The main challenges include extensive validation cycles with clinical safety boards, the 'handover failure' risk between data science and clinical informatics teams, integration with legacy hospital IT systems, and meeting strict API latency and uptime requirements. Projects often stall at integration with existing EHR systems, which have much higher robustness requirements compared to general software.
The main challenges include extensive validation cycles with clinical safety boards, the 'handover failure' risk between data science and clinical informatics teams, integration with legacy hospital IT systems, and meeting strict API latency and uptime requirements. Projects often stall at integration with existing EHR systems, which have much higher robustness requirements compared to general software.
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The main challenges include extensive validation cycles with clinical safety boards, the 'handover failure' risk between data science and clinical informatics teams, integration with legacy hospital IT systems, and meeting strict API latency and uptime requirements. Projects often stall at integration with existing EHR systems, which have much higher robustness requirements compared to general software.
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