Using Decision Analysis To Better Evaluate Pediatric Clinical Guidelines
ABSTRACT Although systematic and explicit, existing evidentiary criteria for clinical guidelines tend to use study design as a surrogate for evidence quality. Moreover, they do not independently characterize evidence quality and net benefits and do not systematically evaluate research needs. Decision analysis, which quantifies the range of potential net benefits based on whatever evidence is available, can augment traditional frameworks. It is particularly useful for pediatric research, where randomized controlled trials are often unavailable and infeasible. Policymakers should incorporate decision analysis into comparative effectiveness research and clinical guidelines.
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ABSTRACT: Although cardiovascular disease (CVD) mortality is declining, atherosclerosis-related diseases remain the leading cause of death. With the next frontier of CVD prevention focused on youth, the 2011 NHLBI Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents called for universal lipid screening of children ages 9–11 and adolescents ages 17–21 years. While atherosclerosis is rarely clinically evident in childhood, childhood risk factors have been linked to adult CVD events. Clinical controversies about screening and treatment exist, in part due to incomplete evidence, the long latency period between screening and adult CVD outcomes and the lack of information available about patient, provider and parent values and preferences. We describe clinical controversies in lipid screening and treatment for specific pediatric populations, highlight knowledge gaps limiting guideline development and implementation and consider innovative approaches that will further inform this discussion.Current Cardiovascular Risk Reports 08/2013; 7(4). DOI:10.1007/s12170-013-0320-2
- Circulation Cardiovascular Quality and Outcomes 11/2008; 1(2):134-7. DOI:10.1161/CIRCOUTCOMES.108.825232 · 5.04 Impact Factor
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ABSTRACT: Public subsidization of technology assessments in general, and Comparative Effectiveness Research (CER) in particular, has received considerable attention as a tool to simultaneously improve patient health and lower the cost of health care. However, little conceptual and empirical understanding exists concerning the quantitative impact of public technology assessments such as CER. This paper analyses the impact of CER on health and medical care spending interpreting CER to shift the demand for some treatments at the expense of others. We trace out the spending and health implications of such demand shifts in private- as well as subsidized health care markets. In contrast to current wisdom, our analysis implies that CER may well increase spending and adversely affect patient health, particularly when treatment effects are heterogeneous across patients. We simulate these economic effects for antipsychotics that are among the largest drug classes of the US Medicaid program and for which CER has been conducted by means of the CATIE trial in 1999. Using conservative estimates, we find that if Medicaid would have eliminated coverage for the least cost-effective treatments of the CATIE trial then under homogeneous effects, it would save about 90% of the $1.3B Medicaid class sales annually in non-elderly adult patient with schizophrenia. However, taking into account the observed heterogeneity in treatment effects, it would incur a loss of health valued annually at about 98% of class spending and thus a net loss of about 8% of annual class spending.