chronic-disease-registry-query

Name: chronic-disease-registry-query
Availability: InStock
Author: LangCare

Query FHIR data to build chronic disease registries and generate structured reports.

53|12|Updated Jan 26, 2026

Search Tags:#registry #data-analysis #outcomes #severity #fhir #disease-registry

Ready to run

npx skills add https://github.com/langcare/langcare-mcp-fhir --skill chronic-disease-registry-query

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: chronic-disease-registry-query
Source: https://github.com/langcare/langcare-mcp-fhir/tree/main/skills/core/population-health/chronic-disease-registry-query
Command: npx skills add https://github.com/langcare/langcare-mcp-fhir --skill chronic-disease-registry-query

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The registry analytics skill enables data-driven insight into chronic disease populations by aggregating and querying FHIR data to build disease registries, enabling health teams to measure prevalence, severity, treatment patterns, and outcomes across patient cohorts.

Core Features & Use Cases

Builds registries for diabetes, hypertension, COPD, asthma, CHF, and CKD from FHIR resources (Condition, Observation, MedicationRequest, Encounter, Patient).
Computes enrollment, severity/stage distributions, current treatment patterns, and longitudinal outcome trends; supports comorbidity and complication analysis.
Generates reproducible registry reports to identify gaps, track improvements, and support care-management decisions.

Quick Start

Run a registry query for a chosen disease (e.g., “diabetes”) on your FHIR server to generate a summarized registry report with demographics, severity, treatments, outcomes, and triggers.

Frequently Asked Questions about chronic-disease-registry-query

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a chronic disease registry from FHIR data?▼

A chronic disease registry aggregates FHIR resources like Condition, Observation, MedicationRequest, and Encounter to build patient cohorts for diabetes, hypertension, COPD, asthma, CHF, and CKD. It reports enrollment, severity, treatment patterns, and outcomes trends to identify care gaps and support care-management decisions.

Can I analyze hypertension severity and treatment patterns using FHIR resources?▼

Yes, you can analyze hypertension severity and treatment patterns by querying FHIR Condition, Observation, and MedicationRequest resources. The registry aggregates this data to compute severity distributions, current treatment regimens, and longitudinal outcomes trends for the targeted patient cohort.

What chronic conditions are supported for registry analysis and outcomes tracking?▼

Supported chronic conditions for registry analysis include diabetes, hypertension, COPD, asthma, CHF, and CKD. The registry extracts FHIR data to compute enrollment, severity stage distributions, treatment patterns, and outcomes trends, while also analyzing comorbidities and complications for each disease cohort.

Does the registry query exclude deceased patients from FHIR cohort analysis?▼

Yes, the registry query excludes deceased patients when extracting and aggregating FHIR data. This ensures the structured registry report accurately reflects active patient populations, allowing health teams to measure prevalence, severity, treatment patterns, and outcomes without skewing the data.

How do I identify care gaps and potential intervention triggers in a disease registry?▼

To identify care gaps and intervention triggers, the registry analyzes comorbidities, complications, and treatment patterns from FHIR Condition, Observation, and MedicationRequest resources. The structured report outputs demographics, trends, and potential intervention triggers to guide care-management decisions.

What's the best way to report comorbidities and complications for chronic disease cohorts?▼

The best way to report comorbidities and complications is by aggregating FHIR Condition and Encounter resources to build disease cohorts. The registry outputs a structured report detailing comorbidity and complication insights alongside demographics, severity distributions, and outcomes trends.