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Title: What role does systems integration play in the laboratory and why is this important to address?

Author for citation: Shawn E. Douglas

License for content: Creative Commons Attribution-ShareAlike 4.0 International

Publication date: February 2024

Interoperability and systems integration

In order to answer this question, we first must discuss the concept of "interoperability," of which integration of other informatics systems is just one component. Interoperability is defined by the Healthcare Information and Management Systems Society (HIMSS) as “the ability of different information systems, devices and applications (‘systems’) to access, exchange, integrate and cooperatively use data in a coordinated manner, within and across organizational, regional and national boundaries” to, in the case of a laboratory, ensure timely, portable, and accurate analytical results (the "deliverable" of most laboratories). While HIMSS' definition is focused on the clinical realm, their definition is robust enough that it, at least in part, can be applied to laboratory-based organizations serving most industries.

Interoperability benefits and challenges show up elsewhere too. Take for example the value of phenotypes, a representation of the genetic analysis of the collective observable traits of an organism, traits caused by the interaction of its genome with the environment. The value of patient phenotyping data is increasingly useful in the fight against known and novel viruses, as well as a broad variety of non-viral diseases. As Ausiello and Shaw note, in order for medicine to advance and produce improved patient outcomes, "traditional clinical information must be combined with genetic data and non-traditional phenotypes and analyzed in a manner that yields actionable insights into disease diagnosis, prevention, or treatment." Whether it's identifying "the measurable phenotypic characteristics of patients that are most predictive of individual variation" in treatment outcomes for chronic pain or COVID-19, phenotypes have utility in the clinical sector.

Here again interoperability between EHRs and laboratory informatics systems comes into play. In a 2019 paper published by Zhang et al. in nph Digital Medicine, the topic of extracting patient phenotypes from laboratory test results fed into EHRs is addressed. The authors state that one of the more difficult aspects of their research is that while "[l]aboratory tests have broad applicability for translational research ... EHR-based research using laboratory data have been challenging because of their diversity and the lack of standardization of reporting laboratory test results." They add:

Despite the great potential of EHR data, patient phenotyping from EHRs is still challenging because the phenotype information is distributed in many EHR locations (laboratories, notes, problem lists, imaging data, etc.) and since EHRs have vastly different structures across sites. This lack of integration represents a substantial barrier to widespread use of EHR data in translational research.

The answer to the clinical and laboratory interoperability question is unclear. A 2019 article in the American Association for Clinical Chemistry's CLN Stat addressed remaining roadblocks, including lack of standards development, data quality issues, clinical data matching, lack of incentivizing health IT optimization, text-based reporting formats, differences in terminology, and HL7 messaging issues. They add that proposals from the Office of the National Coordinator for Health Information Technology (ONC) and the Centers for Medicare and Medicaid Services include possible fixes such as standardized application programming interfaces (API). They also note that middleware may pick up the slack in connecting more laboratory devices, rather than depending on the LIS to handle all the interfacing. On a more positive note, the Office of the National Coordinator for Health Information Technology (ONC) updated its Interoperability Standards Advisory (ISA) Vocabulary/Code Set/Terminology page in November to better "highlight critical public health interoperability needs on COVID-19 in an easily accessible way." Replying to the ONC, HIMSS's Senior Director Jeff Coughlin goes on to add:

There is a growing need to consider data exchange for home settings and considerations around device interoperability. There are a number of applications in use and this setting requires work across a number of systems (emergency medical services, hospital electronic health records, telemedicine system [synchronous and asynchronous] and, remote patient monitoring and device management). ISA should provide guidance on specific standards to assist in exchange with this setting."

Even so, it remains obvious that more work needs to be done in the development and standard use of clinical and laboratory informatics applications if the promise of personalized medicine and the need for improved disease testing and response are to be fulfilled. In particular, how we responsibly protect personal health information while putting its anonymized variants to beneficial use for disease testing and prevention remains a critical question that must be solved in order to better prepare for the next COVID-19.

The why and how of laboratory integration

Why should labs focus on interoperability and systems integration? Let's look at a few industries.

1. In the realm of clinical laboratories, improving interoperability among clinical informatics systems is recognized as an important step towards improving health outcomes. The National Academies of Sciences, Engineering, and Medicine had much to say on this topic in their 2015 publication Improving Diagnosis in Health Care:
   

   Improved interoperability across different health care organizations—as well as across laboratory and radiology information systems—is critical to improving the diagnostic process. Challenges to interoperability include the inconsistent and slow adoption of standards, particularly among organizations that are not subject to EHR certification programs, as well as a lack of incentives, including a business model that generates revenue for health IT vendors via fees associated with transmitting and receiving data.

   
   In particular, the National Academies discussed an additional concern, one that still causes issues today: interfaces between electronic health records (EHR) and the laboratory and other clinical information systems that feed medical diagnostic information into the EHRs. In particular, they found "the interface between EHRs and laboratory and radiology information systems typically has limited clinical information, and the lack of sufficiently detailed information makes it difficult for a pathologist or radiologist to determine the proper context for interpreting findings or to decide whether diagnostic testing is appropriate." EHR integration was also a problem at the peak of the COVID-19 pandemic. In early April 2020, a report from Nature revealed that academic research laboratories wanting to assist with COVID-19 testing efforts had at times been stymied by the incompatibility between academic informatics systems and hospital EHRs. Not only were hospitals using EHRs of differing types, but many of those EHRs were not designed to talk to other EHRs, let alone to academic and research laboratories' informatics systems. Combine this with strict account procedures and the costs of developing interfaces on-the-fly, more than a few medical systems turned away the offer of help from academic and research labs during the height of the pandemic. Had there been greater systems integration across these two essentially disparate lab types, it's possible even more academic laboratories with the necessary testing equipment could have assisted with running patient-based clinical testing. While this constitutes an extreme example, it's possible that a push for improved interoperability across the systems used in commercial clinical diagnostic labs and more academic clinical research labs could have other benefits, for example with improving the state of interdisciplinary research, diagnosis, and treatment of cancer.

As it turns out, HL7- and other standard-based interfaces have long been expensive for many vendors to implement