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- Healthcare Analytics
- Who it's for
- Population health programs
Population health programs
Population health and care management programs follow defined groups of patients over time and report how their outcomes change. Their cohorts are built from claims, registry and clinical extracts, and each source comes with a consent basis the program must record. Start with the cohorts and periods your program already tracks.
How Healthcare Analytics is set up for you
Cohorts by period
Each cohort has a cohort date and a revision, and results are stored per period window, so the trend for a defined group can be followed month by month.
Consent recorded on the data
Each deidentified fact and each cohort carries its consent basis, so a reviewer can confirm the data was used on terms the program accepts.
Exposure alongside counts
Cohort exposure and patient count sit next to the event counts, so rates can be read against the size and exposure of the group.
Source freshness visible
Snapshots record coverage dates and freshness, so a stale claims extract is caught before a cohort is built from it.
Population health and care management programs follow defined groups of patients over time and report how their outcomes change. Their cohorts are built from claims, registry and clinical extracts, and each source comes with a consent basis the program must record. Start with the cohorts and periods your program already tracks.
Pilot one program cohort over a few consecutive periods using a single source extract. Agree the consent bases you record and the exposure measure you use, then build, review and publish the cohorts. Reconcile patient counts with the source before adding further cohorts or sources. Keep identifiable data and the deidentification step in your own systems, and load only the deidentified facts.
[Plan the rollout](/healthcare-analytics/implementation), [review relevant modules](/healthcare-analytics#modules), and [compare the source data](/healthcare-analytics/data-model).
Features to start with
Outcome cohorts
Build each cohort revision from its outcome definition, owner, organization and consent basis.
Deidentified outcome facts
Load observation-level facts under a recorded consent basis and accept or reject each one.
Metric definitions
Approve the numerator, denominator, grain and aggregation method before any result is calculated.
Roles on the team
- Analytics Manager
- Assigns cohort owners, starts publication of reviewed cohort revisions and oversees follow-up work.
- Outcomes Analyst
- Builds cohort revisions, loads deidentified facts and prepares them for independent review.
- Clinical Reviewer
- Records independent review decisions against an exact cohort revision and verifies supporting evidence.
- Data Engineer
- Captures source snapshots, maintains field mappings and resolves failed or unreconciled operation runs.
Set up Healthcare Analytics your way.
Start free, then use Proto to change fields, steps and approvals before your team goes live.