{"id":39051,"date":"2025-12-03T09:33:39","date_gmt":"2025-12-03T09:33:39","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=article&p=39051"},"modified":"2025-12-03T09:33:39","modified_gmt":"2025-12-03T09:33:39","slug":"reshaping-nhs-patient-journeys","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/reshaping-nhs-patient-journeys\/","title":{"rendered":"From Siloed to Event-Driven Care: How Data and AI Are Reshaping NHS Patient Journeys"},"content":{"rendered":"

Rebuilding the flow of care<\/span>\u00a0<\/span><\/h3>\n

At\u00a0DataIQ\u2019s\u00a0World Congress, Ming Tang,\u00a0Chief Data and Analytics Officer\u00a0and\u00a0Chief Digital and Information Officer (Interim), NHS England,\u00a0described how the health system is shifting from siloed, service-centred care to an event-driven model that better reflects how patients move through the system. Today, referrals, tests and follow-ups are often captured in different systems, creating delays and making it harder for clinicians to act quickly.<\/span>\u00a0<\/span><\/p>\n

Ming outlined a long-term programme to connect those interactions, modernise the flow of information and create the foundation for generative AI to support care safely.<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

The architectural shift<\/span>\u00a0<\/span><\/h3>\n

Digitising processes alone does not deliver better care. As Ming put it, if data is scattered across services, clinicians still lack the context they need for the next best action.<\/span>\u00a0<\/span><\/p>\n

This is why the NHS is moving to an events-based architecture; a model where every interaction becomes a structured event that can be connected,\u00a0analysed\u00a0and surfaced when needed. It is a shift that enables real-time insight, demand\u00a0forecasting\u00a0and clearer clinical decision support.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Leadership in synchrony<\/span>\u00a0<\/span><\/h3>\n

To deliver this, the digital and data functions have been brought together.<\/span>\u00a0<\/span><\/p>\n

\u201cTo deliver, we need both of those working in synchrony.\u201d<\/span><\/i>\u00a0<\/span><\/p>\n

This alignment allows for shared standards, consistent\u00a0processes\u00a0and a more joined-up approach to operational redesign, providing\u00a0the conditions where AI can\u00a0be deployed to deliver the transformative care model.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Four programmes enabling connected care<\/span>\u00a0<\/span><\/h3>\n

Ming\u00a0highlighted four major programmes that turn this architectural shift into practical capability across the NHS:<\/span>\u00a0<\/span><\/p>\n

    \n
  1. \n

    The NHS App<\/span><\/h4>\n<\/li>\n<\/ol>\n

    Already widely used, it is evolving into a digital front door where patients can access test results, manage prescriptions and, over time, receive AI-supported guidance through their care pathways.<\/span>\u00a0<\/span><\/p>\n

      \n
    1. \n

      The Single Patient Record<\/span><\/h4>\n<\/li>\n<\/ol>\n

      A longitudinal, person-centred record built on the new architecture. It supports shared care plans, controlled write-back and secure sharing with carers. Given the sensitivity of the data, it is progressing through careful proofs of concept.<\/span>\u00a0<\/span><\/p>\n

        \n
      1. \n

        The Federated Data Platform<\/span><\/h4>\n<\/li>\n<\/ol>\n

        A common data model connecting 240 trusts. Developed through use cases rather than mandates, it helps reduce lost tests, repeated\u00a0procedures\u00a0and administrative handoffs.<\/span>\u00a0<\/span><\/p>\n

          \n
        1. \n

          The National Research Service<\/span><\/h4>\n<\/li>\n<\/ol>\n

          Developed with the\u00a0Wellcome\u00a0Trust, it opens a governed route to using NHS research datasets for clinical trials and population-level studies.<\/span>\u00a0<\/span><\/p>\n

          Together, these programmes create the environment in which generative AI can deliver meaningful support to clinicians and patients.<\/span>\u00a0<\/span><\/p>\n

           <\/p>\n

          Where AI is already making a difference<\/span>\u00a0<\/span><\/h3>\n

          Assistive summarisation<\/span>\u00a0<\/span><\/h4>\n

          Ming\u2019s\u00a0team began experimenting with AI two years ago. Their current model, built on\u00a0Anthropic\u2019s\u00a0Claude and trained on NHS data, produces discharge summaries patients find clearer and easier to understand. Because these outputs influence clinical decisions, they are undergoing MHRA approval.<\/span>\u00a0<\/span><\/p>\n

          Ambient voice<\/span>\u00a0<\/span><\/h4>\n

          Voice-based documentation is a natural fit for clinicians. The next step is automatic coding into clinical systems, followed by triggering routine actions such as booking tests,\u00a0shifting AI from transcription to workflow support.<\/span>\u00a0<\/span><\/p>\n

          Ask FDP<\/span>\u00a0<\/span><\/h4>\n

          Static dashboards\u00a0can fail\u00a0to\u00a0meet executive needs. Ask FDP, a natural-language interface connected to the Federated Data Platform, allows leaders to explore performance data conversationally. It also shows where information comes from, increasing confidence and reducing the burden on analytical teams.<\/span>\u00a0<\/span><\/p>\n

          Join DataIQ<\/span><\/i><\/a>\u00a0to access the full article and all of Ming Tang\u2019s insights.<\/span><\/i>\u00a0<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

          NHS England is rebuilding the data and digital infrastructure behind patient journeys, creating the conditions for safe, scalable, and clinically meaningful use of AI.<\/p>\n","protected":false},"author":19,"featured_media":39053,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,133],"tags":[217,87,794,294,1425],"pillar":[197,194],"class_list":["post-39051","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-reports","tag-ai","tag-leadership","tag-nhs","tag-silo","tag-world-congress","pillar-technology","pillar-leadership"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 01:43:04","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/39051","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=39051"}],"version-history":[{"count":2,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/39051\/revisions"}],"predecessor-version":[{"id":39055,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/39051\/revisions\/39055"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/39053"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=39051"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=39051"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=39051"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=39051"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}