One goal of these new functions is to streamline physician workflows. However, these new EHRs may interface differently with clinical laboratory information systems
Artificial intelligence (AI) developers are making great contributions in clinical laboratory, pathology, radiology, and other areas of healthcare. Now, Electronic Health Record (EHR) developers are looking into ways to incorporate a new type of AI—called “Generative AI”—into their EHR products to assist physicians with time-consuming and repetitive administrative tasks and help them focus on patient-centered care.
Generative AI uses complex algorithms and statistical models to learn patterns from collected data. It then generates new content, including text, images, and audio/video information.
According to the federal Government Accountability Office (GAO), generative AI “has potential applications across a wide range of fields, including education, government, medicine, and law” and that “a research hospital is piloting a generative AI program to create responses to patient questions and reduce the administrative workload of healthcare providers.”
Reducing the workload on doctors and other medical personnel is a key goal of the EHR developers.
Generative AI uses deep learning neural networks modeled after the human brain comprised of layers of connected nodes that process data. It employs two neural networks: a generator [generative network] which creates new content, and a discriminator [discriminative network] which evaluates the quality of that content.
The collected information is entered into the network where each individual node processes the data and passes it on to the next layer. The last layer in the process produces the final output.
Many EHR companies are working toward adding generative AI into their platforms, including:
As our sister publication The Dark Report points out in its December 26 “Top 10 Biggest Lab Stories for 2023,” almost every product or service presented to a clinical laboratory or pathology group will soon include an AI-powered solution.
“We believe that generative AI has the potential of being a personal assistant for every doctor, and that’s what we’re working on,” Girish Navani (above), co-founder and CEO of eClinicalWorks, told EHRIntelligence. “It could save hours. You capture the essence of the entire conversation without touching a keyboard. It is transformational in how it works and how well it presents the information back to the provider.” Clinical laboratory information systems may also benefit from connecting with generative AI-based EHRs. (Photo copyright: eClinicalWorks.)
Generative AI Can Help with Physician Burnout
One of the beneficial features of generative AI is that it has the ability to “listen” to a doctor’s conversation with a patient while recording it and then produce clinical notes. The physician can then review, edit, and approve those notes to enter into the patient’s EHR record, thus streamlining administrative workflows.
“The clinician or support team essentially has to take all of the data points that they’ve got in their head and turn that into a narrative human response,” Phil Lindemann, Vice President of Data and Analytics at Epic, told EHRIntelligence. “Generative AI can draft a response that the clinician can then review, make changes as necessary, and then send to the patient.”
By streamlining and reducing workloads, EHRs that incorporate generative AI may help reduce physician burnout, which has been increasing since the COVID-19 pandemic.
“Language models have a huge potential in impacting almost every workflow,” Girish Navani, co-founder and CEO of eClinicalWorks, told EHRIntelligence. “Whether it’s reading information and summarizing it or creating the right type of contextual response, language models can help reduce cognitive load.”
Generative AI can also translate information into many different languages.
“Health systems spend a lot of time trying to make patient education and different things available in certain languages, but they’ll never have every language possible,” Lindemann said. “This technology can take human language, translate it at any reading level in any language, and have it understandable.”
MEDITECH is working on a generative AI project to simplify clinical documentation with an emphasis on hospital discharge summaries that can be very laborious and time-consuming for clinicians.
“Providers are asked to go in and review previous notes and results and try to bring that all together,” Helen Waters, Executive Vice President and COO of MEDITECH, told EHRIntelligence. “Generative AI can help auto-populate the discharge note by bringing in the discrete information that would be most relevant to substantiate that narrative and enable time savings for those clinicians.”
Many Applications for Generative AI in Healthcare
According to technology consulting and solutions firm XenonStack, generative AI has many potential applications in healthcare including:
The technology is currently in its early stages and does present challenges, such as lack of interpretability, the need for large datasets and more transparency, and ethical concerns, all of which will need to be addressed.
“We see it as a translation tool,” Lindemann told EHRIntelligence. “It’s not a panacea, but there’s going to be really valuable use cases, and the sooner the community can agree on that, the more useful the technology’s going to be.”
Since generative AI can be used to automate manual work processes, clinical laboratories and anatomic pathology groups should be alert to opportunities to interface their LISs with referring physicians’ EHRs. Such interfaces may enable the use of the generative AI functions to automate manual processes in both the doctors’ offices and the labs.
This is important for clinical laboratory leaders to watch, because medical labs often interface with hospital EHRs to exchange vital patient data, a key component of complying with Medicare’s EHR incentive programs. If claims of interoperability are shown to be false, could labs engaged with those hospital systems under scrutiny be drawn into the DOJ’s investigations?
Violating the False Claims Act
In May, Coffey Health System (CHS), which includes Coffey County Hospital, a 25-bed critical access hospital located in Burlington, Kan., agreed to pay the US government a total of $250,000 to settle a claim that it violated the False Claims Act.
CHS’ former CIO filed the qui tam (aka, whistleblower) lawsuit, which allows individuals to sue on behalf of the government and share in monetary recovery. He alleged that CHS provided false information to the government about being in compliance with security standards to receive incentive payments under the EHR Incentive Program.
According to a DOJ press release, “the United States alleged that Coffey Health System falsely attested that it conducted and/or reviewed security risk analyses in accordance with requirements under a federal incentive program for the reporting periods of 2012 and 2013. The government contended that the hospital submitted false claims to the Medicare and Medicaid Programs pursuant the Electronic Health Records (EHR) Incentive Program.”
“Medicare and Medicaid beneficiaries expect that providers ensure the accuracy and security of their electronic health records,” said Stephen McAllister (above), United States Attorney for the District of Kansas, in the DOJ press release. “This office remains committed to protecting the federal health programs and to hold accountable those whose conduct results in improper payments.” (Photo copyright: US Department of Justice.)
The Recovery Act allocated $25 billion to incentivize healthcare professionals and facilities to adopt and demonstrate meaningful use (MU) of electronic health records by January 1, 2014. The federal Centers for Medicare and Medicaid Services (CMS) released the incentive funds when providers attested to accomplishing specific goals set by the program.
The website of the Office of the National Coordinator for Health Information Technology (ONC), HealthIt.gov, defines “meaningful use” as the use of digital medical and health records to:
Improve quality, safety, efficiency, and reduce
health disparities;
Engage patients and their families;
Improve care coordination and population and
public health; and
Maintain privacy and security of patient health
information.
The purpose of the HITECH Act was to address privacy and security concerns linked to electronic storage and transference of protected health information (PHI). HITECH encourages healthcare organizations to update their health records and record systems, and it offers financial incentives to institutions that are in compliance with the requirements of the program.
When eligible professionals or eligible hospitals attest to being in compliance with Medicare’s EHR incentive program requirements, they can file claims for federal funds, which are paid and audited by the Department of Health and Human Services (HHS) through Medicare and Medicaid.
Institutions receiving funds must demonstrate meaningful use
of EHR records or risk potential penalties, including the delay or cancellation
of future payments and full reimbursement of payments already received. In
addition, false statements submitted in filed documents are subject to criminal
laws and civil penalties at both the state and federal levels.
EHR Developers Under Scrutiny by DOJ
EHR vendors also have been investigated and ordered to make
restitutions by the DOJ.
In February, Greenway Health, a Tampa-based EHR developer, agree to pay $57.25 million to resolve allegations related to the False Claims Act. In this case, the government contended that Greenway obtained certification for its “Prime Suite” EHR even though the technology did not meet the requirements for meaningful use.
And EHR vendor eClinicalWorks paid the government $155 million to settle allegations under the False Claims Act. The government maintained that eClinicalWorks misrepresented the capabilities of their software and provided $392,000 in kickbacks to customers who promoted its product.
Legal cases such as these demonstrate that the DOJ will
pursue both vendors and healthcare organizations that misrepresent their
products or falsely attest to interoperability under the terms laid out by
Medicare’s EHR Incentive Program.
Clinical laboratory leaders and pathology groups should carefully
study these cases. This knowledge may be helpful when they are asked to create
and maintain interfaces to exchange patient data with client EHRs.
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