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BACKGROUND: Validating new algorithms, such as methods to disentangle intrinsic treatment risk from risk associated with experiential learning of novel treatments, often requires knowing the ground truth for data characteristics under investigation. Since the ground truth is inaccessible in real world data, simulation studies using synthetic datasets that mimic complex clinical environments are essential. We describe and evaluate a generalizable framework for injecting hierarchical learning effects within a robust data generation process that incorporates the magnitude of intrinsic risk and accounts for known critical elements in clinical data relationships. METHODS: We present a multi-step data generating process with customizable options and flexible modules to support a variety of simulation requirements. Synthetic patients with nonlinear and correlated features are assigned to provider and institution case series. The probability of treatment and outcome assignment are associated with patient features based on user definitions. Risk due to experiential learning by providers and/or institutions when novel treatments are introduced is injected at various speeds and magnitudes. To further reflect real-world complexity, users can request missing values and omitted variables. We illustrate an implementation of our method in a case study using MIMIC-III data for reference patient feature distributions. RESULTS: Realized data characteristics in the simulated data reflected specified values. Apparent deviations in treatment effects and feature distributions, though not statistically significant, were most common in small datasets (n < 3000) and attributable to random noise and variability in estimating realized values in small samples. When learning effects were specified, synthetic datasets exhibited changes in the probability of an adverse outcomes as cases accrued for the treatment group impacted by learning and stable probabilities as cases accrued for the treatm

Designed to assist state and local educational agencies and intermeidate educational units in developing administrative policies for the vocational education of handicapped students, the manual address present policy areas and administrative concerns. Guidelines are presented for policy development in the following nine areas (examples of subtopics in parentheses): planning and administration (cooperation with vocational rehabilitation and other agencies); identification of students (referrals); vocational assessment (vocational counseling and observation of work behavior); individualized education programs; program placement (least restrictive environment and periodic review); service delivery (coordination of services and vocational education modifications); facilities and equipment (accessibility of new construction and adaptive services); personnel (student/staff ratio and inservice training); and fiscal management. (CL)

Exposure to racial discrimination is a prevalent psychosocial stressor in African Americans but may not be significantly associated with hypertension prevalence; degree of stress derived from encounters may be an important determinant. More research is needed to clarify the complex relationship between stress-related racial discrimination and hypertension in African Americans.