STATinMED's cutting edge algorithm applies propensity score matching techniques to your data. The ProbChoice™ algorithm:

• tests the assumptions behind propensity score matching
• statistically chooses the sets of variables to match on
• uses up to 25 different matching techniques
• suggests the best technique for your data applying statistical guidelines published by a STATinMED consultant
• does sensitivity analysis against the unmeasurable factors
• allows you to match more than two categories, such as multi-level treatment choices
• increases the efficiency of your estimator when there is a lack of overlap in the groups

Feel free to download our ProbChoice™ flyer.

STATinMED's cutting edge algorithm uses both propensity score matching and raking techniques, creating patient-level weights adjusted for differences in demographic and socioeconomic factors as well as in health status. The NatWeight™ algorithm:

• adjusts for case mix differences to make a sample nationally representative
• adjusts outcomes (prevalence, cost, utilization) to enhance informed decisions from unbiased results
• combines the power of a large claims database, a convenience sample, with the representativeness of a probability sample

Feel free to download our NatWeight™ flyer.

Health care claims data provide information in a real world setting. However, they do not contain information on disease severity and are not specific to rheumatoid arthritis. The SIFRA™ algorithm:

• is a comorbidity index specifically designed for rheumatoid arthritis
• has low correlation with Charlson Comorbidity Index, Elixhauser Index, and Chronic Disease Score
• has high correlation with rheumatoid arthritis medical records-based index of severity
• improves the risk adjustment by lowering prediction errors in estimation of outcomes measures

Feel free to download our SIFRA™ flyer.