Efforts to find disease genes using high-density single-nucleotide polymorphism (SNP) maps will produce data sets that exceed the limitations of current computational tools. Here we describe a new, efficient method for the analysis of dense genetic maps in pedigree data that provides extremely fast solutions to common problems such as allele-sharing analyses and haplotyping. We show that sparse binary trees represent patterns of gene flow in general pedigrees in a parsimonious manner, and derive a family of related algorithms for pedigree traversal. With these trees, exact likelihood calculations can be carried out efficiently for single markers or for multiple linked markers. Using an approximate multipoint calculation that ignores the unlikely possibility of a large number of recombinants further improves speed and provides accurate solutions in dense maps with thousands of markers. Our multipoint engine for rapid likelihood inference (Merlin) is a computer program that uses sparse inheritance trees for pedigree analysis; it performs rapid haplotyping, genotype error detection and affected pair linkage analyses and can handle more markers than other pedigree analysis packages.
Objective To systematically evaluate the published evidence regarding the characteristics and effectiveness of disease management programmes. Design Meta-analysis. Data sources Computerised databases for English language articles during 1987-2001. Study selection 102 articles evaluating 118 disease management programmes. Main outcome measures Pooled effect sizes calculated with a random effects model. Results Patient education was the most commonly used intervention (92/118 programmes), followed by education of healthcare providers (47/118) and provider feedback (32/118). Most programmes (70/118) used more than one intervention. Provider education, feedback, and reminders were associated with significant improvements in provider adherence to guidelines (effect sizes (95% confidence intervals) 0.44 (0.19 to 0.68), 0.61 (0.28 to 0.93), and 0.52 (0.35 to 0.69) respectively) and with significant improvements in patient disease control (effect sizes 0.35 (0.19 to 0.51), 0.17 (0.10 to 0.25), and 0.22 (0.1 to 0.37) respectively). Patient education, reminders, and financial incentives were all associated with improvements in patient disease control (effect sizes 0.24 (0.07 to 0.40), 0.27 (0.17 to 0.36), and 0.40 (0.26 to 0.54) respectively). Conclusions All studied interventions were associated with improvements in provider adherence to practice guidelines and disease control. The type and number of interventions varied greatly, and future studies should directly compare different types of intervention to find the most effective.