Tuesday, September 28, 2021

AI in healthcare: The tech is here, the users are not - Damo Consulting

Much of this article comes from a podcast by Paddy Padmanabhan@PaddyPadmanabha

Since the beginning of the year, there has been a significant uptick across health plans, healthcare providers, and analytics firms utilizing AI to change how healthcare is delivered and how patients can be more engaged in their care.

"Medical records must become a living record that pulls in data real-time, follows your health, and displays it back to a physician in a useful form."

AI applications in healthcare are all over the map today. Data from my firm’s digital health intelligence database, DamoIntelTM, has identified a significant rise in the launch of AI use cases across clinical and administrative areas in 2020. An analysis of AI/ML applications deployed by the top 50 health systems across the United States identifies that AI-enabled solutions fall into multiple technology categories: machine learning, natural language processing (NLP), conversational interfaces such as chatbots, and robotic process automation (RPA). COVID-related use cases in clinical and administrative areas contributed to the growth in adoption of newer technologies such as chatbots in healthcare.

A focus on real-time interventions with AI-enabled solutions at the point of care

The biggest challenge for AI-enabled care is to deliver insights in real-time into the clinical workflow at the point of care. For example, voice recognition technologies are effective with lower-level tasks such as scribing doctor-patient encounters. However, they are yet to evolve into decision-support systems that deliver additional insights at the point of care for diagnostic and treatment decisions. 

On the other hand, solutions that can deliver real-time insights are yet to reach scale and broad-based adoption. An example is Stanford University’s smartwatch-based COVID diagnosis app, in partnership with Amazon, that analyzes elevated heart rates and other abnormalities for pushing real-time alerts to patients suspected of COVID infection. Dr. Michael Snyder, Professor and Chair of Genetics, is working to scale the solution with the aim of creating a continuous monitoring framework for health indicators at an individual level. His goal it to cover anyone, anywhere who has a smartwatch. Amazon has offered millions in cloud computing credits for similar diagnostic solutions for digital health innovators across the world.

Data collaborations to drive advanced real-time analytics

If there’s one new trend this year, it’s data collaboratives. Truveta, a consortium of 14 health systems launched in February, aims to pool patient data from all the member systems to drive advanced analytics for improved healthcare outcomes. Google has announced a series of partnerships with healthcare enterprises, including Mayo Clinic, Ascension Health, and Highmark. Use cases include but are not limited to data analysis for quality measures, benchmarking, and administrative reporting. In addition to its partnership with Google, Mayo Clinic has launched new data collaboration initiatives with AI startups, targeting data from remote monitoring devices. Highmark, a major health plan based in Pennsylvania, has formed a 10-year partnership with Christiana Care in Delaware to pool medical and claims data to drive better outcomes. Expect to see more consortiums as large payers and providers pool their datasets to drive efficiencies through advanced analytical insights.

Other trends that will drive the AI-enabled future of health care

  • Increased innovation in AI-enabled applications following the CMS final rule that allows patients to access their medical information and share it with developers looking to build new digital health products and services.
  • Hospital rooms of the future that will incorporate superior experiences driven by AI-enabled digital interactions among caregivers, patients and their families. An example is the $1.5 Bn investment by Penn Medicine in Philadelphia. Titled The Pavilion, this 500-bed facility comes with patient rooms featuring interactive 75-foot monitors on the walls. John Donohue, VP of Entity Services for Medicine, has been closely involved in the technology enablement aspects of the patient room of the future. He references Disney-inspired user experience design as a part of the 6-year project in the making.
  • Analytics from remote monitoring devices. AI-enabled applications that ingest and analyze vast amounts of data from home monitoring devices and sensors will drive the next stage of the evolution of health care. As healthcare moves from hospital to home, expect heavy investments in analyzing data from remote sensors and monitoring devices. Amazon’s recently launched Amazon Care offering includes home-based care in addition to virtual care services as part of the overall package. Large health systems such as Kaiser Permanente and Mayo Clinic have also gotten into the game. They have announced investments in Medically Home, a tech firm that caters primarily to home-based care.

The patient is ready now – or is she?

While technologies and the computing infrastructure for AI-enabled care have matured, the adoption of AI-enabled care is driven by the varying readiness levels for the incumbents in the current healthcare ecosystem and concerns around the safety of AI-enabled care, specifically for complex clinical conditions. 

Patients are not sure about AI-enabled care either: a recent study points out that patients find chatbots intrusive and are hesitant to take medical advice from a bot. Administrative use cases for AI-enabled applications may deliver better ROI in the short term. Sachin Patel, CEO of Apixio, a healthcare analytics company acquired by Centene in 2020, attests to a 4x to 7x return on AI applications in financial operations such as risk adjustments.

My firm’s research indicates that over half of all hospitals in the country continue to use electronic health record (EHR) systems as the primary tool at the point of care. New, cloud-based, AI-enabled solutions continue to face challenges in integrating seamlessly into the clinical workflow at the point of care. Interoperability concerns and the challenges with standardization and normalization of healthcare data will continue to remain a significant challenge for AI-enabled applications. Further, standards such as ICD, SNOMED, and FHIR continue to evolve, representing a continuing demand for authoritative code change management and data normalization solutions validated by subject matter experts. New and emerging data sources, such as genomic data, will require additional guardrails around ethics and privacy prior to use in AI applications.

A final concern around AI in healthcare relates to the lack of visibility to how the algorithms are trained to work in healthcare, further exacerbated by systemic bias inherent in many AI applications. Despite advances in AI techniques, algorithms trained on a data set cannot be easily transferred to another data set, especially as the role of operational data and social determinants of health in population health risk assessment increases. As cloud platforms become the dominant data repositories for developing AI-enabled solutions, concerns around the privacy protections for the data will drive trust and consent required for advancing the adoption of AI tools. 

A bright spot for AI in healthcare is brisk pace of AI adoption in administrative functions. Health systems executives must expand the scope of these applications to cover new operational areas, including access and patient engagement, to drive efficiencies and improved quality of experience. Clinical leaders must continue to expand the use of AI applications cautiously and focusing on operational areas that don’t necessarily look to replace human intuition and judgment. An example of this is the use of AI to optimize schedules for chemotherapy at Penn Medicine.

As healthcare leaders look to accelerate the adoption of AI, they must also carefully weigh the costs and benefits of the efforts involved in developing and deploying AI solutions. The question always comes back to what we can do with insights we get back from AI applications. If we cannot move the needle based on the insights and information, clinical leaders must question the value of the program and the energy that goes into producing the insights in the first place. The key is to invest in areas where we can see demonstrated results and build it out from there. We are still several years away from a pervasive use of AI in core clinical aspects of healthcare. Until then, we simply continue to push the frontiers.

AI in healthcare: The tech is here, the users are not - Damo Consulting: The biggest challenges for AI-enabled care are delivering real-time insights into the clinical workflow and gaining acceptance from caregivers as well as patients. Innovative solutions continue to emerge.Originally published on CIO Online Since the beginning of the year, there has been a significant uptick across health plans, healthcare providers, and analytics…

Sunday, May 9, 2021

Telehealth in the Post. Covid 19 era

The Covid 19 pandemic created many changes in health care.  Perhaps the most obvious one was the accessibility of telehealth caused by rules regarding distancing to prevent further spread of the virus.

Contrary to expectations medical offices and clinics were not overwhelmed with worried patients. Medical facilities quickly organized their office visit procedures, including personal protective equipment, careful scheduling, the use of text messaging to patients indicating when they could enter the office. Reception areas were emptied using the new format.

Online portals, and telemedicine removed the necessity for face-to-face visits unless absolutely necessary. Most practices that had adopted EHR in the past ten years were in good position to make a rapid pivot to the new norm.

CMS and private plans quickly began to reimburse for telehealth as well.  Although this may have increased reimbursements, the offsets for better care, and perhaps sicker patients more than offset this expense.  No facts have been released by insurers as yet.

UnitedHealth’s Optum To Broaden Telehealth Offerings In All 50 States

UnitedHealth Group’s Optum healthcare services unit has launched a virtual care business that is expanding telehealth across the U.S. with more specialized medical care providers and services.

UnitedHealth and Optum executives say they have already launched a product they are calling “Optum Virtual Care” that is live in all 50 U.S. states. The effort is “integrating physical care, virtual care, home care and behavioral care,” executives told analysts on a call with Wall Street analysts last week to discuss the company’s first quarter earnings and outlook for the remainder of 2021.

The move deeper into virtual care could have ramifications for smaller telehealth companies given the access to capital Optum has to expand and given UnitedHealth’s status as the nation’s largest health insurer and as a massive provider of medical care. On Monday, UnitedHealth rival Cigna’s Evernorth healthcare services business took a bigger step in the telehealth arena by closing on its acquisition of MDLive.

To compete, Walmart had to acquire telehealth business

“Walmart has had a slow roll out of physical clinics compared to other retail storefronts; they needed a partner to achieve national presence with their healthcare strategy,” Forrester Principal Analyst Arielle Trzcinski wrote in an email. “Without a comprehensive primary care and chronic care delivery model that met consumers in their homes, they would struggle to gain market share against others like Amazon Care that focus on convenience, as well as cost.”

Scottsdale, Ariz.-based MeMD was founded in 2010 by an ER physician, and offers virtual urgent care and behavioral health services. Currently, MeMD’s visits are priced at $65 for an urgent care visit and $230 for a psychiatry visit, according to its website.

At the start of the Covid-19 pandemic, the Centers for Medicare and Medicaid Services and private insurers made the timely decision to rapidly expand coverage for telehealth visits, throwing a lifeline to millions of Americans who needed ongoing medical care despite nationwide stay-at-home orders.

At the time, virtual visits done by video or by telephone were covered at the same rates as conventional, in-person office visits.

Since then, telehealth has become an indispensable part of the U.S. health care system, helping provide patients with safe access to medical care. While video visits have some advantages over telephone visits, they require access to technology, digital literacy, and broadband internet access that are far from ubiquitous. Telehealth access that includes telephone-only visits can help reduce certain health care disparities, as these low-tech visits provide access to essential health care for many whose alternative is no care at all.
A great concern is that payers will revert to old reimbursement restrictions for telemedicine visits. Those rules restricted telehealth visits to remote areas where physician access is limited.

This lifeline may be cut, as CMS has signaled it plans to end reimbursement for telephone-only visits when the public health emergency ends.

Thursday, April 8, 2021

Where are we now with the Digital Health Space ?

It has been some time since Digital Health Space began publishing. Electronic health records are in use throughout all of health care.  The process has been slow but inexorable. Let's take a look at where we are now.

The major vendors have outpaced many smaller companies, however, the smaller systems have found their own niche due to price constraints and the fact that many providers do not require very robust systems.

Large integrated health systems, including universities, and free-standing entities such as Mayo Clinic, Cleveland Clinic and others chose large robust systems.  CMS directed vendor models equipped to extract important data for outcomes and cost containment. Interoperability became common using proprietary health information exchanges built into the vendor system or by using independent Health Information Exchanges.   

In order to compete many smaller entities merged health information technology to gain financial ability to access these robust systems to compete favorably with large systems.  In some cases, these mergers grew into complete new entities.

EHRs are no longer just a digital record. The EHR is credited with creating physician burnout as physicians became clerks inputting data, which took considerable time away from patient care. Data and analytics became essential using machine learning for predictive diagnosis

The addition of machine learning, natural language processing, and language processing are decreasing physician workload. Image recognition recognizes normal and sorts abnormal or questionable images to physicians for definitive diagnosis.

Explosive growth in telehealth occurred due to the Covid 19 pandemic, in 2020. Health payors reimbursed telehealth visits. Telehealth saved the day permitting distancing for most physician visits. Texting became routine for controlling patient flow and waiting room access.  Podium and Sharp Health Care developed a texting system to improve patient communications.  Caregivers are able to seamlessly connect with all patients, from those who have recently visited a care site for the first time or long term patients who have a deep relationship with their physician. With Podium’s Review & Feedback tools, care sites are able to automatically invite the customer to leave a review via text or the messaging app of their choice. Research shows that fast, and easy-to-complete review requests are ideal, and result in more accurate feedback. This integration will save caregivers’ time as well as increase the number and quality of their online reviews on Google, Facebook, Healthgrades and other key sites.
All of this allowed the merger of genomics, proteomics, and precision medicine using genetic engineering, CRISPR, and gene splicing.  Over the counter DNA analysis became common, with varying success to study gene pools and personal Ancestry.  The cost of these tests plummeted exponentially in the past ten years.

Not all is good, however:

Within six months of implementing a new EHR system at two urgent care clinics, clinicians' cognitive workloads more than doubled, according to a study published in Applied Ergonomics.

A news release on the study said researchers examined two urgent care clinics that are part of the Urbana, Ill.-based Carle Health Systems as they transitioned to new EHR systems.

Here are six key findings:

The increase in cognitive workload lasted for more than 30 months.

After two and a half years, the clinicians' cognitive workload remained very high, and the clinic's staff found the new EHR system more difficult than the previous hybrid system that used paper and computers.

Compared to nurses, clinicians reported greater increases in cognitive workload, including higher mental demands and levels of frustration.

Researchers said the data suggested that a portion of the increased cognitive workload resulted from having to use the new EHR system while they were with patients instead of after.

Minor design flaws like slow computer response times and the nonstandard labeling of tools negatively affected the users' perception of the system's usability.

At 30 months, negative usability ratings started to trend downwards. Researchers said the negative usability ratings may have gone back down to the rate they were before the new EHR was implemented if the study had gone on longer.
EPIC and CERNER have outpaced much of the HIT marketplace, favored by integrated health systems. 

1. Small community hospitals have reported the highest satisfaction rates with EHR vendors Meditech's and Epic's platforms, according to a recent KLAS Research report.

2. Tower Health transitioned its remaining hospitals and facilities to the West Reading, Pa.-based health system's Epic EHR.

3. Newport (Wash.) Hospital and Health Services went live on a new shared Epic EHR system on March 13.

4. Epic announced plans for March 17 to open a COVID-19 vaccination clinic for its nearly 10,000 employees.

5. Buffalo, N.Y.-based Catholic Health credited its $135 million investment in Epic as a driving force behind its vaccination program, helping to distribute nearly 12,000 vaccinations to healthcare workers and others in New York's 1A category since late December.

6. Epic and health insurer Humana moved ahead with the next phase of their collaboration to improve patient and provider communication and access to health information. The companies will add support for automated prior authorizations and member insights at the point of care to their jointly developed prescription benefit tool IntelligentRx.

16 hospitals, health systems seeking Allscripts, Cerner, Epic, Meditech talent

Wednesday, March 24, 2021

AIWA | Create Websites Using Just a Keyword

AIWA, what does that stand for?  It is another abbreviation for " Artificial Intelligence Website Assistant ".

By now most people have heard of Artificial Intelligence or "AI".  It is being used with varying success in healthcare and other industries.  It is by no means simple or easy to use. For some tasks such as facial recognition, or image analysis there are off-the-shelf applications that can be adapted for radiology, identifying patients for registration on electronic health records. 

Almost all medical practices, clinics, and hospitals have websites that provide information about your practice ranging from location, telephone numbers, services, telehealth portals, insurance information, and messaging access.  Websites are designed to work on smartphones, laptops. and desktop PCs. Windows,  or macOS.

AIWA also allows for building blogs. 

There are several scenarios where this inexpensive AI program can be useful. As a clinician, your time is very limited.  Unless you are a techie that enjoys code or wants to to try building a website I do not recommend using this tool yourself.  Despite being relatively simple it will not be using your best skill set efficiently. 

In 2021 most students have been required to use and learn computer skills. One of your recently hired employees can build a website for the clinic effectively with simple guidance.

AIWA | Create Websites Using Just a Keyword explains the process.

The choices are:

1. Build the website yourself without AI

2..Build the website yourself using AIWA.
3. Assign the task to an employee with relevant skills.

4. Hire a website builder to build the website.

Perhaps you have a website that is obsolete or your website no longer meets your needs. 

Some of the choices are very expensive such as hiring a web developer, and there are other website builders and programs to build your own website. The build-it-yourself sites such a WordPress, Squarespace, or Wix are widely used. WordPress is commonly used but is not simple or straightforward.  

The way your website is built and coded determines how fast your website loads and displays. AIWA determines this as it builds your pages.  Slow loading or non-loading means a reader will become impatient and leave. your pages with engaging. The first five seconds determine if the reader will continue.  No one enjoys watching "page loading' or watching an hourglass and spinning wheel.

The cost of AIWA is very inexpensive.