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Services provided by the Division of Biostatistics and Bioinformatics in support of clinical and pre-clinical studies include:

Study Design and Management
Data Management and Analysis Services
Practice Considerations


Study Design and Management 

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.

  • Study Design

    • 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


  • Study Management

    • Provide staff for independent Data and Safety Monitoring Boards

    • Develop research plans and conduct independent interim statistical analyses

    • Produce compliance reports for clinical centers


  • Data Management

    • 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


  • Data 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


  • Utilization 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


  • Economic Analysis

    • 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


  • Presentation

    • 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



Data Management and Analysis Services

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.


Practice Considerations

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.