Laboratory information system

Hospitals and labs around the world depend on a laboratory information system to manage and report patient data and test results.

A laboratory information system (LIS) is a software system that records, manages, and stores data for clinical laboratories. An LIS has traditionally been most adept at sending laboratory test orders to lab instruments, tracking those orders, and then recording the results, typically to a searchable database. The standard LIS has supported the operations of public health institutions (like hospitals and clinics) and their associated labs by managing and reporting critical data concerning "the status of infection, immunology, and care and treatment status of patients."

History of the LIS

Advances in computational technology in the early 1960s led some to experiment with time and data management functions in the healthcare setting. Company Bolt Beranek Newman and the Massachusetts General Hospital worked together to create a system that "included time-sharing and multiuser techniques that would later be essential to the implementation of the modern LIS." At around the same time General Electric announced plans to program a hospital information system (HIS), though those plans eventually fell through.

Aside from the Massachusetts General Hospital experiment, the idea of a software system capable of managing time and data management functions wasn't heavily explored until the late 1960s, primarily because of the lack of proper technology and of communication between providers and end-users. The development of the Massachusetts General Hospital Utility Multi-Programming System (MUMPS) in the mid-'60s certainly helped as it suddenly allowed for a multi-user interface and a hierarchical system for persistent storage of data. Yet due to its advanced nature, fragmented use across multiple entities, and inherent difficulty in extracting and analyzing data from the database, development of healthcare and laboratory systems on MUMPS was sporadic at best. By the 1980s, however, the advent of Structured Query Language (SQL), relational database management systems (RDBMS), and Health Level 7 (HL7) allowed software developers to expand the functionality and interoperability of the LIS, including the application of business analytics and business intelligence techniques to clinical data.

In the early 2010s, web-based and database-centric internet applications of laboratory informatics software changed the way researchers and technicians interacted with data, with web-driven data formatting technologies like Extensible Markup Language (XML) making LIS and electronic medical record (EMR) interoperability a much-needed reality. SaaS and cloud computing technologies have since further changed how the LIS is implemented, while at the same time raising new questions about security and stability.

The modern LIS has evolved to take on new functionalities not previously seen, including configurable clinical decision support rules, system integration, laboratory outreach tools, and support for point-of-care testing (POCT) data. LIS modules have also begun to show up in EMR and EHR products, giving some laboratories the option to have an enterprise-wide solution that can cover multiple aspects of the lab. Additionally, the distinction between an LIS and a laboratory information management system (LIMS) has blurred somewhat, with some vendors choosing to use the "LIMS" acronym to market their clinical laboratory data management system.

Purpose and functionality

An LIS is a software solution designed to allow end users to better manage a wide variety of operational and quality management aspects of the academic, government, and commercial clinical laboratories appearing in and around public, private, and mobile healthcare facilities. The reasons for adopting an LIS and other laboratory informatics solutions varies by laboratory, but a December 2019 survey by Medical Laboratory Observer, consisting of 273 respondents, is somewhat revealing of the common purposes for adopting an LIS. Ninety-five percent of respondents indicated they use it to streamline their electronic order entry and result management, with medical data connectivity being the second most popular use. Automation tools, customer relationship management, scheduling, inventory management, revenue management, quality management, and reporting were all also mentioned as important to users. When asked to select from five choices (or provide some other reason) in regard to what their top priority was in selecting an LIS, respondents indicated that their most important priority was providing data analysis mechanisms for all types of pathology, followed by multi-lab interoperability, integration with electronic medical records (EMRs), flexible laboratory management functionality, and real-time automated inventory management.

These responses help paint a picture of what a LIS can do, but there's definitely more to it. Through regulatory, market, patient, and technological pressures, many laboratories have decided that increasingly digitizing the laboratory makes sense in its efforts towards greater compliance, competitiveness, patient outcomes, and efficiency. An LIS deployment primarily focuses on specimen and patient management, data acquisition, and reporting activities; however, its scope can expand much further depending on the scientific discipline (e.g., clinical vs. anatomic pathology) or role the lab plays (e.g., commercial clinical diagnostics vs. government public health).

LIS functionality

An LIS can have a complex list of features, or it may have minimal functionality. Software developers with competent and experienced personnel usually do well with a collection of the required base features, plus any industry-specific features a laboratory may need. But not all developers get it right. The following is a list of LIS functionality that is considered by a variety of experts to be vital to almost any clinical diagnostic or research laboratory.

Test, experiment, and patient management

• specimen log-in and management, with support for unique IDs
• batching support
• barcode and RFID support
• specimen tracking
• clinical decision support, including test ordering tools and duplicate test checks
• custom test management
• event and instrument scheduling
• templates, forms, and data fields that are configurable
• analytical tools, including data visualization, trend analysis, and data mining features
• data import and export
• robust query tools
• document and image management
• project and experiment management
• workflow management
• patient management
• case management
• physician and supplier management

Quality, security, and compliance

• quality assurance / quality control mechanisms, including tracking of nonconformance
• data normalization and validation
• results review and approval
• version control
• user qualification, performance, and training management
• audit trails and chain of custody support
• configurable and granular role-based security
• configurable system access and use (log-in requirements, account usage rules, account locking, etc.)
• electronic signature support
• configurable alarms and alerts
• data encryption and secure communication protocols
• data archiving and retention support
• configurable data backups
• environmental monitoring and control

Operations management and reporting

• customizable rich-text reporting, with multiple supported output formats
• synoptic reporting
• industry-compliant labeling
• email integration
• internal messaging system
• revenue management
• instrument interfacing and data management
• instrument calibration and maintenance tracking
• inventory and reagent management
• third-party software and database interfacing
• mobile device support
• voice recognition capability
• results portal for external parties
• integrated (or online) system help
• configurable language

Discipline-specific LIS

Through the early 2010s, the laboratory information system had been roughly segmented into two broad categories (though other variations existed): the clinical pathology and anatomic pathology LIS.

In clinical pathology the chemical, hormonal, and biochemical components of body fluids are analyzed and interpreted to determine if a disease is present, while anatomic pathology tends to focus on the analysis and interpretation of a wide variety of tissue structures, from small slivers via biopsy to complete organs from a surgery or autopsy. These differences may appear to be small, but the differentiation in laboratory workflow of these two medical specialties led to the creation of different functionalities within LISs. Specimen collection, receipt, and tracking; work distribution; and report generation varies—sometimes significantly—between the two types of labs, requiring targeted functionality in the LIS. Other differences among these two disciplines include:

• Specific dictionary-driven tests are found in clinical pathology environments but not so much in anatomic pathology environments.
• Ordered anatomic pathology tests typically require more information than clinical pathology tests.
• A single anatomic pathology order may be comprised of several tissues from several organs; clinical pathology orders usually do not.
• Anatomic pathology specimen collection may be a very procedural, multi-step process, while clinical pathology specimen collection is routinely more simple.

Over time, the LIS has evolved to address a wide variety of other clinical disciplines, including toxicology, blood banking, molecular diagnostics, public health and epidemiology, and clinical research. Each has their own set of analyses, workflows, operational requirements, and regulatory considerations, in turn requiring specialty functionality in an LIS to address the needs of each. Examples include support for stain panels and histology worksheets in pathology, supporting surge capacity for high-priority analyses in public health, providing medication-based compliance monitoring and interpretive reporting for toxicology, and allowing for electronic crossmatch of human-based medical products in blood banking and transfusion.

Differences between an LIS and a LIMS

There is often confusion regarding the difference between an LIS and a LIMS. While the two laboratory informatics components are related, their purposes diverged early in their existences. Up until recently, the LIS and LIMS have historically exhibited a few key differences:

1. An LIS was traditionally designed primarily for processing and reporting data related to individual patients in a clinical setting. A LIMS was traditionally designed to process and report data related to batches of samples from drug trials, water treatment facilities, and other entities that handle complex batches of data.

2. An LIS would need to satisfy the reporting and auditing needs of hospital accreditation agencies, HIPAA, and other clinical medical practitioners. A LIMS, however, would need to satisfy good manufacturing practice (GMP) and meet the reporting and audit needs of the U.S. Food and Drug Administration and research scientists in many different industries.

3. An LIS was usually most competitive in patient-centric settings (dealing with "subjects" and "specimens") and clinical labs, whereas a LIMS was most competitive in group-centric settings (dealing with "batches" and "samples") that often deal with mostly anonymous research-specific laboratory data.

However, these distinctions began to fade somewhat in the early 2010s as some LIMS vendors began to adopt the case-centric information management normally reserved for an LIS, blurring the lines between the two components further. Thermo Scientific's Clinical LIMS was an example of this merger of the LIS with LIMS, with Dave Champagne, informatics vice president and general manager, stating: "Routine molecular diagnostics requires a convergence of the up-to-now separate systems that have managed work in the lab (the LIMS) and the clinic (the LIS). The industry is asking for, and the science is requiring, a single lab-centric solution that delivers patient-centric results." Abbott Informatics Corporation's STARLIMS product was another example of this LIS/LIMS merger. With the distinction between the two entities becoming less clear, discussions within the laboratory informatics community began to includes the question of whether or not the two entities should be considered the same. As of 2024, vendors continue to recognize the historical differences between the two products while also continuing to acknowledge that some developed LIMS are taking on more of the clinical aspects usually reserved for a LIS.

Regulations, standards, and best practices affecting LIS development and use

A LIS' development and use is affected by regulations, standards, and best practices such as:

• 21 CFR Part 11 Electronic records; Electronic signature: Regulated clinical-focused labs—particularly medical research labs—are expected to comply with U.S. Food and Drug Administration (FDA) regulations like 21 CFR Part 11, which address matters of software validation, data integrity, data retention, audit trails, signed records, and secured access to data. These matters pertain to software systems like the LIS, as well as other systems employed in modern clinical laboratories.
• ASTM E1578 Standard Guide for Laboratory Informatics: This standard is geared towards a variety of stakeholders having some sort of professional interest in laboratory informatics. It intends to educate on and recommend approaches to laboratory software development, acquisition, implementation, and maintenance, including as how they relate to an LIS.
• Clinical Laboratory Improvement Amendments (CLIA): These U.S.-based clinical laboratory requirements affect clinical laboratories at many touch points, designed to better ensure that analytical testing is accurate, precise, and timely. Software systems like the LIS can help these labs better meet CLIA requirements and goals towards quality. The LIS designed with CLIA requirements in mind should also be able to assist with the documentation and audit-readiness required for CLIA compliance.
• Good clinical laboratory practice (GCLP): GCLP takes good laboratory practice (GLP)— a quality- and data-driven approach to ensuring the safety, consistency, high quality, and reliability of developed and produced goods—and adds clinical elements found in CLIA, as well as from the College of American Pathologists (CAP) and the International Organization for Standardization's (ISO's) ISO 15189 standard (below). The objective behind them is "of providing a single, unified document that encompasses [investigational new drug] sponsor requirements to guide the conduct of laboratory testing for human clinical trials." GCLP has many touch points with an LIS, from workflow requirements to how a LIS is used.
• ISO/CAP 15189 Medical laboratories — Requirements for quality and competence: ISO 15189 specifies quality management approaches to clinical laboratory settings. It pulls inspiration from ISO/IEC 17025 while acknowledging the unique characteristics and needs of the clinical lab. The standard's requirements on laboratory need for addressing cybersecurity, system validation, and more apply directly to LMS development and implementation. Additional takes on ISO 15189 can be seen in CAP's CAP 15189 Accreditation Program, which delves into more granular detail of clinical laboratory work, looking at how specific tests are ran and their quality ensured through specific proficiency testing processes, whereas ISO 15189 "seeks to inform the processes from a broad perspective." Even labs providing clinical trials research services have begun turning to ISO/CAP 15189 accreditation, affecting their operations and the informatics systems they choose to employ.

See also

• Laboratory informatics
• Common LIS features

Further reading

• Association of Public Health Laboratories (May 2019). "Laboratory Information Systems Project Management: A Guidebook for International Implementations" (PDF). APHL. https://www.aphl.org/aboutAPHL/publications/Documents/GH-2019May-LIS-Guidebook-web.pdf. 

• Henricks, W.H. (9 October 2012). "LIS Basics: CP and AP LIS Design and Operations" (PDF). Pathology Informatics 2012. University of Pittsburgh. Archived from the original on 10 September 2015. https://web.archive.org/web/20150910050825/http://www.pathinformatics.pitt.edu/sites/default/files/2012Powerpoints/01HenricksTues.pdf.