Novel Opportunities for Improving the Quality of Preanalytical Phase. A Glimpse to the Future?

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The preanalytical phase is crucial for assuring the quality of in vitro diagnostics. The leading aspects which contribute to enhance the vulnerability of this part of the total testing process include the lack of standardization of different practices for collecting, managing, transporting and processing biological specimens, the insufficient compliance with available guidelines and the still considerable number of preventable human errors. As in heavy industry, road traffic and aeronautics, technological advancement holds great promise for decreasing the risk of medical and diagnostic errors, thus including those occurring in the extra-analytical phases of the total testing process. The aim of this article is to discuss some potentially useful technological advances, which are not yet routine practice, but may be especially suited for improving the quality of the preanalytical phase in the future. These are mainly represented by introduction of needlewielding robotic phlebotomy devices, active blood tubes, drones for biological samples transportation, innovative approaches for detecting spurious hemolysis and preanalytical errors recording software products.

1. Lippi G, Banfi G, Church S, Cornes M, De Carli G, Grankvist K, et al. Preanalytical quality improvement. In pursuit of harmony, on behalf of European Federation for Clinical Chemistry and Laboratory Medicine (EFLM) Working group for Preanalytical Phase (WG-PRE). Clin Chem Lab Med 2015; 53: 357-70.

2. Lippi G. Governance of preanalytical variability: travelling the right path to the bright side of the moon? Clin Chim Acta 2009; 404: 32-6.

3. Simundic AM. Preanalytical phase - an updated review of the current evidence. Biochem Med (Zagreb) 2014; 24: 6.

4. Foord AG, Gulland WG. Can Technology Eliminate Human Error? Process Saf Environ Prot 2006; 84: 171-3.

5. Oren E, Shaffer ER, Guglielmo BJ. Impact of emerging technologies on medication errors and adverse drug events. Am J Health Syst Pharm 2003; 60: 1447-58.

6. Lippi G, Simundic AM, Mattiuzzi C. Overview on patient safety in healthcare and laboratory diagnostics. Biochem Med (Zagreb) 2010; 20: 131-43.

7. Simundic AM, Lippi G. Preanalytical phase-a continuous challenge for laboratory professionals. Biochem Med (Zagreb) 2012; 22: 145-9.

8. Lippi G, Baird GS, Banfi G, Bölenius K, Cadamuro J, Church S, et al. Improving quality in the preanalytical phase through innovation, on behalf of the European Federation for Clinical Chemistry and Laboratory Medicine (EFLM) Working Group for Preanalytical Phase (WG-PRE). Clin Chem Lab Med 2017; 55: 489-500.

9. Lippi G, Guidi GC. Risk management in the preanalytical phase of laboratory testing. Clin Chem Lab Med 2007; 45: 720-7.

10. Zidel, T. A Lean Guide to Transforming Healthcare. 1st ed. Am Soc Qual - Quality Press, Milwaukee 2006.

11. Lima-Oliveira G, Lippi G, Salvagno GL, Picheth G, Guidi GC. Laboratory Diagnostics and Quality of Blood Collection. J Med Biochem 2015; 34: 288-94.

12. Ialongo C, Bernardini S. Phlebotomy, a bridge between laboratory and patient. Biochem Med (Zagreb) 2016; 26: 17-33.

13. Simundic AM, Cornes M, Grankvist K, Lippi G, Nybo M, Kovalevskaya S, et al. Survey of national guidelines, education and training on phlebotomy in 28 European countries: an original report by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) working group for the preanalytical phase (WG-PA). Clin Chem Lab Med 2013; 51: 1585-93.

14. Simundic AM, Church S, Cornes MP, Grankvist K, Lippi , Nybo M, et al. Compliance of blood sampling procedures with the CLSI H3-A6 guidelines: An observational study by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) working group for the preanalytical phase (WG-PRE). Clin Chem Lab Med 2015; 53: 1321-31.

15. Lillo R, Salinas M, Lopez-Garrigos M, Naranjo-Santana Y, Gutierrez M, Marin MD, et al. Reducing preanalytical laboratory sample errors through educational and technological interventions. Clin Lab 2012; 58: 911-7.

16. Díaz CE, Fernández R, Armada M, García F. A research review on clinical needs, technical requirements, and normativity in the design of surgical robots. Int J Med Robot 2017 Jan 20. doi:

17. Chen A, Nikitczuk K, Nikitczuk J, Maguire T, Yarmush M. Portable robot for autonomous venipuncture using 3D near infrared image guidance. Technology (Singap World Sci) 2013; 1: 72-87.

18. Chen AI, Balter ML, Maguire TJ, Yarmush ML. Real-time Needle Steering in Response to Rolling Vein Deformation by a 9-DOF Image-Guided Autonomous Venipuncture Robot. Rep U S 2015; 2015: 2633-8.

19. Balter ML, Chen AI, Maguire TJ, Yarmush ML. The System Design and Evaluation of a 7-DOF Image- Guided Venipuncture Robot. IEEE Trans Robot 2015; 31: 1044-53.

20. Chen AI, Balter ML, Maguire TJ, Yarmush ML. 3D Near Infrared and Ultrasound Imaging of Peripheral Blood Vessels for Real-Time Localization and Needle Guidance. Med Image Comput Comput Assist Interv 2016; 9902: 388-96.

21. Lippi G, Cornes MP, Grankvist K, Nybo M, Simundic AM. EFLM WG-Preanalytical phase opinion paper: local validation of blood collection tubes in clinical laboratories. Clin Chem Lab Med 2016; 54: 755-60.

22. Lippi G, Chiozza L, Mattiuzzi C, Plebani M. Patient and Sample Identification. Out of the Maze? J Med Biochem. 2017 36: 107-12.

23. Swedberg C. Chip-size Passive RFID Tag Promises Long Range. Available at: RFID Journal. Last accessed, 20 April 2017.

24. Gravesen P, Raaby Poulsen K, Dirac H. Lab-on-a-chip technology for continuous glucose monitoring. J Diabetes Sci Technol 2007; 1: 372-4.

25. Generelli S, Jacquemart R, de Rooij NF, Jolicoeur M, Koudelka-Hep M, Guenat OT. Potentiometric platform for the quantification of cellular potassium efflux. Lab Chip 2008; 8: 1210-5.

26. Temiz Y, Lovchik RD, Kaigala GV, Delamarche E. Lab-ona- chip devices: How to close and plug the lab? Microelectron Eng 2015; 132: 156-75.

27. Lippi G, Blanckaert N, Bonini P, Green S, Kitchen S, Palicka V, et al. Haemolysis: an overview of the leading cause of unsuitable specimens in clinical laboratories. Clin Chem Lab Med 2008; 46: 764-72.

28. Adcock Funk DM, Lippi G, Favaloro EJ. Quality standards for sample processing, transportation, and storage in hemostasis testing. Semin Thromb Hemost 2012; 38: 576-85.

29. Esfandyarpour R, DiDonato MJ, Yang Y, Durmus NG, Harris JS, Davis RW. Multifunctional, inexpensive, and reusable nanoparticle-printed biochip for cell manipula- tion and diagnosis. Proc Natl Acad Sci U S A 2017; 114: E1306-E1315.

30. Lippi G, Simundic AM. Laboratory networking and sample quality: a still relevant issue for patient safety. Clin Chem Lab Med 2012; 50: 1703-5.

31. Lippi G, Mattiuzzi C. Biological samples transportation by drones: ready for prime time? Ann Transl Med 2016; 4: 92.

32. Boucher P. Domesticating the Drone: The Demilitari - sation of Unmanned Aircraft for Civil Markets. Sci Eng Ethics 2015; 21: 1393-412.

33. Amukele TK, Sokoll LJ, Pepper D, Howard DP, Street J. Can Unmanned Aerial Systems (Drones) Be Used for the Routine Transport of Chemistry, Hematology, and Coagulation Laboratory Specimens? PLoS One 2015; 10: e0134020.

34. Amukele T, Ness PM, Tobian AA, Boyd J, Street J. Drone transportation of blood products. Transfusion 2017; 57: 582-8.

35. Drone Crash Database. Available at: Last accessed: 20 April 2017.

36. Federal Aviation Administration. Unmanned Aircraft Systems. Last accessed: 20 April 2017.

37. Wild G, Murray J, Baxter G. Exploring Civil Drone Acci - dents and Incidents to Help Prevent Potential Air Disasters. Aerospace 2016; 3: 22. doi:

38. Cadamuro J, Wiedemann H, Mrazek C, Felder TK, Ober - kofler H, Fiedler GM, et al. The economic burden of hemolysis. Clin Chem Lab Med 2015; 53: e285-8.

39. Cadamuro J, Mrazek C, Haschke-Becher E, Sandberg S. To report or not to report: a proposal on how to deal with altered test results in hemolytic samples. Clin Chem Lab Med. 2017 Feb 16. doi:

40. Lippi G, Cervellin G, Plebani M. Reporting altered test results in hemolyzed samples: is the cure worse than the disease? Clin Chem Lab Med. 2017 Feb 16. doi:

41. Lippi G. Systematic Assessment of the Hemolysis Index: Pros and Cons. Adv Clin Chem 2015; 71: 157-70.

42. Simundic AM, Nikolac N, Ivankovic V, Ferenec-Ruzic D, Magdic B, Kvaternik M, et al. Comparison of visual vs. automated detection of lipemic, icteric and hemolyzed specimens: can we rely on a human eye? Clin Chem Lab Med 2009; 47: 1361-5.

43. Salvagno GL, Lippi G, Gelati M, Guidi GC. Hemolysis, lipaemia and icterus in specimens for arterial blood gas analysis. Clin Biochem 2012; 45: 372-3.

44. Kobos RK, Abbott SD, Levin HW, Kilkson H, Peterson DR, Dickinson JW. Electrochemical determination of hemoglobin, hematocrit, and hemolysis. Clin Chem 1987; 33: 153-8.

45. Whole Blood Hemolysis Sensor. Patent WO 2014159193 A1. Available at Last access: 20 April 2017.

46. Ito K, Tanaka S, Yamakoshi K, Kamiya A. Development of a compact hemolysis sensor for extracorporeal circulation. Jpn J Artif Organs 1989; 18: 928-31.

47. Park H, Ko DH, Kim JQ, Song SH. Performance evaluation of the Piccolo xpress Point-of-care Chemistry Analyzer. Korean J Lab Med 2009; 29: 430-8.

48. Son JH, Lee SH, Hong S, Park SM, Lee J, Dickey AM, et al. Hemolysis-free blood plasma separation. Lab Chip 2014; 14: 2287-92.

49. Netz UJ, Hirst L, Friebel M. Non-invasive detection of free hemoglobin in red blood cell concentrates for quality assurance. Photon Lasers Med 2015; 4: 193-5.

50. Archibong E, Konnaiyan KR, Kaplan H, Pyayt A. A mobile phone-based approach to detection of hemolysis. Biosens Bioelectron 2017; 88: 204-9.

51. Lippi G, Pavesi F, Avanzini P, Chetta F, Aloe R, Pipitone S. Development of simple equations for effective screening of spurious hemolysis in whole-blood specimens. Int J Lab Hematol 2015; 37: 253-8.

52. Kapur N, Parand A, Soukup T, Reader T, Sevdalis N. Aviation and healthcare: a comparative review with implications for patient safety. JRSM Open 2015; 7: 2054270415616548.

53. International Organization for Standardization 15189: 2012: Medical Laboratories-Requirements for quality and competence. Third Edition, 2012.

54. West J, Atherton J, Costelloe SJ, Pourmahram G, Stretton A, Cornes M. Preanalytical errors in medical laboratories: a review of the available methodologies of data collection and analysis. Ann Clin Biochem 2017; 54: 14-9.

55. Sciacovelli L, Lippi G, Sumarac Z, West J, Garcia Del Pino Castro I, Furtado Vieira K et al. Quality Indicators in Laboratory Medicine: the status of the progress of IFCC Working Group »Laboratory Errors and Patient Safety« project. Clin Chem Lab Med 2017; 55: 348-57.

56. Lippi G, Sciacovelli L, Simundic AM, Plebani M. Innovative software for recording preanalytical errors in accord with the IFCC quality indicators. Clin Chem Lab Med 2017; 55: e51-e53.

57. Theodorson E. Quality assurance in clinical chemistry: a touch of statistics and a lot of common sense. J Med Biochem 2016; 35: 103-12.

58. Bandodkar AJ, Wang J. Non-invasive wearable electrochemical sensors: a review. Trends Biotechnol 2014; 32: 363-71.

59. Gifford R. Continuous glucose monitoring: 40 years, what we've learned and what’s next. Chemphyschem 2013; 14: 2032-44.

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