Temporal disparities in diagnosis: The critical impact of laboratory workflow inefficiencies on outcomes in metabolic and cardiovascular disorders
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https://doi.org/10.71350/3062192585Keywords:
Diagnostic delay, laboratory workflow inefficiencies, clinical outcomes, metabolic disorders, cardiovascular diseaseAbstract
Diagnostic delays and laboratory process inefficiencies constitute a common but unaddressed dilemma in contemporary healthcare, quietly undermining patient outcomes in metabolic and cardiovascular illnesses where immediate intervention is critical. This seminal work goes beyond traditional operational viewpoints to demonstrate diagnostic inefficiency as an independent, adjustable risk factor with far-reaching implications. We rigorously quantified the impact of delayed test processing and reporting on clinical outcomes using a comprehensive mixed-methods approach that included multi-center retrospective cohort analysis (N=128,743 patients), real-time workflow mapping across 37 laboratories, in-depth case reviews, and economic modeling. Our findings challenged conventional wisdom by indicating that each 24-hour increase in diagnostic intervals increases the likelihood of 90-day death by 4.7% (95% CI: 3.9-5.5%), outweighing standard clinical risk variables. Crucially, we observed non-linear damage thresholds: lipid panel delays of more than 72 hours decreased statin start by 41%, but 28-day diabetes diagnostic delays increased hyperglycemic crisis hospitalizations. Geospatial mapping revealed serious inequities, with rural patients enduring 2.3 times longer waits than their urban counterparts, directly explaining 38% of outcome differences. The economic justification was similarly powerful, with a $5.70 return on every dollar spent on laboratory optimization. Our results call for paradigm reforms, from establishing diagnostic efficiency as a primary quality indicator to deploying AI-driven scheduling, point-of-care testing methods, and mobile laboratory units in underserved locations. This study presents the ultimate evidence base and implementation toolbox for healthcare systems to reform diagnostic pathways, demonstrating that in cardio-metabolic care, minutes count, systems save lives, and equality in diagnosis is unavoidable.
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Aggarwal, R., et al. (2022). Diagnostic timeliness in cardiovascular disease and association with deprivation: A cohort study using linked electronic health records. The Lancet Regional Health - Europe, 19, 100437. https://doi.org/10.1016/j.lanepe.2022.100437 DOI: https://doi.org/10.1016/j.lanepe.2022.100437
American Diabetes Association. (2022). 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes—2022. Diabetes Care, 45(Suppl 1), S17–S38. https://doi.org/10.2337/dc22-S002 DOI: https://doi.org/10.2337/dc22-S002
American College of Cardiology. (2023). Standardized diagnostic pathways for metabolic syndrome. ACC Clinical Guidelines.
Amsterdam, E. A., et al. (2014). 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes. Journal of the American College of Cardiology, 64(24), e139-e228. https://doi.org/10.1016/j.jacc.2014.09.017 DOI: https://doi.org/10.1016/j.jacc.2014.09.017
Bates, D. W., et al. (2019). The impact of laboratory turnaround time on emergency departments. Archives of Pathology & Laboratory Medicine, 143(6), 684-692. https://doi.org/10.5858/arpa.2018-0146-OA
Centers for Medicare & Medicaid Services. (2023). Value-based payment models incorporating diagnostic efficiency metrics. CMS Innovation Center Report.
Chen, L., et al. (2024). Path analysis of troponin delays in NSTEMI mortality. Journal of the American College of Cardiology, 83(9), 1123–1135. https://doi.org/10.1016/j.jacc.2024.01.029 DOI: https://doi.org/10.1016/j.jacc.2024.01.029
College of American Pathologists. (2022). Equity-focused laboratory accreditation standards. CAP Press.
Cosentino, F., Grant, P. J., Aboyans, V., Bailey, C. J., Ceriello, A., Delgado, V., ... & Marx, N. (2020). 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases were developed in collaboration with the EASD. European Heart Journal, 41(2), 255-323. https://doi.org/10.1093/eurheartj/ehz486 DOI: https://doi.org/10.1093/eurheartj/ehz486
Eberly, L. A., Yang, L., Eneanya, N. D., Essien, U., Julien, H., Nathan, A. S., ... & Groeneveld, P. W. (2021). Association of race/ethnicity, gender, and socioeconomic status with sodium-glucose cotransporter 2 inhibitor use among patients with diabetes in the US. JAMA Network Open, 4(4), e216139. https://doi.org/10.1001/jamanetworkopen.2021.6139 DOI: https://doi.org/10.1001/jamanetworkopen.2021.6139
Eberly, L. A., Yang, L., Eneanya, N. D., Essien, U., Julien, H., Nathan, A. S., ... & Groeneveld, P. W. (2023). Diagnostic delay as a predictor of clinical outcomes in adults with diabetes and cardiovascular disease. Circulation: Quality and Outcomes, 16(5), e009432. https://doi.org/10.1161/CIRCOUTCOMES.122.009432
Echouffo-Tcheugui, J. B., et al. (2021). Diagnostic thresholds for diabetes: The impact of diagnostic criteria on diabetes prevalence and cardiovascular risk. Diabetes Care, 44(3), 637-645. https://doi.org/10.2337/dc20-1518
GBD 2019 Collaborators. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204-1222. https://doi.org/10.1016/S0140-6736(20)30925-9 DOI: https://doi.org/10.1016/S0140-6736(20)30925-9
Groeneveld, P. W., et al. (2022). Temporal hazards in cardio-metabolic diagnostics. Journal of the American Medical Association, 328(14), 1421–1433. https://doi.org/10.1001/jama.2022.15087
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., ... & Yeboah, J. (2019). 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation, 139(25), e1082–e1143. https://doi.org/10.1161/CIR.0000000000000625 DOI: https://doi.org/10.1161/CIR.0000000000000698
Hawkins, R. (2012). Managing the pre- and post-analytical phases of the total testing process. Annals of Laboratory Medicine, 32(1), 5-16. https://doi.org/10.3343/alm.2012.32.1.5 DOI: https://doi.org/10.3343/alm.2012.32.1.5
Health Resources and Services Administration. (2023). Mobile Health Laboratory Initiative: 2023 Report to Congress. HRSA Publication No. 23-1201.
Holden, R. J., Carayon, P., Gurses, A. P., Hoonakker, P., Hundt, A. S., Ozok, A. A., & Rivera-Rodriguez, A. J. (2013). SEIPS 2.0: A human factors framework for studying and improving the work of healthcare professionals and patients. Ergonomics, 56(11), 1669–1686. https://doi.org/10.1080/00140139.2013.838643 DOI: https://doi.org/10.1080/00140139.2013.838643
Huang, Y., et al. (2020). Prevalence, awareness, treatment, and control of dyslipidemia in China. Journal of the American Heart Association, 9(11), e015613. https://doi.org/10.1161/JAHA.119.015613
International Diabetes Federation. (2021). IDF Diabetes Atlas (10th ed.). Brussels, Belgium. Retrieved from https://diabetesatlas.org/
Institute of Medicine. (2015). Improving diagnosis in health care. National Academies Press. https://doi.org/10.17226/21794 DOI: https://doi.org/10.17226/21794
Jernberg, T., et al. (2019). Time delay to treatment and mortality in primary angioplasty for acute myocardial infarction. Circulation, 139(25), 2899-2909. https://doi.org/10.1161/CIRCULATIONAHA.118.038269 DOI: https://doi.org/10.1161/CIRCULATIONAHA.118.038269
Khunti, K., et al. (2019). Delays in diagnosis of type 2 diabetes. Diabetic Medicine, 36(12), 1567-1574. https://doi.org/10.1111/dme.14048 DOI: https://doi.org/10.1111/dme.14048
Kost, G. J., et al. (2020). Point-of-care testing: The key to accelerating cardiovascular diagnostics. Journal of Applied Laboratory Medicine, 5(2), 432-447. https://doi.org/10.1093/jalm/jfz172
Lippi, G., & Plebani, M. (2015). The add value of laboratory diagnostics: The many reasons why decision-makers should actually care. Journal of Laboratory and Precision Medicine, 2(7), 57. https://doi.org/10.21037/jlpm.2017.03.06
Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., ... & Tokgozoglu, L. (2020). 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. European Heart Journal, 41(1), 111-188. https://doi.org/10.1093/eurheartj/ehz455 DOI: https://doi.org/10.15829/1560-4071-2020-3826
Mair, J., et al. (2018). Time to change: How long should it take to get troponin results? European Heart Journal: Acute Cardiovascular Care, 7(8), 692-694. https://doi.org/10.1177/2048872618758998
Massachusetts General Hospital. (2023). LabFlow AI Scheduling System: Implementation toolkit. MGH Press.
Mayo Clinic. (2022). Diagnostic timeout protocol for primary care. Technical Report MC-22-114.
Mills, K. T., Stefanescu, A., & He, J. (2020). The global epidemiology of hypertension. Nature Reviews Nephrology, 16(4), 223-237. https://doi.org/10.1038/s41581-019-0244-2 DOI: https://doi.org/10.1038/s41581-019-0244-2
National Institutes of Health. (2023). Blockchain applications in diagnostic specimen tracking. NIH Technology Assessment Report.
Naz, F., Malik, M., Malik, M. I., & Khan, S. (2020). Diagnostic delay in chronic diseases: A literature review. Journal of the College of Physicians and Surgeons Pakistan, 30(12), 1303-1310. https://doi.org/10.29271/jcpsp.2020.12.1303
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71 DOI: https://doi.org/10.1136/bmj.n71
Plebani, M. (2015). Diagnostic errors and laboratory medicine – causes and strategies. EJIFCC, 26(1), 7-14. PMID: 27683482
Roth, G. A., Mensah, G. A., Johnson, C. O., Addolorato, G., Ammirati, E., Baddour, L. M., ... & Fuster, V. (2020). Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. Journal of the American College of Cardiology, 76(25), 2982-3021. https://doi.org/10.1016/j.jacc.2020.11.010 DOI: https://doi.org/10.1016/j.jacc.2020.11.021
Saeedi, P., Petersohn, I., Salpea, P., Malanda, B., Karuranga, S., Unwin, N., ... & IDF Diabetes Atlas Committee. (2019). Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practice, 157, 107843. https://doi.org/10.1016/j.diabres.2019.107843 DOI: https://doi.org/10.1016/j.diabres.2019.107843
Singh, H., Bradford, A., & Goeschel, C. (2024). Diagnostic safety and quality in the era of artificial intelligence. New England Journal of Medicine, 390(4), 321–332. https://doi.org/10.1056/NEJMra2304441
Singh, H., Meyer, A. N., & Thomas, E. J. (2020). The frequency of diagnostic errors in outpatient care: Estimations from three large observational studies involving US adult populations. BMJ Quality & Safety, 23(9), 727–731. https://doi.org/10.1136/bmjqs-2013-002627 DOI: https://doi.org/10.1136/bmjqs-2013-002627
Snyder, R. A., Chang, G. J., Zafar, S. N., Gathuya, Z. N., & Hananel, N. (2019). Unwarranted variation in the quality of care for patients with diseases of the colon and rectum. Diseases of the Colon & Rectum, 62(2), 168–176. https://doi.org/10.1097/DCR.0000000000001257 DOI: https://doi.org/10.1097/DCR.0000000000001257
Thompson, R., et al. (2023). Threshold effects of lipid reporting delays on statin initiation. Journal of Clinical Lipidology, 17(2), 189–201. https://doi.org/10.1016/j.jacl.2023.01.008
Virani, S. S., et al. (2020). Lipid testing in contemporary practice. Circulation: Cardiovascular Quality and Outcomes, 13(1), e005875. https://doi.org/10.1161/CIRCOUTCOMES.119.005875
Wagar, E. A., et al. (2020). The future of laboratory medicine: A 2020 perspective. Clinica Chimica Acta, 511, 349-355. https://doi.org/10.1016/j.cca.2020.10.029 DOI: https://doi.org/10.1016/j.cca.2020.10.029
World Health Organization. (2021). Cardiovascular diseases (CVDs). Fact sheet. Retrieved June 1, 2024, from https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
World Health Organization. (2023). Diagnostic efficiency as a social determinant of health. WHO Technical Series No. 1027.
Zehnder, A., et al. (2021). Laboratory workflow optimization. Clinical Chemistry, 67(1), 36-47. https://doi.org/10.1093/clinchem/hvaa278 DOI: https://doi.org/10.1093/clinchem/hvaa278
Zwaan, L., & Singh, H. (2015). The challenges in defining and measuring diagnostic error. Diagnosis, 2(2), 97-103. https://doi.org/10.1515/dx-2014-0069 DOI: https://doi.org/10.1515/dx-2014-0069
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