Expertise in real-world data

Our research program operates within an integrated care system with robust information technology, including our electronic health record, Kaiser Permanente HealthConnect®. Working with real-world health information requires a team with diverse expertise.

Biostatistics expertise

Investigators from our Division of Biostatistics Research work closely with investigators from other divisions and physician investigators at our medical centers, providing expertise and guidance on study design, power and sample size calculations, data management, data analysis and interpretation, and statistical methodology.

Some of our areas of expertise include:

  • clinical trials
  • genetic studies
  • longitudinal data
  • multi-level models
  • marginal structural models
  • Bayesian statistics
  • competing risks
  • structural equation modeling
  • nonparametric methods
  • model misspecifications
  • high-dimensional data
  • Monte Carlo methods
  • categorical data analysis
  • spatial analysis
  • causal inferences

Each division has at least one dedicated collaborative biostatistician research scientist assigned to provide statistical guidance on its research studies. In addition, each division has its own group of dedicated staff support, including analysts and programmers. Our statisticians, analysts, and programmers have expertise in R and SAS programming.

Clinical informatics and database development

The Clinical Informatics and Research Databases team develops and maintains a rich network of research data systems, databases, research applications, and registries that support our research program and selective patient care management activities.

Some of our areas of expertise include:

  • Oracle, Exadata, Teradata, and SQL server databases
  • database architecture and modeling
  • database consultation
  • application front-end user interface development
  • application architecture and modeling
  • web service development
  • natural language processing
  • text information extraction
  • medical image processing and analysis
  • deep learning and machine learning
  • predictive modeling
  • geocoding
  • information integration, including data linkage to birth and mortality information

In addition, the Clinical Informatics and Research Databases team has expertise in the following programming languages and tools: SAS, R, Python, C/C++, Perl, Apache, Hive, Ruby and Geographic Information System (GIS), Angular, ASP, .net, MVC, Java Spring, and MATLAB.