Automation, integration, and digital transformation – Keys to benchmarking in a smart core lab

The implementation of total lab automation (TLA), middleware, artificial intelligence (AI)-assisted clinical decision making, and adoption of paperless workflows is instrumental in the transformation of the laboratory, more specifically, influencing clinical validation, procedure efficiency, data handling, data analysis, and much more. Laboratory IT functionalities help us in sample tracking, sample archiving, accounting of tests, audit trail, auto validation, critical result reporting (e.g., auto notification to clinician/nursing staff), data export, generation of monthly statistics reports, inventory management, moving averages, real-time TAT monitoring, indices interpretation, serum indices interpretation, etc. AI helps in computing risk stratification score of laboratory data and clinical data, using expert system and evidence-based guidelines. Increasing cost-containment pressures make the application of this technology highly approachable.

Rapid changes in diagnostic sector, coupled with parallel advances in smart core lab and digital transformation technology in diagnostic platforms, have stimulated the evolution of approaches for AI and robotic elements in routine laboratory process flow. Laboratory processes are streamlined to ensure provision of reliable and timely test results, appropriate alliance with brain-to-brain loop, thus enhancing quality of care and patient safety.

The new smart core laboratory is combining revenue generation with quality healthcare through automation, activity-based costing, LEAN improvement carbon footprint reduction. The concept of Lundberg loop, commonly known as the brain-to-brain loop for laboratory testing originates from the brain of the primary care physician, who is involved in selecting the laboratory tests and ends in the final reporting of the test result to the ordering physician. Basically, there are pre-pre-examination, pre-examination, examination, and post-examination. and post-post-examination steps involved in the total process. Total lab automation and digitization of total testing process brings process excellence in laboratory work flow.

There is a strong need to create a sustained technology policy and supply chain policy framework through a thrust on innovation and allocation of resources for fast pacing the development of the IVD sector. A strong diagnosis technology model needs to be formulated, which will ensure that technologically advanced healthcare is available to all sections of the population.

We also need to bridge the supply–demand gap by digitization. The challenges during first and second waves of Covid pandemic suggest focusing on the opportunities and bridging the supply–demand gap. Involvements require different level of investments – both short-term measures and long-term measures for incremental improvements in diagnostic care domain.

Diagnosticians, laboratory staff along with other key stake holders of the lab, like administrators, supply-chain professionals, distributors, IVD industry have responded to the challenge with initiatives to standardize and harmonize inventory management, resource allocation, cost of ownership, codification with the help of digital technology to drive supply chain efficiency during this pandemic time.

Mainly three key points, like codification, standardization, and global harmonization helped in efficiency building, when it came to supply chain. Efficiency depended on commercial excellence, demand management, and compliance management system to mitigate the impact of supply chain shortages. Digitization helped us to plug many parts, which were leaking in the supply chain, and finally it helped in building trust of our patients.

Digital and technology transformation journey with total lab automation in diagnostic platforms helped us to achieve the following:

• Reduction of time-traps;
• Optimization of staff motion;
• Elimination of unnecessary transportation;
• Improving customer satisfaction meter;
• Cost reduction;
• Enhanced employee productivity (e.g., samples per FTE);
• World-class external quality control performance score;
• Enhanced employee satisfaction meter;
• Improved patient outcome;
• Decrease in sample rejection rate;
• Six-Sigma score monitoring;
• Workspace utilization (e.g., tests per square meter);
• Turnaround time (TAT) optimization;
• Carbon footprint reduction;
• Water waste reduction;
• Elimination of non-value-added (NVA) steps;
• Verifying the business value-added (BVA) steps;
• Reduction of complexity in process work flow;
• Decrease in error rates;
• Reduce number of reruns;
• Enhanced operational productivity and confidence, resulting in patient satisfaction.

Efficiently managing intensifying pressures is critical to the sustainability of laboratory management, and requires new strategies to reduce cost burden, while maintaining quality. Increasing cost-containment pressures makes the application of this technology highly approachable.

Hospitals can benefit from digital and technology transformation journey, both operationally and clinically. Lab automation and digitization can help our hospitals and laboratories deliver greater outcomes, increase stakeholder collaboration, and enhance communication between lab and administration. Timely reporting of diagnostic test results to clinicians and all stakeholders is essential for effective disease and public health management. The Smart Core Laboratory in Kokilaben Dhirubhai Ambani Hospital & Medical Research Institute is focused on delivering results in the most efficient way, in terms of quality, cost, speed, using the process of observe, document, think, act, repeat.

AI helps in computing risk stratification score of laboratory data and clinical data, using expert system and evidence-based guidelines. The clinical decision support solution help standardize care in your hospitals with a combination of informatics and change management.

Implementation of digital transformation with TLA in the laboratory improves revenues, suggests patient-specific next steps, tests utilization, improves quality, standardizes treatment protocols as per local and international guidelines, improves patient satisfaction, provides patient-specific interpretation and next steps, improves standardized care by flagging patients, applies risk algorithms and provides better interpretation.

Acknowledgement: Dr Varsha Vadera and Shuchi Singhal, Biochemistry & Immunology Team, Kokilaben Dhirubhai Ambani Hospital & Medical Research Institute, Mumbai.