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    <title>topic CUSTOMER STORY | ENSEMBLE: Optimizing reimbursement through proactive healthcare strategies in Lakebase Articles</title>
    <link>https://community.databricks.com/t5/lakebase-articles/customer-story-ensemble-optimizing-reimbursement-through/m-p/156673#M34</link>
    <description>&lt;P&gt;&lt;SPAN&gt;"&lt;/SPAN&gt;&lt;I&gt;&lt;SPAN&gt;The data platform we’ve built with Databricks gives us a treasure trove of usable, enriched data that sets us apart from anyone else in the industry. It’s the foundation for solving problems no one else can.&lt;/SPAN&gt;&lt;/I&gt;&lt;SPAN&gt;"&lt;/SPAN&gt;&lt;SPAN&gt;&lt;BR /&gt;&lt;/SPAN&gt;&lt;STRONG&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; - Grant Veazey, CTO, Ensemble&lt;BR /&gt;&lt;BR /&gt;&lt;/STRONG&gt;&lt;STRONG&gt;Ensemble&lt;/STRONG&gt;&lt;SPAN&gt;, a leading revenue cycle management partner for U.S. hospitals and health systems, unified &lt;/SPAN&gt;&lt;STRONG&gt;2PB+ of provider, payer, and clinical data&lt;/STRONG&gt;&lt;SPAN&gt; on the &lt;/SPAN&gt;&lt;STRONG&gt;Databricks Data Intelligence Platform&lt;/STRONG&gt;&lt;SPAN&gt; to help healthcare organizations recover more revenue, faster. With &lt;/SPAN&gt;&lt;STRONG&gt;Databricks AI, Lakebase, and Managed MLflow&lt;/STRONG&gt;&lt;SPAN&gt;, Ensemble is moving from fragmented systems and manual pipelines to a more proactive, AI-ready revenue cycle.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;Key highlights:&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;20% improvement in organizational efficiency:&lt;/STRONG&gt;&lt;SPAN&gt; Ensemble improved internal efficiency by about &lt;/SPAN&gt;&lt;STRONG&gt;20%&lt;/STRONG&gt;&lt;SPAN&gt; as teams moved off disconnected SQL Server environments and manual workflows.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;3–5% improvement in net revenue yield:&lt;/STRONG&gt;&lt;SPAN&gt; Customers are seeing a &lt;/SPAN&gt;&lt;STRONG&gt;3–5% uplift in net revenue yield&lt;/STRONG&gt;&lt;SPAN&gt;, helping providers recover revenue that might otherwise be lost.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;2PB+ unified and enriched data foundation:&lt;/STRONG&gt;&lt;SPAN&gt; More than &lt;/SPAN&gt;&lt;STRONG&gt;2 petabytes&lt;/STRONG&gt;&lt;SPAN&gt; of data now sit in a harmonized, AI-ready environment, creating a stronger base for predictive models and low-latency insights.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;AI-ready operations with Databricks AI:&lt;/STRONG&gt;&lt;SPAN&gt; Databricks AI is built to help teams &lt;/SPAN&gt;&lt;STRONG&gt;build and deploy quality AI agent systems&lt;/STRONG&gt;&lt;SPAN&gt; with custom evaluation and governance for agent workflows.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Faster app and agent workflows with Lakebase and Managed MLflow:&lt;/STRONG&gt; &lt;STRONG&gt;Lakebase&lt;/STRONG&gt;&lt;SPAN&gt; provides a Postgres database integrated with the lakehouse for operational workloads, while &lt;/SPAN&gt;&lt;STRONG&gt;Managed MLflow&lt;/STRONG&gt;&lt;SPAN&gt; supports tracing, evaluation, and model management for AI applications and agents.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/customers/ensemble/ai" target="_blank" rel="noopener"&gt;&lt;span class="lia-unicode-emoji" title=":link:"&gt;🔗&lt;/span&gt;&amp;nbsp;Check out the full story here&amp;nbsp;&lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_left:"&gt;👈&lt;/span&gt;&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 12 May 2026 10:55:12 GMT</pubDate>
    <dc:creator>Tushar_Parekar</dc:creator>
    <dc:date>2026-05-12T10:55:12Z</dc:date>
    <item>
      <title>CUSTOMER STORY | ENSEMBLE: Optimizing reimbursement through proactive healthcare strategies</title>
      <link>https://community.databricks.com/t5/lakebase-articles/customer-story-ensemble-optimizing-reimbursement-through/m-p/156673#M34</link>
      <description>&lt;P&gt;&lt;SPAN&gt;"&lt;/SPAN&gt;&lt;I&gt;&lt;SPAN&gt;The data platform we’ve built with Databricks gives us a treasure trove of usable, enriched data that sets us apart from anyone else in the industry. It’s the foundation for solving problems no one else can.&lt;/SPAN&gt;&lt;/I&gt;&lt;SPAN&gt;"&lt;/SPAN&gt;&lt;SPAN&gt;&lt;BR /&gt;&lt;/SPAN&gt;&lt;STRONG&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; - Grant Veazey, CTO, Ensemble&lt;BR /&gt;&lt;BR /&gt;&lt;/STRONG&gt;&lt;STRONG&gt;Ensemble&lt;/STRONG&gt;&lt;SPAN&gt;, a leading revenue cycle management partner for U.S. hospitals and health systems, unified &lt;/SPAN&gt;&lt;STRONG&gt;2PB+ of provider, payer, and clinical data&lt;/STRONG&gt;&lt;SPAN&gt; on the &lt;/SPAN&gt;&lt;STRONG&gt;Databricks Data Intelligence Platform&lt;/STRONG&gt;&lt;SPAN&gt; to help healthcare organizations recover more revenue, faster. With &lt;/SPAN&gt;&lt;STRONG&gt;Databricks AI, Lakebase, and Managed MLflow&lt;/STRONG&gt;&lt;SPAN&gt;, Ensemble is moving from fragmented systems and manual pipelines to a more proactive, AI-ready revenue cycle.&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;&lt;FONT size="4"&gt;&lt;STRONG&gt;Key highlights:&lt;/STRONG&gt;&lt;/FONT&gt;&lt;/P&gt;
&lt;UL&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;20% improvement in organizational efficiency:&lt;/STRONG&gt;&lt;SPAN&gt; Ensemble improved internal efficiency by about &lt;/SPAN&gt;&lt;STRONG&gt;20%&lt;/STRONG&gt;&lt;SPAN&gt; as teams moved off disconnected SQL Server environments and manual workflows.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;3–5% improvement in net revenue yield:&lt;/STRONG&gt;&lt;SPAN&gt; Customers are seeing a &lt;/SPAN&gt;&lt;STRONG&gt;3–5% uplift in net revenue yield&lt;/STRONG&gt;&lt;SPAN&gt;, helping providers recover revenue that might otherwise be lost.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;2PB+ unified and enriched data foundation:&lt;/STRONG&gt;&lt;SPAN&gt; More than &lt;/SPAN&gt;&lt;STRONG&gt;2 petabytes&lt;/STRONG&gt;&lt;SPAN&gt; of data now sit in a harmonized, AI-ready environment, creating a stronger base for predictive models and low-latency insights.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;AI-ready operations with Databricks AI:&lt;/STRONG&gt;&lt;SPAN&gt; Databricks AI is built to help teams &lt;/SPAN&gt;&lt;STRONG&gt;build and deploy quality AI agent systems&lt;/STRONG&gt;&lt;SPAN&gt; with custom evaluation and governance for agent workflows.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;LI style="font-weight: 400;" aria-level="1"&gt;&lt;STRONG&gt;Faster app and agent workflows with Lakebase and Managed MLflow:&lt;/STRONG&gt; &lt;STRONG&gt;Lakebase&lt;/STRONG&gt;&lt;SPAN&gt; provides a Postgres database integrated with the lakehouse for operational workloads, while &lt;/SPAN&gt;&lt;STRONG&gt;Managed MLflow&lt;/STRONG&gt;&lt;SPAN&gt; supports tracing, evaluation, and model management for AI applications and agents.&lt;/SPAN&gt;&lt;/LI&gt;
&lt;/UL&gt;
&lt;P class="p8i6j01 paragraph"&gt;&lt;A style="background-color: #ff3621; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold; display: inline-block;" href="https://www.databricks.com/customers/ensemble/ai" target="_blank" rel="noopener"&gt;&lt;span class="lia-unicode-emoji" title=":link:"&gt;🔗&lt;/span&gt;&amp;nbsp;Check out the full story here&amp;nbsp;&lt;span class="lia-unicode-emoji" title=":backhand_index_pointing_left:"&gt;👈&lt;/span&gt;&lt;/A&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 12 May 2026 10:55:12 GMT</pubDate>
      <guid>https://community.databricks.com/t5/lakebase-articles/customer-story-ensemble-optimizing-reimbursement-through/m-p/156673#M34</guid>
      <dc:creator>Tushar_Parekar</dc:creator>
      <dc:date>2026-05-12T10:55:12Z</dc:date>
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