Study findings highlight financial impact underinsured have on healthcare providers, including clinical laboratories and pathology groups
Commonwealth Fund’s 2024 Biennial Health Survey released in November shows that not only are Americans underinsured, but many are swimming in medical debt. This is not good news for clinical laboratories. Simply put, labs must collect deductibles, copays, and out of pocket amounts from insured patients. If the patient is underinsured, that means the lab probably has to collect more—even 100%—of total charges directly from the patient.
The study conducted between March and June of 2024 collected data from 8,201 respondents ages 18-64, and despite two of every three respondents carrying health insurance through their employers, one of every four is underinsured, according to a Commonwealth Fund news release.
A further 44% of respondents have medical debt, with one of every four calling their out-of-pocket payments “nearly unaffordable,” the news release notes. Additionally, one out of five had a gap in coverage during the year.
“Congress, employers, insurers, and healthcare providers all play a role in lowering costs and making care more affordable, so families can avoid debt and get the care they need to stay healthy,” said Sara R. Collins, PhD, lead study author and Commonwealth Fund Senior Scholar and Vice President for Health Care Coverage and Access and Tracking Health System Performance, in the news release.
Astute laboratory managers will look beyond the study’s face value and consider the profound impact such findings could have on their own labs.
“While having health insurance is always better than not having it, the findings challenge the implicit assumption that health insurance in the United States buys affordable access to care,” the Commonwealth Fund said of its 2023 study. This sentiment rings true in the Funds’ latest findings as well.
“The Affordable Care Act has covered 23 million people and cut the uninsured rate in half. But high costs are a serious problem for many Americans, regardless of the kind of insurance they have,” said Sara R. Collins, PhD (above), lead study author and Commonwealth Fund Senior Scholar and Vice President for Health Care Coverage and Access and Tracking Health System Performance, in a news release. Clinical laboratories and anatomic pathology groups are greatly affected by underinsured patients. (Photo copyright: Commonwealth Fund.)
Labs Often Must Collect Payments Upfront
Many patients are in high deductible health plans and may forgo or delay ordered lab tests. Labs collect patient deductibles, copays, and out-of-pocket expenses directly from patients. However, underinsured patients may be required to pay for 100% of the services they receive, requiring the lab to collect these payments upfront.
Underinsured patients already facing a mountain of debt may struggle to pay for lab services. The debt many owe is substantial. “Nearly half (48%) of all adults with medical debt owe $2,000 or more; one of five (21%) carry a staggering $5,000 or more in debt,” Commonwealth Fund noted in its study.
Thus, collecting money owed is proving to be a problem for healthcare providers. Patient collection rates are plummeting to 48%, with “providers writing off more bad debt from patients with insurance,” TechTarget reported.
“Lower patient collection rates left providers facing bad debt. The analysis showed that 1.54% was the bad debt write-offs as a percentage of total claim charges in 2023. Researchers note that the percentage may be small, but the total cash amount equated to over $17.4 billion last year,” TechTarget added.
Having some rather than no insurance is not the safety net for patients previously thought. When it comes to the insured, their debt “accounts for 53% of the estimated $17.4 billion that hospitals, health systems, and medical practices wrote off as bad debts in 2023,” Business Wire noted, citing data from Kodiak Solutions’ quarterly revenue cycle benchmarking report.
Delaying Critical Lab Tests
The challenges the insured face with debt impacts labs in the long run. A staggering 57% of survey respondents reported passing on needed care because they could not afford it, and of those, 41% said their health concerns worsened when they denied themselves that care, Commonwealth Fund noted.
Increasingly poor health means patients might struggle to collect sufficient income to pay for their now added expenses, further causing them to struggle to pay for anything insurance might not cover, such as doctor ordered lab tests.
The affect this has on hospitals and medical laboratories casts light on the healthcare marketplace as a whole. It’s a trend that needs to be further studied.
“Most hospital bad debt is associated with insured patients, and nearly one in three hospitals report over $10M in bad debt,” are two of the top five financial healthcare statistics reported by Definitive Healthcare in a 2023 report.
“Expanding patient collection strategies may be key to maximizing revenue and avoiding losses,” TechTarget suggested.
Possible Solutions
The Commonwealth Fund study made clear that employer-covered healthcare does not guarantee affordable care or that ample care will be provided. Possible solutions from the study called on policymakers to “expand coverage and lower costs for consumers.” It added that “extending enhanced premium tax credits and strengthening protections against medical debt could make coverage more protective and affordable.”
Until a solution can be found, it’s wise to stay abreast of this trend and how it can impact the bottom line of clinical laboratories and anatomic pathology groups nationwide.
Anatomic pathologists understand that, along with breast cancer, diagnostic testing for prostate cancer accounts for a high volume of clinical laboratory tests. Thus, a recent study indicating that a new artificial intelligence (AI)-based software tool can dramatically improve physicians’ ability to identify the extent of these cancers will be of interest.
“The study found that Unfold AI’s patient-specific encapsulation confidence score (ECS), which is generated based on multiple patient data points, including MRI scans, biopsy results, PSA [prostate-specific antigen] data, and Gleason scores, is critical for predicting treatment success,” an Avenda press release states. “These findings emphasize the importance of Unfold AI’s assessment of tumor margins in predicting treatment outcomes, surpassing the predictive capability of conventional parameters.”
“Unfold AI’s ability to identify tumor margins and provide the ECS will improve treatment recommendations and allow for less-invasive interventions,” said study co-author Wayne Brisbane, MD, a urologic oncologist and UCLA medical professor, in another press release. “This more comprehensive approach enhances our ability to predict treatment outcomes and tailor interventions effectively to individual patient needs.”
“This study is important because it shows the ability of AI to not only replicate expert physicians, but to go beyond human ability,” said study co-author Wayne Brisbane, MD (above), a urologic oncologist and UCLA medical professor, in a press release. “By increasing the accuracy of cancer identification in the prostate, more precise and effective treatment methods can be prescribed for patients.” Clinical laboratories that work with anatomic pathologists to diagnose prostate and other cancers may soon have a new AI testing tool. (Photo copyright: UCLA.)
How Unfold AI Works
To gauge the extent of prostate tumors, surgeons typically evaluate results from multiple diagnostic methods such as PSA tests and imaging scans such as MRIs, according to a UCLA press release. However some portions of a tumor may be invisible to an MRI, causing doctors to underestimate the size.
Unfold AI, originally known as iQuest, was designed to analyze data from PSA, MRI, fusion biopsy, and pathology testing, according to a company brochure. From there, it generates a 3D map of the cancer. Avenda’s website says the technology provides a more accurate representation of the tumor’s extent than conventional methods.
“Accurately determining the extent of prostate cancer is crucial for treatment planning, as different stages may require different approaches such as active surveillance, surgery, focal therapy, radiation therapy, hormone therapy, chemotherapy, or a combination of these treatments,” Brisbane said in the UCLA press release.
Putting AI to the Test
In the new study, the UCLA researchers enlisted seven urologists and three radiologists to review 50 prostate cancer cases. Each patient had undergone prostatectomy—surgical removal of all or part of the prostate—but might have been eligible for focal therapy, a less-aggressive approach that uses heat, cryotherapy, or electric shocks to attack cancer cells more selectively.
The physicians came from five hospitals and had a wide range of clinical experience from two to 23 years, the researchers noted in The Journal of Urology.
They reviewed clinical data and examined MRI scans of each patient, then “manually drew outlines around the suspected cancerous areas, aiming to encapsulate all significant disease,” the press release states. “Then, after waiting for at least four weeks, they reexamined the same cases, this time using AI software to assist them in identifying the cancerous areas.”
The researchers analyzed the physicians’ work, evaluating the accuracy of the cancer margins and the “negative margin rate,” indicating whether the clinicians had identified all of the cancerous tissue. Using conventional approaches, “doctors only achieved a negative margin 1.6% of the time,” the press release states. “When assisted by AI the number increased to 72.8%.”
The clinicians’ accuracy was 84.7% when assisted by AI versus 67.2% to 75.9% for conventional techniques.
They also found that clinicians who used the AI software were more likely to recommend focal therapy over more aggressive forms of treatment.
“We saw the use of AI assistance made doctors both more accurate and more consistent, meaning doctors tended to agree more when using AI assistance,” said Avenda Health co-founder and CEO Shyam Natarajan, PhD, who was senior author of the study.
“These results demonstrate a marked change in how physicians will be able to diagnose and recommend treatment for prostate cancer patients,” said Natarajan in a company press release. “By increasing the confidence in which we can predict a tumor’s margins, patients and their doctors will have increased certainty that their entire tumor is treated and with the appropriate intervention in correlation to the severity of their case.”
UCLA’s study found that AI can outperform doctors both in sensitivity (a higher detection rate of positive cancers) and specificity (correctly detecting the sample as negative). That’s relevant and worth watching for further developments.
Pathologists and clinical laboratory managers should consider this use of AI as one more example of how artificial intelligence can be incorporated into diagnostic tests in ways that allow medical laboratory professionals to diagnose disease earlier and more accurately. This will improve patient care because early intervention for most diseases leads to better outcomes.
Researchers note that many sources of errors associated with diagnostic testing involve how providers order tests and how specimens are handled
ECRI (Emergency Care Research Institute), a non-profit organization that focuses on healthcare quality and patient safety, has released results from a study which lays blame for most diagnostic errors on systemic issues that arise during clinical laboratory, radiology, and other diagnostic testing processes. These issues relate to “ordering, collecting, processing, obtaining results, or communicating results,” the organization stated in a news release.
“It’s a common misconception that if a patient has a missed or incorrect diagnosis, their doctor came up with the wrong hypothesis after having all the facts,” said ECRI President and CEO Marcus Schabacker MD, PhD, in the news release. “That does happen occasionally, but we found that was tied to less than 3% of diagnostic errors. What’s more likely to break the diagnostic process are technical, administrative, and communication-related issues. These represent system failures, where many small mistakes lead to one big mistake.”
The researchers based their analysis on reports of adverse patient safety events and “near-misses” submitted to ECRI and the Institute for Safe Medication Practices (ISMP) in 2023. Healthcare providers submitted the data from across the US, ECRI noted.
From a total of 3,014 patient safety events, ECRI determined that 1,011 were related to diagnostic errors. Then, it sorted the events based on “the appropriate step in the diagnostic process where the breakdown occurred,” according to the news release.
ECRI did not reveal how many errors were related to clinical laboratory testing as opposed to radiological or ultrasound imaging.
“The problem of diagnostic safety comes down to the lack of a systems-based approach,” said ECRI President and CEO Marcus Schabacker MD, PhD (above), in a news release. “Since there are multiple potential failure points, a single intervention is insufficient.” Diagnostic errors can also include imaging/radiology and other types of diagnostic procedures—not just clinical laboratory tests. (Photo copyright: ECRI.)
Where Errors Occur
According to ECRI’s analysis, the largest number of errors by far (nearly 70%) happened during the clinical laboratory testing process. Among these, “more than 23% were a result of a technical or processing error, like the misuse of testing equipment, a poorly processed specimen, or a clinician lacking the proper skill to conduct the test,” ECRI stated. “Another 20% of testing errors were a result of mixed-up samples, mislabeled specimens, and tests performed on the wrong patient.”
Outside the testing process, other errors occurred during monitoring and follow-up (12%) and during referral and consultation (9%).
One major factor behind diagnostic errors, ECRI noted, was miscommunication among providers and between providers and patients.
The organization also cited “productivity pressures that prevent providers from exploring all investigative options or from consulting other providers” as leading to diagnostic errors.
In some cases, providers who ordered lab tests delayed reviewing the results or the patients were not notified of the results.
“Referrals to specialists or requests for additional consultations can complicate the process, presenting more potential failure points,” ECRI noted.
Troubling Imaging Anecdotes, Previous Studies
The ECRI news release cites two de-identified patient stories, both related to imaging. One case involved a woman who “experienced abdominal pain and abnormal vaginal bleeding,” but a diagnosis of uterine cancer was delayed nearly a year. “MRIs were ordered, but not all the results were reviewed, as her symptoms worsened. Despite masses being detected on an ultrasound, a missed appointment and communication barriers delayed her diagnosis. She was finally diagnosed after severe pain led to hospitalization.”
In one “near-miss” incident, a patient did not receive an essential carotid ultrasound procedure prior to being scheduled for open-heart surgery. Staff caught the omission and canceled the surgery. A later ultrasound “revealed he would have had a catastrophic surgical outcome if the surgery had proceeded as scheduled,” ECRI stated.
Two earlier studies noted in the news release highlight the impact of diagnostic errors.
A 2017 study, published in the journal BMJ Quality Safety, estimated that diagnostic errors affect approximately 5% of US adults—a total of 12 million—each year. In that paper, the authors combined estimates from three observational studies that defined diagnostic error in similar ways.
“Based upon previous work, we estimate that about half of these errors could potentially be harmful,” the authors wrote.
And a 2024 study published in the same journal estimated that 795,000 Americans die or become permanently disabled each year due to misdiagnosis of dangerous diseases. “Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined,” the authors wrote.
Recommendations for Providers, Labs
ECRI advised that healthcare providers should adopt a “total systems safety approach and human-factors engineering” to reduce diagnostic errors. This is good advice for clinical laboratories as well.
Specific steps should include “integrating EHR workflows, optimizing testing processes, tracking results, and establishing multidisciplinary diagnostic management teams to analyze safety events,” the news release states.
Schabacker also advised patients to “ask questions to understand why their doctor is ordering tests, and are those tests urgent,” he said. “Schedule your appointments and tests quickly and follow up with your provider if you’re awaiting results. If possible, ask a family member or friend to join you in important appointments, to help ask questions and take notes.”
Clinical laboratory managers have been alerted to the involvement of lab testing in incidents of medical errors. This report by ECRI is more evidence of the gaps in care delivery that often contribute to medical error. Medical lab professionals may want to review the ECRI report to learn more about what the authors identify as the specific breakdowns in care processes that contribute to medical errors.
Findings may lead to new clinical laboratory biomarkers for predicting risk of developing MS and other autoimmune diseases
Scientists continue to find new clinical laboratory biomarkers to detect—and even predict risk of developing—specific chronic diseases. Now, in a recent study conducted at the University of California San Francisco (UCSF), researchers identified antibodies that develop in about 10% of Multiple Sclerosis (MS) patients’ years before the onset of symptoms. The researchers reported that of those who have these antibodies, 100% develop MS. Thus, this discovery could lead to new blood tests for screening MS patients and new ways to treat it and other autoimmune diseases as well.
The UCSF researchers determined that, “in about 10% [of] cases of multiple sclerosis, the body begins producing a distinctive set of antibodies against its own proteins years before symptoms emerge,” Yahoo Life reported, adding that “when [the patients] are tested at the time of their first disease flare, the antibodies show up in both their blood and cerebrospinal fluid.”
That MS is so challenging to diagnose in the first place makes this discovery even more profound. And knowing that 100% of a subset of MS patients who have these antibodies will develop MS makes the UCSF study findings quite important.
“This could be a useful tool to help triage and diagnose patients with otherwise nonspecific neurological symptoms and prioritize them for closer surveillance and possible treatment,” Colin Zamecnik, PhD, scientist and research fellow at UCSF, told Yahoo Life.
“From the largest cohort of blood samples on Earth, we obtained blood samples from MS patients years before their symptoms began and profiled antibodies against self-autoantibodies that are associated with multiple sclerosis diagnosis,” Colin Zamecnik, PhD (above), scientist and research fellow at UCSF, told Yahoo Life. “We found the first molecular marker of MS that appears up to five years before diagnosis in their blood.” These findings could lead to new clinical laboratory tests that determine risk for developing MS and other autoimmune diseases. (Photo copyright: LinkedIn.)
UCSF Study Details
According to the MS International Foundation Atlas of MS, there are currently about 2.9 million people living with MS worldwide, with about one million of them in the US. The disease is typically diagnosed in individuals 20 to 50 years old, mostly targeting those of Northern European descent, Yahoo Life reported.
To complete their study, the UCSF scientists used the Department of Defense Serum Repository (DoDSR), which is comprised of more than 10 million individuals, the researchers noted in their Nature Medicine paper.
From that group, the scientists identified 250 individuals who developed MS, spanning a period of five years prior to showing symptoms through one year after their symptoms first appeared, Medical News Today reported. These people were compared to 250 other individuals in the DoDSR who have no MS diagnosis but who all had similar serum collection dates, ages, race and ethnicities, and sex.
“The researchers validated the serum results against serum and cerebrospinal fluid results from an incident MS cohort at the University of California, San Francisco (ORIGINS) that enrolled patients at clinical onset. They used data from 103 patients from the UCSF ORIGINS study,” according to Medical News Today. “They carried out molecular profiling of autoantibodies and neuronal damage in samples from the 500 participants, measuring serum neurofilament light chain measurement (sNfL) to detect damage to nerve cells.
“The researchers tested the antibody patterns of both MS and control participants using whole-human proteomeseroreactivity which can detect autoimmune reactions in the serum and CSF,” Medical News Today noted.
Many who developed MS had an immunogenicity cluster (IC) of antibodies that “remained stable over time” and was not found in the control samples. The higher levels of sNfL in those with MS were discovered years prior to the first flare up, “indicating that damage to nerve cells begins a long time before symptom onset,” Medical News Today added.
“This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes,” the UCSF scientists wrote in Nature Medicine.
“We believe it’s possible that these patients are exhibiting cross reactive response to a prior infection, which agrees with much current work in the literature around multiple sclerosis disease progression,” Zamecnik told Yahoo Life.
It “validates and adds to prior evidence of neuro-axonal injury occurring in patients during the MS preclinical phase,” the researchers told Medical News Today.
Implications of UCSF’s Study
UCSF’s discovery is a prime example of technology that could soon work its way into clinical use once additional studies and research are done to support the findings.
The researchers believe their research could lead to a simple blood test for detecting MS years in advance and discussed how this could “give birth to new treatments and disease management opportunities,” Neuroscience News reported.
Current MS diagnosis requires a battery of tests, such as lumbar punctures for testing cerebrospinal fluid, magnetic resonance imaging (MRI) scans of the spinal cord and brain, and “tests to measure speed and accuracy of nervous system responses,” Medical News Today noted.
“Given its specificity for MS both before and after diagnosis, an autoantibody serology test against the MS1c peptides could be implemented in a surveillance setting for patients with high probability of developing MS, or crucially at a first clinically isolated neurologic episode,” the UCSF researchers told Medical News Today.
The UCSF discovery is another example of nascent technology that could work its way into clinical use after more research and studies. Microbiologists, clinical laboratories, and physicians tasked with diagnosing MS and other autoimmune diseases should find the novel biomarkers the researchers identified most interesting, as well as what changed with science and technology that enabled researchers to identify these biomarkers for development.
HIMSS names SMC a ‘world leader’ in digital pathology and awards the South Korean Healthcare provider Stage 7 DIAM status
Anatomic pathologists and clinical laboratory managers in hospitals know that during surgery, time is of the essence. While the patient is still on the surgical table, biopsies must be sent to the lab to be frozen and sectioned before going to the surgical pathologist for reading. Thus, shortening time to answer for frozen sections is a significant benefit.
This effort in surgical pathology is part of a larger story of the digital transformation underway across all service lines at this hospital. For years, SMC has been on track to become one of the world’s “intelligent hospitals,” and it is succeeding. In February, SMC became the first healthcare provider to achieve Stage 7 in the HIMSS Digital Imaging Adoption Model (DIAM), which “assesses an organization’s capabilities in the delivery of medical imaging,” Healthcare IT News reported.
As pathologists and clinical laboratory leaders know, implementation of digital pathology is no easy feat. So, it’s noteworthy that SMC has brought together disparate technologies to reduce turnaround times, and that the medical center has caught the eye of leading health information technology (HIT) organizations.
“The digital pathology system established by the pathology department and SMC’s information strategy team could be one of the good examples of the fourth industrial revolution model applied to a hospital system,” anatomic pathologist Kee Taek Jang, MD (above), Professor of Pathology, Sungkyunkwan University School of Medicine, Samsung Medical Center told Healthcare IT News. Clinical laboratory leaders and surgical pathologists understand the value digital pathology can bring to faster turnaround times. (Photo copyright: Samsung Medical Center.)
Anatomic Pathologists Can Read Frozen Sections on Their Smartphones
Prior to implementation of its 5G digital pathology system, surgeons and their patients waited as much as 20 minutes for anatomic pathologists to traverse SMC’s medical campus to reach the healthcare provider’s cancer center diagnostic reading room, Healthcare IT News reported.
Now, SMC’s integrated digital pathology system—which combines slide scanners, analysis software, and desktop computers with a 5G network—has enabled a “rapid imaging search across the hospital,” Healthcare IT News noted. Surgical pathologists can analyze tissue samples faster and from remote locations on digital devices that are convenient to them at the time, a significant benefit to patient care.
“The system has been effective in reducing the turnaround time as pathologists can now attend to frozen test consultations on their smartphone or tablet device via 5G network anywhere in the hospital,” Jean-Hyoung Lee, SMC’s Manager of IT Infrastructure, told Healthcare IT News which noted these system results:
TAT decreased from 20 minutes to 10 minutes.
Transferring scans of large frozen tissues up to three gigabyte in size is now possible through the 5G network.
Additionally, through the 5G network, pathologists can efficiently access CT scans and MRI data on proton therapy cancer treatments. Prior to the change, the doctors had to download the image files in SMC’s Proton Therapy Center, according to a news release from KT Corporation, a South Korean telecommunications company that began working with SMC on building the 5G-connected digital pathology system in 2019.
DIAM is an approach for gauging an organization’s medical imaging delivery capabilities. To achieve Stage 7—External Image Exchange and Patient Engagement—healthcare providers must also have achieved all capabilities outlined in Stages 5 and 6.
In addition, the following must also have been adopted:
The majority of image-producing service areas are exchanging and/or sharing images and reports and/or clinical notes based on recognized standards with care organizations of all types, including local, regional, or national health information exchanges.
The application(s) used in image-producing service areas support multidisciplinary interactive collaboration.
Patients can make appointments, and access reports, images, and educational content specific to their individual situation online.
Patients are able to electronically upload, download, and share their images.
“This is the most comprehensive use of integrated digital pathology we have seen,” Andrew Pearce, HIMSS VP Analytics and Global Advisory Lead, told Healthcare IT News.
SMC’s Manager of IT Planning Seungho Lim told Healthcare IT News the medical center’s goal is to become “a global advanced intelligent hospital through digital health innovation.” The plan is to offer, he added, “super-gap digital services that prioritize non-contact communication and cutting-edge technology.”
For pathologists and clinical laboratory leaders, SMC’s commitment to 5G to move digital pathology data is compelling. And its recognition by HIMSS could inspire more healthcare organization to make changes in medical laboratory workflows. SMC, and perhaps other South Korean healthcare providers, will likely continue to draw attention for their healthcare IT achievements.