Hospitals’ New Message for Patients: Stay Home
Politico / By Daniel Payne
Health systems are trying to move more of the work they do to your house.
Sensors that enable staff to monitor patients remotely are less intrusive than they once were, meaning more patients comply with wearing them. That enables care providers to watch over someone from afar, Jiang Li, CEO of remote care company Vivalink, said.
“Almost everybody’s thinking about how to make adjustments to embrace new technology,” Li said. “This trend definitely will continue — it will continue on a global scale, not just the U.S.”
Most providers have increased their spending on technology in recent years, including an emphasis on telehealth and remote care, according to a 2023 report.
Health regulators are taking note — and engaging in the conversation.
Dr. Meena Seshamani, deputy administrator and director of the Centers for Medicare and Medicaid Services, said in a statement that the agency “continually assesses opportunities” to better the speed and reliability of care, including via technology. That assessment includes discussions “with the medical community and patient advocates on an ongoing basis.”
Some large hospitals are essentially opening tech consulting operations, selling the systems they’ve built in-house, or their staff’s expertise.
“You’re finding more health systems say: ‘What else could we do that is not necessarily wildly profitable but that just covers its own costs plus a little bit so that we can turn around and do other things?’” said Niyum Gandhi, chief financial officer and treasurer at Mass General Brigham.
Mass General, a major Boston hospital system, has done just that. It created an artificial intelligence business, relying on tech industry players, from GE HealthCare to Nvidia, to validate its tools. The health system, like other large health providers, is building its own AI products too, with some seeing opportunities to license them to peers.
That’s not a business plan just anyone can pursue.
In underserved areas, care options are shrinking. Rural hospitals have cut services that they see as unsustainable, even if they’re important to patients in the area.
Congress, in an effort to preserve care in rural areas, created a new Medicare payment designation for rural hospitals that would allow facilities to eliminate inpatient services to keep emergency rooms open.
And some doctors, in both small and large systems, are skeptical that technology is a panacea. Even where state-of-the-art tech is available, they worry they won’t be able to examine patients as thoroughly — or at all — when care is remote. Investigations into the use of remote monitoring sometimes suggested it led to substandard care.
But for patients looking for the convenience of the remote care they got during the pandemic — or hospitals who see remote care as a path to financial stability and better care — the future is coming.
“Things are going in the right direction,” Couris said. |
The Wrong Way to Use AI in Healthcare
The Rowan Report / By Tim Rowan, Editor Emeritus
Lawsuits are beginning to pile up against insurance companies participating in the Medicare Advantage program. The complaint? The wrong way to use AI in healthcare is with faulty algorithms to approve or deny claims. While AI can be extremely helpful in streamlining administrative tasks — comparing physician notes with Home Health assessments and nursing notes or reading hospital discharge documents — it seems not to be any good at deciding whether to approve or deny care.
The Wrong Way to Use AI in Healthcare Example 1
The Minnesota case, November, 2023, UnitedHealth Group:
- An elderly couple’s doctor deemed extended care medically necessary
- UnitedHealth’s MA arm denied that care
- Following their deaths, the couple’s family sued UnitedHealth, alleging:
- Straight Medicare would have approved the extended care
- United uses an AI model developed by NaviHealth called nH Predict to make coverage decisions
- UnitedHealth Group acquired NaviHealth in 2020 and assigned it to its Optum division
- nH Predict is known to be so inaccurate, 90% of its denials are overturned when appealed to the ALJ level
- UnitedHealth Group announced in October, 2023 that its division that deploys nH Predict will longer use the NaviHealth brand name but will refer to that Optum division as “Home & Community Care.”
The family’s complaint stated, “The elderly are prematurely kicked out of care facilities nationwide or forced to deplete family savings to continue receiving necessary medical care, all because [UnitedHealth’s] AI model ‘disagrees’ with their real live doctors’ determinations.”
The Wrong Way to Use AI in Healthcare Example 2
The Class-Action case, December 2023, Humana:
- A lawsuit was filed on December 12, 2023 in the U.S, District Court for the Western District of Kentucky
- It was filed by the same Los Angeles law firm that filed the Minnesota case the previous month, Clarkson
- The suit notes that Louisville-based Humana also uses nH Predict from NaviHealth
- The plaintiffs claim, “Humana knows that the nH Predict AI Model predictions are highly inaccurate and are not based on patients’ medical needs but continues to use this system to deny patients’ coverage.”
- The suit says Medicare Advantage patients who are hospitalized for three days usually are eligible to spend as many as 100 days getting follow-up care in a nursing home, but that Humana customers are rarely allowed to stay as long as 14 days.
- A Humana representative said Humana their own employed physicians see AI recommendations but make final coverage decisions.
What Makes This Possible
According to experts we speak with, there are many ways to use data analytics. The insurance companies named in the lawsuits use predictive decision making. This way of analyzing data compares a patient to millions of others and deduces what treatment plan might be suitable for one patient, based on what was effective for most previous patients. Opponents of this method have called it “data supported guessing.”…
Read Full Article |
The Right Way to Use AI in Healthcare
The Rowan Report / By Tim Rowan, Editor Emeritus
For better or worse, healthcare has begun the inevitable adoption of Artificial Intelligence. Before you consider adopting AI technology, know that there is a wrong way and a right way to use AI in healthcare. In a companion article this week, we describe the criticism insurance companies are getting for deploying AI in healthcare to harm patients. As a balance, here is a review of a product that we find to be using AI in healthcare to help both patients and Home Health Agencies.
The Problem
Home Health referral documents from physicians or hospitals can consist of more than 100 electronically transmitted pages. Some agencies report occasional packets exceeding 1,000 pages, often in a variety of data formats. Some are standard data formats, such as a face sheet, but most are unstructured, consisting of images or narrations, sometimes in paragraphs, sometimes in incomplete sentences. Worse, patient data interoperability can be limited by unstructured data.
More often than not, most of these pages are never read. Thoroughly interpreting that much data is nearly impossible for a human. Consequently, nurses too often approach an admission evaluation visit with an incomplete picture of a patient. The result can be gaps in care or treatment, inaccurate OASIS assessments, incomplete or poorly sequenced diagnosis codes, and improper care plans. These obstacles can impact both patient outcomes and agency revenue.
One Newly Available Solution for the Right Way to use AI in Healthcare
We recently attended a product demonstration and followed it up with updated descriptions to learn details about new product developments. Over the next three months, Select Data, in full disclosure one of our sponsors, will be introducing an AI-powered suite of products that has been designed over many years of development to support clinical, data driven decision-making. One by one, it addresses the problems described above.
The new system, SmartCare, empowers clinicians to harness previously hidden insights while reducing bias and cognitive overload. It enables them to steer their decisions with enhanced precision while maintaining their pivotal role in patient care, eliminating one of the common reasons many Home Health administrators hesitate to invite AI into agency processes. It does, however, make the care team’s job easier and facilitates better decision-making.
- AI can read those 100 to 1,000 page referral documents in minutes, where a human may require days.
- SmartCare uses AI to synthesize relevant medical history to provide a care snapshot highlighting the key diagnosis, focus and considerations for care, and recommended OASIS clinical discipline. It highlights any areas for clarification needed from physician or admitting nurse.
- Clinicians can search and index specific words in unstructured data, such as narratives, to instantly identify any detail of a patient’s condition in an easy-to-read interface. Nurses approach the initial OASIS visit armed with all of a referring clinician’s relevant care findings.
- Recommendations for diagnostic codes strictly follow Medicare PDGM guidelines.
Suite of Tools
1 – RISE stand for Rapid Intake Summary & Evaluation. This component of the suite summarizes all clinical data from referral sources and your EHR. It compiles this data to provide clinically relevant diagnoses, focus of care, and recommendations for skilled disciplines. This is the part of the tool that reads referral documents and supports informed decision-making. The advantages we detected go a bit beyond the technical…
Read Full Article
|
Lymphedema Compression Treatment Items: New DMEPOS Benefit Category
Starting January 1, 2024, Medicare pays for lymphedema compression treatment items for Medicare Part B patients. CMS updated the following manuals with information on this new DMEPOS benefit category:
|
|
|
