Release-of-information vendor Verisma acquires Olah Healthcare Technology, which offers enterprise archiving for legacy data.
Synapticure, a virtual provider of care for neurodegenerative disease patients, raises $25 million in Series A funding.
Care collaboration and communication software company TigerConnect acquires Twiage, a New York City-based business that coordinates communication between EMS and hospital emergency departments.
Microsoft enhances Microsoft 365 Copilot with task automation, new agents for Teams meetings and employee self-service, and a Copilot Control System for IT management.
Samsung rolls out One UI 6 Watch features to older models, which adds AI-powered tools such as health recommendations, sleep analysis, and sleep apnea detection.
Vanderbilt University Medical Center’s Department of Biomedical Informatics and InterSystems will work together on biomedical informatics and AI research. VUMC-DBMI will develop FHIR and interoperability training coursework that includes hands-on labs that will use InterSystems products.
BrightHeart earns FDA 510 (k) clearance for its AI-powered analysis of fetal heart ultrasounds.
Washington University School of Medicine and BJC Health System launch the Center for Health AI, which will focus on using AI to personalize patient care.
The National Institutes of Health develops an AI algorithm called TrialGPT that matches patients to clinical trials for which they are eligible.
Stepful – whose AI platform delivers training to working adults for medical jobs such as medical assistant, pharmacy technician, and surgical technician – raises $32 million in a Series B funding round. The company expects to train 30,000 students this year in programs that can be completed in as little as four months for $2,500. It matches its students to one of its 8,000 partner clinics and hospitals for hands-on training.
Cedars-Sinai investigators develop an AI-powered process to automate the classification of patients by the severity of their cancer, which could help get them into clinical trials faster.
The New York Times runs an article titled “Elon Musk Asked People to Upload Their Health Data. X Users Obliged.” Experts warn that posting images to any AI tool is not protected by HIPAA, also noting that X’s terms of service allows the company to share data with related companies.
Meanwhile, Elon Musk responds to a small study in which doctors who used ChatGPT to diagnose test patients using only their case histories performed only slightly better than those who didn’t use it, but ChatGPT by itself outperformed the doctors. Experts say that nobody really knows how doctors think, especially when they use their personal experience or intuition to diagnose patients.
A user of Google’s Gemini AI chatbot posts screenshots a session where it went off the rail when asked a question about households.
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HHS OIG rates HHS’s information security program as “not effective” in its annual review, the same rating it gave HHS last year.
Citizen Health formally debuts with $14.5 million in seed funding to offer patients health data technology tailored to those suffering from rare diseases.
ThoroughCare Secures $5 Million in Series A Funding from Empactful Capital
Care coordination software vendor ThoroughCare raises $5 million in Series A funding.
Sanford Health Unveils Physical Hub for Virtual Care
Sanford Health (SD) opens its new Virtual Care Center to offer areas for provider education and training, innovation, and patient and family experience simulations.
SIS Expands Capabilities with Strategic Acquisition of Surgical Notes
Surgical Information Systems acquires Surgical Notes, which offers billing, coding, and transcription services to ambulatory surgery centers.
HHS OIG rates HHS’s information security program as “not effective” in its annual review, the same rating it gave HHS last year.
OIG made six recommendations to HHS:
I applied several sources of matching, including dollar-for-dollar money provided by my Anonymous Vendor Executive, to the annual donation of reader Mark to fully fund these Donors Choose teacher grant requests. I was reading today that teachers, who aren’t necessarily richly compensated in the first place, spend an average of nearly $1,000 of their own money each year to buy supplies and resources for their students, so the funded projects below are kind of a big deal:
None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.
Care coordination software vendor ThoroughCare raises $5 million in Series A funding.
John Supra, MS (UpStream) joins Cone Health (NC) as chief digital health and analytics officer.
Guidehouse names Mark Korth. MHA, MBA (Intermountain Healthcare) and Angela Hunt, RN, MBA (Vizient) partners in its health segment.
Virtual second opinion provider The Clinic by Cleveland Clinic appoints David Peter, MD, MBA – who was interim president, VP, and chief medical officer of Cleveland Clinic Indian River Hospital – to chief medical officer.
Fairfax Radiology Centers promotes Terry Johnson, MA, MBA to CIO.
Memorial Hermann Health System promotes Oliver Galicki, MHSA to VP of clinical applications.
Matt Ripkey (Redox) joins Blockit as VP of sales and marketing.
Episode Solutions promotes Kyle Cooksey to president and CEO.
Emory Healthcare (GA) will launch a population health collaborative across its primary care network using technology and value-based managed care services from Guidehealth.
Arcadia announces GA of Vista Push automated performance analytics and Enhanced Benchmarks, which incorporate recently acquired CareJourney’s market intelligence and analytics.
EHR vendor Canvas Medical announces Anova, an EHR for longevity medicine.
The Digital Medicine Society launches its International Regulatory Pathways project to help digital health technology developers understand country-specific regulatory insights to get products to market faster.
Smart ring maker Oura will integrate glucose biosensing data from Dexcom, which will invest $75 million in Oura’s Series D funding round. Oura says that 97% of its users are interested in the effect of food on their health.
In Scotland, Royal Aberdeen Children’s Hospital is piloting Kinetic-ID’s Bedside Intelligent Cabinet for patient self-administration of medications. The hospital will explore integration with its EHR to keep prescriptions current.
Sanford Health (SD) opens its new Virtual Care Center, which offers areas for provider education and training, innovation, and patient and family experience. Accelerator rooms are also available for digital health startups that want to partner with Sanford on scaling their products.
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Ahead of its launch in the US, Paris-based BrightHeart receives FDA clearance for its AI-powered fetal heart ultrasound assessment software.
Trust reverses £65m EPR procurement decision after court claim
Mersey and West Lancashire Teaching Hospitals NHS Trust decides not to implement an EHR developed by Altera Digital Health and Insight Direct due to ongoing legal wrangling it would likely face from disgruntled software competitor System C.
Emory Healthcare (GA) will launch new a population health program across its primary care network using technology and value-based managed care services from Guidehealth.
The practices in which I’ve spent the majority of my clinical time over the past few years don’t use AI-assisted or ambient transcription technologies. One uses human scribes, while the other leaves physicians to their own devices for finding ways to become more efficient with their documentation.
In the urgent care setting, my scribes have always been cross trained. They started out as patient care technicians or medical assistants, and if they had excellent performance and a desire to learn, they could request to enter the in-house scribe training program. During that multi-month period, they received additional training in medical terminology, clinical documentation, regulations and requirements, and understanding the physician thought process for history-taking, creating a differential diagnosis, and ultimately creating and documenting a care plan.
Many of our human scribes had the goal of attending medical school or PA school, so they had a strong drive to learn as much as possible while doing their job. As they learned our habits for seeing patients and describing our findings, they would sometimes prompt us for something that we might have forgotten to mention or might not have performed during the exam. Because of the level of cross training, they could also assist us with minor procedures during the visit rather than just standing there and waiting for us to describe some findings.
Towards the end of the visit, when the physician typically summarizes the findings for the patient and describes the plan of care, the scribes would review and clean up the notes so that they were ready for our signature as soon as the patient disposition was complete. I would often be able to sign my notes in real time, and even if I had to wait until the end of the day, it might take me less than a minute to review each note because of the diligence they used capturing the visit.
Human scribes are also helpful when conducting sensitive visits, which often happen in the urgent care environment as we discuss a patient’s sexual history or perform sensitive portions of the physical exam. In those situations, our scribes served as both chaperones and assistants, providing support to patients when needed and assisting with specimen collection – uncapping and capping jars and tubes, ensuring accurate labeling, etc. I’ve had scribes help patients take their shoes and socks off and assist them in getting on the exam table and returning to a chair. When contrasting a visit that uses a human scribe to one where the physician has to perform their own documentation, there’s a substantial difference in the time that it takes to complete the visit, and not just from a documentation standpoint.
In speaking with my colleagues who have transitioned from human scribes to either virtual scribes or AI-assisted technologies in similar practice environments, they note that they miss the physical assistance of the scribe. No one is in the room with them who can step out and grab supplies or equipment when a situation occurs where it would be more efficient to do that instead of the physician stepping out to get what they need. There are also flow issues when chaperones are needed or when assistance is needed during a procedure, which can make the day bumpier.
Some colleagues with whom I recently discussed this mentioned that their organizations didn’t consider these workflow changes when moving to non-human documentation assistance strategies. One said that he felt that everyone thought it would be so much cheaper to not pay a person that they forgot to calculate in the time physicians would now be spending doing things that they didn’t have to do in the past.
It’s a classic parallel to what we experienced back in the early days of EHR implementation, when there were constant encounters with unintended consequences. One example: in a paper-based workflow where no one reconciled medications, implementing an EHR that requires medication reconciliation is going to increase visit duration, whether it’s done by an assistant or the physician. They should have been doing medication reconciliation in the first place because it’s a patient safety issue, but the EHR took the blame as forcing them to do something they didn’t think was important. Now we have different unintended consequences when we layer on more sophisticated technologies such as AI-assisted documentation.
One colleague described the problem of excessive summarization, where his organization’s AI documentation solution took a lengthy physician / patient discussion that included detailed risks and benefits of treatment or lack thereof and condensed it down into two sentences. When that happens, one has to consider the downstream ramifications. Will a physician even see that it’s been condensed in that way, or are they just signing notes without reviewing them to keep their inbox clear? That situation happens more than many would think. If a physician catches the issue, will they spend the time editing the note or will they just move on because they’re pressed for time? And if they do take the time to edit the visit note, will they capture all the nuances of the discussion exactly as it had occurred with that particular patient?
Another colleague, who is also a clinical informaticist, mentioned that having AI documentation solutions doesn’t fix underlying physician behavior challenges. The physician who never finished his notes at the end of the day and instead left them for Saturday mornings still leaves them for Saturday mornings, which means that he’s reviewing documentation that’s up to five days old and for visits that are no longer fresh in his mind. It’s creating issues with the technology platform, since recordings have to be kept until the notes are signed, and it’s skewing metrics for chart closure that were important to measure the success of the project.
The team that implemented the solution could have anticipated this had they looked at baseline chart closure rates, but they were in such a hurry to get the solution rolled out that now they’re having to go back and examine that data retrospectively. They also missed the opportunity to coach those physicians during the implementation phase about the patient safety value of closing notes in a timely manner.
Others have noted issues with using AI solutions to examine documentation after the fact, such as only using data from structured fields. This is great when you have a specialty that does a lot of structured documentation, but doesn’t work well in one where the subtleties of the patient’s story are largely captured via free text.
I recently attended a lecture where they discussed the hazards of using AI tools in the pediatric population, since so much of the language used in capturing a child’s status varies based on the age of the patient. For example, saying a patient is “increasingly fussy” has a meaning that goes beyond the words themselves and has a different impact when treating an infant versus an older child or a teenager.
The pediatricians also mentioned the difficulty in obtaining consent for use of AI tools during visits, especially when only one parent is present or when the child might be brought to the office by a caregiver such as a nanny or sitter. Although those individuals may have capacity to consent to treatment, they may not have specific ability to consent to the use of AI tools. There is also the issue of the child’s consent to being recorded. Although the laws generally allow parents to consent on behalf of their children, obtaining the permission of an adolescent patient is an ethical issue as well, and one which physicians may not have the time to address appropriately due to packed schedules.
The dialogue around use of AI solutions has certainly changed over the last year, and we’ve gone beyond talking about how cool it is to addressing the questions it has raised with expanding use. It’s great to see people asking thoughtful questions and even better to see vendors incorporating ethical discussions into their implementation processes. We’ll have to see what this landscape looks like in another year or two. I suspect that we will have found many other areas that need to be addressed.
How is your organization balancing the addition of AI solutions with the need for human assistants and the need to respect patient decisions? Leave a comment or email me.
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Healthcare’s Hidden Cost Crisis: How Middlemen and Outdated Tech are Bankrupting America
By Navin Nagiah
Navin Nagiah, MS is co-founder and CEO of Daffodil Health.
Recent articles, including those in The New York Times, have shone a spotlight on how middlemen contribute to rising healthcare costs, notably out-of-network (OON) pricing companies like MultiPlan and pharmacy benefit managers (PBMs), whose fees often obscure and inflate costs. While these analyses are thorough, they often focus on single facets of a sprawling, deeply rooted problem.
The truth is more intricate and defies simplistic solutions. High costs in US healthcare have accrued over decades, shaped by actions across the board, from government policy to insurer practices, provider pricing, and patient behavior.
The presence of intermediaries such as PBMs, OON re-pricing firms, and healthcare consultants reflects the US healthcare model’s structural complexity. As a hybrid of public, private, and even cash-based systems, it has produced a $4.1 trillion industry — 22% of the total economy — where $1 trillion alone goes toward administrative costs, with an estimated $500 billion of that deemed unnecessary or wasted.
For ordinary Americans, this complexity translates into hardship. Forty-one percent are burdened with medical debt; 46% forgo needed care due to cost; and 58% of debt collection involves medical bills. This financial strain is unsustainable for individuals, society, and the nation at large.
An underlying issue is healthcare pricing, which is inelastic, opaque, and tethered to outdated systems. Unlike typical markets, healthcare prices in the US do not respond to supply and demand. The pricing framework is labyrinthine, requiring deep domain expertise to navigate tens of thousands of procedural codes and varied pricing methods. Additionally, administrative systems used by both payers and providers often rely on outdated technology, exacerbating inefficiencies.
However, this does not make the primary actors — whether insurers, providers, or third-party entities — the villains of the story. In a capitalist framework, each stakeholder is incentivized to prioritize revenue and profits. Healthcare is no exception. It’s probable that any rational actor in similar roles would make comparable decisions.
The question we must address is: How do we move forward? What changes are necessary to begin mending this broken system?
The solution demands both regulatory and technological reform. First, let us take a closer look at regulation, where bipartisan consensus on the need for reform offers rare common ground. The No Surprises Act, for instance, was enacted under one administration and implemented by another, underscoring shared political will to mitigate healthcare’s impact on everyday Americans. Yet if we are to achieve genuine change, regulatory bodies need to adopt a more thoughtful and strategic approach.
Understand the market dynamics of payers and providers
Insurers and providers operate with the goals of revenue and profit growth, which regulators and regulations often fail to consider. Laws that don’t account for potential loopholes simply shift costs rather than reduce them, creating the illusion of progress. It is imperative to keep in mind that rising healthcare costs implies higher revenue for providers; a higher revenue for providers means higher premiums, i.e. revenue for payers.
The stock market rewards revenue growth way more than improved margins. This provides extensive incentive to payers and providers to be innovative in how they “shift costs” when regulations are passed.
Regulation must be crafted with an understanding of its potential impact on healthcare costs for ordinary people, avoiding the squeezed balloon effect, where costs shift without any overall cost reduction.
Recognize healthcare’s local monopolies
While other sectors, like technology, are subject to national antitrust scrutiny, healthcare operates across many local micro-markets with localized monopolies. Regulation should reflect this structure, addressing these micro-monopolies with tailored policies that account for regional market dynamics.
Stop adding to the middlemen problem
Regulations must be enacted with caution to avoid inadvertently inflating the healthcare sector’s administrative footprint. The Transparency in Coverage Act, for example, while intended to increase transparency, has spawned a cottage industry of compliance tools companies and consultants — more middlemen — with minimal impact on consumer costs. Future regulations should include clear expectations and mechanisms for affordable, effective compliance without adding new categories of middlemen to the already bloated system. Additionally, regulatory enforcement should be robust, ensuring that non-adherence results in significant penalties that deter cost-shifting practices.
Without these considerations, regulatory measures may perpetuate the inefficiencies they aim to resolve. Now more than ever, Americans need a healthcare system that prioritizes access, transparency, and genuine affordability. Legislative reform, combined with strategic enforcement, could be the first step toward this elusive goal.
Second, let us take a closer look at technology. Once a system, any system, reaches a certain level of complexity, simplifying it again becomes a near-impossible task. However, technology offers a pathway to managing complexity in ways that improve usability and efficiency. Consider the internet. It’s an enormous, convoluted system, yet search engines allow us to find information quickly and (usually) accurately.
In healthcare, however, technology has so far largely added to both complexity and the cost burden rather than easing it. Generative AI could mark a turning point. This technology is unique in its ability to emulate human skills like storytelling, a talent that was once thought exclusive to humans, which helps achieve shared understanding and collaboration. The potential is enormous. AI systems can now analyze, interpret, and convey information much like a human, which could impact healthcare administration, a sector valued at $1 trillion, half of which is estimated to be wasteful expenditure.
Take the process of claim re-pricing and payment as an example. After a doctor generates a bill for reimbursement, that claim may pass through as many as 10 companies and 12 software systems, each with its own requirements and procedures, before the doctor is paid. This labyrinthine process stems from decades of regulations, changing market dynamics, and piecemeal ad hoc solutions. Yet by deploying Generative AI and semi-autonomous agents, we could digitize and automate this entire process from end to end, significantly cutting down on time, costs, and redundancies.
Similar opportunities exist across other healthcare administration processes, whether in prior authorizations, member enrollment, or patient management. I am not suggesting that technology or Gen AI is a silver bullet. This is a long-term undertaking, demanding deep expertise in both healthcare and technology, a rigorous attention to detail, and considerable patience. Still, nothing in the nature of the problem makes it unsolvable.
Companies routinely embark on “moonshot” projects that demand decades to bear fruit, like Facebook’s Metaverse, Elon Musk’s SpaceX and Neuralink, and Google’s Waymo, Wing, and Loon. These projects capture public imagination and dominate media cycles, but moonshots in healthcare administration, though less glamorous, offer far greater potential for transforming lives.
We need to encourage visionary entrepreneurs to pursue these difficult challenges within healthcare. Initiatives that, though unglamorous, offer substantial benefits to consumers and society at large. Government support is also crucial. Legislation that promotes competition within local healthcare markets and policies that encourage innovative solutions for complex healthcare issues would drive meaningful progress.
Tackling Diabetes Distress in Dual Eligibles Requires Integrated Care Management
By Barbara Greising
Barbara Greising, MBA is chief commercial officer at Podimetrics.
Diabetes is a demanding condition. Slipping up even a little can quickly lead to devastating outcomes, and there’s never, ever a day off.
The constant stress can lead to feelings of discouragement, isolation, frustration, and exhaustion, especially when the consequences of suboptimal self-management can be so severe. For example, every 3.5 minutes, someone in the US loses a limb due to complications of type 2 diabetes (T2D), and up to 50%of those individuals may face death as a result within just two years.
For people living with diabetes and behavioral health challenges, such as a large number of the socioeconomically complex dual-eligible Medicare/Medicaid (DE) population, the outcomes could potentially be even more catastrophic, with mortality risks up tofour times higherthan people with either condition alone.
Up to 45% of mental health conditions and cases of severe psychological distress go undetected among people being treated for diabetes. And with nearly a third of DEs experiencing a serious mental health disorder of some kind, including major depression, that’s a potentially huge number of high-needs people who are not getting appropriate care.
Without proactive, personalized mental health support for these individuals, “diabetes distress” can take root, leaving up to half of people with diabetes feeling overwhelmed, defeated, disengaged, and less equipped to manage their everyday needs at some point in their health journey.
It is crucial to understand the root causes of diabetes distress, particularly in high-risk, highly complex DE populations, and develop proactive, personalized strategies rooted in integrated case management techniques that merge effective mental healthcare resources and socioeconomic support with more traditional approaches.
The first step for assisting people with diabetes is knowing if they need help. Standardized questionnaires like thePHQ-9 can be helpful, but these tools are not usually designed to uncover diabetes-specific concerns, nor are they always used at the most effective points in the diabetes management process.
Providers and health plans may consider augmenting data collection efforts with more targeted measurement tools for diabetes distress, such as the American Diabetes Association’s Problem Areas in Diabetes (PAID) Scale. This check sheet asks detailed questions, such as if the person feels scared, angry, or discouraged when thinking about living with diabetes, what their support system looks like, and how much energy diabetes care takes from them each day.
Providers should also look at patient barriers from every angle to reveal hidden challenges. For example, when one patient stopped engaging in daily self-monitoring for diabetic foot ulcers, it wasn’t because she didn’t understand the importance. It was because she couldn’t get to her doctor’s office to get a refill of her blood pressure medication. The frustrating situation and negative health effects from being off her meds meant she wasn’t feeling able to take care of herself fully.
When the patient received help to get connected with plan-based home care benefits to see a primary care provider for a refill, she reengaged with her foot care immediately, and at the same time, avoided an ED visit for potential hypertension complications.
Regularly fielding holistic questions about self-care competencies in the routine primary care environment is important, but plans and providers should also consider refreshing their data at other key points, such as during specialty visits for associated complications and before discharge from a hospital due to a diabetes-related event. This can ensure that individuals get the help they need when they need it, before diabetes distress becomes overwhelming.
Case managers can assist with this process by spearheading the development of compassionate, informed patient-provider and/or member-health plan relationships. These care team “quarterbacks” can help connect individuals with social workers, psychologists, psychiatrists, substance abuse counselors, and other behavioral health professionals to augment clinical care.
Case managers, especially those with nursing backgrounds, often have the training, intuition, and experience to identify people who may be struggling with a variety of non-clinical concerns and can successfully pair these insights with their clinical knowledge of diabetes management to support and guide people with diabetes to better glycemic control and improved overall mental health and well-being.
To be effective, however, case managers must be equipped with the tools and resources to perform this work appropriately. For example, health plans and provider networks will need to ensure that high-quality mental health resources, such as patient support programs, social workers, and counseling options, are consistently available for referral in a timely and affordable manner.
Case managers also need digital infrastructure to make referrals to socioeconomic support organizations, monitor the use of personal medical devices like continuous glucose monitors, and interact with individuals according to their preferred communication channels.
Diabetes distress is not a condition that can be wholly cured by a single pill or one-and-done injection. Instead, it requires ongoing attention and flexible degrees of management to establish and maintain emotional and mental equilibrium in the face of prolonged stress.
That means Medicare and Medicaid health plans, providers, case managers, patients, and unpaid caregivers must collaborate closely at all times to build a scaffolding of support around every individual.
Care team leaders should ensure that people with diabetes understand how, when, and why to use their medications and personal devices, especially when adding new technologies to the mix. Regular follow-ups around socioeconomic concerns and mental health status will be essential to success, including periodic refreshes of questionnaires and other patient-provided data. Health plans, health networks, and other industry stakeholders will need to remain dedicated to expanding access to mental and behavioral healthcare resources, especially in communities with a higher prevalence of diabetes.
By collecting the right information and getting people connected to the most appropriate resources for their needs, case managers can reduce the impact of diabetes distress on dual-eligible individuals and create the conditions for success for the tens of millions of people living with diabetes.
Upheal, which offers a clinical documentation personal assistant for mental health professionals, raises $10 million in a Series A funding round.
DEA and HHS Extend Telemedicine Flexibilities through 2025
The DEA and HHS will extend telemedicine prescribing flexibilities for an additional year.
Urgent care telehealth provider HealthLynked reports Q3 results: revenue down 56%, EPS –$0.01 versus $0.00.
Södra Älvsborg Hospital in Sweden pauses its use of the recently implemented Oracle Health Millennium. The regional director apologized, acknowledging that “the introduction has not gone according to plan.”
Specific user complaints include system slowness as well as displaying incorrect diagnoses, such as changing “no bleeding” to “bleeding.”
Hundreds of employees staged a demonstration to return to the old system, citing decreased efficiency and patient safety. Västra Götalands Medical Association is considering taking legal action over patient safety risks.
The previous system has been reactivated and some functions have been moved back to paper while Millennium problems are being addressed.
According to one chief physician, “It’s a lousy system that’s completely impossible to work in. These days, I’ve basically been unable to produce any healthcare.”
From Lanman: “Re: AblePay. Do any readers know anything about it? My big health system says that those who can’t pay will get assistance, while those who can ‘may’ save up to 13%. Anyone know if it is legit / good idea?” The company’s website says that it contracts with providers at higher rates, provides members with cards with AblePay as the secondary payer, and guarantees that providers will be paid within two weeks of billing. Online member reviews are mixed, with one saying that it’s better to ask the hospital for a cash discount from rack rates or use the hospital’s no-interest payment plan instead of giving AblePay a credit card number that they will charge immediately. Your comments are welcome, especially if you have AblePay experience as a patient or provider.
Poll respondents like Madison as the US’s health tech capital. A couple of folks questioned why a Cerner-less KCMO or Minneapolis weren’t listed as choices.
New poll to your right or here: Have you taken a consumer DNA test such as Ancestry or 23andMe? Several of my acquaintances, especially older ones who were raised in different cultural times, have been shocked to find evidence of previously unknown siblings, learned that they were raised by someone who wasn’t their biological parent, or saw strong indications of being the result of incest.
I funded some new Donors Choose teacher grant requests using money that was provided by my Anonymous Vendor Executive, who is happy to offer a 1:1 match on your donation that you can submit as below. Companies that donate a matchable $1,000 will receive a couple of sentences in an HIStalk news post to convey any message they choose (a company pitch, for example).
These are the new, fully funded projects, all of which involved historically underfunded schools in which at least 50% of students come from low-income households:
General Overview
Product roadmap
TEFCA
None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.
WellSky releases SkySense, AI-powered tools for its EHR sollutions that extract key information, perform ambient scribing, and summarize chart data.
Upheal, which offers a clinical documentation personal assistant for mental health professionals, raises $10 million in a Series A funding round.
Urgent care telehealth provider HealthLynked reports Q3 results: revenue down 56%, EPS –$0.01 versus $0.00. HLYK shares have lost 12% in the past 12 months, valuing the company at $11 million.
UT Health San Antonio promotes Michael Schnabel, MBA to VP/CIO.
Pete D’Addio, MS (Moffit Cancer Center) joins LCMC Health as VP of technology.
Truveta Data says that its EHR-sourced database contains the de-identified records of 120 million patients.
ProPublica calls out the lax enforcement of state regulations that require insurers to keep their provider directories current. A previous New York study of “ghost networks” found that 86% of the listed mental health professionals had incorrect contact information, weren’t actually in the stated network, or weren’t accepting new patients.
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Impilo Secures Series A Funding! Looking to Transform Healthcare Access Nationwide
Remote care software and services startup Impilo announces $11.5 million in Series A funding.
WashU Medicine, BJC Health System launch Center for Health AI
Washington University School of Medicine and BJC Health System in Missouri develop the Center for Health AI, which will develop and deploy healthcare AI technologies to improve patient care, streamline clinical workflows, and reduce administrative burdens.
The US Virgin Islands Office of Health Information Technology will work with CRISP Shared Services to develop an HIE.
Forward, a primary care delivery company that brought AI-powered doc-in-a-box CarePods to market last November, abruptly shuts down. Current patients will have access to care support until December 13, according to an announcement posted on what’s left of the company’s website.
Former employees said key problems were lack of patient interest, skeptical commercial building landlords, blood draw technology failures that forced the company to stop offering lab tests, and machines that left patients stuck inside.
Forward managed to install just five of the devices, which cost $1 million each to build.
My analysis of the original announcement, especially given the history of Forward’s predecessors and comments made by its members, wasn’t optimistic.
None scheduled soon. Previous webinars are on our YouTube channel. Contact Lorre to present or promote your own.
Babylon Health founder Ali Parsa, PhD launches healthcare AI assistant company Quadrivia with seed funding from a Swedish VC firm. (A bit of a health kiosk-related side note: Babylon, which shut down last year, acquired Smart Health Station vendor Higi for $5 million in 2022.)
Impilo raises $11.5 million in Series A funding. The company offers white label remote care software and support services.
Thomas Elbert (Health Catalyst) joins Get Well as COO.
Niagra Health in Ontario goes live on Oracle Health.
Sentara Norfolk General Hospital (VA) implements Andor Health’s ThinkAndor virtual nursing technology.
UConn John Dempsey Hospital (CT) rolls out 15 video monitoring camera carts as part of its new telesitter program.
A new report from the Government Accountability Office points out that HHS has failed to act on several GAO cybersecurity recommendations made earlier this year. It stresses that the department must do a better job of coordinating and monitoring ransomware mitigation efforts and tracking provider adoption of cybersecurity practices so that it can better determine the need for cybersecurity resources.
The Defense Health Agency and US military hospitals in Japan warn patients of a website masquerading as the MHS Genesis patient portal that attempts to direct visitors to download a non-existent MHS Genesis mobile app. The DHA Cyber Operations Center has since blocked the fake site, which uses a .info rather than .mil web address.
A study of primary care appointments at five VA clinics reveals that physicians often don’t digitally document what patients discuss with them during the visit. Physician-initiated concerns were included in 92% of EHR notes, while just 45% of patient-initiated discussions were documented. Researchers also noticed that nearly 50% of notes found in the EHR for these appointments were not found in visit transcripts.
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I have a couple of medical licenses that expire at the end of the year, so I spent some time taking care of those renewals. Failing to renew on time is an expensive mistake that can cause issues with credentialing and can result in disciplinary action if you inadvertently practice in a state where you’re not current. Although I rely on my clinical employer’s credentialing team to remind me, I also have appropriate reminders on my personal calendar to ensure I don’t miss a critical deadline. Most states where I’m licensed allow online renewal and the process takes only a few minutes, as long as there are no changes to your address, no new criminal convictions or malpractice claims, and you have a valid credit card.
As I was wrapping up it was a good reminder to make sure that all my professional memberships were renewed as well, so that they could be in the books for the 2024 fiscal year. Although most of those run January through December, I realized that my HIMSS membership had expired during the summer and either I missed it, or I didn’t receive a reminder. I guess I didn’t notice because I receive plenty of emails from HIMSS on a near-daily basis, and wouldn’t one think they’d suspend communications if you’re not paying dues? I would also think they’d send multiple reminders before expiration and continue to send reminders after, since HIMSS membership renews on a rolling basis. There was no penalty for late renewal and in fact my expiration date shifted, so it was like getting four months of membership for free since nothing had changed, at least in my opinion. I suspect that individual memberships like mine are the lowest thing on the organization’s priority list, so I shouldn’t be surprised. I’m not sure how valuable a HIMSS membership is anymore – maybe some readers should weigh in on how I could be getting more from my money than a discounted HIMSS conference registration rate.
From Jersey Girl: “It’s not just the WNBA – a health system logo is going to be featured on an NBA jersey for the first time.” Congratulations to Memorial Hermann Health System, whose patch will appear on Houston Rockets jerseys this season. The system already owns naming rights for the team’s training center, so it’s not surprising. A quick assist from Chat GPT tells me that patch rights go for $7M to $10M each year, so I hope the health system is going to get some significant return on its investment. That’s a lot of community health screenings or discounted health services that could be provided with that kind of money. Are you a health system exec willing to speak off the record about what these deals mean to your institution? Feel free to reach out anonymously.
AI is everywhere, so I was interested to see this recent JAMA Viewpoint article titled “Translating AI for the Clinician.” Most of my local colleagues think of AI as “using Chat GPT to write patient letters,” but don’t think too far beyond that. The authors note the need for a framework “for clinicians and patients to understand AI in the context of clinical practice, including the evidence of efficacy, safety, and monitoring in real-world clinical use.” I’ve been on the patient side of AI-augmented patient portal responses and ambient documentation, and during zero of those encounters has there been any mention to me as a patient about the use of AI or the risks and benefits of consenting to it being used as part of my care. As a clinical informaticist I know better – but the situation illustrates the need to better educate clinicians on the need to have some kind of a consent process around the use of these tools. The authors call for organizations to spend time considering the different activities inherent in patient care – elements such as interacting with patients, creating visit notes, interpreting tests, and delivering treatments – and to think about the best ways to leverage AI in those scenarios. This sounds like a rational approach to me – actually identifying a problem to solve versus creating a solution in search of a problem. Although many of the current uses of AI are well-reasoned, there are still a number of startups addressing the latter.
I’ve not used ambient documentation solutions as a clinician, so I reached out to a couple of friends to find out how their organizations are handling consent. One admitted that they addressed it during the pilot phase, but that by and large physicians just want it installed and are assuming that it’s addressed in the standard “consent to treat” forms that patients sign at the front desk or online via the patient portal. The only person who is actively having a consent conversation is a pediatrician, where the idea of consent is a big issue in general due to nuances of privacy and confidentiality when you’re caring for adolescents. Learning more about this topic reminded me how broad of a field clinical informatics has become and how one informaticist can’t possibly know everything. Although most large institutions have entire teams tackling these issues, the average physician trying to purchase an individual contract from one of the AI documentation vendors probably doesn’t know what questions to ask. The authors call for organizations to treat AI like they treat new drugs or medical devices – with testing and follow up to ensure that treatments are effective. Unfortunately, millions of patients are already part of a large experiment without even knowing it.
The Anchorage Daily News reports that nurses are concerned about the implementation of virtual nursing in their communities. I’ve worked on a couple of virtual nursing projects in the last few years, and they’ve generally been well received, so I was interested in the specific concerns. Nurses are concerned that having virtual colleagues managing discharge planning and patient education will concentrate additional work on the bedside nurses, stressing an already burdened work force by driving up patient-to-nurse ratios. The nurses’ union has filed a complaint with the National Labor Relations Board alleging unfair labor practices, so it’s not a concern that will go away any time soon. Hospital nursing has changed dramatically during the time between when I was a student and today, and frankly the only constant about patient care is that it will continue to change. The article notes that unlike some states, Alaska does not have a mandated patient-to-nurse ratio. I’ll be keeping an eye on this one to see how the labor complaint plays out.
Do you have virtual nursing at your institution and if so, how has it been received? Leave a comment or email me.
Email Dr. Jayne.
Inside Forward’s failed attempt to revolutionize the doctor’s office
AI-powered doc-in-the-box manufacturer Forward shuts down after an eight-year run, during which it raised $650 million.
The Future of Telehealth.org with Doxy.me
Telemedicine software developer Doxy.me acquires professional development and consulting organization Telehealth.org.
Harvard Medical School Alum Donates $6 Million for AI Health Care Education
Inovalon founder and CEO Keith Dunleavy, MD donates $6 million to his alma mater, Harvard Medical School, to expand education in AI in healthcare.
HHS has still not addressed key cyber recommendations, GAO says
A new report from the Government Accountability Office points out that HHS has failed to act on GAO cybersecurity recommendations made earlier this year, and stresses that the department must do a better job of coordinating ransomware mitigation efforts and tracking provider adoption of cybersecurity practices.
Google launches Learn About, a conversational AI learning companion that helps users learn about any topic.
Inovalon founder and CEO Keith Dunleavy, MD donates $6 million to his alma mater, Harvard Medical School, to expand education in AI in healthcare.
AI-powered doc-in-the-box manufacturer Forward, which said at the November 2023 launch of its CarePod that it hoped to deploy 3,200 of the machines in the next year, shuts down. The company had raised $650 million in funding. Former employees said key problems were lack of patient interest, skeptical commercial building landlords, blood draw technology failures that forced the company to stop offering lab tests, and machines that left patients stuck inside. Forward managed to install just five of the devices, which cost $1 million each to build. My analysis of the original announcement wasn’t optimistic.
Maverick Medical AI launches CodePilot, which offers real-time medical coding and MIPS/MACRA compliance notifications.
Apple is preparing to launch its first AI hardware device, an Echo-like wall mounted smart display for homes that will allow users to control apps, use FaceTime as an intercom, play music, and eventually to operate a robotic arm.
Johns Hopkins researchers train a robot by showing it videos of surgical procedures, after which the da Vinci Surgical System robot performed as well as a human doctor in manipulating a needle, lifting tissue, and suturing. The imitation learning involved videos that were recorded on cameras that were attached to da Vinci robots all over the world. The robot even learned behaviors that weren’t contained in the videos, such as picking up a dropped needle.
Researchers use AI-analyzed computer vision to predict neurological changes in NICU babies.
A UCSD hospital neurology ICU nurse who is also the nursing union rep says that he is terrified by “the creep of AI in our hospitals.” He observes:
Mr. H, Lorre, Jenn, Dr. Jayne.
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Lauren Patrick is president and CEO of Healthmonix.
Tell me about yourself and the company.
I am an IT engineer kind of person by training. I spent about 15 years working for consulting companies such as Capgemini and E&Y. I founded Healthmonix when I moved to Philadelphia about 15 years ago and wanted to do something more meaningful than selling tickets on the internet or compiling part lists for engineering firms.
Healthmonix is a healthcare analytics company that primarily focuses on quality metrics, with the MIPS and MSSP programs in particular. We got our start developing quality measures before everybody came to know what they were. I started working with the University of Pennsylvania to put together some CME programs. To figure out where the gaps in need were, we started using the Epic system to figure out what physicians knew and maybe what they didn’t know, then worked to provide performance improvement.
We work on quality metrics and now cost metrics as well, then help providers improve in those areas.
How do practices work and think differently in a value-based care model?
Rather than looking at fee-for-service — where every time you provide a service to a beneficiary or a patient, you are figuring out how to bill for that – it is focused on how to best take care of that patient, how to best serve that patient’s needs, and how to understand what that patient wants from their care.
How do you support practices that may have a mix of value-based and fee-for-service, or that work with multiple value-based care programs?
We take in all of the data for all patients. For the Medicare quality reporting program in particular, you have to report on all of your patients. No matter who the payer is – self-pay, private, Medicaid, or Medicare — all of those patients have to be included in your quality metrics panel in order to report to Medicare and get the incentives or avoid penalties. We track what their insurance is and can partition that data. We can show you quality metrics of your Humana patients versus straight Medicare fee-for-service patients.
We’re bringing all that data in, putting it in a repository, and then saying, here are the quality metrics that Medicare really cares about. We can show you those metrics from that data. Because of the way that we’ve built the software, we can also take that data and show you quality metrics that perhaps apply to Humana. We can take that same repository of information and pull it out in all the different ways for different reporting that is required. That’s quite a challenge, but that’s part of the beauty of coming at it from a data-based perspective. We pull all that data in and then build those quality metrics to help these folks report out with as little burden as possible.
How do physician behavior and education fit in?
While payment drives a lot of the participation in our programs, I started out working with UPenn trying to figure out how we could help providers improve. At the heart of what I want to do personally is to make a difference and help these people improve. But sometimes doctors will see these quality metrics put up on a screen somewhere and they will say, “No, these are wrong.”
We say, OK, let’s drill into them. Let’s take a look. This is the quality metric. You agree that this should be the standard of care, right? Let’s look at how your patients are or are not adhering to that. From there, you have to softly get these physicians into it. We’ve taught our physicians that they are knowledgeable and are out there making day-to-day decisions. To say to them, “Maybe you need to do something different“ is really a little bit of a shock to their system. It’s a standard cycle where they don’t believe, then they accept it, and then they have to figure out how they can change.
Is it enough to provide convincing data, or does change require having people on the ground to nudge them?
It depends on the personality of the physician. It also depends on the metric. You have to make sure that the measures that you’re putting in front of them are meaningful and something that the doctors can buy into.
When we started, we were looking at A1Cs. Let’s get the A1Cs down under fill in the blank – some doctors feel that nine is appropriate, some feel that seven is appropriate. Figuring out what that metric is, getting everybody to agree to that metric, and then having them work towards that. If they feel like it’s the right quality measure, then they are much more willing to work towards it.
When we do this, we look at process measures, which would be like filling out a prior auth or making sure that you put the meds in the EHR or whatever. But it’s the outcome measures that we are all striving for. Let’s make sure that our patients’ diabetes is in control. Let’s make sure their blood pressure is in control. Let’s make sure that they can walk out of the emergency department healthy. Let’s make sure that the patient’s objectives, in terms of what they want, are being adhered to. If you put the right metrics in front of these docs, they are much more willing to buy in, but you read journal articles all the time about how doctors don’t like a lot of the metrics that are being imposed by some of these programs.
What challenges are involved with collecting data from multiple systems and then packaging it together so that it is reliable?
That’s probably one of the biggest challenges industry-wide. We work very hard to pull data out of a variety of systems. Part of the challenge that we have now is that we might be reporting for not just an individual practice, but for an accountable care organization, which is a group of doctors that have banded together to say, “We are going to take responsibility for making sure that Mrs. Jones is healthy.” We have to pull all the data from all of those various practices and put it into one dashboard. We have to say, these are the outcome measures for Mrs. Jones, and who is working on that?
It’s hard to pull that data together because some of it is in an Athena system, some is in an Epic system, and some is in a billing system. Bringing it all together is one of the biggest challenges. We don’t just bring in a file, dump it, and say we’re done. We work with providers to understand where they are putting the data. A lot of times one doctor will put it in one field and another doctor will put it in a different field, so we have to understand that we have to get it from both fields. We spend a lot of time on data integration.
Has 21st Century Cures and broader interoperability improved that, or will it in the future?
That’s the dream. Everybody keeps saying FHIR, bulk FHIR, and all the regs that have come out. But some of the EHRs are kicking and screaming. They don’t want to share their data. Some of them just don’t have it together. Some doctors don’t put the data in the right fields for a standardized mechanism for data integration to be effective.
What progress has been made with accountable care organizations?
Everybody says that’s the brass ring. That’s what we’re striving for. But I heard somebody from Intermountain say that it’s a 30-year journey. We are all working towards figuring out how to do accountable care.
CMS was a little stifled by the pandemic for a few years and the growth of ACOs didn’t occur 2020 through 2023. We are hoping that we are back on track. We see more and more patients being involved in some sort of accountable care relationship. That’s good. That’s what we want. We want somebody to be in charge of that patient’s health and to be looking at the whole patient. What we at Healthmonix are trying to do is to bring all that data together so they can see the picture of the whole patient.
Does having information available from multiple systems create new opportunities?
Yes, absolutely, and not just with EHRs. Social determinants look at where the patient lives. What sort of life does that patient have in terms of a support system? Are they in a food desert? Are they getting the sort of social support that they need? Then, combining that in. As we move forward, we’re integrating more and more sources of data so that when that patient walks into that care facility, a provider can get a much better picture of what is going on with that patient.
How do providers use the social determinants screening? Do any of the quality measures have it built in?
To get physicians started with using them, the Medicare programs, the ACOs, are giving providers bonuses for tracking those metrics. We call that pay for reporting. Then as we go forward, they are starting to factor those into measures. A lot of the measures are what we call risk based, where we take in social determinants or other patient history and give the provider credit for the fact that it’s a harder patient to take care of.
Is MIPS the only program that looks at these measures?
MIPS is a CMS program. It adjusts the payment that providers get from Medicare for fee-for-service. If you don’t participate in MIPS, you’ll get a 9% penalty on every single claim that you turn in to Medicare the following year. That’s a big hit. If you turn the data in that we compile — if we turn the data in for you, essentially — and you do well, then you can get up to a 2% to 5% incentive on every bill that you put into CMS next year.
CMS drives a lot of it, but there’s a whole rulemaking process that we participate in. We will draw up some of the quality measures that are in the MIPS and CMS programs, and then CMS will decide if they think it’s a good thing or not. Once CMS adopts it, it funnels out to private payers because there’s a certain standard of care that you want to adhere to for patients. A lot of what we do is based on science.
How does the cost analytics part of MIPS work?
MIPS decided that part of the score that you get from Medicare is based on this cost component. CMS is looking at how much is it costing to take care of your patients for certain episodes of care. When you have a knee surgery, what is it really costing CMS in terms of all the claims that come in for that knee surgery? That includes X-rays, anesthesiologist, the surgery if you’re in an ambulatory surgery center, the post-acute care that happens for 30 days afterwards, and complications. We look at that as a whole to say that the total cost of that knee surgery was X. We look at everybody across the US and figure out what the average was. If you did better than the average, then we say, yay, you’re doing great, and we give you an incentive. If you’re doing worse, then CMS will ding you for that.
What factors will be most important for the company over the next few years?
Data integration is a huge one. Can they really work to build better data interoperability? Because that will help a great deal. But I still think that we are going to need to spend a lot of time on data integration.
The other thing is that CMS is by far the leader in terms of where we’re going in terms of value-based care. Looking at the programs that they put forth, it will be interesting now with Mr. Trump to see how much he supports or does not support the movement into value-based care. I didn’t see a lot of changes in the four years of his prior administration, but there will probably be some changes in the next four years since he feels like he’s got a little bit more of a mandate. Those sorts of things will impact where we go with this.
Everybody’s favorite term right now is artificial intelligence. We report data for 50,000 providers across the US. To do these cost metrics, we gather a lot of claims data from CMS as well. We have a pretty big repository of healthcare data. Now we are digging into that data to understand the correlation between patients with great outcomes, both in terms of cost of care and in terms of quality, and all the other factors that are in there. We are trying to use AI to see if using this medication for this patient is associated with better outcomes. If you go to this kind of post-acute facility versus that kind of post-acute facility, does it impact the cost of care? I am hugely interested in exploring this as we go forward so that we can form this feedback loop with our providers to say, you’re doing really well here, and here are some areas where you can improve based on our analysis of data.
Digital physical therapy services provider Sword Health reportedly lays off 13 physical therapists, about 17% of its clinicians, as it prepares for an IPO and follows through on plans to manage more patients using AI.
23andMe cuts 40% of its workforce and discontinues therapeutics division
23andMe will eliminate 200 roles and shutter its therapeutics division in an effort to restructure its business, which has seen declining revenue and plummeting shares over the last 12 months.
Babylon founder Ali Parsa launches healthcare AI assistant company Quadrivia with seed funding from Norrsken.
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