In medical laboratories, the appropriateness challenge directly revolves around the laboratory test and its proper selection, data analysis, and result reporting. However, laboratories have also a role in the appropriate management of those phases of total testing process (TTP) that traditionally are not under their direct control. So that, the laboratory obligation to act along the entire TTP is now widely accepted in order to achieve better care management. Because of the large number of variables involved in the overall TTP structure, it is difficult to monitor appropriateness in real time. However, it is possible to retrospectively reconstruct the body of the clinical process involved in the management of a specific laboratory test to track key passages that may be defective or incomplete in terms of appropriateness. Here we proposed an appropriateness check-list scheme along the TTP chain to be potentially applied to any laboratory test. This scheme consists of a series of questions that healthcare professionals should answer to achieve laboratory test appropriateness. In the system, even a single lacking answer may compromise the integrity of all appropriateness evaluation process as the inability to answer may involve a significant deviation from the optimal trajectory, which compromise the test appropriateness and the quality of subsequent steps. Using two examples of the check-list application, we showed that the proposed instrument may offer an objective help to avoid inappropriate use of laboratory tests in an integrated way involving both laboratory professionals and user clinicians.
Research funding: None declared.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
Informed consent: Not applicable.
Ethical approval: Not applicable.
1. Mrazek, C, Simundic, AM, Salinas, M, von Meyer, A, Cornes, M, Cadamuro, J. Inappropriate use of laboratory tests: how availability triggers demand – examples across Europe. Clin Chim Acta 2020;505:100–7. https://doi.org/10.1016/j.cca.2020.02.017.Search in Google Scholar
2. Mrazek, C, Haschke-Becher, E, Felder, TK, Keppel, MH, Oberkofler, H, Cadamuro, J. Laboratory demand management strategies-an overview. Diagnostics 2021;11:1141. https://doi.org/10.3390/diagnostics11071141.Search in Google Scholar
3. Salinas, M, López-Garrigós, M, Flores, E, Leiva-Salinas, M, Asencio, A, Lugo, J, et al.. Managing inappropriate requests of laboratory tests: from detection to monitoring. Am J Manag Care 2016;22:e311–6.Search in Google Scholar
4. Miyakis, S, Karamanof, G, Liontos, M, Mountokalakis, TD. Factors contributing to inappropriate ordering of tests in an academic medical department and the effect of an educational feedback strategy. Postgrad Med 2006;82:823–9. https://doi.org/10.1136/pgmj.2006.049551.Search in Google Scholar
6. Schünemann, HJ, Mustafa, RA, Brozek, J, Santesso, N, Bossuyt, PM, Steingart, KR, et al.. GRADE Working Group. GRADE guidelines: 22. The GRADE approach for tests and strategies-from test accuracy to patient-important outcomes and recommendations. J Clin Epidemiol 2019;111:69–82. https://doi.org/10.1016/j.jclinepi.2019.02.003.Search in Google Scholar PubMed
7. Valdés, IP, Ramírez-Santana, M, Basagoitía, A, Testar, X, Vásquez, JA. Medicina traslacional e innovación en salud: mecanismos y perspectivas [Translational medicine and innovation in health: mechanisms and perspectives]. Rev Med Chile 2018;146:890–8. https://doi.org/10.4067/s0034-98872018000700890.Search in Google Scholar PubMed
10. Plebani, M, Laposata, M, Lundberg, GD. The brain-to-brain loop concept for laboratory testing 40 years after its introduction. Am J Clin Pathol 2011;136:829–33. https://doi.org/10.1309/ajcpr28hwhssdnon.Search in Google Scholar PubMed
11. ISO 15189:2012. Medical laboratories – requirements for quality and competence, 3rd ed. International Organization for Standardization; 2012. Available from: https://www.iso.org/standard/56115.html.Search in Google Scholar
15. Monaghan, PJ, Lord, SJ, St John, A, Sandberg, S, Cobbaert, CM, Lennartz, L, et al.. Test evaluation working group of the European federation of clinical Chemistry and laboratory medicine. Biomarker development targeting unmet clinical needs. Clin Chim Acta 2016;460:211–9. https://doi.org/10.1016/j.cca.2016.06.037.Search in Google Scholar PubMed
16. Eaton, KP, Levy, K, Soong, C, Pahwa, AK, Petrilli, C, Ziemba, JB, et al.. Evidence-based guidelines to eliminate repetitive laboratory testing. JAMA Intern Med 2017;177:1833–9. https://doi.org/10.1001/jamainternmed.2017.5152.Search in Google Scholar PubMed
17. Janssens, PM, Staring, W, Winkelman, K, Krist, G. Active intervention in hospital test request panels pays. Clin Chem Lab Med 2015;53:731–42. https://doi.org/10.1515/cclm-2014-0575.Search in Google Scholar PubMed
18. Vidyarthi, AR, Hamill, T, Green, AL, Rosenbluth, G, Baron, RB. Changing resident test ordering behavior: a multilevel intervention to decrease laboratory utilization at an academic medical center. Am J Med Qual 2015;30:81–7. https://doi.org/10.1177/1062860613517502.Search in Google Scholar PubMed
19. Rubinstein, M, Hirsch, R, Bandyopadhyay, K, Madison, B, Taylor, T, Ranne, A, et al.. Effectiveness of practices to support appropriate laboratory test utilization: a laboratory medicine best practices systematic review and meta-analysis. Am J Clin Pathol 2018;149:197–221. https://doi.org/10.1093/ajcp/aqx147.Search in Google Scholar PubMed PubMed Central
20. Liu, S, Reese, TJ, Kawamoto, K, Del Fiol, G, Weir, C. A theory-based meta-regression of factors influencing clinical decision support adoption and implementation. J Am Med Inf Assoc 2021;28:2514–22. https://doi.org/10.1093/jamia/ocab160.Search in Google Scholar PubMed PubMed Central
21. Houben, PH, Winkens, RA, van der Weijden, T, Vossen, RC, Naus, AJ, Grol, RP. Reasons for ordering laboratory tests and relationship with frequency of abnormal results. Scand J Prim Health Care 2010;28:18–23. https://doi.org/10.3109/02813430903281758.Search in Google Scholar PubMed PubMed Central
22. Lang, T, Royal College of Pathologists. National minimum re-testing interval project: a final report detailing consensus recommendations for minimum re-testing intervals for use in clinical biochemistry. London: ACB; 2013.Search in Google Scholar
24. Braga, F, Pasqualetti, S, Aloisio, E, Panteghini, M. The internal quality control in the traceability era. Clin Chem Lab Med 2020;59:291–300. https://doi.org/10.1515/cclm-2020-0371.Search in Google Scholar PubMed
25. Braga, F, Pasqualetti, S, Panteghini, M. The role of external quality assessment in the verification of in vitro medical diagnostics in the traceability era. Clin Biochem 2018;57:23–8. https://doi.org/10.1016/j.clinbiochem.2018.02.004.Search in Google Scholar PubMed
26. Mullier, F, Vanpee, D, Jamart, J, Dubuc, E, Bailly, N, Douxfils, J, et al.. Comparison of five D-dimer reagents and application of an age-adjusted cut-off for the diagnosis of venous thromboembolism in emergency department. Blood Coagul Fibrinolysis 2014;25:309–15. https://doi.org/10.1097/mbc.0000000000000020.Search in Google Scholar PubMed
27. Crawford, F, Andras, A, Welch, K, Sheares, K, Keeling, D, Chappell, FM. D-dimer test for excluding the diagnosis of pulmonary embolism. Cochrane Database Syst Rev 2016:CD010864.10.1002/14651858.CD010864Search in Google Scholar
28. Palareti, G, Cosmi, B, Legnani, C, Tosetto, A, Brusi, C, Iorio, A, et al.. PROLONG Investigators. D-dimer testing to determine the duration of anticoagulation therapy. N Engl J Med 2006;355:1780–9. https://doi.org/10.1056/nejmoa054444.Search in Google Scholar
29. Caruso, S, Szoke, D, Birindelli, S, Falvella, FS, Dolci, A, Panteghini, M. Improving D-dimer testing appropriateness by controlling periodicity of retesting: prevention is better than cure. Clin Chem Lab Med 2022;60:e175–6. https://doi.org/10.1515/cclm-2022-0389.Search in Google Scholar PubMed
30. Meijer, P, Haverkate, F, Kluft, C, de Moerloose, P, Verbruggen, B, Spannagl, M. A model for the harmonisation of test results of different quantitative D-dimer methods. Thromb Haemostasis 2006;95:567–72. https://doi.org/10.1160/th05-01-0042.Search in Google Scholar PubMed
31. Aloisio, E, Serafini, L, Chibireva, M, Dolci, A, Panteghini, M. Hypoalbuminemia and elevated D-dimer in COVID-19 patients: a call for result harmonization. Clin Chem Lab Med 2020;58:e255–6. https://doi.org/10.1515/cclm-2020-1038.Search in Google Scholar PubMed
32. Birindelli, S, Panzeri, A, Carnevale, A, Pasqualetti, S, Dolci, A, Panteghini, M. Impact of the introduction of ACL TOP 750 LAS for hemostasis testing on the workflow of a total automation laboratory. Clin Chem Lab Med 2017;55:S219.Search in Google Scholar
33. Robert-Ebadi, H, Robin, P, Hugli, O, Verschuren, F, Trinh-Duc, A, Roy, PM, et al.. Impact of the age-adjusted D-dimer cutoff to exclude pulmonary embolism: a multinational prospective real-life study (the RELAX-PE study). Circulation 2021;143:1828–30. https://doi.org/10.1161/circulationaha.120.052780.Search in Google Scholar
36. Masetto, T, Eidizadeh, A, Peter, C, Grimmler, M. National external quality assessment and direct method comparison reflect crucial deviations of procalcitonin measurements in Germany. Clin Chim Acta 2022;529:67–75. https://doi.org/10.1016/j.cca.2022.02.007.Search in Google Scholar
38. Bouadma, L, Luyt, CE, Tubach, F, Cracco, C, Alvarez, A, Schwebel, C, et al.. PRORATA Trial Group. Use of procalcitonin to reduce patients’ exposure to antibiotics in intensive care units (PRORATA trial): a multicentre randomised controlled trial. Lancet 2010;375:463–74. https://doi.org/10.1016/s0140-6736(09)61879-1.Search in Google Scholar
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