‘Care Studio’ is designed to give physicians a ‘single, centralized view’ of patients’ records that are spread among multiple disparate databases within a healthcare system
Lack of interoperability between electronic health records (EHRs) has been a thorn in the side of healthcare providers—including clinical laboratorians and pathologists—who have to search multiple healthcare organizations’ databases to pull together medical records on individual patients. Google Health claims it may have the answer to the longstanding issue of siloed patient records.
Google Health and St. Louis-based Ascension, one of the largest healthcare systems in the US, have announced the clinical pilot of their new Care Studio platform. The software tool, according to the Care Studio website, “leverages Google’s expertise in organizing information to help clinicians find health record information faster.
“The tool’s Clinical Search feature,” Google Health continues, “enables nurses and doctors to simply type what they’re looking for and quickly find the specific information requested—which might otherwise require significant time and effort to uncover.”
Essentially, Care Studio complements existing EHR systems and enables healthcare providers to quickly search and organize previously siloed patient healthcare data stored on multiple EHRs within a health system. If successful, such a tool would clearly help streamline physicians’ workflows and shave hours off their daily patient research.
According to Google Health, Care Studio is a cross-platform EHR tool that gives clinicians a “single, centralized view that brings forward a patient’s hospital visits, outpatient events, laboratory tests, medications and treatments, and progress notes.”
Gathered data then can be visualized in tables, graphs, and other formats.
“Using Google’s expertise in organizing complex information, Care Studio (above) provides a unified view of patient records, making them more accessible and useful for clinicians,” Peter Clardy, MD, Senior Clinical Specialist at Google Health, said in the launch video. “In Care Studio, you can browse and search through patient information.” Clinical laboratory test results will be included in these screen views. (Photo copyright: YouTube/Ascension.)
According to Medical Device Network, Google and Ascension originally introduced Care Studio to a small number of providers at Ascension’s Nashville and Jacksonville, Fla., locations. They are now expanding the pilot to more nurses and physicians working in clinical settings.
“So, why Google?” David Feinberg, MD (above), VP, Google Health, asked in a video announcement. “Google is really, really good at organizing information, and these electronic health records have amazing amounts of information. But they are unusable. So, we want to bring the functionality of Google—the way to kind of organize information—so doctors can spend more time holding your hand, looking into your eye, and having the difficult conversations with you instead of being data clerks. Part of that is allowing them to find the needle in the haystack in your medical record in seconds, instead of days.” This, of course, would include clinical laboratory test results, which make up 80% of all medical records. (Photo copyright: YouTube/Google Health.)
In a blog post, Eduardo Conrado, Executive Vice President, Strategy and Innovation at Ascension, wrote, “In current EHR systems, clinical information too often is buried in siloed records scattered across hospitals, clinics, urgent care centers, pharmacies, physician offices, labs, and other sites of care, making it challenging for physicians and caregivers to efficiently deliver coordinated and precise care.
“When information is finally retrieved from these disparate EHR systems,” he added, “it is usually poorly organized and fragmented. Most clinicians work in an environment where data is incomplete, inaccessible, and delivered in disjointed bursts of information without context.”
COVID-19 Accelerates Need for Improvements in Data Access
Conrado notes that the ability for clinicians to quickly retrieve and organize a patient’s complete clinical history is “the essence of delivering effective and efficient care.” He wrote that the “once-in-a-generation” COVID-19 pandemic has accelerated the need for improvements in public health infrastructure, health technology services, and care delivery models and “reinforced the significant impact that complex and often confusing EHR systems, and the fragmentation of patient health data, have on delivering effective care.”
While the collaboration between Ascension and Google began in 2018, Conrado said “remarkable” progress was made on Care Studio this past year.
Conrado did not state how long the clinical pilot of Care Studio would last but emphasized that the technology will be enhanced with additional features and improvements based on feedback from pilot clinicians. Ultimately, the clinical search tool will be made available to all caregivers across Ascension’s 2,600 sites of care, including 145 hospitals and more than 40 senior living facilities in 19 states and the District of Columbia.
Clinical laboratories should welcome this development. Any software tool or information technology that allows clinical laboratory test data to move across different EHRs will help interoperability.
Media reports in the United Kingdom cite bad timing and centralization of public health laboratories as reasons the UK is struggling to meet testing goals
Clinical pathologists and medical laboratories in UK and the US function within radically different healthcare systems. However, both countries faced similar problems deploying widespread diagnostic testing for SARS-CoV-2, the novel coronavirus that causes COVID-19. And the differences between America’s private healthcare system and the UK’s government-run, single-payer system are exacerbating the UK’s difficulties expanding coronavirus testing to its citizens.
The Dark Daily reported in March that a manufacturing snafu had delayed distribution of a CDC-developed diagnostic test to public health laboratories. This meant virtually all testing had to be performed at the CDC, which further slowed testing. Only later that month was the US able to significantly ramp up its testing capacity, according to data from the COVID Tracking Project.
However, the UK has fared even worse, trailing Germany, the US, and other countries, according to reports in Buzzfeed and other media outlets. On March 11, the UK government established a goal of administering 10,000 COVID-19 tests per day by late March, but fell far short of that mark, The Guardian reported. The UK government now aims to increase this to 25,000 tests per day by late April.
This compares with about 70,000 COVID-19 tests per day in
Germany, the Guardian reported, and about 130,000 per day in the US
(between March 26 and April 14), according to the COVID Tracking Project.
“Ministers need to explain why the NHS [National Health Service] is not testing to capacity, why we are falling behind other countries, and what measures they will put in place to address this situation as a matter of urgency,” MP Keir Starmer (above) said in Parliament in late March, The Guardian reported. (Photo copyright: The Guardian.)
What’s Behind the UK’s Lackluster COVID-19 Testing
Response
In January, when the outbreak first hit, Public Health England (PHE) “began a strict program of contact tracing and testing potential cases,” Buzzfeed reported. But due to limited medical laboratory capacity and low supplies of COVID-19 test kits, the government changed course and de-emphasized testing, instead focusing on increased ICU and ventilator capacity. (Scotland, Wales, and Northern Ireland each have separate public health agencies and national health services.)
Later, when the need for more COVID-19 testing became
apparent, UK pathology laboratories had to contend with global shortages of
testing kits and chemicals, The Guardian reported. At present, COVID-19 testing
is limited to healthcare workers and patients displaying symptoms of pneumonia,
acute
respiratory distress syndrome, or influenza-like illness, PHE stated in “COVID-19:
Investigation and Initial Clinical Management of Possible Cases” guidance.
Another factor that has limited widespread COVID-19 testing is the country’s highly-centralized system of public health laboratories, Buzzfeed reported. “This has limited its ability to scale and process results at the same speed as other countries, despite its efforts to ramp up capacity,” Buzzfeed reported. Public Health England, which initially performed COVID-19 testing at one lab, has expanded to 12 labs. NHS laboratories also are testing for the SARS-CoV-2 coronavirus, PHE stated in “COVID-19: How to Arrange Laboratory Testing” guidance.
Sharon Peacock, PhD, PHE’s National Infection Service Interim Director, Professor of Public Health and Microbiology at the University of Cambridge, and honorary consultant microbiologist at the Cambridge clinical and public health laboratory based at Addenbrookes Hospital, defended this approach at a March hearing of the Science and Technology Committee (Commons) in Parliament.
“Laboratories in this country have largely been merged, so we have a smaller number of larger [medical] laboratories,” she said. “The alternative is to have a single large testing site. From my perspective, it is more efficient to have a bigger testing site than dissipating our efforts into a lot of laboratories around the country.”
Writing in The Guardian, Paul Hunter, MB ChB MD, a microbiologist and Professor of Medicine at University of East Anglia, cites historic factors behind the testing issue. The public health labs, he explained, were established in 1946 as part of the National Health Service. At the time, they were part of the country’s defense against bacteriological warfare. They became part of the UK’s Health Protection Agency (now PHE) in 2003. “Many of the laboratories in the old network were shut down, taken over by local hospitals or merged into a smaller number of regional laboratories,” he wrote.
US Facing Different Clinical Laboratory Testing Problems
Meanwhile, a few medical laboratories in the US are now contending with a different problem: Unused testing capacity, Nature reported. For example, the Broad Institute of MIT and Harvard in Cambridge, Mass., can run up to 2,000 tests per day, “but we aren’t doing that many,” Stacey Gabriel, PhD, a human geneticist and Senior Director of the Genomics Platform at the Broad Institute, told Nature. Factors include supply shortages and incompatibility between electronic health record (EHR) systems at hospitals and academic labs, Nature reported.
Politico
cited the CDC’s narrow testing criteria, and a lack of supplies for collecting
and analyzing patient samples—such as swabs and personal protective equipment—as
reasons for the slowdown in testing at some clinical laboratories in the US.
Challenges Deploying Antibody Tests in UK
The UK has also had problems deploying serology tests designed to detect whether people have developed antibodies against the virus. In late March, Peacock told members of Parliament that at-home test kits for COVID-19 would be available to the public through Amazon and retail pharmacy chains, the Independent reported. And, Politico reported that the government had ordered 3.5 million at-home test kits for COVID-19.
However, researchers at the University of Oxford who had been charged with validating the accuracy of the kits, reported on April 5 that the tests had not performed well and did not meet criteria established by the UK Medicines and Healthcare products Regulatory Agency (MHRA). “We see many false negatives (tests where no antibody is detected despite the fact we know it is there), and we also see false positives,” wrote Professor Sir John Bell, GBE, FRS, Professor of Medicine at the university, in a blog post. No test [for COVID-19], he wrote, “has been acclaimed by health authorities as having the necessary characteristics for screening people accurately for protective immunity.”
He added that it would be “at least a month” before suppliers could develop an acceptable COVID-19 test.
In the United States, the Cellex COVID-19 test is intended for use by medical laboratories. As well, many research sites, academic medical centers, clinical laboratories, and in vitro diagnostics (IVD) companies in the US are working to develop and validate serological tests for COVID-19.
Within weeks, it is expected that a growing number of such
tests will qualify for a Food and Drug Administration (FDA) Emergency Use
Authorization (EUA) and become available for use in patient care.
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.
