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Clinical Laboratories and Pathology Groups

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Clinical Laboratories and Pathology Groups

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Blockchain Technology Could Impact How Clinical Laboratories and Pathology Groups Exchange Lab Test Data

Insurers might use blockchain technology to enable instantaneous verification and interoperability of healthcare records, which could impact clinical laboratory payment systems

Medical laboratories and anatomic pathology groups are keenly aware that connected, secure, interoperable health records are critical to smooth, efficient workflows. However, the current often dysfunctional state of health information technology (HIT) in America’s healthcare system often disrupts the security and functionality of information exchange between hospital and ancillary practice patient record systems.

One solution to this could be blockchain technology. With its big data and abundant touchpoints (typically: insurer, laboratory, physician, hospital, and home care), the healthcare industry could be ripe for blockchain information exchanges. Blockchain might enable secure and trusted linkage of payer, provider, and patient data. But what exactly is blockchain technology and how might it impact your laboratory?

Blockchains Could Transform Healthcare

Blockchain refers to a decentralized and distributed ledger that enables the interface of computer servers for the purpose of making, tracking, and storing linked transactions.

“At its core, blockchain is a distributed system recording and storing transaction records. More specifically, blockchain is a shared, immutable record of peer-to-peer transactions built from linked transaction blocks and stored in a digital ledger,” explained risk-management group Deloitte in a report, which goes on to state:

  • “Blockchain technology has the potential to transform healthcare, placing the patient at the center of the healthcare ecosystem and increasing the security, privacy, and interoperability of health data. This technology could provide a new model for health information exchanges (HIE) by making electronic medical records more efficient, disintermediated, and secure.
  • “Blockchain relies on established cryptographic techniques to allow each participant in a network to interact (e.g., store, exchange, and view information), without pre-existing trust between the parties.
  • “In a blockchain system, there is no central authority; instead, transaction records are stored and distributed across all network participants. Interactions with the blockchain become known to all participants and require verification by the network before information is added, enabling trustless collaboration between network participants while recording an immutable audit trail of all interactions.”

Key principles of blockchain (above) demonstrate the decentralization of the healthcare data. In some ways, this resembles electronic health record (EHR) systems that feature federated databases, rather than centralized databases. (Image copyright: Deloitte.)

Instant Verifications and Authorizations at Point-of-Care

In a Healthcare Finance News (HFN) article, insurers acknowledged blockchain’s potential for information verification and authorizations in real-time, fast payments, and access to patient databases that could fulfill population health goals.

“Everybody that is part of a transaction has access to the network. There’s no need for an intermediary. Blockchain allows for verification instantly,” noted Chris Kay, JD, Senior Vice President and Chief Innovation Officer at Humana, in the HFN article.

At clinical laboratories, blockchain could enable nearly instantaneous verification of a patient’s health insurance at time of service. Blockchain also could enable doctors to review a patient’s medical laboratory test results in real-time, even when multiple labs are involved in a person’s care.

“Everyone has to have a node on the blockchain and have a server linked to the blockchain. The servers are the ones talking to one another,” explained Kay. “What’s really transformative about this is it takes the friction out of the system. If I see a doctor, the doctor knows what insurance I have because it’s on the network. All this is verified through underlying security software.”

Healthcare Obstacles to Overcome

Breaking down data silos and loosening proprietary holds on information can help healthcare providers prepare for blockchain. However, in our highly regulated industry, blockchain is at least five years away, according to blockchain experts in a Healthcare IT News (HIT News) article.

“We’re hearing that blockchain is going to revolutionize the way we interact with and store data. But it’s not going to happen tomorrow. Let’s find smaller problems we can solve as a starting point—projects that don’t have the regulatory hurdles—and then take baby steps that don’t require breaking down all the walls,” advised Joe Guagliardo, JD, Intellectual Property/Technology Attorney and Chair of the Blockchain Technology Group at Pepper Hamilton, a Philadelphia-based law firm, in the HIT News article.

Healthcoin: Rewarding Patients for Improved Biomarkers

One company has already started to work with blockchain in healthcare. Healthcoin is a blockchain-based platform aimed at prevention of diabetes, heart disease, and obesity. The idea is for employers, insurers, and others to use Healthcoin (now in pre-launch) to reward people based on biomarker improvements shown in medical laboratory tests.

Healthcoin’s Chief Executive Officer Diego Espinosa and Chief Operating Officer Nick Gogerty, founded the company in 2016 after Espinosa, who had been diagnosed with diabetes, made diet changes to reverse it, according to an article in Bitcoin Magazine.

“When I saw my blood labs, the idea for Healthcoin was born—shifting the focus of prevention to ‘moving the needle’ on biomarkers, as opposed to just measuring steps,” Espinosa told Bitcoin Magazine.

Blockchain Provides Security

What does blockchain provide that isn’t available through other existing technologies?  According to Deloitte, it’s security and trust.

“Today’s health records are typically stored within a single provider system. With blockchain, providers could either select which information to upload to a shared blockchain when a patient event occurs, or continuously upload to the blockchain,” Deloitte notes. “Blockchain’s security and ability to establish trust between entities are the reasons why it can help solve the interoperability problem better than today’s existing technologies.”

Should Clinical Laboratories Prepare for Blockchain?

It’s important to note that insurers are contemplating blockchain and making relevant plans and strategies. Dark Daily believes the potential exists for blockchain technology to both disrupt existing business relationships, including those requiring access to patient test data, and to create new opportunities to leverage patient test data in real-time that could generate new revenue sources for labs. Thus, to ensure smooth payments, medical laboratory managers and pathology group stakeholders should explore blockchain’s value to their practices.

—Donna Marie Pocius

 

Related Information:

Blockchain Opportunities for Health Care: A New Model for Health Information Exchanges

Blockchain Will Link Payer, Provider, Patient Data Like Never Before

Old Ways of Thinking Won’t Work for Blockchain, Experts Say

Blockchain-Styled Solutions for Healthcare on the Rise

Can Blockchain Give Healthcare Payers Better Analytical Insight?

Blockchain in Health and Life Insurance: Turning a Buzzword into a Breakthrough

Does Blockchain Have a Place in Healthcare?

University of Michigan Study Links Value-Based Care Programs to Lower Readmission Rates and $32 Million in Medicare Savings in 2015; Clinical Laboratories Play Critical Role

Meaningful use, accountable care organizations, and bundled payment initiatives work best together to reduce readmissions, UM research suggests

Ever since the Centers for Medicare and Medicaid Services (CMS) implemented the Hospital Readmission Reduction Program (HRRP) in 2012, healthcare organizations all over America have sought to prevent unnecessary hospital readmissions within 30 days of discharge. For some clinical laboratories, this meant performing precise microbiology testing to ensure patients are discharged with prescriptions for oral antibiotics in-hand to combat possible infections. Now, a recent study reports that the effort could be paying off, and clinical laboratories played a critical role.

Research performed at the University of Michigan (UM) has linked lower readmission rates under the HRRP to voluntary value-based programs. The three value-based programs the UM researchers identified as contributing to the successful lowering of hospital readmission rates are:

The UM researchers published their findings in the Journal of the American Medical Association (JAMA) Internal Medicine. It could be the first study to demonstrate that synergistic value-based reward programs facilitate healthcare improvement and efficiency. As opposed to HRRP financial penalties alone that is, according to a UM news release.

Researchers Had No Expectations of Payment Reform Programs

Researchers at UM found that all three programs operating together in 2015 (the last year included in the longitudinal study) resulted in about 2,400 fewer readmissions and a $32-million savings to Medicare, the UM release noted.

The team analyzed data on patients treated at 2,877 hospitals from 2008 through 2015 for:

Their source of information was publicly available Hospital Compare readmission data.

“We had no real expectations that hospitals’ participation in voluntary reforms would be associated with additional reductions in readmissions. We thought that it was just as likely that hospital participation in meaningful use, accountable care organization programs, or the Bundled Payment for Care [Improvement] Initiative may be distracting to hospitals, limiting readmissions reduction,” stated Andrew Ryan, PhD, in ACEPNow, a publication of the American College of Emergency Physicians (ACEP) in Irving, Texas. Ryan is an Associate Professor, Health Management and Policy, at UM’s School of Public Health.

More Participation Leads to Greater Reduction in Readmissions

Nevertheless, the UM researchers linked more reductions in readmissions based on common diagnoses to value-based “reward-style” programs than to HRRP financial penalties. And the more value-based programs a provider implemented, the greater reduction in hospital readmission rates, the study found.

Nearly all hospitals studied were participating in at least one of the value-based programs by 2015, as compared to no program participants in 2010, when the Affordable Care Act was signed into law, noted a Healthcare Dive article.

illustrates the reduction in hospital readmissions starting in 2012

The chart above from the Kaiser Family Foundation (KFF) illustrates the reduction in hospital readmissions starting in 2012, which multiple studies have linked to the CMS Hospital Readmission Reduction Program (HRRP). The rates, according to the KFF, are risk adjusted to account for age and certain medical conditions. (Image copyright: Kaiser Family Foundation.

For 56 providers that were not participating in value-based care programs by 2015, researchers found the following readmission reductions also were associated with HRRP:

  • 3% drop in heart failure readmissions;
  • 76% drop in heart attack readmissions; and
  • 82% decline in pneumonia readmissions.

For the majority of providers, however, escalating value-based care program participation resulted in greater readmission rate reductions, the study noted.

Readmission Reductions for Heart Failure Patients

Noting the influence of value-based programs, HealthcareDIVE and FierceHealthcare reported the following results for the heart-failure patients studied:

  • ACOs result in 2.1% annual readmission reduction;
  • MU participation attributed to a 2.3% drop in annual readmission reduction;
  • Involvement in all three programs (ACOs, MU, and bundled payments) result in the largest annual readmission declines for hospitals of 2.9%.

Readmission Reductions for Heart Attack, Pneumonia Patients

For myocardial infarction patients, the study showed these effects from value-based programs on readmission declines:

  • 7% from ACO launch;
  • 5% associated with MU; and
  • 2% readmission reductions when all programs were in effect.

For pneumonia patients, the research suggested these changes in readmission declines were associated with value-based programs:

  • 4% from ACO launch;
  • 4% due to MU; and
  • 9% when all programs were in effect.

The researchers advise that providers, aiming for quality improvement and cost savings, should leverage as many of these programs as possible.

“There is a reason to believe these [value-based] programs are reinforcing the broader push to value-based care. Our findings show the importance of a multi-pronged Medicare strategy to improve quality and value,” noted Ryan in the UM news release.

Clinical Laboratories Play Key Role in Reducing Readmissions

Accurate medical laboratory testing plays a critical role in the success of these hospital readmission reduction programs. Thus, all pathologists and laboratory personnel should congratulate themselves for a job well done. And commit to continuing their outstanding performance.

—Donna Marie Pocius 

Related Information:

Association Between Hospitals’ Engagement in Value-Based Reforms and Readmission Reduction in the Hospital Readmission Reduction Program

Voluntary Value-Based Health Programs Dramatically Reduce Hospital Readmissions

Value-Based Reforms Linked to Readmission Reductions

Hospitals Participating in Value-Based Programs Have Lower Readmission Rates

Study: Value-Based Care Programs Reduce Readmissions

Involving Patient’s Family in Discharge Process Linked to 25% Reduction in Hospital Readmissions

Integrating Caregivers at Discharge Significantly Cuts Patient Readmissions, Pitt Study Finds

Hospitals with Lowest 30-Day Readmission Rates Succeed at Reducing Rates by Improving Care Coordination and Monitoring of Patients After Discharge

Coverage of Alexion Investigation Highlights the Risk to Clinical Laboratories That Sell Blinded Medical Data

Despite blinding data and following protocols, a recent investigation in Bloomberg Businessweek shows that clinical laboratories can be at risk in deals with pharmaceutical and big data companies

While big data is transforming how healthcare is both researched and applied, it also offers opportunities for clinical laboratories to create additional revenue from the endless streams of data generated by diagnostic tests and genetic assays. However, these opportunities come at a cost.

Data mining and pharmaceutical companies are turning to medical laboratories for blinded data (patients’ names are removed) to aid in their research and marketing efforts. Although the data is blinded to adhere to consumer privacy protocols, a story on the biopharmaceutical company Alexion (NASDAQ:ALXN) in Bloomberg Businessweek shows how clinical laboratories may be at risk for civil and legal ramifications, as well as public relation concerns.

When Blinded Patient Data Is Not Blind

Despite requirements to anonymize medical data, the increased computing and data collection abilities of data mining companies make it possible to bridge gaps in information by collating multiple data sources. Companies then can make assumptions about the data with relative accuracy.

With Alexion’s drug Soliris, the blinded data was enough to locate healthcare professionals treating patients with paroxysmal nocturnal hemoglobinuria (PNH), a rare disease of the blood, and atypical hemolytic uremic syndrome (aHUS) a rare disease of the immune system.

Cover of the Bloomberg Businessweek issue containing the article on Pharmaceutical companies’ use of blinded patient data for marketing high-cost “orphan drugs” that were developed to treat just one specific rare disease. (Photo copyright: Bloomberg Businessweek.)

On the surface, this seems like an ideal example of how making clinical laboratory and pathology data available to companies can be beneficial to patients and a victory for healthcare.

However, the Bloomberg Businessweek article highlights a darker side of the issue, noting, “Alexion set out to persuade doctors to test more frequently for PNH and aHUS—and to find a way to glimpse these test results, which traditionally have been shared only among the patient, the doctor ordering the test, and the lab.”

Liability and Risk in Age of Big Data

By reaching out to doctors and encouraging them to route lab tests to preferred medical laboratories with which they allegedly had partnered, Alexion could collect information and compare it to their database to pinpoint opportunities to sell their orphan drug Soliris. An orphan drug contains a unique pharmaceutical agent that was developed to treat a specific rare disease.

Five clinical laboratory companies are named in the story. While these laboratories might have followed regulations and the partnerships might be legal, news stories such as these could result in public relations crises and damaged reputations.

According to the Bloomberg Businessweek article, Alexion is resolving legal or regulatory concerns in at least seven countries. Though there is no precedent for medical laboratories assuming liability or being implicated in the crimes of a company to which they sold blinded data, the possibility exists.

Increased Scrutiny as Privacy Becomes a Public Concern

Healthcare big data continues to unlock new opportunities and create new approaches in treating disease and improving health around the world. However, as the public gains awareness of how healthcare big data is collected, shared, and used, greater scrutiny of how the data is handled, and the parties involved, will likely follow.

Dark Daily reported on the balancing act faced by laboratories in a 2016 e-briefing titled, “Trading in Medical Data: Is this a Headache or an Opportunity for Pathologists and Clinical Laboratories?

That e-briefing cites a Scientific American article in which author Adam Tanner, a fellow at Harvard University’s Institute for Quantitative Social Science, states, “At present, the system is so opaque that many doctors, nurses, and patients are unaware that the information they record or divulge in an electronic health record, or the results from lab tests they request or consent to, may be anonymized and sold.”

In a similar story, Ancestry recently experienced how fast opinions can shift when certain online publications questioned the terms and conditions of the company’s AncestryDNA service. In a matter of days, the service went from an interesting example of consumer genomics to a trending topic on social media.

In the Slate article “Who Owns Your Genetic Data After a Home DNA Test?,” author Jacob Brogan notes, “Even if Ancestry maintains its current commitment to protecting its customers’ data, its willingness to profit from that information may raise red flags for the future of consumer genetic testing.”

While Ancestry might resolve its immediate troubles with an update to its terms of service governing how and when it sells the genetic information of its customers, the hit to the company’s reputation could continue to impact its business. This is something the five clinical lab companies affiliated with Alexion and named in the Bloomberg Businessweek story may be experiencing as well.

As competition increases and clinical laboratories work to cultivate and improve revenue streams and reduce costs, it remains important to stay ahead of trends—and public opinion—by choosing partnerships carefully and remaining transparent about how patient data is collected, shared or sold, and used.

—Jon Stone

Related Information:

When the Patient Is a Gold Mine: The Trouble With Rare-disease Drugs

Your Medical Data Is for Sale, and There’s Nothing You Can Do About It

How Data Brokers Make Money Off Your Medical Records

Who Owns Your Genetic Data After a Home DNA Test?

Big Data Projects at Geisinger Health Are Beginning to Help Physicians Speed Up Diagnosis and Improve Patient Care

While many of the major gains promised by electronic health records (EHRs) and big data remain elusive, Geisinger Health’s Unified Data Architecture demonstrates how big data might help healthcare providers and clinical laboratories optimize care, improve outcomes, and control costs as the technology evolves

Use of big data in healthcare gets plenty of hoopla these days. Many experts predict great things as clinical laboratory test data is pooled with other patient information and demographic data. But there are many technical problems to be overcome before the full potential of healthcare big data can be translated into ways that improve the health of individuals.

Big data in healthcare is essential to the success of both precision medicine and population health management. However, without the ability to consolidate other data sources and provide intuitive ways for healthcare providers to access, analyze, and utilize the data coming from the various sources, such as clinical laboratory and anatomic pathology test results, much of the data can be underutilized or overlooked.

Medical laboratories continue to generate increased amounts of data, much of which often finds its way into electronic health record (EHR) systems and other data silos. A Harvard Business Review (HBR) report from doctors at Geisinger Health in Pennsylvania shows how this data might be used.

Consolidating Data to Create Cohesive Snapshots of Patient Health

The HBR report attributes Geisinger’s ability to utilize big healthcare data to its Unified Data Architecture (UDA). According to a Healthcare Informatics article, Geisinger’s UDA was based on Hadoop and other open source software. According to the doctors who wrote the HBR report, “… pulling meaningful data aggregated from many sources back out of EHRs has historically been vexingly complex. The potential insight from these data are limited in practice by the shortcomings of traditional data repositories.”

Geisinger’s UDA addresses two key issues the Healthcare Informatics authors see as obstacles to the expanded, easier use of big healthcare data:

  1. Lack of ways to deal with unstructured patient notes that do not adhere to traditional database organizational structures; and
  2. Data silos created when multiple departments collect data but use separate storage systems.

Using natural language processing (NLP), the UDA system can pull critical information from long-form written reports or analyses.

Big data graphic above from Nuance, developer of intelligent systems for healthcare and other industries, illustrates the challenges involved in acquiring, sifting, managing, and utilizing big data in healthcare. (Graphic copyright: Nuance.)

Geisinger’s system connects nurses on the floor, medical technologists in the clinical laboratory, and surgeons in operating rooms to the same pools of data. However, it also pulls in data from external sources, such as pathology groups, other reference or medical laboratories, and even patient-worn mobile medical devices. The HBR report states, “The integration of data from Health Information Exchanges, clinical departmental systems (such as radiology and cardiology), patient satisfaction surveys, and health and wellness apps provides us with a detailed, longitudinal view of the patient.”

Big Data Helps Healthcare Professionals Spot Future Worries

Geisinger’s Abdominal Aortic Aneurysm (AAA) Close the Loop Program—named semi-finalists in Healthcare Informatics’ 2016 Innovator Awards Program—is an example of how NLP and data collation offers benefits often overlooked with traditional approaches.

Geisinger doctors found that AAAs typically are discovered during care for another condition. Often, the conditions for which the patient seeks care are more serious than the small AAA and it isn’t mentioned. While AAAs might be noted in patient records, healthcare providers typically do not look for the data. Thus, left untreated, a AAA can develop into a serious condition that could have been prevented.

NLP enables Geisinger doctors to analyze UDA data for warning signs of AAA and create follow-up and treatment plans that might otherwise remain overlooked. According to the HBR report, this program has led to 12 lifesaving operations to date that might otherwise have been missed.

Real-Time, Comprehensive Updates Offer Big Gains in Combating Sepsis

Big healthcare data shows potential for treating many life-threatening conditions, such as sepsis. Prompt treatment is essential to positive outcomes in sepsis cases. Physicians at Geisinger use the company’s UDA data to both pinpoint when sepsis indicators appeared, as well as to consolidate data from across a patient’s care continuum to optimize treatment.

Instead of sorting through disparate streams of data from various operational areas and reports, data is combined into a consolidated dashboard featuring real-time physiologic metrics, such as:

  • Blood pressure measurements;
  • Blood culture results; and
  • Antibiotic administration.

The HBR report notes, “By tracking, aggregating, and synthesizing all sepsis-patient data, we expect we will be able to both reduce the incidence of hospital-acquired sepsis and improve its management.”

Using Big Data to Track Surgical Supply Chains and Waste

With the unique cost and outcome aspects of each surgical case, and the differences in payouts from payers, creating big data for tracking the efficiency and waste of surgeries is difficult without a big picture view of the factors. Using their UDA, Geisinger can track the exact supplies used in an operation along with the outcome, recovery, cost, and follow-up data related to the procedure.

“This gives surgeons and administrators an important new view of how they perform comparatively from both a cost and outcome perspective,” noted the HBR report’s authors.

Big data is still a developing technology. Nevertheless, programs such as at Geisinger Health offer useful lessons into how data streaming from clinical laboratories, pathology assays, operating rooms, intensive care units, and even personal health-tracking devices might be combined to provide a unified patient record. That would make it possible for caregivers to use analytical tools to tailor each patient’s care and treatment to his or her specific conditions and physiology.

—Jon Stone

Related Information:

How Geisinger Health System Uses Big Data to save Lives

How Unleashing Trapped Clinical Data Has Saved Lives at Geisinger Health System

The 2016 Healthcare Informatics Innovator Awards Program: Semifinalists

Unified Data Architecture Allows Patient Insights

At Geisinger Health System, Advanced Analytics Pave the Way to Better Outcomes

New Geisinger Initiative Digs Deep into the Wild, Unstructured World of Big Data

Geisinger Reaps System-wide Benefits with Big Data Approach

Trends in Genomic Research That Could Impact Clinical Laboratories and Anatomic Pathology Groups Very Soon

Genomics is quickly becoming the foundational disruptor technology on which many new and powerful clinical laboratory tests and procedures will be based

Genomics testing has become accessible, affordable, and in some instances, life-saving. Clinical laboratories and pathology groups are handling more genomic data each year, and the trend does not appear to be slowing down. Here are current trends in genomic research that soon could be bringing new capabilities to medical laboratories nationwide.

Improved Data Sharing

Sometimes genetic tests don’t translate into better outcomes for patients because medical labs are limited in how they can share genomic data. Thus, experts from various disciplines are seeking ways to integrate genomic data sharing into the hospital and laboratory clinical workflow in a form that’s easily accessible to doctors. (more…)

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