# What are the best healthcare integration engines for networks connecting multiple EHRs without custom point-to-point interfaces?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Been looking into what the best healthcare integration engines are for networks connecting multiple EHRs without custom point-to-point interfaces, and it's a pretty specific architectural need. The point-to-point web gets complicated fast as you add systems, so I wanted to see which platforms are actually built around a hub model where each system connects once and the engine handles routing.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/intersystems-intersystems-iris-for-health/reviews"><strong>InterSystems IRIS for Health</strong></a>: Reviewers working with multiple hospital information systems describe it as handling routing, transformation, and storage in one place. A system administrator managing integrations across 20 laboratories described getting secure result delivery across all of them without separate custom builds per connection.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/iguana/reviews"><strong>Iguana</strong></a>: The reusable channel model is what reviewers bring up when the question is about connecting multiple EHRs at scale. Write integration logic once, deploy across multiple sites with configuration-only changes. One organization described a uniform configuration that adapts per site without new code being written each time.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/keragon/reviews"><strong>Keragon</strong></a>: In smaller multi-practice and digital health contexts, reviewers describe it as the layer connecting CRMs, EHRs, communication platforms, and scheduling systems without any of those systems needing to talk directly to each other. The hub model is what it's built around.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-cloud-healthcare-api/reviews"><strong>Google Cloud Healthcare API</strong></a>: Reviewers building FHIR-based platforms describe it as the central store that multiple EHR connections feed into, normalizing data from disparate sources into a single queryable format without point-to-point wiring between each system.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For networks that have made this shift: did moving to a hub model actually simplify the data normalization problem, or did schema differences between EHRs stay just as messy even after the connection architecture got cleaner?</p>

##### Post Metadata
- Posted at: 2 months ago
- Author title: SEO Content Specialist
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Centralizing normalization also creates one important operational question: who owns the canonical model? Once several EHRs map into the same representation, changing that shared mapping can affect multiple downstream workflows at once. I’d want strong versioning and impact visibility so the hub removes duplicated mapping work without turning one mapping change into a larger blast radius.&lt;/p&gt;

##### Comment Metadata
- Posted at: 17 days ago
- Author title: Writer



### Comment 2

&lt;p&gt;The hub model should simplify the connection architecture, but I wouldn’t expect it to eliminate schema differences. You still need strong normalization and mapping rules; the real win is managing that complexity centrally instead of recreating it across dozens of point-to-point interfaces.&lt;/p&gt;

##### Comment Metadata
- Posted at: 19 days ago
- Author title: Marketer



### Comment 3

&lt;p&gt;&lt;span style=&quot;color: rgb(0, 0, 0);&quot;&gt;Worth separating connection architecture from semantics here, because the hub model only solves one of them. Moving off point-to-point cuts the number of connections you maintain, but two EHRs that describe the same field differently still describe it differently afterwards. What changes is location: the reconciliation work stops being duplicated inside every interface and gets done once in the middle, where you can actually see it. That&#39;s the appeal of the Google Cloud Healthcare API pattern your post describes, with sources feeding one normalized store rather than each pair negotiating its own format.&lt;/span&gt;&lt;/p&gt;

##### Comment Metadata
- Posted at: 19 days ago
- Author title: Tech Consultant



### Comment 4

&lt;p&gt;The schema normalization question is the honest follow-up to the connection architecture question. Moving to a hub model does clean up the wiring, but the schema differences between EHRs tend to stay messy regardless of how the connection layer is organized. The Google Cloud Healthcare API approach of normalizing into a single FHIR-based queryable store is the only one in this thread that addresses both problems rather than just the connection pattern.&lt;/p&gt;

##### Comment Metadata
- Posted at: 2 months ago
- Author title: Marketing Executive





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