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Rapid Analytics and Informatics


Rapid Analytics Unit

The Rapid Analytics Unit conducts focused analyses and applied research studies that have operational impact for The Permanente Medical Group (TPMG). This unit, located within the Division of Research, collaborates with TPMG physicians to provide a utility for rapid-turnaround projects on high-priority topics in specialty and primary care. Projects are selected with the guidance of TPMG executives in collaboration with clinical chiefs. Typical projects by this unit take 3 to 12 months to complete and use only existing computerized data.

In addition to conducting focused analytic projects, this unit’s research scientists and programmer/analysts help physicians develop research ideas designated as high priority by regional executives and clinical program leaders. The unit also supports selected participants in the Physician Researcher Program.

Examples of projects include:

  • Rapid case ascertainment of testicular cancer to support regional networking of care
  • Teleneurology for rapid treatment of stroke: Evaluation of a new program
  • Familial hypercholesterolemia: Algorithms to identify potential cases

To suggest an idea for a Rapid Analytics Unit project, please contact

Targeted Analysis Program

The Targeted Analysis Program supports projects that address questions of high value to both quality leaders and researchers. Projects typically are co-led by a Division of Research scientist and a regional clinical or operational leader. To be eligible, a project must primarily use existing data and must be feasible within 6 months or less with a budget of $36,000 or less. Projects are selected based on a competitive application process. Key selection criteria are the potential to contribute to operational excellence and potential to lead to a research product.

Examples of projects include:

  • Blood pressure control: Finding opportunities to reduce disparities
  • Pediatric obesity: Weight tracking in a high-risk population
  • Electronic nicotine delivery systems: Identification in the electronic health record via natural language processing

Learn more about the program from Julie Schmittdiel, PhD, TAP program director.