Laboratory informatics is a specialized field that combines multiple disciplines to optimize operations for labs facing increasing competition and a changing technology landscape. It encompasses a range of tasks and systems designed to streamline processes, manage lab data, and facilitate data analysis and reporting.
Most labs use software like laboratory information management systems (LIMS), electronic laboratory notebooks (ELN), laboratory execution systems (LES), various data management and integration tools, and business solutions to support lab operations. However, managing these systems and other technologies in the lab as separate entities can lead to disjointed processes, redundant effort, and unexpected gaps in functionality.
A more effective approach is to execute a lab informatics program, which manages all these systems, as well as other key disciplines, within a unified lab informatics strategy. This strategy must be revised periodically and updated as the business, best practices, and technologies evolve.
The disciplines that make up the field of laboratory informatics
Anyone new to laboratory informatics, and even seasoned informatics veterans, might be surprised by how many disciplines are involved in this complex field today, including the management of people, processes, and the ecosystem of software vendors. Leading labs have a cohesive strategy that covers all these areas to ensure that lab processes are streamlined, technology is up-to-date, and everyone understands their unique roles.
People management
Labs require skilled personnel to operate effectively, but equally important are processes that help them perform their best. A lab informatics leader is responsible for confirming that software solutions are built with a straightforward user experience that enables these professionals to complete their tasks without confusion. Personnel also need training and development to use evolving lab systems proficiently. This is crucial for maintaining quality control, operational efficiency, and regulatory compliance.
When updating or implementing new lab systems, you must also ensure change management is in place. People management includes helping personnel overcome resistance to new systems, smoothing transitions, and minimizing disruptions to lab operations. Encouraging collaboration, communication, and teamwork is also key to continuous improvement and troubleshooting when there are challenges to be resolved.
Another critical task is managing access controls. Giving personnel only the access they must have to perform their roles helps maintain data integrity and protect sensitive data from unauthorized access.
Process management
When managing processes in the lab, it’s important to understand the business needs. These requirements should drive the direction of all activities to ensure alignment with the lab’s strategic goals. With an understanding of the business requirements, you’ll be better positioned to prioritize tasks, allocate resources, and focus on the processes that add the most value. For instance, a lab wanting to improve turnaround times for diagnostic tests should prioritize automation and streamlined workflows.
You’ll also want to:
- Build process maps to represent lab workflows. These will help with identifying bottlenecks, redundancies, and opportunities for optimization.
- Document the requirements of these processes to help ensure successful outcomes related to regulatory standards, quality benchmarks, and stakeholder expectations.
- Perform a capability analysis to assess the lab’s ability to perform processes effectively. This will help you make informed decisions about resource allocation, training needs, and investment in new technologies or methodologies.
- Implement automation in areas such as sample handling, analysis, and reporting.
Technology management
Managing the technology in a lab is another key responsibility for a lab informatics leader. Your lab’s software stack could consist of standalone components—such as LIMS, ELN, LES, and inventory management software—or be integrated to create an end-to-end solution. Each of these tools must be maintained, with updates performed promptly to ensure the lab does not experience downtime and is not vulnerable to a cyberattack.
Many labs implement artificial intelligence and machine learning (AI/ML) technologies to improve lab performance. AI/ML algorithms can identify patterns, predict outcomes, and provide insights based on the lab’s data. They can also monitor processes in real-time to ensure quality and compliance, detecting anomalies and suggesting corrective actions. Similarly, labs can use robotic process automation (RPA) to automate repetitive tasks, increasing efficiency and reducing errors.
Because lab businesses are constantly evolving to meet stakeholder demands and remain competitive, you’ll need to review your technology solutions regularly to ensure they continue to serve business requirements. If your analysis indicates gaps in the lab’s capabilities, you might have to extend your existing systems with new features or replace them with a more modern solution.
Data management
Laboratory informatics leaders are also responsible for safeguarding a lab’s valuable data. Using your knowledge of data science and engineering, you’ll want to ensure data is only accessible to authorized users and that errors are avoided as much as possible by automating systems to reduce manual input and unnecessary duplication.
Applying FAIR principles will mean data is easily findable, accessible, interoperable, and reusable, so it’s simpler to share information between systems within your lab or with other organizations if collaboration is one of your strategic goals. It will also help with traceability and auditability for regulatory reporting.
As part of your laboratory informatics strategy, you’ll want to assess your lab’s analytics and reporting capabilities. With sophisticated analytics, lab data can inform decision-making, support scientific discoveries, and help streamline operations. If your lab is a clinical lab, analytics are necessary to interpret complex diagnostic data and improve patient outcomes.
Governance
Labs need clear governance policies and procedures to maintain data integrity and security, and the trust of stakeholders and customers. Computer systems validation, for example, confirms that a computer system reliably does what it is designed to do. This type of governance is especially critical for labs that must maintain regulatory compliance.
You’ll need to document change control procedures and security controls. These will help the lab minimize the risk of downtime and unauthorized access to sensitive data, such as personal information and intellectual property.
Your lab’s governance policies must also address regulatory requirements, such as the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Keeping up-to-date with the latest regulations and standards is crucial. This means continuous education and training to ensure lab processes and systems remain compliant.
Ecosystem management
Managing the lab’s informatics ecosystem is another critical component of a laboratory informatics program. This includes managing vendor solutions—choosing the right vendor systems, negotiating contracts, and tracking performance against service-level agreements (SLAs).
A laboratory informatics leader should keep current with emerging best practices, such as lean principles. This will help you support efforts to refine lab workflows and processes. Other best practices commonly used in software development are known as the catalog of design patterns. Software built with creational, structural, and behavioral patterns uses common constructions, making it easier to maintain and extend. Understanding these patterns will help you confirm that your internal development efforts or those of external vendors provide a solid foundation for changes or new features as the lab grows.
Building a robust laboratory informatics program
A healthy laboratory informatics program will have a cohesive strategy for all these disciplines to ensure optimal lab performance. However, it’s not enough to create a strategy once. It needs to be a living document that evolves with the business. As the leader of the laboratory informatics program, you should reassess each area of the strategy periodically and update it to match new business requirements. Doing this could help your lab reduce costs, improve efficiency, and accelerate the development of innovative solutions that can change lives.
If your lab is currently focused on scaling the business, check out our previous post about how to scale successfully.
