> 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/snomed-ct-data-analytics-guide/8-data-architectures/8.1-patient-records-for-analytics.md).
# Patient Records for Analytics
Electronic patient record systems typically require high performance, high reliability and no (or limited) downtime. Any operation that effects these key criteria need to be kept to an absolute minimum, so as not to disturb the clinical and documentation activities of busy clinicians.
Many analytics activities require large volumes of data to be processed, which may slow down or even 'lock out' clinical transactions that are being performed at the same time. For this reason, population-based analytics and clinical research is typically not performed directly on patient records in their native clinical system. Instead, analytics directly over 'live' patient records tends to be restricted to point of care analytics activities, such as historical summaries, clinical decision support and point of care reporting. These analytics activities tend to demand the most up to date data possible to ensure its accuracy. They also tend to only require data for a single patient, which can be efficiently accessed using a patient identifier index.
The following figure illustrates a simple architecture in which the data store for patient records is directly used for reporting and analytics purposes.
Analytics directly over patient records
***
Provide Feedback
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.snomed.org/snomed-ct-practical-guides/snomed-ct-data-analytics-guide/8-data-architectures/8.1-patient-records-for-analytics.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
