Services provided by the Division of Biostatistics and Bioinformatics in support of clinical and pre-clinical studies include:
We create and accumulate relevant study criteria. Factors such as sample size, randomization schemes and compliance requirements are taken into account in the design and execution of all studies.
Structure (e.g., clinical trials, Phase I, II, III and IV designs, pharmacokinetic/dynamic and pharmacoepidemiology designs, post-marketing, adverse events)
Sample size and power
Randomization schemes including Web-based
Protocol explanations for Institutional Review Boards
Structures to improve subject compliance
Provide staff for independent Data and Safety Monitoring Boards
Develop research plans and conduct independent interim statistical analyses
Produce compliance reports for clinical centers
Provide PDF, Web, fax, scanned and manual entry of data
Train research and operational staff in data management for a study
Develop data capture, storage and sharing procedures in compliance with federal regulations ensuring the integrity and confidentiality of patient data
Develop appropriate database structures and reporting schemes
Provide ongoing data quality monitoring and analysis
Develop and execute standard analysis schemes to determine significant differences and influential variables such as
Analysis of variance (ANOVA) to compare baseline to later study time results both between and within subjects and groups-application of mixed-model procedures
Analysis of trends and time series
Data imputation to adjust for missing values
Microarray and proteomics analysis
Analysis of the factors influencing effective utilization
Examination of cluster and nested effects that produce differences in such factors as clinics, clinicians, clients or patients
Perform cost and cost/benefit analysis using standard clinical and quality of life measurements
Develop prediction models that suggest how appropriate utilization can result in cost savings, as well as conducting studies to verify the effectiveness of these predictions
Present and interpret results for Data and Safety Monitoring Boards or scientific advisory boards
Produce graphs, tables, and reports tailored to the audience and linked to examples of individual patient profiles
Write final reports or papers and provide appropriate presentation materials
Study data are captured by a number of input methods then compiled in compliance with federal regulations. Ongoing monitoring of assimilated information assures the integrity and relevance of the collected data while maintaining patient confidentiality. Any trends and differences are taken into account in the final analysis.
We provide statistically and clinically meaningful reports for the following types of analyses:
Comparing outcome changes between baseline and predetermined intervals from one patient group to another. Groups can be divided by provider type, co-morbid state, demographic information, socioeconomic information, etc.
Trend analysis-evaluation of trends within the same patient groups at predetermined intervals.
Time-series analysis-this sophisticated technique allows data sets to be analyzed to determine if seasonal or other time factors affect results.
Cluster analysis-some patients are clustered within certain groupings, such as physicians, clinics, plans or clients. Some statistical techniques (like a random-effects mixed model) can test for significant differences between these clusters.
Regression models to identify risk factors of high utilization. This technique would analyze factors that can become predictors of certain outcomes.
Quality control/assurance schemes can vary from simple range checking on data entry to cross-variable validation and re-randomized subsample comparisons.
Utilization and economic analyses can be examined to determine potential cost-saving measures in the care of affected patients. Further studies can verify the effectiveness of these indicators.
Proper education is a critical element of any study. In addition to the support for investigator protocols described above, staff personnel provide classes in basic statistics and the use of SAS and JMP software for clinical and basic science investigators. Core faculty also teaches graduate level statistics courses for the Department of Biostatistics and Informatics at the University of Colorado Denver.
The Division of Biostatistics and Bioinformatics maintains a Web page on the National Jewish intranet with useful statistical information, links for obtaining additional information, and a list server for responding to questions about SAS or JMP. Core members also assist in training fellows and serve as advisors for investigators, fellows, or PhD candidates who take advance training in quantitative aspects of medicine, biostatistics or epidemiology.