Industry
Life Sciences
Patient-centered Care Models Taking Center Stage in Life Sciences
Healthcare
Patient-centered Care: Health and Wellness Redefined
Solution
Data and Analytics
Harness the Power of Data and Analytics for better Business Outcomes
HIGHLIGHTS
- Technology has revolutionized the healthcare industry with initiatives like telemedicine, remote monitoring, epharmacy, and digital well-being monitoring apps.
- AI-driven multiomics is reshaping drug discovery, and recent innovations in big data analytics are improving patient care and enhancing patient longevity.
- The care continuum concept has gained tremendous momentum, owing to innovative and robust technologies such as point-of-care testing (POCT), artificial intelligence, virtual reality, and 3D bioprinting.
- A centralized and collaborative care model that associates the role of POCTs in the three mainstays of care—early at-home testing, advanced hospital testing, and continuous recovery and monitoring at home—is integral for quick and early at-home and lab diagnosis, appropriate treatments, personalized therapies, enhanced future patient journey, and continuous monitoring.
On this page
The role of POCTs in continuum care
The continuum care and patient management concept applies to an integrated healthcare system in which a patient is guided and looked after at every step.
With the help of POCTs, faster diagnosis and decision-making are possible today, even in resource-limited settings or in the absence of laboratory equipment. Home diagnostics is evolving fast as people realize the convenience of at-home testing kits and collection tests and how they can be safe from hospital-acquired infections (HAIs).
Newer cutting-edge techniques are emerging at break-neck speed, and several traditional POCTs developed during recent years are paving the way for next-generation POCTs. Advances in areas like microfluidics, multiomics and big data analytics, molecular assays, organ-on-a-chip (OOC) or lab-on-a-chip (LOC), biosensors, and bioimaging have brought out a visible paradigm shift in diagnostics offerings. Technology-based omics such as next-generation sequencing (NGS) and molecular and CRISPR-based diagnostics have enhanced personalized medicine, while AI-based omics have reshaped and revolutionized drug discovery processes.
The latest molecular POCT platforms and microfluidic devices have scored well over the traditional lateral flow assays (LFA) and tests owing to better sensitivity, specificity, and advanced data processing capabilities with real-time insights. Undoubtedly, we are witnessing an era of patient care transformation under the aegis of early diagnostic POCTs, advanced medical devices, AI-ML, multiomics, and precision medicine.
The key enabler of the care continuum
Digital transformation is the core driver across the healthcare spectrum.
With the adoption of technologies such as AI-ML, deep learning, and meta-learning for imaging analytics, biomarker discovery, metagenomics, wearables, sensors, and digital apps for continuum care, the healthcare sector has paved the way for next-generation POCTs. Concepts like the bio digital twin model and bioimaging are evolving tremendously. While the bio digital twin model is based on AI and multiscale modeling of organs, bioimaging involves multi-modalities like advanced X-rays, CT and PET scans, electron microscopy, molecular and mass spectrometry imaging to identify markers for various disease conditions, including analytics of histopathological images for predicting dosage combination and optimization.
The radiogenomics approach includes image analytics data and phenotype data to prepare statistically significant prediction models by deep learning for patients' stratification, pilot therapeutic strategies, and estimate clinical outcomes. Today, dedicated apps and portals are available where a healthcare provider (HCP) can process and upload the image generated by bioimaging. Proprietary AI-ML models can identify markers for several disease conditions and convey POCT-related risk assessment outcomes from multiple modalities.
Identifying the gaps
Despite the advances in digital technologies, other aspects such as regulatory, instrument connectivity, infrastructure, and issues around patient data can offset the convenience of POCTs.
Another concern is the level of training received by the healthcare professionals in using POCT equipment and diagnostic platforms and further interpreting the test results and preparing reports correctly. In situations like these, the doctors and clinical personnel are wary of referring to dubious reports which can ultimately hamper their clinical decision-making process and delay the treatment or therapy process.
Accuracy is sometimes compromised for portability. Commonly reported concerns for clinical chemistry analyzers and platforms are specificity, sensitivity issues, and biotin interferences. Poorly calibrated instruments and platforms also pose a big risk to the authenticity of the diagnostic reports generated. The absence of proper connectivity hampers the data transmissions and electronic health record (EHR) maintenance, delaying clinical decision-making. Incorrect, delayed, or poorly diagnosed clinical decisions can worsen the clinical outcomes for a patient and can be life-threatening.
A centralized approach to continuum care
An approach that highlights three mainstays of care with an understanding of how these co-exist, and what role POCTs play, is an essential requirement.
A collaborative continuum care model would need to consider advanced POCTs that can overcome the current hiccups, plug the gaps, and address the entire diagnostic value chain, including the evolution of roles of various stakeholders across the healthcare spectrum.
Patients can use home-based self-diagnostic kits for remote monitoring and to convey the findings to healthcare professionals at an early stage. In the acute stage, advanced POCTs generating clinical data from omics-based biomarkers, AI-supported image analytics, and precision diagnostics demand seamless workflows and infrastructure. The need for continuous monitoring is high during the rehabilitative phase, and this calls for uninterrupted bidirectional connectivity of POCT platforms and instruments, smooth mapping for effective clinical decision-making, and a centralized system on the cloud for quick and efficient data tracking and management.
Figure 1
Future patient journey across the care continuum
Figure 1
A collaborative model of the care ecosystem (Figure 1) based on home-based early kits, advanced POCTs, precision diagnostics, and digital health will improve monitoring and reliability. It will enable quicker diagnosis, more immediate treatments, and faster patient recovery. With this, the healthcare industry will be able to overcome the existing challenges of POCTs to a greater extent as it works on the principle of data centralization and ensures efficient connectivity across the diagnostics ecosystem. Caregivers and healthcare policymakers need this type of continuum care model, as it will further accentuate patient experience while strategically focusing on absolute wellness and complete care offerings.
