This scenario represents population-level quality reporting for preventive care rather than a single patient chart. A measure resource defines the intent and metadata for tracking wellness visit completion among eligible members, aligned with accountable care and public health style dashboards. The accompanying library carries the computable logic clinicians and analysts expect in modern quality programs.
from zato_fhir.test.r4.v1 import Scenarios, TestData
for qm in Scenarios.quality_measure:
measure = qm.measure
print(measure.status)
report = qm.measure_report
print(report.status)
library = qm.library
print(library.status)This scenario represents population-level quality reporting for preventive care rather than a single patient chart. A measure resource defines the intent and metadata for tracking wellness visit completion among eligible members, aligned with accountable care and public health style dashboards. The accompanying library carries the computable logic clinicians and analysts expect in modern quality programs.
The measure report summarizes results for a reporting period in a favorable light: completion reaches ninety-two percent in the synthetic dataset, signaling strong performance without invoking exception workflows. There is no patient resource here because the focus is aggregate measurement suitable for registries, payers, and quality improvement teams validating pipelines end to end.
3 resources per instance, 30 total across 10 instances.
| FHIR resource type | Role in this scenario |
|---|---|
Measure | Definition of the preventive visit completion quality indicator |
MeasureReport | Period results showing ninety-two percent completion in test data |
Library | Shared logic such as CQL referenced by the measure |
FHIR resources per instance | 3 |
Total resources (10 instances) | 30 |
Distinct resource types | 3 |
Scenario identifier | `Scenarios.quality_measure` |
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