Pathologists and clinical laboratory scientists may find one hospital’s use of a machine-learning platform to help improve utilization of lab tests both an opportunity and a threat
Variation in how individual physicians order, interpret, and act upon clinical laboratory test results is regularly shown by studies in peer-reviewed medical journals to be one reason why some patients get great outcomes and other patients get less-than-desirable outcomes. That is why many healthcare providers are initiating efforts to improve how physicians utilize clinical laboratory tests and other diagnostic procedures.
This effort came about after clinical and administrative leadership at Flagler Hospital realized that only about one-third of its physicians regularly followed certain medical decision-making guidelines or clinical order sets. Armed with these insights, staff members decided to find a solution that reduced or removed variability from their healthcare delivery.
Reducing Variability Improves Care, Lowers Cost
Variability in physician care has been linked to increased healthcare costs and lower quality outcomes, as studies published in JAMA and JAMA Internal Medicine indicate. Such results do not bode well for healthcare providers in today’s value-based reimbursement system, which rewards increased performance and lowered costs.
Clinical order sets are designed to be used as part of clinical decision support systems (CDSS) installed by hospitals for physicians to standardize care and support sound clinical decision making and patient safety.
However, when doctors don’t adhere to those pre-defined standards, the results can be disadvantageous, ranging from unnecessary services and tests being performed to preventable complications for patients, which may increase treatment costs.
“Over the past few decades we’ve come to realize clinical variation plays an important part in the overuse of medical care and the waste that occurs in healthcare, making it more expensive than it should be,” Michael Sanders, MD (above) Flagler’s Chief Medical Information Officer, told Modern Healthcare. “Every time we’re adding something that adds cost, we have to make sure that we’re adding value.” (Photo copyright: Modern Healthcare.)
Flagler’s AI project involved uploading clinical,
demographic, billing, and surgical information to the AyasdiAI platform, which then
employed machine learning to analyze the data and identify trends. Flagler’s
physicians are now provided with a fuller picture of their patients’ conditions,
which helps identify patients at highest risk, ensuring timely interventions that
produce positive outcomes and lower costs.
How Symphony AyasdiAI Works
The AyasdiAI application utilizes a category of mathematics called topological data analysis (TDA) to cluster similar patients together and locate parallels between those groups. “We then have the AI tools generate a carepath from this group, showing all events which should occur in the emergency department, at admission, and throughout the hospital stay,” Sanders told Healthcare IT News. “These events include all medications, diagnostic tests, vital signs, IVs, procedures and meals, and the ideal timing for the occurrence of each so as to replicate the results of this group.”
Caregivers then examine the data to determine the optimal
plan of care for each patient. Cost savings are figured into the overall
equation when choosing a treatment plan.
Flagler first used the AI program to examine trends among their pneumonia patients. They determined that nebulizer treatments should be started as soon as possible with pneumonia patients who also have chronic obstructive pulmonary disease (COPD).
“Once we have the data loaded, we use [an] unsupervised
learning AI algorithm to generate treatment groups,” Sanders told Healthcare
IT News. “In the case of our pneumonia patient data, Ayasdi produced nine
treatments groups. Each group was treated similarly, and statistics were given
to us to understand that group and how it differed from the other groups.”
Armed with this information, the hospital achieved an 80% greater physician adherence to order sets for pneumonia patients. This resulted in a savings of $1,350 per patient and reduced the readmission rates for pneumonia patients from 2.9% to 0.4%, reported Modern Healthcare.
The development of a machine-learning platform designed to
reduce variation in care (by helping physicians become more consistent at
following accepted clinical care guidelines) can be considered a warning shot
across the bow of the pathology profession.
This is a system that has the potential to become interposed
between the pathologist in the medical laboratory and the physicians who refer
specimens to the lab. Were that to happen, the deep experience and knowledge
that have long made pathologists the “doctor’s doctor” will be bypassed.
Physicians will stop making that first call to their pathologists, clinical
chemists, and laboratory scientists to discuss a patient’s condition and
consult on which test to order, how to interpret the results, and get guidance
on selecting therapies and monitoring the patient’s progress.
Instead, a “smart software solution” will be inserted into
the clinical workflow of physicians. This solution will automatically guide the
physician to follow the established care protocol. In turn, this will give the
medical laboratory the simple role of accepting a lab test order, performing
the analysis, and reporting the results.
If this were true, then it could be argued that a laboratory
test is a commodity and hospitals, physicians, and payers would argue that they
should buy these commodity lab tests at the cheapest price.
Cerner and Epic are the industry’s revenue leaders, though smaller vendors remain popular with physician groups
Sales of electronic health record (EHR) systems and related hardware and services reached $31.5 billion in 2018. And those sales will increase, according to a 2019 market analysis from Kalorama Information. This is important information for clinical laboratories and anatomic pathology groups that must interface with the EHRs of their physician clients to enable electronic transmission of lab orders and test results between doctor and lab.
Kalorama’s ranking includes familiar big EHR manufacturer names—Cerner (NASDAQ:CERN) and Epic—and includes a new name, Change Healthcare, which was born out of Change Healthcare Holding’s merger with McKesson. However, smaller EHR vendors remain popular with many independent physicians.
“We estimate that 40% of the market is not in the top 15 [in total revenue rankings],” said Bruce Carlson, Kalorama’s publisher, in an exclusive interview with Dark Daily. “There’s a lot of room. There are small vendors out there—Amazing Charts, e-MDs, Greenway, NextGen, Athena Health—that show up on a lot of physician surveys.”
“The EHR is really important,” noted Bruce Carlson (above), Publisher at Kalorama. “Since there are a variety of systems—sometimes different from the LIS [laboratory information management system]—you want to make sure you know the vendors and the space.” Carlson says opportunities remain for new entrants in the 700-plus competitor space, which is expected to see continued mergers and acquisitions that will affect clinical laboratories and their client physicians. (Photo copyright: Twitter.)
Interoperability a Key Challenge, as Most Medical
Laboratories Know
Interoperability—or the lack thereof—remains one of the
industry’s biggest challenges. For pathologists, that means seamless electronic
communication between medical laboratories and provider hospitals can be
elusive and can create a backlash against EHR vendors.
Kalorama notes a joint investigation by Fortune and Kaiser Health News (KHN), titled, “Death by a Thousand Clicks: Where Electronic Health Records Went Wrong.” The report details the growing number of medical errors tied to EHRs. One instance involved a California lawyer with herpes encephalitis who allegedly suffered irreversible brain damage due to a treatment delay caused by the failure of a critical lab test order to reach the hospital laboratory. The order was typed into the EHR, but the hospital’s software did not fully interface with the clinical laboratory’s software, so the lab did not receive the order.
“Many software vendors and LIS systems were in use prior to
the real launching of EHRs—the [federal government] stimulus programs,” Carlson
told Dark Daily. “There are a lot of legacy systems that aren’t
compatible and don’t feed right into the EHR. It’s a work in progress.”
Though true interoperability isn’t on the immediate horizon, Carlson expects its arrival within the next five years as the U.S. Department of Health and Human Services ramps up pressure on vendors.
“I think it is going to be a simple matter eventually,” he
said. “There’s going to be much more pressure from the federal government on
this. They want patients to have access to their medical records. They want one
record. That’s not going to happen without interoperability.”
Other common criticisms of EHRs include:
Wasted provider time: a recent study published in JAMA Internal Medicine notes providers now spend more time in indirect patient care than interacting with patients.
Physician burnout: EHRs have been shown to increase physician stress and burnout.
Not worth the trouble: The debate continues over whether EHRs are improving the quality of care.
Negative patient outcomes: Fortune’s investigation outlines patient safety risks tied to software glitches, user errors, or other flaws.
There’s No Going Back
Regardless of the challenges—and potential dangers—it appears EHRs are here to stay. “Any vendor resistance of a spirited nature is gone. Everyone is part of the CommonWell Health Alliance now,” noted Carlson.
Clinical laboratories and pathology groups should expect
hospitals and health networks to continue moving forward with expansion of
their EHRs and LIS integrations.
“Despite the intensity of attacks on EHRs, very few health systems are going back to paper,” Carlson said in a news release. “Hospital EHR systems are largely in place, and upgrades, consulting, and vendor switches will fuel the market.”
Thus, it behooves clinical laboratory managers and
stakeholders to anticipate increased demand for interfaces to hospital-based
healthcare providers, and even off-site medical settings, such as urgent care
centers and retail health clinics.
According to Damo Consulting’s 2019 Healthcare
IT Demand Survey, when it comes to spending money on information
technology (IT), healthcare executives believe AI and digital healthcare
technologies—though promising—need more development.
Damo’s report notes that 71% of healthcare providers
surveyed expect their IT budgets to grow by 20% in 2019. However, much of that
growth will be allocated to improving EHR functionality, Healthcare Purchasing News reported
in its analysis of Damo survey data.
As healthcare executives plan upgrades to their EHRs,
hospital-based medical laboratories will need to take steps to ensure
interoperability, while avoiding disruption to lab workflow during transition.
The survey also noted that some providers that are considering
investing in AI and digital health technology are struggling to understand the
market, the news release states.
“Digital and AI are emerging as critical areas for technology spend among healthcare enterprises in 2019. However, healthcare executives are realistic about their technology needs versus their need to improve care delivery. They find the currently available digital health solutions in the market are not very mature,” explained Paddy Padmanabhan (above), Chief Executive Officer of Damo Consulting, in a news release. (Photo copyright: The Authors Guild.)
Providers More
Positive Than Vendors on IT Spend
Damo Consulting is a Chicago-area based healthcare and
digital advisory firm. In November 2018, Damo surveyed 64 healthcare executives
(40 technology and service leaders, and 24 healthcare enterprise executives). Interestingly, healthcare providers were more
positive than the technology developers on IT spending plans, reported HITInfrastructure.com, which
detailed the following survey findings:
79% of healthcare executives anticipate high
growth in IT spending in 2019, but only 60% of tech company representatives
believe that is so.
75% of healthcare executives and 80% of vendor
representatives say change in healthcare IT makes buying decisions harder.
71% of healthcare executives and 55% of vendors say
federal government policies help IT spending.
50% of healthcare executives associate
immaturity with digital solution offerings.
42% of healthcare providers say they lack
resources to launch digital.
“While information technology vendors are aggressively
marketing ‘digital’ and ‘AI,’ healthcare executives note that the currently
available solutions in these areas are not very mature. These executives are
confused by the buzz around ‘AI’ and ‘digital,’ the changing landscape of who
is playing what role, and the blurred lines of capabilities and competition,” noted
Padmanabhan in the survey report.
The survey also notes that “Health systems are firmly
committed to their EHR vendors. Despite the many shortcomings, EHR systems
appear to be the primary choice for digital initiatives among health systems at
this stage.”
Some Healthcare
Providers Starting to Use AI
Even as EHRs receive the lion’s share of healthcare IT
spends, some providers are devoting significant resources to AI-related
projects and processes.
For example, clinical
pathologists may be intrigued by work being conducted at Cleveland Clinic’s Center for
Clinical Artificial Intelligence (CCAI), launched in March. The CCAI is using
AI and machine learning in pathology, genetics, and cancer research, with the
ultimate goal of improving patient outcomes, reported Becker’s Hospital Review.
“We’re not in it because AI is cool, but because we believe
it can advance medical research and collaboration between medicine and
industry—with a focus on the patient,” Aziz Nazha, MD, Clinical
Hematology and Oncology Specialist and Director of the CCAI, stated in an
article posted by the American Medical Association (AMA).
AI Predictions Lower
Readmissions and Improve Outcomes
Cleveland Clinic’s CCAI reportedly has gathered data from
1.6 million patients, which it uses to predict length-of-stays and reduce
inappropriate readmissions. “But a prediction itself is insufficient,” Nazha told
the AMA. “If we can intervene, we can change the prognosis and make things
better.”
The CCAI’s ultimate goal is to use predictive models to “develop
a new generation of physician-data scientists and medical researchers.” Toward
that end, Nazha notes how his team used AI to develop genomic biomarkers that identify
whether a certain chemotherapy drug—azacitidine (aka,
azacytidine and marketed as Vidaza)—will work for specific patients. This is a
key goal of precision
medicine.
CCAI also created an AI prediction model that outperforms
existing prognosis scoring systems for patients with Myelodysplastic
syndromes (MDS), a form of cancer in bone marrow.
Meanwhile, at Johns
Hopkins Hospital, AI applications track availability of beds and more. The
Judy Reitz Capacity Command Center, built in collaboration with GE Healthcare Partners, is a
5,200 square feet center outfitted with AI apps and staff to transfer patients
and help smooth coordination of services, according to a news release.
Forbes described the Reitz command
center as a “cognitive hospital” and reports that it has essentially enabled
Johns Hopkins to expand its capacity by 16 beds without undergoing bricks-and-mortar-style
construction.
In short, medical laboratory leaders may want to interact
with IT colleagues to ensure uninterrupted workflows as EHR functionality evolves.
Furthermore, AI developments suggest opportunities for clinical laboratories to
leverage patient data and assist in improving the diagnostic accuracy of providers
in ways that improve patient care.
Despite the widespread adoption of electronic health record (EHR) systems and billions in government incentives, lack of interoperability still blocks potential benefits of digital health records, causing frustration among physicians, medical labs, and patients
Clinical laboratories and anatomic pathology groups understand the complexity of today’s electronic health record (EHR) systems. The ability to easily and securely transmit pathology test results and other diagnostic information among multiple providers was the entire point of shifting the nation’s healthcare industry from paper-based to digital health records. However, despite recent advances, true interoperability between disparate health networks remains elusive.
One major reason for the current situation is that multi-hospital health systems and health networks still use EHR systems from different vendors. This fact is well-known to the nation’s medical laboratories because they must spend money and resources to maintain electronic lab test ordering and resulting interfaces with all of these different EHRs.
Healthcare IT News highlighted the scale of this problem in recent coverage. Citing data from the Healthcare Information and Management Systems Society (HIMSS) Logic database, they note that—when taking into account affiliated providers—the typical health network engages with as many as 18 different electronic medical record (EMR) vendors. Similarly, hospitals may be engaging with as many as 16 different EMR vendors.
The graphics above illustrates why interoperability is the most important hurdle facing healthcare today. Although the shift to digital is well underway, medical laboratories, physicians, and patients still struggle to communicate data between providers and access it in a universal or centralized manner. (Images copyright: Healthcare IT News.)
The lack of interoperability forces healthcare and diagnostics facilities to develop workarounds for locating, transmitting, receiving, and analyzing data. This simply compounds the problem.
Pressure from Technology Giants Fuels Push for Interoperability
According to HITECH Answers, the Centers for Medicare and Medicaid Services (CMS) has paid out more than $38-billion in EHR Incentive Program payments since April 2018.
Experts, however, point out that government incentives are only one part of the pressure vendors are seeing to improve interoperability.
“There needs to be a regulatory push here to play referee and determine what standards will be necessary,” Blain Newton, Executive Vice President, HIMSS Analytics, told Healthcare IT News. “But the [EHR] vendors are going to have to do it because of consumer demand, as things like Apple Health Records gain traction.”
Another solution, according to TechTarget, involves developing application programming interfaces (APIs) that allow tech companies and EHR vendors to achieve better interoperability by linking information in a structured manner, facilitating secure data transmission, and powering the next generation of apps that will bring interoperability ever closer to a reality.
TechTarget reported on how University of Utah Hospital’s five hospital/12 community clinic health network, and Intermountain Healthcare, also in Utah, successfully used APIs to develop customized interfaces and apps to improve accessibility and interoperability with their Epic and Cerner EHR systems.
Diagnostic Opportunities for Clinical Laboratories
As consumers gain increased access to their data and healthcare providers harness the current generation of third-party tools to streamline EHR use, vendors will continue to feel pressure to make interoperability a native feature of their EHR systems and reduce the need to rely on HIT teams for customization.
For pathology groups, medical laboratories, and other diagnosticians who interact with EHR systems daily, the impact of interoperability is clear. With the help of tech companies, and a shift in focus from government incentives programs, improved interoperability might soon offer innovative new uses for PHI in diagnosing and treating disease, while further improving the efficiency of clinical laboratories that face tightening budgets, reduced reimbursements, and greater competition.
Future EHRs will focus on efficiency, machine learning, and cloud services—improving how physicians and medical laboratories interact with the systems to support precision medicine and streamlined workflows
When the next generation of electronic health record (EHR) systems reaches the market, they will have advanced features that include cloud-based services and the ability to collect data from and communicate with patients using mobile devices. These new developments will provide clinical laboratories and anatomic pathology groups with new opportunities to create value with their lab testing services.
Proposed Improvements and Key Trends
Experts with EHR developers Epic Systems, Allscripts, Accenture, and drchrono spoke recently with Healthcare IT News about future platform initiatives and trends they feel will shape their next generation of EHR offerings.
They include:
Automation analytics and human-centered designs for increased efficiency and to help reduce physician burnout;
Improved feature parity across mobile and computer EHR interfaces to provide patients, physicians, and medical laboratories with access to information across a range of technologies and locations;
A shift toward cloud-hosted EHR solutions with support for application programming interfaces (APIs) designed for specific healthcare facilities that reduce IT overhead and make EHR systems accessible to smaller practices and facilities.
Should these proposals move forward, future generations of EHR platforms could transform from simple data storage/retrieval systems into critical tools physicians and medical laboratories use to facilitate communications and support decision-making in real time.
And, cloud-based EHRs with access to clinical labs’ APIs could enable those laboratories to communicate with and receive data from EHR systems with greater efficiency. This would eliminate yet another bottleneck in the decision-making process, and help laboratories increase volumes and margins through reduced documentation and data management overhead.
Cloud-based EHRs and Potential Pitfalls
Cloud-based EHRs rely on cloud computing, where IT resources are shared among multiple entities over the Internet. Such EHRs are highly scalable and allow end users to save money by hiring third-party IT services, rather than maintaining expensive IT staff.
Kipp Webb, MD, provider practice lead and Chief Clinical Innovation Officer at Accenture told Healthcare IT News that several EHR vendors are only a few years out on releasing cloud-based inpatient/outpatient EHR systems capable of meeting the needs of full-service medical centers.
While such a system would mean existing health networks would not need private infrastructure and dedicate IT teams to manage EHR system operations, a major shift in how next-gen systems are deployed and maintained could lead to potential interoperability and data transmission concerns. At least in the short term.
Yet, the transition also could lead to improved flexibility and connectivity between health networks and data providers—such as clinical laboratories and pathologist groups. This would be achieved through application programming interfaces (APIs) that enable computer systems to talk to each other and exchange data much more efficiently.
“Perhaps one of the biggest ways having a fully cloud-based EHR will change the way we as an industry operate will be enabled API access.” Daniel Kivatinos, COO and founder of drchrono, told Healthcare IT News. “You will be able to add other partners into the mix that just weren’t available before when you have a local EHR install only.”
Paul Black, CEO of Allscripts, believes these changes will likely require more than upgrading existing software or hardware. “The industry needs an entirely new approach to the EHR,” he told Healthcare IT News. “We’re seeing a huge need for the EHR to be mobile, cloud-based, and comprehensive to streamline workflow and get smarter with every use.” (Photo copyright: Allscripts.)
Reducing Physician Burnout through Human-Centered Design
As Dark Daily reported last year, EHRs have been identified as contributing to physician burnout, increased dissatisfaction, and decreased face-to-face interactions with patients.
Combined with the increased automation, Carl Dvorak, President of Epic Systems, notes next-gen EHR changes hold the potential to streamline the communication of orders, laboratory testing data, and information relevant to patient care. They could help physicians reach treatment decisions faster and provide laboratories with more insight, so they can suggest appropriate testing pathways for each episode of care.
“[Automation analytics] holds the key to unlocking some of the secrets to physician well-being,” Dvorak told Healthcare IT News. “For example, we can avoid work being unnecessarily diverted to physicians when it could be better managed by others.”
Black echoes similar benefits, saying, “We believe using human-centered design will transform the way physicians experience and interact with technology, as well as improve provider wellness.”
Some might question the success of the first wave of EHR systems. Though primarily built to address healthcare reform requirements, these systems provided critical feedback and data to EHR developers focused not on simply fulfilling regulatory requirements, but on meeting the needs of patients and care providers as well.
If these next-generations systems can help improve the quality of data recording, storage, and transmission, while also reducing physician burnout, they will have come a long way from the early EHRs. For medical laboratory professionals, these changes will likely impact how orders are received and lab results are reported back to doctors in the future. Thus, it’s worth monitoring these developments.
