> For the complete documentation index, see [llms.txt](https://docs.snomed.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.snomed.org/snomed-ct-practical-guides/implementation-maturity-framework-guide/snomed-ct-implementation-maturity-assessment/maturity-assessment-for-vendors-software-products/example-vendor-software-product.md).

# Example - Vendor / Software Product

## Scenario

A mature EHR product that:

* Has broad SNOMED CT coverage across core clinical modules
* Provides good usability (search, selection, UI integration)
* Supports basic interoperability standards
* Relies on semi-manual terminology update processes
* Has limited advanced analytics and AI capabilities

This reflects a typical commercially mature product, where usability and core functionality are strong, but deeper terminology and data capabilities lag behind.

***

## Step 1: Score Key Questions

### KPA: Scope of SNOMED CT Implementation

| Question         | Selected Option              | Score |
| ---------------- | ---------------------------- | ----- |
| EHR Modules      | Comprehensive – most modules | 75    |
| Clinical Domains | Moderate scope               | 50    |

KPA Score = (75 + 50) ÷ 2 = 62.5

***

### KPA: Terminology Provisioning and Maintenance

| Question                    | Selected Option                                   | Score |
| --------------------------- | ------------------------------------------------- | ----- |
| Update Processes            | Basic structured process (manual effort required) | 25    |
| Localization & Notification | Limited localization                              | 25    |

KPA Score = 25

***

### KPA: Usability and Tool Support

| Question           | Selected Option                              | Score |
| ------------------ | -------------------------------------------- | ----- |
| Search & Interface | Intuitive interfaces (synonyms, suggestions) | 50    |
| Feedback & Metrics | Metrics actively tracked                     | 75    |

KPA Score = 62.5

***

### KPA: Interoperability

| Question      | Selected Option                             | Score |
| ------------- | ------------------------------------------- | ----- |
| Data Exchange | Standard-based integration (e.g., FHIR/HL7) | 50    |

KPA Score = 50

***

### KPA: Advanced Decision Support and Analytics

| Question               | Selected Option                       | Score |
| ---------------------- | ------------------------------------- | ----- |
| Decision Support       | Defined tools (standard CDS features) | 50    |
| Analytics Capabilities | Basic analytics (reporting only)      | 25    |

KPA Score = (50 + 25) ÷ 2 = 37.5

***

## Step 2: Overall Maturity Level

| Area                    | Score | Level              |
| ----------------------- | ----- | ------------------ |
| Scope of Implementation | 62.5  | Level 3            |
| Terminology Management  | 25    | Level 1–2          |
| Usability               | 62.5  | Level 3            |
| Interoperability        | 50    | Level 2–3          |
| Analytics & CDS         | 37.5  | Level 2            |
| Overall                 | 47.5  | Level 2 – Emerging |

Domain Score = (62.5 + 25 + 62.5 + 50 + 37.5) ÷ 5 = 47.5

→ Level 2 – Emerging (upper range)

***

## Interpretation

#### Strengths

* Strong coverage across clinical modules
* Good usability and user experience
* Solid foundation for interoperability
* Active use of user feedback for improvements

#### Weaknesses

* Weak terminology lifecycle management (updates, versioning, localization)
* Limited automation in terminology provisioning
* Basic analytics and limited decision support capabilities

***

### Priority Actions

To progress to Level 3 – Advanced, the vendor should:

#### 1. Strengthen Terminology Management

* Implement automated SNOMED CT update pipelines
* Introduce version control and release management
* Improve localization and extension handling

#### 2. Enhance Analytics and CDS

* Expand decision support capabilities
* Introduce predictive and real-time analytics
* Enable better use of coded data

#### 3. Improve Interoperability Depth

* Expand terminology services (value sets, mappings)
* Strengthen semantic interoperability across systems

***

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