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Screening for type 2 diabetes mellitus: a cost-effectiveness analysis.
Thomas J Hoerger1, Russell Harris, Katherine A Hicks
1RTI International, Research Triangle Park, North Carolina 27709, USA. tjh@rti.org
Annals of Internal Medicine
|May 6, 2004
Summary
Targeted diabetes screening for individuals with hypertension is more cost-effective than universal screening. The optimal strategy involves targeted screening for those aged 55 to 75 years, maximizing health benefits and resource allocation.
Area of Science:
- Health economics
- Preventive medicine
- Diabetes management
Background:
- No randomized controlled trials exist for diabetes screening.
- Cost-effectiveness models can guide preferred screening strategies in the absence of direct evidence.
- Evaluating screening strategies is crucial for efficient healthcare resource allocation.
Purpose of the Study:
- To estimate the incremental cost-effectiveness of two diabetes screening strategies.
- Compare targeted screening in hypertensive individuals versus universal screening.
- Determine the most cost-effective approach for diabetes detection.
Main Methods:
- Utilized a Markov model for lifetime analysis.
- Incorporated data from the United Kingdom Prospective Diabetes Study and Hypertension Optimal Treatment trial.
- Analyzed costs and quality-adjusted life-years (QALYs) from a US primary care perspective.
Main Results:
- Targeted screening in hypertensive individuals demonstrated more favorable cost-effectiveness ratios across all ages compared to universal screening.
- At age 55, targeted screening yielded a cost per QALY of $34,375, while universal screening cost $360,966 per QALY.
- Screening was found to be most cost-effective for individuals aged 55 to 75 years.
Conclusions:
- Diabetes screening targeted to hypertensive individuals is a more cost-effective strategy than universal screening.
- The most cost-effective approach involves targeted screening for individuals aged 55 to 75 years.
- Limitations include not considering dyslipidemia screening and using data from clinically detected diabetes for benefit estimation.
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