<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Interoperability on phiz</title><link>https://phiz.ca/tags/interoperability/</link><description>Recent content in Interoperability on phiz</description><generator>Hugo</generator><language>en</language><copyright>Powered by [Wellington-Dufferin-Guelph Public Health](https://wdgpublichealth.ca/)</copyright><lastBuildDate>Tue, 07 Apr 2026 00:00:00 -0400</lastBuildDate><atom:link href="https://phiz.ca/tags/interoperability/index.xml" rel="self" type="application/rss+xml"/><item><title>Designing Data Lakehouses for Public Health</title><link>https://phiz.ca/posts/2026-04-data-lakehouse/</link><pubDate>Tue, 07 Apr 2026 00:00:00 -0400</pubDate><guid>https://phiz.ca/posts/2026-04-data-lakehouse/</guid><description/></item><item><title>From Legacy Portals to Data Pipelines: Safe Water with Browser Automation</title><link>https://phiz.ca/posts/2026-01-browser-automation/</link><pubDate>Mon, 12 Jan 2026 00:00:00 -0500</pubDate><guid>https://phiz.ca/posts/2026-01-browser-automation/</guid><description>&lt;p>Public health work relies heavily on digital systems to support surveillance, reporting, and operations. In practice, this often means working within web-based portals accessed through a browser. Many of these systems were not designed with automation or modern data integration in mind. As a result, routine tasks can consume substantial staff time and, in some cases, make otherwise valuable workflows impractical.&lt;/p>
&lt;p>Browser-based automation provides a pragmatic way to work within these constraints. Rather than replacing existing systems, it allows public health teams to interact with them programmatically, freeing capacity for analysis, decision-making, and community impact.&lt;/p></description></item><item><title>Complex Systems in Practice: Modernizing Public Health Data Flows</title><link>https://phiz.ca/posts/2026-01-complex-systems/</link><pubDate>Tue, 06 Jan 2026 00:00:00 -0500</pubDate><guid>https://phiz.ca/posts/2026-01-complex-systems/</guid><description>&lt;blockquote>
&lt;p>Complexity starts when causality breaks down.&lt;/p>
&lt;p>— &lt;cite>Nigel Goldenfeld&lt;sup id="fnref:1">&lt;a href="#fn:1" class="footnote-ref" role="doc-noteref">1&lt;/a>&lt;/sup>&lt;/cite>&lt;/p>&lt;/blockquote>
&lt;p>The first step in any innovation project is understanding where the friction lies. Where does the work slow down? Where do risks emerge? And who bears the burden of inefficient systems?&lt;/p>
&lt;p>In public health, many of these pain points are embedded in our data flows. Manual processes, fragmented systems, and unclear ownership are common features of legacy infrastructure. While often invisible to those outside the system, these challenges directly affect our ability to deliver timely, effective, and equitable public health services.&lt;/p></description></item></channel></rss>