Background
Urinary tract infections and recurrent urinary tract infections pose substantial burdens
on patients and healthcare systems. Testing and treatment strategies are increasingly
important in the age of antibiotic resistance and stewardship.
Objective
This study aimed to evaluate the cost effectiveness of urinary tract infection testing
and treatment strategies with a focus on antibiotic resistance.
Study Design
We designed a decision tree to model the following 4 strategies for managing urinary
tract infections: (1) empirical antibiotics first, followed by culture-directed antibiotics
if symptoms persist; (2) urine culture first, followed by culture-directed antibiotics;
(3) urine culture at the same time as empirical antibiotics, followed by culture-directed
antibiotics, if symptoms persist; and (4) symptomatic treatment first, followed by
culture-directed antibiotics, if symptoms persist. To model both patient- and society-level
concerns, we built 3 versions of this model with different outcome measures: quality-adjusted
life-years, symptom-free days, and antibiotic courses given. Societal cost of antibiotic
resistance was modeled for each course of antibiotics given. The probability of urinary
tract infection and the level of antibiotic resistance were modeled from 0% to 100%.
We also extended the model to account for patients requiring catheterization for urine
specimen collection.
Results
In our model, the antibiotic resistance rate was based either on the local antibiotic
resistance patterns for patients presenting with sporadic urinary tract infections
or on rate of resistance from prior urine cultures for patients with recurrent urinary
tract infections. With the base case assumption of 20% antibiotic resistance, urine
culture at the same time as empirical antibiotics was the most cost-effective strategy
and maximized symptom-free days. However, empirical antibiotics was the most cost-effective
strategy when antibiotic resistance was below 6%, whereas symptomatic treatment was
the most cost-effective strategy when antibiotic resistance was above 80%. To minimize
antibiotic use, symptomatic treatment first was always the best strategy followed
by urine culture first. Sensitivity analyses with other input parameters did not affect
the cost-effectiveness results. When we extended the model to include an office visit
for catheterized urine specimens, empirical antibiotics became the most cost-effective
option.
Conclusion
We developed models for urinary tract infection management strategies that can be
interpreted for patients initially presenting with urinary tract infections or those
with recurrent urinary tract infections. Our results suggest that, in most cases,
urine culture at the same time as empirical antibiotics is the most cost-effective
strategy and maximizes symptom-free days. Empirical antibiotics first should only
be considered if the expected antibiotic resistance is very low. If antibiotic resistance
is expected to be very high, symptomatic treatment is the best strategy and minimizes
antibiotic use.
Key words
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Article info
Publication history
Published online: August 18, 2021
Accepted:
August 12,
2021
Received in revised form:
July 21,
2021
Received:
December 15,
2020
Footnotes
The authors report no conflict of interest.
The authors report no funding sources.
Cite this article as: Wang R, LaSala C. Role of antibiotic resistance in urinary tract infection management: a cost-effectiveness analysis. Am J Obstet Gynecol 2021;225:550.e1-10.
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