Modeling strategy to identify patients with primary immunodeficiency utilizing risk management and outcome measurement

This study seeks to generate analytic insights into risk management and probability of an identifiable primary immunodeficiency defect. The Jeffrey Modell Centers Network database, Jeffrey Modell Foundation’s 10 Warning Signs, the 4 Stages of Testing Algorithm, physician-reported clinical outcomes, programs of physician education and public awareness, the SPIRIT® Analyzer, and newborn screening, taken together, generates P values of less than 0.05%. This indicates that the data results do not occur by chance, and that there is a better than 95% probability that the data are valid. The objectives are to improve patients’ quality of life, while generating significant reduction of costs. The advances of the world’s experts aligned with these JMF programs can generate analytic insights as to risk management and probability of an identifiable primary immunodeficiency defect. This strategy reduces the uncertainties related to primary immunodeficiency risks, as we can screen, test, identify, and treat undiagnosed patients. We can also address regional differences and prevalence, age, gender, treatment modalities, and sites of care, as well as economic benefits. These tools support high net benefits, substantial financial savings, and significant reduction of costs. All stakeholders, including patients, clinicians, pharmaceutical companies, third party payers, and government healthcare agencies, must address the earliest possible precise diagnosis, appropriate intervention and treatment, as well as stringent control of healthcare costs through risk assessment and outcome measurement. An affected patient is entitled to nothing less, and stakeholders are responsible to utilize tools currently available. Implementation offers a significant challenge to the entire primary immunodeficiency community.