Background: Missing data present a challenge to many research projects. The problem is often pronounced in studies utilizing self-report scales, and literature addressing different strategies for dealing with missing data in such circumstances is scarce. The objective of this study was to compare six different imputation techniques for dealing with missing data in the Zung Self-reported Depression scale (SDS).

BackgroundWe have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance.MethodsA multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year.ResultsThe prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit.ConclusionThe ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.

Compared with calcium-based phosphate binders, use of sevelamer in dialysis patients is associated with similar to slightly higher phosphate levels, similar calcium phosphate product, and slightly lower serum calcium levels. There was no evidence that sevelamer reduced all-cause mortality, cardiovascular mortality, the frequency of symptomatic bone disease or health-related quality of life.

The cost per QALY gained for treating all dialysis patients with sevelamer exceeds what would usually be considered good value for the money. While the high cost per QALY was in part due to the inclusion of the costs of dialysis and transplant in the analysis, the cost per QALY gained remained relatively unattractive even when these costs were excluded. Although a lower cost per QALY gained is realized when only patients older than 65 years are treated, this strategy remains economically unattractive, particularly given the uncertainty of clinical benefit in this group.

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