Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2013 Nov 15;8(11):e78962.
doi: 10.1371/journal.pone.0078962. eCollection 2013.

The landscape of inappropriate laboratory testing: a 15-year meta-analysis

Affiliations
Meta-Analysis

The landscape of inappropriate laboratory testing: a 15-year meta-analysis

Ming Zhi et al. PLoS One. .

Abstract

Background: Laboratory testing is the single highest-volume medical activity and drives clinical decision-making across medicine. However, the overall landscape of inappropriate testing, which is thought to be dominated by repeat testing, is unclear. Systematic differences in initial vs. repeat testing, measurement criteria, and other factors would suggest new priorities for improving laboratory testing.

Methods: A multi-database systematic review was performed on published studies from 1997-2012 using strict inclusion and exclusion criteria. Over- vs. underutilization, initial vs. repeat testing, low- vs. high-volume testing, subjective vs. objective appropriateness criteria, and restrictive vs. permissive appropriateness criteria, among other factors, were assessed.

Results: Overall mean rates of over- and underutilization were 20.6% (95% CI 16.2-24.9%) and 44.8% (95% CI 33.8-55.8%). Overutilization during initial testing (43.9%; 95% CI 35.4-52.5%) was six times higher than during repeat testing (7.4%; 95% CI 2.5-12.3%; P for stratum difference <0.001). Overutilization of low-volume tests (32.2%; 95% CI 25.0-39.4%) was three times that of high-volume tests (10.2%; 95% CI 2.6-17.7%; P<0.001). Overutilization measured according to restrictive criteria (44.2%; 95% CI 36.8-51.6%) was three times higher than for permissive criteria (12.0%; 95% CI 8.0-16.0%; P<0.001). Overutilization measured using subjective criteria (29.0%; 95% CI 21.9-36.1%) was nearly twice as high as for objective criteria (16.1%; 95% CI 11.0-21.2%; P = 0.004). Together, these factors explained over half (54%) of the overall variability in overutilization. There were no statistically significant differences between studies from the United States vs. elsewhere (P = 0.38) or among chemistry, hematology, microbiology, and molecular tests (P = 0.05-0.65) and no robust statistically significant trends over time.

Conclusions: The landscape of overutilization varies systematically by clinical setting (initial vs. repeat), test volume, and measurement criteria. Underutilization is also widespread, but understudied. Expanding the current focus on reducing repeat testing to include ordering the right test during initial evaluation may lead to fewer errors and better care.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Literature Search Strategy and Results, 1997–2012.
The indicated databases were searched as described in the main text and File*Results from searching with and without subheadings.
Figure 2
Figure 2. Histograms of Study Measures of Inappropriate Laboratory Test Utilization, 1997–2012.
Cumulative distributions of A, overutilization vs. underutilization (P<0.001); B, overutilization, initial vs. repeat testing (P<0.001); C, overutilization, restrictive vs. permissive criteria (P<0.001); and D, overutilization, subjective vs. objective criteria (P = 0.027). Each curve can be interpreted as the probability (y-axis) that a test was at least as inappropriate as indicated on the x-axis. For example in panel B, a third of study measures of initial testing (open arrowhead, y-axis) found at least 60% inappropriateness (closed arrowhead, x-axis).

Comment in

References

    1. Alexander B (2012) Reducing healthcare costs through appropriate test utilization. Critical Values 5: 6–8.
    1. Song Z, Safran DG, Landon BE, He Y, Ellis RP, et al. (2011) Health Care Spending and Quality in Year 1 of the Alternative Quality Contract. N Engl J Med 365: 909–918. - PMC - PubMed
    1. Fisher E, Shortell S (2010) Accountable care organizations: accountable for what, to whom, and how. JAMA 304: 1715–1716. - PubMed
    1. Fisher E, Staiger D, Bynum J, Gottlieb D (2007) Creating accountable care organizations: The extended hospital medical staff. Health Aff (Millwood) 26: 44–57. - PMC - PubMed
    1. McClellan M, McKethan A, Lewis J, Roski J, Fisher E (2010) A national strategy to put accountable care into practice. Health Aff (Millwood) 29: 982–990. - PubMed