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		<title>A Guide to Healthcare Data Models: From Patient Records to Interoperability, Claims &#038; AI</title>
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					<comments>https://santeware.com/a-guide-to-healthcare-data-models-from-patient-records-to-interoperability-claims-ai/#respond</comments>
		
		<dc:creator><![CDATA[superadmin]]></dc:creator>
		<pubDate>Mon, 26 Oct 2026 06:57:40 +0000</pubDate>
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					<description><![CDATA[Healthcare data and interoperability Why healthcare data models matter Healthcare information is created across electronic health records, laboratories, imaging systems, pharmacies, billing platforms, insurers and research databases. Each system may structure and describe information differently. Healthcare data models help organize that information so it can be stored, exchanged, compared and used consistently. A data model [&#8230;]]]></description>
		
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		<title>FHIR + AI in Healthcare: From Interoperable Health Data to Intelligent Healthcare</title>
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		<dc:creator><![CDATA[superadmin]]></dc:creator>
		<pubDate>Sat, 17 Oct 2026 05:38:42 +0000</pubDate>
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		<category><![CDATA[#HealthcareInteroperability]]></category>
		<category><![CDATA[#HealthInformatics]]></category>
		<category><![CDATA[#RevenueCycleManagement]]></category>
		<category><![CDATA[ClinicalIntelligence]]></category>
		<category><![CDATA[EMR]]></category>
		<category><![CDATA[FHIR]]></category>
		<category><![CDATA[FHIRAI]]></category>
		<category><![CDATA[FHIRIntegration]]></category>
		<category><![CDATA[HealthcareAutomation]]></category>
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		<guid isPermaLink="false">https://santeware.com/?p=33594</guid>

					<description><![CDATA[Healthcare Data &#124; FHIR Interoperability &#124; Artificial Intelligence &#124; Healthcare Automation Introduction Healthcare organizations today rely on multiple systems to manage patient information, clinical encounters, laboratory results, medications, diagnostic reports, claims, and remote patient monitoring data. Although these systems generate valuable information, connecting it and making it useful across different healthcare workflows remains a significant [&#8230;]]]></description>
		
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		<title>Why Most EMR Implementations Struggle with Data Quality — And It’s Not the Software!</title>
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					<comments>https://santeware.com/why-most-emr-implementations-struggle-with-data-quality-and-its-not-the-software/#respond</comments>
		
		<dc:creator><![CDATA[superadmin]]></dc:creator>
		<pubDate>Sun, 12 Apr 2026 06:39:20 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[#AIInHealthcare]]></category>
		<category><![CDATA[#ClinicalData]]></category>
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					<description><![CDATA[Introduction   Healthcare organizations across globally are investing heavily in EMR and HIS transformations. New systems promise better workflows, improved patient care, and data-driven decision-making and also implementation of AI tools on top of it. Yet, many implementations face the same challenge shortly after go-live: Partial migration or mapping issues Incomplete records or inconsistent patient formats [&#8230;]]]></description>
		
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