6/5/23

I spent the weekend largely unplugged, catching up on some household projects and indulging my need for quality time in the kitchen. My last-minute run for pickling and baking supplies created an interesting assortment of items at the grocery checkout, but when you like to do things old school, sometimes you really do need three kinds of vinegar and a jar of bay leaves.

My pickling efforts were slightly more successful than the baking one, which resulted in the first time I’ve ever had to admit that it’s possible to have too much sugar in a cake. When I finally reconnected this weekend, my inbox seemed to be forming a theme around the topic of healthcare IT gone bad.

First, there was the story of the National Eating Disorder Association chatbot being decommissioned after it recommended harmful behaviors, including dieting and calorie restriction. The organization at least owned the problem, stating that the advice being given was “against our policies and core beliefs.” Apparently the chatbot, called Tessa, was created around proven cognitive behavioral tools that have been shown to reduce eating disorders. However, it appears that programmers may have tried to make it work more like ChatGPT and ended up running off the rails. The original tool used pre-programmed responses and was not intended to be adaptive or to use AI features.

It’s been interesting to watch chatbots evolve over the last couple of years. Quite a few vendors claim to have created AI-enabled chatbots, but when you look behind the scenes, they end up being sophisticated (or sometimes not so sophisticated) decision trees. I’ve seen some alleged healthcare chatbots that are constructed by teams that don’t even have clinicians on them, which is truly worrisome. It’s always surprising to see the logos of organizations who have bought into the hype and probably never asked to speak to the clinical person behind the proverbial curtain.

When ChatGPT came to the forefront in recent months, I saw several companies try to leapfrog good design and development principles in an effort to be able to say that their product was using the technology. I’ve worked with enough technology organizations and on enough different projects to know that trying to cut steps out of the software development lifecycle is never a good idea.

The steps that organizations typically try to cut are the ones that are the most critical in my book: planning, analysis, and testing. They forget that the whole point of the process is to be efficient from both time and cost perspectives. When you rush to market, you usually end up paying for it on the back end with broken functionality and unhappy users. The piece that it feels like people forget though is that when you’re in healthcare IT, that can translate to patient harm. Developers always need to remember that regardless of whether you call them users, consumers, or patients, the person on the other side of the code is someone’s parent, child, friend, or loved one.

The next story wasn’t about AI run amok, but was about more than 400 Grail patients receiving notices that they may have cancer. The company immediately pointed fingers at its third-party telemedicine vendor, PWNHealth. In digging into the details of the issue, more than half of those receiving the erroneous letters hadn’t even had their blood drawn.

The test in question is Galleri, which can screen for 50 kinds of cancer through a single blood draw. Large healthcare organizations like Mercy have jumped on board with it, offering the tests on a cash-pay basis even though they aren’t part of guidelines-based recommendations. The test costs $950, and if I had paid that kind of money, I would be doubly aggravated to receive an erroneous letter before I even had my sample collected. I had heard of the test when Mercy first started advertising it, but didn’t realize until I read the articles this weekend that it has not completed human clinical trials. There’s a study in the UK that’s at the halfway point, though. Despite that, more than 85,000 patients have spent the money to have the test performed, with only a handful of insurers providing coverage.

I’ve been on the other side of an erroneous medical testing result and it’s a horrific experience, leading you to wonder even if your corrected result is valid. In my case I had my pathology slides re-read by an outside pathologist because I didn’t know which reading to trust. Not every patient has the knowledge to ask for that or the resources to pay for it. Also in my case, the test orders were placed by a local physician who knew me well and with whom I had a relationship, which was a great support as we worked through the issue. Grail, whose owner is DNA-sequencing equipment Illumina is already under fire from regulators in both the US and Europe due to monopoly concerns. It will be interesting to see how this unfolds.

The third story wasn’t about healthcare IT as much as about AI in general, looking at specifically how AI would compare to humans on judging whether rules have been broken. A study done by Massachusetts Institute of Technology examined how AI would handle such things as a post violating a site’s rules or a dog being in violation of apartment rules. Researchers concluded that since AI can be trained on data sets that don’t include human validation, results may skew more harshly. A researcher in the field, Professor Marzyeh Ghassemi, is quoted as saying, “Humans would label the features of images and text differently if they knew those features would be used for a judgment. This has huge ramifications for machine learning systems in human processes.” Definitely something to think about when it feels like everyone is clamoring for more AI.

I would be remiss if I didn’t say happy birthday to the HIStalk team as the healthcare IT universe celebrates its 20th anniversary. One of my vendor executive friends recommended it to me when I first started my healthcare IT journey, and I never dreamed I would be part of the team. It’s been quite a ride with a lot of ups and downs in the industry, and I still remember sending my application to join the team by way of my trusty BlackBerry. Looking through old posts and revisiting what we thought was wild and crazy at the time, some of those news items pale in comparison to the issues of today. Here’s to the future of HIStalk as it continues to chronicle our topsy-turvy industry and to be everyone’s favorite source of healthcare news, opinion, rumors, and gossip.

Email Dr. Jayne.

Morning Headlines 6/5/23

Eating disorder group pulls chatbot sharing diet advice

The National Eating Disorder Association shuts down its chatbot after users report that it gave them inappropriate advice for managing eating disorders, such as advising them to diet.

Fuse Oncology Closes Funding Round with Support from Leading Health Systems in the Southern US

Fuse Oncology, a Cone Health spin-off specializing in radiation oncology software, closes a $9 million Series A funding round led by Cone Health Ventures and Northeast Georgia Health Ventures.

Software snafu leads to 400 Grail patients getting bogus letters saying they might have cancer

Cancer screening company Grail blames third-party telemedicine vendor PWNHealth for sending 400 people letters inappropriately warning them that they may have cancer.

HHS’ big data-sharing decision

Politico reports that HHS is accepting proposals from organizations interested in taking over management of the TEFCA data-sharing initiative, which is currently overseen by the nonprofit Sequoia Project.

Monday Morning Update 6/5/23

Top News

The National Eating Disorder Association shuts down its chatbot after users report that it gave them inappropriate advice for managing eating disorders, such as advising them to diet.

The association closed its human-staffed help line in May 2023, a few days after its employees unionized. Help line employees and volunteers fielded 70,000 calls per year.

The medical school team that created the chabot says it was never intended to be a replacement for the help line. They also suspect that the organization introduced bugs in trying to make the chatbot look like ChatGPT even though it is a rules-bases system that can’t generate unique responses. 

Reader Comments

From Smidge: “Re: HIE. I saw a new doctor who downloaded my health and demographic information from an HIE and some of it was outdated or truncated. I’m wondering if others have seen this. It may have been caused by another provider’s system merge.”

From Another Dave: “Re: Scanadu Scout. Remember that? Mine still works on those occasions where I find it in my drawer of broken dreams. This one might make it to the marketplace.” Scanadu’s so-called Tricorder system died in a big cloud of hype dust when it gave up on bringing the Scout to market in mid-2017. Meanwhile, smartphones are slowly adding Scout-like technologies, and UCSD engineers have developed a 10-cent phone clip that allows measuring blood pressure using the phone’s camera and flash.

HIStalk Announcements and Requests

Most readers aren’t making big money via side jobs.

New poll to your right or here: Has your cell phone ever been a key driver of a life-changing improvement to your health? Feel free to click the Comment link after voting to provide details.

Thanks to the following companies that recently supported HIStalk. Click a logo for more information.

Webinars

None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.

Acquisitions, Funding, Business, and Stock

India-based Apollo Hospitals will sell a 6% stake in its online platform for $200 million, valuing the business at up to $3 billion. Apollo HealthCo was launched in June 2021, merging the company’s digital health and telehealth products with the intention of raising investor capital to expand.

Sales

• Belgian hospitals AZ Sint Jan and AZ Sint Lucas select Sectra One Cloud for enterprise imaging.

Privacy and Security

Molecular diagnostic company Enso Biochem announces via an SEC filing that the clinical test information of 2.5 million people was exposed in an April 2023 ransomware attack.

Other

Microsoft researchers train a GPT-4 model using a PubMed Central dataset extract of diagnostic images and their captions to inexpensively create a conversational assistant for biomedicine in one day.

Cancer screening company Grail blames third-party telemedicine vendor PWNHealth for sending 400 people letters inappropriately warning them that they may have cancer.

South Australia Health has failed to deliver on its promise of implementing a crucial result tracking and notification feature within its Altera Digital Health Sunrise EHR system, three years after the death of a patient whose adenocarcinoma diagnosis was delayed by three months. SA Health says a Sunrise upgrade later this year is required before introducing Compass, a task tracking function that reminds doctors when they don’t review test results promptly.

Where would you start if you were CEO of this major ambulatory EHR vendor as profiled in a new KLAS report?

Sponsor Updates

• Be Well Primary Care (TX) transitions to EClinicalWorks V12.
• Azara Health publishes a new resource and strategy guide, “Leveraging Social Drivers of Health Data to Promote Health Equity Advancement.”
• AvaSure adds AI enhancements to its TeleSitter virtual care platform, including augmented alerts for patient falls and elopement, and predictive fall risk identification.
• NeuroFlow publishes a new whitepaper, “Navigating the Integrated Behavioral Health Landscape: A Roadmap for Providers and Organizations.”
• Orbita will present at the Healthcare Contact Center Conference taking place June 7-9 in Atlanta.
• Nuance publishes a new case study, “DAX expands access to care at WellSpan Health.”
• Wolters Kluwer Health partners with Ariadne Labs and its Better Evidence program to donate over 100,000 UpToDate subscriptions.

Blog Posts

• Effective HCP engagement: Timely, Relevant, and Personalized (OptimizeRx)
• Optimizing the Transfer and Call Centers – Methodist Le Bonheur + Call Center (PerfectServe)
• Premier Survey Reveals Key Insights on Workplace Violence Incidents in Healthcare* (Premier)
• How Does Your Access Center Measure Up? (Tegria)
• What healthcare gets wrong about patient engagement (Hint: Sending a text message isn’t enough.) (Upfront Healthcare)
• Delivering better patient financial care: 3 takeaways from Renown Health’s success (Waystar)
• FAQ: Double Your Reach: Marketing Hacks for Inside and Outside Your Practice (WebPT)

Contacts

Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates.
Send news or rumors.
Contact us.

Morning Headlines 6/2/23

FDA-approved Alzheimer’s drugs will be covered by Medicare, with some limitations, CMS says

CMS announces that Medicare Part B will cover the use of FDA-approved monoclonal antibodies to slow the progression of Alzheimer’s disease, but will require doctors to populate patient registries for real-world tracking of the performance of those treatments.

Biden plans to pick physician Mandy Cohen to lead CDC

President Biden will reportedly choose Aledade executive and former North Carolina health secretary Mandy Cohen, MD, MPH as director of the CDC.

Lightning Step Divests AVA Billing & Consulting, Reinforcing Focus on Core Behavioral Health Software Solutions

Behavioral healthcare software vendor Lightning Step sells its Ava Billing & Consulting subsidiary to RCM company Medusind.

News 6/2/23

Top News

CMS announces that Medicare Part B will cover the use of FDA-approved monoclonal antibodies to slow the progression of Alzheimer’s disease, but will require doctors to populate patient registries for real-world tracking of the performance of those treatments.

The Alzheimer’s Association says that requiring patient registries for coverage should be reconsidered because of the clinician data entry workload that is required. The association wants to know more about how data will be submitted, how the CMS-facilitated portal or other registries will work, and how patients and physicians can enroll.

Reader Comments

From Zippydoodle: “Re: non-existent HIPAA certifications. HIPAA compliance is a process, not an event, and there is no single body that certifies a company as being HIPAA compliant. Startups in particular that should be saying ‘we will sign BAAs’ instead declare that they are HIPAA compliant or HIPAA certified.” Companies need to be HIPAA compliant, not HIPAA certified,  and HHS has been clear that it requires the former and doesn’t recognize the latter. 

From Austin Keeping Weird: “Re: Founder Wellness and Blood Draw Party. Some influencer who isn’t affiliated with healthcare is promoting a digital health startup event. So many things wrong: the free blood draw panel for folks who are likely amply insured while much of Texas isn’t, the IV bar that has nothing to do with wellness, and the ice baths that create images of attendees in Speedos. Digital health companies who attend will soon discover that their sustainability is associated with payers or prescribers, not vanity faux medicine.” Maybe the unnamed company should launch a TikTok challenge.

From Laff Riot: “Re: Florida patient data law. I’m surprised that few comments have been made given the number of health IT companies that use offshore resources for support, development, or billing services. Florida providers and their vendors have little time to review or modify contracts to ensure that offshore resources do not have access to PHI.” The newly modified Florida Electronic Health Records Exchange Act, which takes effect July 1, prohibits providers from storing patient records offshore or allowing access to US-stored data to anyone who is outside the US or Canada. Providers must also ensure that patient data that is stored in the cloud is physically housed in the US.  A couple of websites mentioned of the law a few days after reading about it on HIStalk, but otherwise it has drawn little attention. Given that compliance will be far from universal by the due date, it’s all about enforcement and penalties.

From Billie Gene: “Re: gene editing to reverse/stop a hereditary condition. Laudable R&D to advance precision medicine or another over-reach by pharma?” Genetic telehealth provider Genome Medical will offer genetic counseling to participants in a company’s clinical trial of a gene editing process for treating sickle cell disease. Much of medical research isn’t laudable since profit is the intention and the reward, but I would have good feelings about the company if their treatment alleviated my SCD symptoms.

HIStalk Announcements and Requests

Are you Rockies-bound next week for MUSE Inspire? Some of my sponsors are, and here’s what they will be doing there.

I have some very slightly overlapping background with someone I was interviewing today and they asked if I knew Brad Dodge. I instantly said yes, recalling that his company back in the day, Dodge Communications and specifically Brian Parrish, designed the HIStalk logo you see at the top of this page that has served me well for more than 10 years (I am obviously from the “ain’t broke” school of rebranding). Thanks to Brad and Brian for volunteering to create what turned out to be a long-lasting graphic.

Listening: WITCH (We Intend To Cause Havoc), a Zamrock band from 1970s Zambia, where bands emulated the psychedelic sounds they heard from the US. The band’s (and the country’s) rough history left it with just one surviving member, 72-year-old Emmanuel “Jagari” Chanda, whose day job is gemstone miner. They are releasing a new album this week and are on a long US tour.

HIStalk turns 20 years old this week. I was bored over the Memorial Day weekend of 2003 and decided to jot down a few temporary thoughts about my health system IT job to help me keep things straight in my head. I didn’t expect or necessarily even want anyone to read it, and given my limited attention span and lack of interest in hobbies in general, I definitely didn’t plan to still be doing it 20 years later.

Webinars

None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.

Acquisitions, Funding, Business, and Stock

BJC HealthCare and Saint Luke’s Health System will merge to form a 28-hospital system with $10 billion in annual revenue.

Sales

• Ardent Health Services will deploy Loyal’s consumer engagement solutions.

People

Leadership Development Worldwide hires Shane Danaher, MBA (Divurgent) as COO.

Government and Politics

President Biden will reportedly choose Aledade executive and former North Carolina health secretary Mandy Cohen, MD, MPH as director of the CDC.

Other

UnitedHealth cancels its plan to require prior authorizations for colonoscopies, instead requiring physicians to submit patient information before performing a procedure to quality for a “gold card” expedited approval process that will be rolled out next year. Three provider groups say the new plan is just as laborious for practices as the PA process would have been.

A New York Times report says that doctors at the “wealth nonprofit” Allina Health System aren’t allowed to see patients who have unpaid medical bills. Reporters found a document in which employees were told to cancel appointments for patients who own $4,500 or more and to lock their EHR records so that appointments can’t be scheduled. Doctors say they are used to seeing EHR messages that a patient “will no longer be eligible to receive care because of unpaid medical balances.” Patients with unpaid bills can continue to be seen only if they obtain a loan from the hospital or file bankruptcy.

Sponsor Updates

• Careport Health staff volunteer with Cradles to Crayon, which provides children with the resources they need to thrive.
• University Health (TX) upgrades to Agfa Healthcare’s Enterprise Imaging 8.2, and adds Enterprise Imaging for Cardiology.
• Arrive Health publishes a new whitepaper, “The Terrifying Truth About America’s Healthcare Affordability Crisis.”
• Baker Tilly releases a new Healthy Outcomes Podcast, “Key insights for not-for-profit leaders in behavioral health.”
• ChartSpan partners with HAPevolve, a subsidiary of The Hospital and Healthsystem Association of Pennsylvania, to offer preventative care programs to Medicare patients.
• CHIME launches its Trailblazers Podcast, with the first episode focused on “Developing the HIT Leaders of Tomorrow.”
• Divurgent releases a new episode of The Vurge Podcast, “Tips for Managing Cyber Risks in Healthcare.”
• Azara Healthcare releases a resource and strategy guide titled “Leveraging Social Drivers of Health Data to Promote Health Equity Advancement.”
• Ellkay will exhibit at AHIP June 13-15 in Portland, OR.
• The VA’s Veterans Data Integration and Federation Enterprise Platform, which supports longitudinal patient records using InterSystems HealthShare, wins a 2023 Forum Innovation Award.
• Rhapsody publishes a new case study, “From data ingestion to production in less than 30 days: How Zephyr AI uses Rhapsody Semantic to create precise AI models at scale.”

Blog Posts

• 4 Business Insights to Help Your Healthcare Practice Grow in 2023 (AdvancedMD)
• Robotic Process Automation Nets Multiple Benefits for Tidewater Physicians Multispecialty Group (AGS Health)
• How Southwestern Health Resources uses quality data to transform care delivery (Arcadia)
• Helping Intensive Care Teams at Great Ormond Street Hospital to Navigate Data (Aridhia)
• 4 Steps to Streamline Your Revenue Cycle Tech Stack (Availity)
• Building Board Engagement to Mature Your ECRM Program (Clearwater)
• Consensus Cares: The DEI Council and the #DoGoodChallenge (Consensus Cloud Solutions)
• Building the Future of Data: Dimensional Insight’s Mentorship Initiative (Dimensional Insight)
• Empowering Healthcare Excellence: Vital Role of Clinical Asset Management (Optimum Healthcare IT)
• How to build organizational resilience: six proven steps (Everbridge)
• 3 Elements for Successful Workforce Management: Embracing a New Way of Thinking in Health Delivery (Impact Advisors)
• Figure it out or fail: Extracting the value from unstructured data (Intelligent Medical Objects)
• 4 Strategies to Help a Multigenerational Workforce Thrive (Keysight)
• Guide Patients to the Right Care With Your Find Care Experience (Kyruus)
• 3 Tech Considerations for Painless Anesthesia (Medhost)

Contacts

Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates.
Send news or rumors.
Contact us.

EPtalk by Dr. Jayne 6/1/23

Midwestern health systems BJC Healthcare and Saint Luke’s (Kansas City) have announced plans to join through a $10 billion merger. They have been previously connected through participation in the BJC Collaborative, which Saint Luke’s joined in 2012 as the organizations sought to share resources and cut costs.

Announcements from the organizations note plans to operate under their existing brands and operate from headquarters in both St. Louis and Kansas City. Detailed plans for the merger are slated to unfold through the rest of the year, with a goal of closing the deal by the end of the year. I reached out to some Midwestern friends who know both organizations well and it sounds like there may be some significant cultural differences that come into play. It should be an interesting one to watch.

I receive dozens of cold call emails every day despite my best efforts to filter them into junk mail or spam folders. My favorite of the week was one that gave three different stylistic treatments to the healthcare entitlement program for seniors: MediCare, MediCARE, and ultimately Medicare. Maybe their marketing team will eventually create a style guide so that they can remain consistent, but since I made use of the block sender functionality, I hopefully won’t be seeing it again.

I don’t practice as often as I used to, but when I do, there’s always a patient who asks about something they saw on the internet and how it might relate to their reason for seeking medical care. A recent Forbes article discusses data that more than a third of members of Generation Z trust TikTok more than doctors. It’s not the only player in the equation – another 44% of adults surveyed visit YouTube before contacting their physician. One in five respondents trust health influencers more than they trust medical professionals, citing access, cost, and avoiding judgment from medical professionals.

The article goes on to emphasize the need for care providers to meet patients where they are. I agree with that approach. I’ve not seen many mainstream health organizations fine tuning their social media sites to go after that demographic, but I’ll keep an eye out. There is plenty of medical misinformation out there that needs to be countered, but competing against influencers might be an uphill battle.

For health systems and other organizations that are trying to build their brands (and often renaming themselves in the process), they might want to target older demographics. A recent article notes that members of Generation X and Baby Boomers are twice as likely to trust brands than members of Generation Z. Topping that brand list and possibly providing inspiration for marketers: Band-Aid, UPS, Amazon, Lysol, and Kleenex followed by Cheerios, Visa, Dove, The Weather Channel, and FedEx. The survey noted that Generation Z doesn’t trust many brands to do the right thing – non-profit brands were the only category to which it responded well. I tried to poll a couple of the members of Generation Z about the topic, but hit a dead end because they were heads-down on their phones.

I have a visit later this week with a new physician who is part of the medical group where I’m already established. I was relieved to receive an electronic check-in notice through the patient portal. My previous physician left the practice for health reasons, but I’ve been a patient in both the practice and its database since 2019 (and in its precursor, which was converted, for a decade prior) so it should have been smooth sailing.

I completed the electronic check-in and was met with a notice that “you might be asked to complete additional paperwork in the office,” which jogged my memory that indeed they had mailed me a packet six months prior. I found it in the file sorter on my desk and was dismayed to find that it contained four pages of materials that are redundant to my existing chart, including the pharmacy information and medication list that I just confirmed during the electronic check-in process. When I scheduled the appointment, I made it clear that I was transferring from her former partner. Since I’ve been seen within the past three years by a physician of the same subspecialty who bills under the same tax ID, I’m technically an established patient even though I’m new to her. I assume they send the “new patient” paperwork to everyone, but it’s still disheartening.

No one wants to arrive at the office and be turned away because they don’t have the (totally unnecessary) paperwork, so here I sit filling out information when I’m 100% confident that it’s all in the chart already, because I’ve seen it in my past visit notes. The real kicker was when I arrived at page four and found the “physical examination do not write below this line” section, where presumably the physician (who has a multi-million-dollar EHR) will not be documenting my exam because her contract requires her to use said EHR if she wants to get her annual bonus. I helped institute those contracts in a past life, and according to my former colleagues, they are still in place, so that should make for a fun conversation when I get to my appointment. The photocopies themselves are no longer crisp and are marked by smears from repeated copying, which is just sad.

Getting to the end of the paperwork, I realized that it didn’t even ask for some of the key elements of my history that are important to the topic of the upcoming visit, as well as being critically important for a physician in that subspecialty regardless of whether they’re a topic of this specific visit or not. As a physician, I know this is a big deal, but many patients might not volunteer that information if the physician doesn’t specifically ask for it.

Based on the paperwork and the pre-visit experience, I’m not confident of what to expect from this visit. For an organization that is worried about patient experience and their patient satisfaction ratings, I’ll be sure to give appropriate feedback when the inevitable survey arrives in my inbox. If they’re interested in some management consulting and EHR optimization, I might just know someone.

What’s the most frustrating healthcare IT-related issue you encounter as a patient? Leave a comment or email me.

Email Dr. Jayne.

Morning Headlines 6/1/23

Hyro Raises $20M in Funding to Advance Responsible AI-Powered Communications for Enterprise

Hyro, which offers conversational AI-powered healthcare workflow and conversation solutions, raises $20 million in a Series B funding round.

Wellstar to open innovation center in Midtown Atlanta

Wellstar Health System will open an innovation center in Atlanta this fall to house its recently launched Catalyst venture firm.

Axuall Secures $20 Million Series B Capital Raise after Accelerated Market Growth and Healthcare Enterprise Adoption

Healthcare workforce software firm Axuall raises $20 million in a Series B funding round.

Strive Health Raises $166 Million in Series C Funding from NEA, CVS Health Ventures and Others

Kidney care company Strive Health raises $166 million in a Series C funding round, bringing its total raised to $386 million since launching five years ago.

Healthcare AI News 5/31/23

News

Microsoft adds intelligent meeting recap to Teams Premium, which generates meeting notes, a task list, and personalized timeline markers.

In Australia, five-hospital South Metropolitan Health Service orders doctors to stop using ChatGPT for work-related activity, citing confidentiality concerns. SMHS found that at least one doctor used ChatGPT to create a discharge summary, backtracking on an earlier statement in which it said that several doctors were creating notes in ChatGPT and then pasting them into the EHR.

Business

AI chipmaker Nvidia hits a market capitalization of $1 trillion following a strong quarterly report, joining nine companies that have reached that mark including Apple, Microsoft, Alphabet, Amazon, and Saudi Aramco. A $10,000 investment in the company five years ago would be worth nearly $60,000 today.

Hyro, which offers conversational AI-powered healthcare workflow and conversation solutions, raises $20 million in a Series B funding round.

In England, AI drug discovery company Benevolent AI, which went public last year in a SPAC merger, will cut half of its workforce and scale back its laboratory facilities. The company had hoped to license its AI-designed drug candidate for atopic dermatitis, but it failed to improve symptoms in early-stage clinical trials.

Research

Researchers use AI to design an antibiotic for treating hospital-acquired infections caused by the broadly resistant Acinetobacter baumannii bacteria. Researchers tested thousands of drugs for their ability to kill the bacteria or slow its spread, trained AI on the results, and then ran the resulting AI model against 6,700 other drugs to generate a 240-drug short list of candidates. The AI-chosen drug, abaucin, targets the bacteria specifically and therefore is less likely to cause drug resistance. Laboratory and clinical testing will take several years, with the first AI antibiotics expected to reach the market in 2030.

Opinion

Google Health debunks five myths about medical AI:

• The more data, the better. Data quality matters more and expert adjudication in touch cases helps improve labeling quality.
• AI experts are all you need. Building an AI system requires a multidisciplinary team.
• High performance provides clinical confidence. Real-world validation is needed to make sure the model generalizes to real-life patients.
• AI fits easily into workflows. AI should be designed around human users.
• Launch means success. AI systems must be monitored to detect potential issues when patient populations or environmental factors change.

Other

Nvidia profiles Nigeria-based physician, informaticist, and machine learning scientist Tobi Olatunji, MD, MS, who started Intron Health to transcribe physician dictation using AI with 92% accuracy across 200 African accents. The company was supported by Nvidia’s startup program. He earned a Georgia Tech computer science master’s and a UCSF master’s in medical informatics after he completed medical school in Nigeria.

Contacts

Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates.
Send news or rumors.
Contact us.

Readers Write: It’s Time for EHRs to Alleviate, Not Exacerbate, Clinician Burnout

It’s Time for EHRs to Alleviate, Not Exacerbate, Clinician Burnout
By Nancy Pratt, RN

Nancy Pratt, RN, MSN is senior vice president of clinical product development of CliniComp of San Diego, CA.

We all see the headlines – clinician burnout is taking an enormous toll. It is estimated that 47% of US healthcare workers may leave the profession by 2025. One of the most-cited sources contributing to burnout is electronic health records (EHRs), with nearly 60% of physicians in one poll suggesting that EHRs need a complete overhaul.

In my work with clinicians, their biggest frustration with EHRs is time. So much of their time is spent doing manual, EHR-related tasks, causing them to spend nearly twice as much time in the EHR as they do with patients. A poll by Stanford Medicine found that hospital-based physicians spent 25 of the 37 minutes on behalf of each patient in the EHR.

It doesn’t need to be this way. By collaborating with physicians, nurses, pharmacists, and other clinicians, EHRs can become a trusted part of care delivery processes, freeing clinicians to focus on their patients and recapture the most satisfying qualities of their professions. With a focus on human-centered design, EHRs can help reduce clinician burnout in three ways:

Capture documentation naturally as part of the workflow

Given the frustration with documentation, EHRs need to move beyond focusing on transactions to creating efficient, supportive workflows for all clinicians. One process that is often frustrating and burdensome is medication reconciliation. A well-designed EHR workflow can present this critical step at a natural point in the care process. By presenting a side-by-side comparison of what’s current and what’s needed for the patient, the process becomes a fast and accurate way for physicians to manage medications.

Bring device data into the workflow automatically

Using standard integration protocols, such as APIs, EHRs can automatically integrate data from bedside monitoring and other devices into user-focused workflows. Instead of requiring nurses to enter data manually, the EHR should be fully integrated, perform calculations automatically, and present in a user-friendly way. In addition to reducing errors and manual tasks, nurses working with monitored patients report saving as much as 15 to 20 minutes per patient per shift with this level of integration.

Remove downtime as a barrier

It’s surprising that system maintenance and upgrades still require planned downtime for many EHRs, slowing down care delivery with manual, paper-based workarounds. Unplanned downtime, experienced by 96% of organizations according to one study, can be even more onerous. EHRs should be built upon modern foundational architectures that don’t require scheduled downtime and have built-in redundancy to prevent unplanned downtime. Preventing downtime alleviates a common source of stress for clinicians when care delivery is hampered by lack of access to patient information.

It’s time for the industry to listen when so many clinicians say EHRs need to be revamped. Using flexible, well architected technologies and collaborating with clinicians, EHRs can enhance rather than hinder care delivery. At last, EHRs can support clinician wellness by enabling them to provide the highest quality patient care, bringing the joy of helping patients back into their day-to-day work.

Readers Write: Ineffective TCM Programs are Keeping Patients in the Hospital

Ineffective TCM Programs are Keeping Patients in the Hospital
By Briana Rodriguez, RN

Briana Rodriguez, RN is director of clinical services of LIghtbeam Health Solutions of Irving, TX.

The healthcare industry is facing an uphill battle, as staffing shortages persist while the demand for clinical professionals continues to increase. With fewer skilled workers to perform necessary care delivery tasks, healthcare organizations must be thoughtful with their clinical resources. One area that is causing clinical and financial strain on organizations due to limited resources is transitional care management (TCM) programs.

According to the Centers for Medicare and Medicaid Services (CMS), nearly 20% of all Medicare patients discharged from a hospital will be readmitted within 30 days, driving over $26 billion in additional costs each year. There are a multitude of reasons, both preventable and unpreventable, that a patient may be readmitted to the hospital. Chief among them is being enrolled into an inefficient, uncoordinated transitional care management program that fails to maintain engagement and make timely contact.

Understanding how and why your organization’s TCM program is insufficient is the first step to make meaningful process changes that demonstrate success in reducing readmission rates, lowering healthcare costs, and improving patient outcomes.

The goal of any TCM program is to perform timely and thorough patient follow-ups within crucial post-discharge windows to ensure quality of care and reduce patient complications. A standard transitional care management program comprises three main elements:

• Interactive contact. Initial patient outreach is performed within 48 hours post-discharge by a supervised staff member with the skills to address the patient’s status.
• Coordinating care behind the scenes. Care teams provide non-face-to-face services, such as clinical education, addressing follow-up needs, provider communication, referrals, and scheduling assistance.
• Follow-up visit. A face-to-face visit is scheduled with a provider within 7-14 days post-discharge, depending on medical severity

However, staffing shortages and insufficient resources can make even the three basic components of a TCM program difficult to accomplish. What sets a successful, effective TCM program apart is the ability to provide regular outreach, keep patients engaged, and identify issues before they require inpatient stay. These processes begin long before a patient is discharged from a hospital.

In today’s digital age, healthcare organizations have options that have only emerged within the last decade. Solutions like remote patient monitoring and telehealth garnered attention following the social distancing periods that took place during the COVID-19 pandemic. Ever since, the healthcare industry at large has seen how beneficial similar strategies can be when it comes to reaching more vulnerable patients. When given the right capabilities, clinical professionals can work at the top of their license and provide the highest quality care to patients, wherever they are.

Leveraging these tools and resources, transitional care management teams can automate repetitive tasks, streamline workflows, and reach more patients by engaging them at home. Some key aspects that can be further built into an efficient TCM program to increase patient engagement and reduce costs include:

• Coordinating with hospitals to notify care teams of discharges.
• Making the initial patient contact within 48 hours of discharge.
• Reviewing the discharge process and medication schedule with the patient.
• Scheduling a face-to-face visit within 1-2 weeks.
• Confirming all patient appointments to ensure continuity of care.
• Performing follow-up calls.
• Providing support for barriers to care by leveraging local, available resources.
• Supporting patients in the 30-day period post-discharge.
• Documenting all services throughout the patient’s TCM journey.

There are several reasons that transitional care management programs can fail. If providers are not able to identify high-risk patients with co-morbidities before they are discharged, these patients have a higher chance of developing complications that could result in further inpatient stay. TCM programs can also fail if clinical staff is not able to contact patients during crucial follow-up windows, especially the initial 48 hours post-discharge.

Noticing an increase in readmissions, post-discharge complications, and delays in interactive contact with patients may indicate that care teams are not reaching patients in a timely manner. If you notice these issues, it is important to find out the cause of the gap and to pinpoint the right solution, workflow, or strategy to close it.

Ineffective TCM programs cause patients to return to the hospital and drive avoidable costs into the billions. The first step to improve an inefficient TCM program is to arm healthcare staff with the tools and resources they need to reach out to patients, make an impact, and maintain engagement throughout their care journey. This can include investing in technology to streamline communication, leveraging analytics to identify high-risk patients, and enabling staff to work at the top of their license.

With the technology of today, healthcare organizations have access to solutions that weren’t available ten years ago. Outsourcing care coordinators extends the capabilities of care teams, while adopting tools like remote patient monitoring expands their reach.

Even when a TCM program possesses all these elements, it’s essential to assess their performance regularly, make process updates, and assess patient feedback and satisfaction. This can be done by tracking certain metrics, such as readmission rates, acute events, skilled nursing facility data, and more.

By understanding the elements of an efficient TCM program, identifying where gaps exist, and making necessary process changes, healthcare organizations can reduce readmissions, lower costs, and improve outcomes.

Readers Write: Return Data to Hospitals and Researchers for Patients

Return Data to Hospitals and Researchers for Patients
By Amanda Borens

Amanda Borens, MS is chief data officer of Aridhia Informatics of Glasgow, Scotland.

As a data scientist formerly working in global health, I have firsthand knowledge of how challenging it is to recruit patients for clinical trials and observational studies, and how transformational a culture of open collaboration and data sharing can be. I have cancer diagnoses in my history, accompanied by so much fatigue from being extensively examined and poked and prodded, but I’m also a scientist in the health technology industry with appreciation for the way that humans advance medical knowledge.

I have eagerly signed up for clinical studies and taken on extra burdens, such as blood draws and filling out forms, to help researchers as well as those in training. Even when that means being examined by a nervous medical student and then repeating myself to a physician.

Then why did I balk when my health system asked me to participate by openly sharing my EHR data for research?

I collaborated with renowned medical ethicists who taught me to embrace the idea that a patient owns their data. That idea was cemented in me when I became a participant in various studies that led to peer-reviewed publication. I had been working in my non-profit world to aggregate data from multiple sources to learn more about rare diseases. I became frustrated that companies would keep shareable data confidential to avoid letting competition find insights that they had missed. I was shocked to learn that many scientists in academic settings hoard data in the same way, fearing that someone might find something they missed in the data and publish it.

In all cases, the stewards of the data seemed to forget that patients sacrificed time, blood, energy, and more to help all humanity, not the personal careers of their physicians or the bottom lines of sponsoring drug companies. That intention matters, and is worth honoring.

This brings me to my personal hesitation when asked to share my EHR data for research. I’ve been to data science conferences where abstracts were presented by employees of this health system. I know the kinds of questions my data would answer. Those questions tend to be focused on how to keep hospitals profitable. While I know that this is a valid concern for administrators in hospitals, I want my personal health information to be used to help other patients like me have a better experience, and I don’t much care what that would cost.

I want to be a piece of data that led to a cure for this, a better treatment for that, an earlier detection of my cancer for others, a less-invasive surveillance journey, or a better experience with caregivers. I want to share my EHR data with my incredible team of oncologists and researchers so they can learn. I want my data to be compiled with that of others so that they can learn more and faster.

However, I know that my doctor won’t be able to access aggregated data that way in my clinic. I know he had to use an Excel spreadsheet to keep track of data in the landmark oncology study he recruited me to join.

Conversely, aggregated claims databases can be used to answer questions about health economics. Some cost money to access, and sometimes researchers can access those external data sources with cost waived. Beyond payer-aggregated data sets, Epic has a respectable database and Cerner does too, both of which are valuable for review of de-identified patient data. But what about empowering researchers and clinicians in their unique patient communities? Shouldn’t we be honoring the patients’ commitment to advancing medical science by empowering clinicians and researchers to more easily use more data in their own hospitals? What does that look like?

The US government mandates that healthcare IT developers like Cerner and Epic provide their customer base with a certified FHIR API to support patient access to health information by December 31, 2022 as part of the 21st Century Cures Act Final Rule. This mandate requires that certified health IT developers publish “service base URLs” or “endpoints” for all customers in a machine-readable format at no charge. I hope this will be an inflection point.

Additionally, patient-focused drug development mandates are demanding greater listening to the voice of the patient, and that means tighter connection between pharmaceutical companies and real-world data from clinical settings. Hospitals with an investment in a next-generation research environment will be able to procure industry funding to collaborate in a secure, audited cloud environment that is dynamic and connected to anonymized EHR data alongside observational or interventional study data. A nice side benefit? That same (already funded) environment may provide a subset of hospital researchers with identifiable patient data that can be used to implement research findings into clinical practice in a timelier fashion.

As a patient, I’d donate my data to that hospital in a heartbeat.

Imagine a world where patients and clinicians collaborate to improve healthcare, then take a look at what Great Ormond Street Hospital for Children is doing with their research environment for a wonderful example. Pediatricians there have been studying precision dosing regimens and collaborating across continents to share dosing models where pediatric populations were excluded from clinical trials. This isn’t happening in one hospital’s data warehouse, and it isn’t happening with access to a single EHR or aggregated repository. It’s possible because of connecting different types of data of across borders and across time, but all in a next-generation research environment that connects people.

The transformative possibilities do not end there. What if a research hospital was able to collect clinical data from EHR and combine it with multiomics data from an academic research university where bioinformatics pipelines are optimized to provide a list of variants for each patient? How might they learn about patient subpopulations and disease progression or predict responses to interventions? That sort of collaboration should be the norm, but it requires us to think bigger than one data warehouse, one data type, or one organization at a time. Let’s make it happen.

HIStalk’s Guide to MUSE Inspire 2023

Access EForms

Booth #413
Contact: Landon Light, national sales representative for Meditech accounts
landon.light@accesseforms.com
972.897.2877

Access is the preferred ESignature partner for Meditech hospitals, and for good reason. Our relationship with Meditech goes beyond just being a “partner” – it’s a deep integration that enables our solutions to seamlessly integrate with Meditech’s ecosystem. By expanding Meditech’s capabilities, we empower hospitals to provide patients with convenient ESignature solutions on their own devices anywhere, anytime. With Access, Meditech hospitals can streamline their workflows, reduce errors, and improve the overall patient experience. Join the many Meditech hospitals that have already chosen Access as their trusted ESignature partner and revolutionized their patient ESignature solutions. And, discover Focus by Access, the solution that simplifies patient intake by extending ESignature and intake capabilities directly to your patients’ devices, providing the experience and convenience they expect in today’s modern world.

CereCore

Booth #418
Contact: Jillian Whitefield, business development manager
Jillian.Whitefield@CereCore.net
248.891.5557

Your top priorities at MUSE are ours, too. Visit to see all the ways you can connect with CereCore about providing an EHR that best supports patient care, including educational sessions and career opportunities. Our team is ready to connect. Making the move to Meditech Expanse? Let’s talk about your journey to one EHR, navigating a multi-EHR health system, and more. Optimizing Meditech one of your priorities? Help us understand your goals, because we have helped health systems across the nation 0improve efficiency from clinical operations to revenue cycle. Looking for secure Meditech hosting and backup solutions? Sometimes this needs to be your first step. Let us help you determine the most cost-effective solution by comparing your options. Wanting to grow in your career? Career-changing, industry-shaping job opportunities are on our horizon, and possibly yours. Talk with us about your career plans.

CloudWave

Booth #512
Contact: Christine Mellyn, VP of marketing
cmellyn@gocloudwave.com
781.636.8169

Visit us in booth #512 to learn how CloudWave can help with your cloud strategy or how to advance your cybersecurity readiness. The company will also be sponsoring the Charging Station. Also at the event, members of CloudWave’s team will be presenting the following educational and showcase sessions:  

• “Best Practices for Securing Healthcare IT Across Public, Private, and Cloud Edge Environments.” Thursday, June 8 3:10 p.m. MT. Moderated by Tim Quigley, chief client officer, CloudWave. Presenters include Matt Donahue, chief technology officer, CloudWave; John Gomez, chief security and engineering officer, CloudWave; and Eric Gasser, RN, CHCIO, vice president and CIO, information systems, Wooster Community Hospital Health System.
• “Take Advantage of Emerging Healthcare Cybersecurity Trends to Advance Your Security Strategy.” Saturday, June 10, 8:30 a.m. MT. Presented by John Gomez.
• “Product Showcase: Cybersecurity-as-a-Service – Advance Your Cybersecurity Program and Remove the Burden from Your IT Team.” Thursday, June 8, 1:30 p.m. MT. Presented by John Gomez.

Elsevier

Booth # 609
Contact: Clint Jones, senior director of partnerships
w.jones.2@elsevier.com
816.262.6634

As a global leader in information and analytics, Elsevier helps physician and nurse professionals advance science, reduce care variability, engage patients, and improve health outcomes for the benefit of society. For over 140 years, healthcare professionals have trusted our content to support education, training, development, and decisions about patient care. We offer solutions and services that help customers utilize and integrate content to improve practice, reduce care variability, engage patients, and promote a culture of quality, safety, and satisfaction.   

We invite MUSE attendees to stop by our booth #609 to discuss how Elsevier’s advanced clinical knowledge solution, ClinicalKey, streamlines access to consistent, evidence-based information to help clinicians, as well as hear your thoughts and input on future development, your needs, skills learning, and integration. Let’s talk about where you want to expand your own Meditech relations and where we can offer help. Elsevier is participating in the MUSEO prize drawings, so bring your game card with you when you come to visit us, and we’ll give you a MUSEO sticker to help you become eligible to win great prizes!

Fortified Health Security

Booth 218

Contact: Rob Pullins, growth manager
rpullins@fortifiedhealthsecurity.com
615.600.4002

Fortified Health Security provides a wide variety of purpose-built services to help healthcare organizations evaluate their unique risk appetite, strengthen their cybersecurity posture, and improve operations throughout their security journey. The company is committed to creating a stronger healthcare landscape that benefits more clients, protects more patient data, and reduces more risk.   

Fortified activities and team member talks: 

• “Incident Response Program Maturity: How to Prepare for the Worst Day Ever,” Thursday, June 8 at 2:20 pm with Russell Teague, VP, advisory services and threat operations.
• Networking event and cocktail hour at the Après Ski section of the Pinyons Lobby Bar, Thursday, June 8, from 6-9 pm.   
• Stop by our booth to play MUSEO.

Tegria

Booth #409
Contact: Mark Valutkevich, senior account executive
mark.valutkevich@tegria.com

Tegria is a full service, READY-certified consulting and technology services firm. We offer comprehensive end-to-end solutions including advisory, consulting, and managed services to help clients maximize technology, transform operations, improve financials, and optimize care. Please stop by Booth #409 to say hello and speak with our Meditech experts.  

Tegria is hosting a subterranean happy hour at the Rockies Grotto in the Grand Lodge on Wednesday, June 7 from 4:30 to 7:00 p.m. MT. The event will feature an open bar and a variety of light bites. Prepare to unwind and connect with fellow MUSE attendees in this unique space. Tegria team members will be mingling and are ready to chat all things Meditech, including how you can best navigate the road to Expanse. We hope to see you there! RSVP here.

Tegria team members will be participating in two educational sessions:   

• “Hardware Planning – Do’s and Don’ts When Moving to Expanse.” Thursday, June 8, 1:30 – 2:10 p.m. MT. Presenters: Priscilla Sandberg (Pure Storage), Nassim Abouzeid (Meditech), and Frank Tollefson (Tegria). Room: Red Rock 8. If you are planning on going to Expanse from Magic, Client/Server, or 6.x, there are few challenges you need to understand about the new infrastructure you will be running. Join us to discuss the major differences in platform infrastructure and some of the adjustments that customers can anticipate making when moving to Expanse. We will also be discussing the best practices behind the infrastructure design, data protection, and ongoing system support.   
• “A Study in Moving to Expanse – Pre, Intra, and Post-LIVE.” Friday, June 9, 1:20 – 2:05 p.m. MT. Presenters: Mike Bartman (Tegria), Mark Valutkevich (Tegria), Todd Prellberg (RML). Room: Red Rock 8. This session aims to provide attendees with a comprehensive understanding of the key principles and best practices involved in successfully implementing Meditech Expanse in a hospital setting. By the end of the session, attendees will be able to apply these principles and practices to their own healthcare organizations, identifying opportunities for improving their current EMR systems or adopting new ones.

Morning Headlines 5/31/23

Carrum Health Raises $45M in Series B Funding

Carrum Health, whose platform helps employers manage employee healthcare costs, raises $45 million in a Series B funding round.

Anatomy IT Acquires Iris Solutions to Expand Presence in Ambulatory Healthcare

Health IT and cybersecurity solutions vendor Anatomy IT acquires dental and medical software company Iris Solutions.

Florida Bans Offshoring of Certain Patient Information

A new Florida law prohibits the state’s providers from storing EHR data outside the US, its territories, or Canada, including those patient records that are hosted in the cloud or by a third party.

News 5/31/23

Top News

Carrum Health, whose platform helps employers manage employee healthcare costs, raises $45 million in a Series B funding round.

HIStalk Announcements and Requests

Poll respondents aren’t convinced that the VA will finish its Oracle Cerner implementation.

New poll to your right or here: Did you sell $10,000 or more in products or services from your own company in the past year?

Listening: new from Yes, a 55-year-old band with no original members left whose recent live shows have been innumerable but awful. I walked out on them a couple of years ago because they sounded like a bad tribute band (which they kind of are) in playing their old album cuts slower, lower, and lazier in a seemingly desperate money grab, but this new music is actually pretty good even if a bit wimpy compared to their sweeping epics of yesteryear. I still prefer old concert videos, such as original singer Jon Anderson doing “Awaken” with Iceland-based rock band Todmobile (gets me every time) and the the full band’s symphonic live version of “Soon.” For me, Yes scores high in the all-important “what music would you want played at your funeral” test. It will outlive the many band members who wrote, recorded, and performed it over decades.

Webinars

None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.

Acquisitions, Funding, Business, and Stock

Health IT and cybersecurity solutions vendor Anatomy IT acquires dental software company Iris Solutions.

Dock Health, which specializes in automated healthcare task management, raises $5 million in funding. The company was created from Boston Children’s Hospital’s innovation department in 2020.

Weight loss app Noom launches a telemedicine service to offer consumers access to prescription weight-loss medications like Ozempic and Wegovy.

A new KLAS report looks at remote patient monitoring technology vendors.

Sales

• Niagra Health in Ontario will implement Sectra One enterprise imaging.
• Corterra Healthcare (KS) chooses Medsphere’s Wellsoft EHR and RCM Cloud for a new behavioral health hospital.

People

Rebecca Manne, RN (Optimum Healthcare IT) joins Continuum Health IT as EVP of EHR Implementation.

Announcements and Implementations

Premier launches SmartPO, digital supply chain procurement and inventory management technology that will enable continuum of care providers to better identify cost savings and use staff resources more effectively.

A University of Michigan national poll of people aged 50-80 finds that 78% have a patient portal (half of those have more than one), 55% used it in the past month, half provided access to family members, and most were comfortable logging in and navigating it. People preferred the portal over the telephone for getting test results, updating personal information, getting medical records copies, and requesting refills, but they liked the telephone better for reporting symptoms, scheduling appointments, and requesting referrals.

The former Cerner Continuous Campus is under purchase contract to be turned into apartments and commercial space, although no companies have expressed interest in the campus’s 660,000 square feet of vacant offices.

A small study finds that smart watches and wristbands do a good job of correctly detecting atrial fibrillation even though they don’t have access to outside algorithms.

Government and Politics

VA Secretary Denis McDonough promises to look into reports that the VA medical center in Spokane will be forced to cut staff due to a budget shortfall caused by the troubled EHR Modernization program. He reiterated that he stands by statements made by VA Under Secretary for Health Shereef Elnahal that budget concerns related to the Oracle Cerner system will not result in layoffs.

Former Theranos CEO Elizabeth Holmes reports to a Texas prison after her losing her bid to remain free while appealing her conviction for investor fraud, which led to an 11-year sentence.

Privacy and Security

A new Florida law prohibits the state’s providers from storing EHR data outside the US, its territories, or Canada, including those patient records that are hosted in the cloud or by a third party.

Other

The bankrupt, non-profit Idaho Health Data Exchange replaces its executive director. The organization launched in 2009 using federal grants and ongoing funds from the HITECH act that ran out in 2021.

Mayo Clinic and University of California, San Francisco researchers determine that pairing AI imaging and volumetric breast density algorithms can help in predicting long-term risk of breast cancer, particularly invasive diseases. Their study used Volpara Health’s TruDensity algorithm and ScreenPoint Medical’s Transpara image-based risk tool.

In perhaps the first incident of AI leading to professional embarrassment or worse, defense attorneys ask to have a man’s personal injury lawsuit dismissed after noticing that most of the legal citations it included were not real. The plaintiff’s lawyer, who has practiced for 30 years, admitted that he had used ChatGPT for the first time and was not aware that it could generate false information. He even asked ChatGPT if the citations were real and was assured incorrectly that the cases “are real and can be found in reputable legal databases.”

Sponsor Updates

• Wolters Kluwer Health wins the NorthFace ScoreBoard Service Award for the twelfth consecutive year for superior customer service.
• OptimizeRx CEO Will Febbo provides a mid-year strategic update.
• Nordic Consulting names Samara Lattimer (Akkodis) a new client partner in the UK and Ireland.
• Aridhia Informatics Chief Data Officer Amanda Borens, MS is featured in an “Engineering Field of Dreams” podcast titled “Spelunking Adventures in Data.”
• Spok will join the broad-market Russell 3000 Index on June 26.
• West Monroe releases a new podcast, “Why All Companies Should ‘Shift Left’.”

Blog Posts

• COVID-19 Interoperability Alliance Retrospective (Clinical Architecture)
• AONL 2023: Drawing inspiration to fuel the future of nursing (Meditech)
• Amplifying Success: How Integrated Behavioral Health Programs Can Achieve the Quintuple Aim (NeuroFlow)
• How Can Healthcare Providers Improve Their Data Integrity to Achieve Better Insights? (NTT Data)
• 360Dx: Legislation Would Provide Medicare Coverage for Pharmacy-Based Testing (OmniSys)
• Safeguarding security and privacy in the age of generative AI (Orbita)
• Healthcare Coding Series: LOINC Codes (Pivot Point Consulting)
• Partnering with a Revenue Cycle Management Company to Tackle Hospitalist Billing (PMD)
• Young Upstart to Four-Star Admiral: The Chance Events of Dr. Brett Giroir (Surescripts)
• Designing a Comprehensive Caregiver Support Strategy: Empowering the Unsung Heroes of Healthcare (Trualta)
• 4 Signs Your PT Patient is About to Drop Out (WebPT)
• Jump to the Front of the Line for National Network Access (Zen Healthcare IT)
• What is the Focus of a Care Plan? (Zynx Health)
• Healthcare CIOs Talk: How to Navigate AI, Analytics, and Automation (CereCore)

Contacts

Mr. H, Lorre, Jenn, Dr. Jayne.
Get HIStalk updates.
Send news or rumors.
Contact us.

Morning Headlines 5/29/23

Walgreens’ Profit Drive: Employee Cuts Amid Transformation to Consumer Healthcare

Walgreens will lay off 504 mostly corporate employees as the retail pharmacy shifts its focus to more patient care.

Health startup Noom is now adding Ozempic and other weight loss injectables to its offerings, says ‘outcomes are so much better’

Weight loss app Noom launches a telemedicine service to offer consumers access to prescription weight-loss medications like Ozempic and Wegovy.

$1 million donation will expand Montana Pediatrics’ after-hours telemedicine program

Montana Pediatrics will use a $1 million donation to expand its after-hours pediatric telemedicine program.