Frequency of Testing for Dyslipidemia: A Systematic Review and Budget Impact Analysis.
Bibliographic record
Abstract
BACKGROUND: Current Canadian guidelines recommend annual screening for hyperlipidemia in people with a Framingham risk score (FRS) of greater than 5%. In those with a FRS of less than 5%, lipid screening is recommended every 3 to 5 years. OBJECTIVES: We aimed to determine the most cost-effective frequency of lipid profile testing in adults with different levels of cardiovascular risk based on published literature, to determine current frequency of lipid screening in Ontario, and to calculate the cost of aligning current with recommended frequencies. METHODS: We systematically searched for studies (from 2000 to 2012) evaluating the cost-effectiveness of lipid profile testing frequency in adults. Using the Canadian Community Health Survey and linked health administrative databases, we calculated the FRS for each survey respondent on every day from 2005 to 2011. Average current frequency of lipid testing was calculated according to the total number of patient days spent in each FRS category and the number of lipid tests occurring on those days. Extrapolating these outcomes to the Ontario population, we estimated the expected budget impact of aligning current rates of lipid testing with rates recommended by the Canadian Cardiovascular Society (CCS) guidelines. RESULTS: No studies evaluated the cost-effectiveness of lipid monitoring frequency. Our database analysis revealed that people in the very low risk group are tested an average of once every 4.4 years, those in the low risk group are tested once every 2 years, those in the intermediate risk group are tested every 1.4 years, and those in the highest risk group are tested annually. If we compare these rates to those recommended by the CCS guidelines, an additional 3.6 million tests would be needed to achieve recommended rates of lipid testing. At a cost of $14.48 per test, the expected cost to the province would be $52.2 million. LIMITATIONS: The results were analysed in aggregate, leading to the potential for ecological fallacy. In addition, because data pertaining to drug prescriptions in Ontario are only available for people over 65 years of age, the analysis did not account for the influence of statin treatment on the frequency of lipid testing. CONCLUSIONS: Our findings show that there is currently no evidence to inform the optimal frequency of lipid testing. People in Ontario at low-low, low, intermediate, and high risk are being tested once every 4.4, 1.9, 1.4, and 1.0 times per year, respectively. According to the CCS guidelines, this represents under-testing in the low and intermediate groups. Achieving the recommended rates of testing would cost approximately $52.2 million. Given the large cost of implementing such a change and the uncertainty on which CCS guidelines are based, it would be prudent to await the results of further research before making such a large investment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.018 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".