News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel

News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel
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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

Hoping to Become Heavyweights in Healthcare Big Data, IBM Watson Health Teams Up with Siemens Radiology and In Vitro Diagnostics Businesses

Big data offers new opportunities for healthcare providers, clinical laboratories, and pathology groups, and this new alliance hopes to accelerate big data capabilities

Big data has the potential to deliver unprecedented insight into optimizing the patient care experience and managing outcomes for healthcare providers. That is particularly true for clinical laboratories, and pathology groups. Yet, with the sheer amount of data generated by today’s ever-expanding menus of diagnostic procedures, communicating this data between systems and analyzing data at high-levels still presents challenges.

To help healthcare organizations jumpstart their Big Data programs, key stakeholders are joining forces. One such alliance involves Siemens Healthineers and IBM Watson Health. In an October 2016 press release, the two organizations announced a five-year global strategic alliance aimed at helping healthcare professionals optimize value-based care that leverages increasingly complex data collected for use in precision medicine.

What should intrigue pathologists and medical laboratory managers about this new alliance is the fact that Siemens Healthineers owns two of the world’s largest businesses in radiology/imaging and in vitro (IVD). Thus, it can be expected that the alliance will be looking to identify ways to combine radiology data with clinical laboratory data that produce knowledge that can be applied to clinical care. (more…)

Unstructured Data Is a Target for New Collaboration Involving IBM’s Watson Health and Others; Could Help Pathologists and Radiologists Generate New Revenue

If this medical imaging collaborative develops a way to use the unstructured data in radiology images and anatomic pathology reports, it could create a new revenue stream for pathologists

Unstructured data has been regularly recognized as one Achilles heel for the anatomic pathology profession. It means invaluable information about the cancers and other diseases diagnosed by surgical pathologists are “locked up,” making it difficult for this information to be accessed in efforts to advance population health management (PHM) or conduct clinical studies.

Similarly, medical imaging has an essential role in the diagnosis of cancer and other diseases. And, like most anatomic pathology reports, medical imaging also is considered to be “unstructured” by data experts because it is not easily accessible by computers, reported Fortune magazine.

Unstructured Data in Anatomic Pathology and Radiology

Now one of the world’s largest information technology companies wants to tackle the challenge of unstructured data in radiology images. IBM (NYSE: IBM) Watson Health launched a global initiative involving 16 health systems, radiology providers, and imaging technology companies.

The Watson Health medical imaging collaborative is working to apply cognitive computing of radiology images to clinical practice. IBM aims to transform how physicians use radiology images to diagnose and monitor patients. (more…)

Two Lab Leaders Present Different Ways to Help Physicians Get Greater Value from Clinical Pathology Laboratory Testing

In response to healthcare’s transformation, a pathologist and a lab CEO describe two powerful ways that medical laboratories can collaborate with physicians, patients, health systems, and health insurers to deliver more value

DATELINE: Phoenix, Arizona—It may be appropriate that, with the pace of change heating up in both healthcare and the clinical laboratory industry, it was here in the hot Sonoran Desert that more than 500 medical laboratory professionals gathered last week for the annual Sunquest User Group Conference (SUG) hosted by Sunquest Information Systems. (more…)

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