Advances in point-of-care testing and the importance of connectivity

point-of-care testing
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Felicia Longobardi of Abbott outlines key advances in point-of-care testing and how digital connectivity can be used to improve outcomes within healthcare.

In recent years, point-of-care testing (POCT) has become invaluable to healthcare professionals globally, and across more therapy areas than ever before. But one key aspect still to be unlocked is the huge potential of connectivity – matching the innovative new technology within POCT to the abundance of health data now available to create one seamless, efficient, and optimal healthcare experience, for professionals and patients alike.

Point-of-care and connectivity for seamless patient care

Point-of-care testing is a test performed at or near to the site of the patient – essentially it is a laboratory test conducted outside of the laboratory setting1. It offers a rapid turnaround time compared with traditional laboratory testing, with a potentially immediate impact on patient care1. Point-of-care testing improves patient outcomes with higher quality of care by providing immediate information to the physicians about the patient’s condition1.

The benefits of these types of rapid diagnostic tools are many – results are available immediately2-5, and practice workflow is improved, leading to operational and economic benefits3-5,7. For patients, point-of-care testing is more convenient compared with traditional laboratory testing and has been shown to increase patient satisfaction3-5,7. As a monitoring or screening tool, it can be used to support health screenings in those at risk of cardiovascular disease (CVD) and improve patient compliance with testing frequency3,7. There is now overwhelming evidence that POCT can offer significant strengthening of the diagnostic precision of clinicians in a wide variety of areas3,8-9.

POCT is estimated to be increasing by at least 10−12% per year, with some areas increasing by 30% per year1. However, connectivity – meaning the process by which POCT devices link with the laboratory or hospital information systems and electronic medical records – is not always established where POCT is adopted1. An open-access data management system has the potential to automatically validate and transfers patient results obtained from POCT devices to electronic medical records, monitor and manage data, POCT devices, and operators, and also links with wider health data (e.g., from patient ‘wearables’ technology for example)1. Connectivity allows testing operations in healthcare to be managed seamlessly and more effectively1.

The expanding reach of point-of-care diagnostics

Point-of-care testing has become available across a vast array of therapeutic areas, from HbA1c ‘finger-prick’ tests for monitoring glycaemic control in diabetes patients7, to C-reactive protein (CRP) testing to guide antibiotic prescribing6,9-10. More recently, it has become critical as a rapid diagnostic tool during the COVID-19 pandemic11.

But perhaps less well-known key areas in which POCT use is of particular value include, for example, in diabetic kidney disease (DKD), where there is a 49% higher health expenditure compared with patients with diabetes, but without kidney disease12. Regular screening of both albumin-creatine ratio (ACR) and estimated glomerular filtration rate (eGFR)12,13 is recommended at all stages in this patient group, especially as the degree of albuminuria (increased ACR) is associated with risk of cardiovascular disease (CVD), kidney disease progression and mortality14,15. Even in patients without diabetes, and without any background disease, ACR predicts all-cause mortality and cardiovascular mortality16, and can prove a useful screening tool for CKD and microvascular complications17,18.

Point-of-care testing is also of value for paediatricians in screening for familial hypercholesterolemia (FH). Approximately 90% of the 1.3 million Americans with FH are unaware of their condition, which can lead to premature atherosclerotic cardiovascular disease (ASCVD)19,20. The Centers for Disease Control and Prevention (CDC) defines FH as a Tier 1 genomic application (having significant potential for positive impact on public health)21. Yet implementation of evidenced based practices for FH screening is still suboptimal22-24. POCT desk top analysers could have great potential to improve outcomes in this area of paediatric healthcare.

There is also great potential benefit in terms of reducing cardiovascular mortality with POCT. According to the World Health Organization, 80% of premature deaths from heart attack and stroke could be avoided,25 and combined reduction in HbA1c, systolic blood pressure and lipids decrease CV events by 75%26. Point-of-care lipid panel testing can quickly help screen patients to identify if they may need a referral, on-going monitoring, or a discussion around lifestyle factors3.

Connectivity and data-driven healthcare transformation

So where does connectivity fit into all this? Digital data collection, utilisation of real-word data and personalised patient care are all contributing to the rapid development of a new healthcare landscape. Dramatic advances in data science, supported by a need to reduce healthcare costs and advances in digital tools are providing innovative opportunities. The unprecedented technological drive in the last decade, including advances in artificial intelligence (AI), and an abundance of medical data has allowed the healthcare industry to respond with a variety of innovations, including within the POCT space1.

Not only does POCT improve workflow optimisation3-5 but connectivity within a POCT system makes medical data available through multiple digital platforms for multiple healthcare stakeholders. The use of information systems directly interfaced with POCT devices or connected through a middleware, serve to ensure that results are transmitted without manual interventions as soon as they are generated. This fulfils the requirements of both accuracy and timeliness for optimising clinical decisions1.

Information collected by POCT devices and analysed by AI technology can enable personalised patient management and help in decision making, allowing far more effective use of data generated by POCT1. This increase of digital density and ‘Big Data’ collection can help create predicative algorithms via machine learning systems. This strategy could then be used to provide personalised solutions for patient management1. Connectivity in POCT also has an added benefit of fewer repeats ordered and make the service more efficient and cost effective1.

Advances in POCT devices mean that connectivity is already built in. Thanks to a direct network, POCT devices can transfer a variety of data, including results, sample types and analytes, to a centralised, secure network27. This means that healthcare professionals can access data at any time, transfer and email results, and manage patients seamlessly. Misidentified patients and out of range results can be monitored and flagged automatically.

Education for better implementation of POC systems

As we move towards a more digitally focused healthcare landscape, tools such as point-of-care testing will be invaluable. But the importance of effective implementation is fundamental, and digital connectivity is the backbone of this approach. One of the ways in which we, at Abbott, are contributing to this implementation is via education around POCT.

Our knowledge platform is an educational resource for healthcare professionals, providing professionally accredited learning on POCT. Working with an external expert faculty, content covers multiple clinical disciplines, including respiratory health, diabetes, and cardiovascular disease, and provides a range of multi-media learning options. Learners can access content by registering (for free) online via desktop, mobile or tablet.

Abbott – A Leader in Rapid Point-of-Care Diagnostics.


  1. Erasmus, et al. Connectivity strategies in managing a POCT service. EJIFCC. 2021;32(2):190-194
  2. Ivaska, et al. Accuracy and feasibility of point-of-care white blood cell count and C-reactive protein measurements at the pediatric emergency department. PLoS ONE. 2015;10(6):e0129920
  3. El Osta, et al. Does use of point-of-care testing improve cost-effectiveness of the NHS Health Check programme in the primary care setting? A costminimisation analysis. BMJ Open. 2017;7:e015494
  4. Plüddemann, et al. Point-of-care testing for the analysis of lipid panels: primary care diagnostic technology update. Br J Gen Pract. 2012;62(596):e224-e226
  5. Patzer, et al. Implementation of HbA1c point of care testing in 3 german medical practices: impact on workflow and physician, staff, and patient satisfaction. J Diabetes Sci Technol. 2018;12(3):687-694
  6. Cook, et al. Respiratory tract infections (RTIs) in primary care: narrative review of C reactive protein (CRP) point-of-care testing (POCT) and antibacterial use in patients who present with symptoms of RTI. BMJ Open Resp Res. 2020;7:e000624
  7. Crocker, et al. Implementation of point-of-care testing in an ambulatory practice of an academic medical center. Am J Clin Pathol. 2014;142(5):640-6
  8. Apple, et al. Implementation of high-sensitivity and point-of-care cardiac troponin assays into practice: some different thoughts. Clin Chem. 2021;67(1):70-78
  9. O’Brien, et al. EUnetHTA report 2019. Rapid assessment on other health technologies using the HTA Core Model for Rapid Relative Effectiveness Assessment. C-reactive protein point-of-care testing (CRP POCT) to guide antibiotic prescribing in primary care settings for acute respiratory tract infections (RTIs). EUnetHTA Project ID: OTCA012
  10. Verbakel, et al. Impact of point-of-care C reactive protein in ambulatory care: a systematic review and meta-analysis. BMJ Open. 2019;9:e025036
  11. Chau, et al. COVID-19 clinical diagnostics and testing technology. Pharmacotherapy. 2020;40(8):857-868
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  16. Jörgensen, et al. The combined effect of albuminuria and inflammation on all-cause and cardiovascular mortality in nondiabetic persons. J Intern Med. 2008;264(5):493-501
  17. Bakke, et al. Type 2 diabetes in general practice in Norway 2005–2014: moderate improvements in risk factor control but still major gaps in complication screening. BMJ Open Diab Res Care. 2017;5:e000459
  18. Gasparini, et al. Prevalence and recognition of chronic kidney disease in Stockholm healthcare. Nephrol Dial Transplant. 2016;31(12):2086-2094
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  20. Singh, et al. Familial hypercholesterolemia among young adults with myocardial infarction. J Am Coll Cardiol. 2019;73(19):2439-2450
  21. CDC. Genomics & Precision Health. Tier 1 genomic application toolkit for public health departments. Available at:
  22. Knowles, et al. Cascade screening for familial hypercholesterolemia and the use of genetic testing. JAMA. 2017;318:381-382
  23. Lee, et al. New case detection by cascade testing in familial hypercholesterolemia: A systematic review of the literature. Circ Genom Precis Med. 2019;12:e002723
  24. Ferranti, et al. Cholesterol screening and treatment practices and preferences: a survey of united states pediatricians. J Pediatr. 2017;185:99-105
  25. World Health Organisation. The top 10 causes of death. 2018. Available from:
  26. Consentino, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J 2019;41(2):255-323
  27. Nichols, et al. AACC Guidance document on management of point-of-care testing. J Appl Lab Med. 2020;5(4):762-787

This article is from issue 20 of Health Europa Quarterly. Click here to get your free subscription today.

Contributor Details

Felicia Longobardi

EMEA Integrated Business Operations & Marketing Director
Abbott Rapid Diagnostic Cardiometabolic
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