Cohort Definitions Framework


Product Overview

Cohort Definition Framework – Due to regulatory concerns and lack of available tools, researchers are often challenged obtaining even basic information about patient cohorts that are defined with complex rule sets. De-identified Cohort Builder allows non-technical users to input clinical and demographic criteria to identify specific populations of patients and obtain basic analytic data on those populations. The tool is ideal for researchers preparing a grant submission or IRB proposal. Access to the tool can be streamlined since there is no protected health information (PHI). In-Development


  • Population data available at three fundamental levels of granularity: patient-centric data such as demographics, problem lists, medication, labs, and orders (e.g., asthma, beta 2 agonists, and PFT orders); episode-centric data gathered from facility billing and specific to a facility account (e.g., pregnancy); and encounter-centric data derived from a patient encounter (e.g., appendectomy).
  • Populations stratified by diagnosis, place in the clinical hierarchy (clinical program, care process family, and care process), orders, medications, labs, and demographics.
  • Support for de-identified version to support research needs.


Metrics Include

  • Patients
  • Facility Accounts
  • Encounters
  • Clinical Programs
  • Care Process Families
  • Care Processes
  • Medications: Generic, Therapeutic Class, Pharmaceutical Class
  • Laboratory Orders
  • Demographics

See Sample Screenshots of Cohort Definitions Framework

Data Sources

  • Data comes from the EMR and may include patient problems, medications administered, laboratory orders and results, orders, APRDRGs (billing data), and ICD diagnoses and procedures

Cohort Definition Framework: A Deeper View


Clinical quality improvement initiatives and clinical studies require precisely defined patient populations. Having a clinician-friendly way to dynamically and simply interact with the data in the EDW can make this patient cohort definition process more efficient.

What types of problems does ACO Explorer address?

The task of defining patient cohorts for quality improvement projects or clinical studies is often shared by several people working in various clinical and technical roles. Typically, the complex questions of the clinician experts must be transmitted to technical team members, who then conduct the queries and produce a custom-built report—one that will likely require several iterative reviews before it meets the needs of the clinicians. This process of iteratively defining patient cohorts can be time-consuming—and it delays progress on meaningful clinical improvement and research.

Use Cases

A researcher is planning a study to investigate the use of ACE inhibitors in elderly patients with diabetes to determine the need for potassium supplementation. The researcher would like to know how many patients in the last year have diabetes, are older than age 65, have at least one order for an ACE inhibitor, and at least one serum potassium measurement.

Anticipated Improvements

  • Decreased time and resources required to create more precise patient registries for improvement projects and clinical studies.
  • Greater ease in planning resource needs and duration for studies, due to the ability to quickly determine number of members likely to qualify for research study within a given time period.

Success Measure

  • Registry identification: Identify potential $ saved from more efficient definition of patient cohorts.
  • Accelerated improvement: Lower time and resources spent on iterative population registry definitions for improvement work teams.
  • Better Information: Deliver rapid, clear insight into study recruitment potential, inclusion criteria, associated resources, and potential study timelines.