Healthcare data: Leveraging potential to inform decision-making in the lab

The volume of healthcare data available is vast and is increasing. It is estimated that approximately 30% of the world’s data volume is generated by the healthcare industry, and it is predicted to continue to grow at a faster rate than data from manufacturing, financial services, and media and entertainment.¹

Keeping up with this constantly expanding data is challenging. Added to this is the fact that the data itself is not standardized and can come from a variety of sources, be in different formats and locations, and have inconsistent definitions e.g., when physicians have differing ideas on diagnostic criteria. All of these factors combine to create a complex data environment.² However, the enormous potential for use makes this a challenge some are determined to solve. 

At this year’s Healthcare Information and Management Systems Society (HIMSS) Global Health Conference & Exhibition, Frani Gerst, Global Head of Marketing, Roche Information Solutions, Lori Roche, Marketing Development Executive, Roche Information Solutions, Nam Tran Ph.D., M.S., HCLD (ABB), CLS, MLS (ASCP)cm, FADLM Professor and Senior Director of Clinical Pathology, University of California, Davis, and Jina Forys MBA, MLS (ASCP) Director, Acute Laboratory, University of Minnesota Medical Center discussed how this data can be leveraged to inform decision-making in a lab setting.

Although many of us feel familiar with healthcare data through our access to apps or monitoring devices such as wearables, the data we receive is a distilled and curated picture of what is available. Behind the patient interface, there is a wealth of information where raw data has yet to be refined. “We often feel patient facing data is most important because of its visibility, but in reality, this is the tip of the iceberg and there’s far more healthcare data hidden from patients and bedside providers and only seen or used by lab personnel,” says Dr. Nam Tran PhD. 

Within the laboratory setting there are two data areas Dr. Tran believes hold untapped value: 

• Analyzer-specific data: This information is only visible to the laboratory or even the manufacturer, but contains data such as raw analytical data, specimen quality, reagent data and operator data 

• LIS and Middleware data: This information is semi-visible to select people such as laboratory and IT, but is not always accessible to others. It contains data including testing results, quality control data, lab operational data, and test utilization data 

Frani Gerst also points out the potential use of lab specific data in healthcare. “If you look at lab data, it is estimated to influence 60 to 70% of medical decisions.³ That statistic is very, very powerful when you think about the opportunity we have to leverage the gold mine of data that’s already in the laboratory, and to start to drive significant decision-making, not only for the operation but for the patients that we all serve,” she says.

Although the potential of this healthcare data is not yet being fully met, Jina Forys has already seen the impact it can have on efficiencies in the lab. 

With a goal for centralized testing Jina and her team needed to know that if more core testing was run at one main lab, it wouldn’t impact any acute testing required at that site. “We can’t let the volume from the whole system slow us down, so how do we feel confident that we would still be able to get our acute test results out quickly?” she says. 

The lab was able to look at instrument utilization data to determine at what capacity the analyzers were operating, which confirmed they could add volume without impacting performance. Jina notes, “We were able to bring all of our infectious disease testing from our specialty lab up into our core lab, which reduced the total cost.”

Another way Jina and her team have been able to utilize data has directly affected the performance of care teams. Turnaround times for test results are critical for care teams in the emergency room as Jina explains, “If the lab is taking too long, they can’t discharge patients, they can’t admit patients, they can’t make care decisions for their patients.”

By monitoring the turnaround times of testing, the team noticed a dip in performance at the same time each day. On further analysis of data from their analyzers, they realized that increased test volume from hospital rounds coincided with daily maintenance on one of two available analyzers, which meant the lab had less capacity at a critical time. “It was so obvious”, Jina says, “Once we saw the picture we were able to quickly share this information with our team and adjust the daily maintenance to a different time.”

Frani Gerst agrees that the power of data is in providing this clarity. She notes, “It’s not always obvious, but in many cases just having the visibility gives you the opportunity to make the right decision. That is why we at Roche are so pleased to partner with our customers to solve challenges in this space.” So that more institutions are able to leverage data in the best way possible, Dr. Tran believes there are some key barriers to be addressed. 

• Data access: In order to leverage raw data, there needs to be more open access to systems and partnerships with manufacturers.
• Data communicability: There are still multiple formats of imagery influenced by radiology or pathology that have not been standardized yet. More standardization of data formats is necessary for better interoperability in the digital pathology world.
• Multiple platform types: Health systems are operating across multiple platform types and interfaces, but moving towards an ‘ecosystem’ based approach would allow data to transfer more seamlessly.
• Low visibility data: Although we are seeing some use, we need further solutions to create value of less visible data from analyzers and the LIS/middleware.

To start to overcome barriers and fully leverage data, Lori Roche says involving key stakeholders is critical. “It’s about knowing what the problem is and then navigating through it with IT teams and security teams to answer those questions and really understand what are their capabilities, what are their limitations? It’s about working side by side with teams to bring solutions forward,” she says. 

From lab teams consulting with IT teams to physicians training in clinical informatics to labs partnering with innovative vendors, a collaborative effort is required. Frani Gerst believes anything is possible if all stakeholders are working to meet a collective goal. “If the vendor, the physician, the lab, the hospital, and the care settings are focused on what’s best for the patient, that’s when we win,” she says.