Cost Savings from a New Protocol for Diagnosing Pulmonary Embolism
Author Information
Author(s): Gospodarevskaya Elena V, Goergen Stacy K, Harris Anthony H, Chan Thomas, de Campo John F, Wolfe Rory, Gan Eng T, Wheeler Michael B, McKay John
Primary Institution: Centre for Health Economics, Monash University, Australia
Hypothesis
Implementing an evidence-based clinical protocol will not change the number of correctly diagnosed pulmonary embolism patients but will save resources.
Conclusion
The study found that using a new clinical protocol for diagnosing pulmonary embolism can save the Australian healthcare system between $3.1 million to $3.7 million annually.
Supporting Evidence
- The new protocol reduced the use of diagnostic imaging tests without increasing the risk of misdiagnosing pulmonary embolism.
- Cost savings were primarily due to a reduction in the number of pulmonary vascular imaging tests for low-risk patients.
- The negative predictive value of the new protocol was found to be 99%.
- Implementation of the protocol involved training sessions for emergency department staff.
- The study included a total of 930 patients across both control and intervention groups.
- Annual cost savings for the healthcare system were estimated between $3.1 million to $3.7 million.
- Patients categorized as low risk and with negative D-dimer results had a very low incidence of pulmonary embolism.
- The study demonstrated that the new protocol is as effective as existing practices.
Takeaway
Doctors can use a simple test to check for a serious lung problem called pulmonary embolism, which saves money and helps patients without putting them at risk.
Methodology
A cost-minimisation study comparing diagnostic tests in a historical cohort and an intervention group using a new clinical protocol.
Potential Biases
Potential bias due to the non-randomized design and reliance on historical controls.
Limitations
The study used a non-random historic control group, which may introduce bias.
Participant Demographics
The control group had 185 patients with a mean age of 56.2 years, while the intervention group had 745 patients with a mean age of 55.0 years.
Statistical Information
P-Value
0.002
Confidence Interval
95% CI = 96% – 100%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website