{
  "id": "AIBD-0064",
  "title": "Brainomix 360 Stroke AI supports immediate stroke identification at Royal Berkshire Hospital; 83-year-old transferred for thrombectomy within 25 minutes",
  "summary": "AI-supported scan identified Jean Hines's major stroke on arrival; transferred in 25 minutes for successful thrombectomy; good recovery.",
  "date_observed": "2025-08-01",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers.",
  "category": "protective response",
  "unexpected": false,
  "purpose": "Brainomix 360 Stroke is built to analyze stroke imaging and support rapid treatment and transfer decisions, including selection for thrombectomy. This is its intended function.",
  "system": "Brainomix 360 Stroke",
  "model_version": null,
  "developer": "Brainomix",
  "deployer": "NHS England / Royal Berkshire Hospital",
  "location": "Reading, United Kingdom",
  "domain": "Healthcare - acute stroke care",
  "segment": "Hospital stroke imaging decision support",
  "benefit_type": "Improved Physical Health",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 3,
      "reason": "Rapid transfer enabled thrombectomy for a major stroke and she reports no serious disabilities. The AI's contribution was the time saved."
    },
    {
      "group": "organizational",
      "depth": 2,
      "reason": "NHS England reports a 25-minute door-in-door-out for this patient against a 64-minute average reduction at primary stroke centers. It also reports a doubling of thrombectomy rates (2.3% to 4.6%) at participating sites."
    }
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  "ai_role": {
    "status": "assessed",
    "statement": "The AI-supported scan read identified the major stroke immediately on arrival, enabling a 25-minute door-in-door-out. The treatment itself (thrombectomy) was delivered by the Oxford team. The stroke would very likely have been diagnosed without AI. So the AI's contribution is the speed of decision and transfer. The Lancet Digital Health study (which has Brainomix co-authors alongside NHS lead authors) supports that at population level."
  },
  "evidence": [
    {
      "kind": "press release",
      "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance. NHS England news, 2 December 2025.",
      "title": "'Life-changing' AI support helping stroke patients get a second chance",
      "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/",
      "date": "2025-12-02",
      "written_by": "deployer",
      "quote": "A scan carried out immediately on arrival — supported by the Brainomix AI imaging tool — identified a major stroke and the need for urgent specialist treatment."
    },
    {
      "kind": "press release",
      "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance (second quotation).",
      "title": "'Life-changing' AI support helping stroke patients get a second chance",
      "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/",
      "date": "2025-12-02",
      "written_by": "deployer",
      "quote": "Within just 25 minutes of reaching the emergency department, Jean was on her way by blue-light ambulance to the John Radcliffe Hospital in Oxford"
    },
    {
      "kind": "peer-reviewed study",
      "citation": "Nagaratnam K, Neuhaus AA, Fensome L, et al. (2025). Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study. The Lancet Digital Health 7(12):100927. Three Brainomix employees and the corresponding author (dual NHS/Brainomix affiliation) are among 21 authors; lead authors are NHS and University of Oxford.",
      "title": "Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study",
      "url": "https://europepmc.org/abstract/MED/41339157",
      "date": "2025-12-02",
      "written_by": "makers",
      "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS."
    }
  ],
  "replication": {
    "produced_by": [
      "AI stroke imaging with results available to the admitting team immediately after the scan",
      "A regional transfer pathway from primary stroke center to a thrombectomy center"
    ],
    "must_hold": [
      "Rapid ambulance transfer and an available thrombectomy team",
      "Clinicians act on the AI-supported read without waiting for a separate specialist report"
    ],
    "echoes": [
      {
        "date": "2025-12-02",
        "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)",
        "model_version": null,
        "outcome": "recurred",
        "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Brainomix flags Jean Hines's stroke; transferred in 25 minutes",
  "metric": "transferred in 25 minutes for successful thrombectomy",
  "comparator": {
    "against": "thrombectomy rate at the same 26 hospitals before the software was implemented, with the 81 non-implementing hospitals as the background trend",
    "before": "2·3% (376 of 15 969 patients)",
    "after": "4·6% (751 of 15 428 patients), a relative increase of 100%",
    "basis": "measured",
    "quote": "For evaluation sites, the pre-implementation endovascular thrombectomy rate was 2·3% (376 of 15 969 patients) and the post-implementation rate was 4·6% (751 of 15 428 patients), a relative increase of 100%. For non-evaluation sites, the pre-implementation rate was 1·6% (1431 of 88 712 patients) and the post-implementation rate was 2·6% (2410 of 89 900 patients), a relative increase of 62·5% (odds ratio [OR] for the interaction between site and time period 1·24 [95% CI 1·08-1·43]; p=0·0026).",
    "url": "https://europepmc.org/abstract/MED/41339157"
  },
  "later": {
    "status": "scaled",
    "date": "2025-12-02",
    "note": "Four months after the inferred date of Jean Hines's stroke, the Lancet Digital Health study reported the same software systematically implemented in 26 NHS hospitals and associated with doubled thrombectomy rates.",
    "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS. These results support the routine use of AI imaging software in the management of patients with stroke.",
    "url": "https://europepmc.org/abstract/MED/41339157"
  },
  "value": null,
  "developer_country": "United Kingdom",
  "deployer_country": "United Kingdom",
  "unrated_because": null,
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      "change": "Record drafted from the cited sources.",
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      "editor": "AIBD"
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    {
      "date": "2026-10-20",
      "change": "NHS England item dated 2 December 2025 and the Lancet Digital Health item and echo dated 2025-12-02 from the Wayback Machine capture and the Europe PMC record, and category moved from specific harm prevented to protective response with prevention unproven with the taxonomy note rewritten, because no source shows that the AI changed this patient's outcome rather than the pathway timing.",
      "source": "NHS England news, 2 December 2025 (Wayback Machine capture of 9 December 2025 of https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/); Europe PMC record MED:41339157 (firstPublicationDate 2025-12-02)",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Added what the benefit is measured against, what happened since from the cited sources.",
      "source": "https://europepmc.org/abstract/MED/41339157; https://europepmc.org/abstract/MED/41339157",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://www.brainomix.com/contact/; https://en.wikipedia.org/wiki/Royal_Berkshire_Hospital",
      "editor": "AIBD"
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      "date": "2026-10-21",
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          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "title",
            "headline"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "a9d99f6616f7021e77b998362e17b8b0156769d248596b153f6ac094aba09b20"
          ],
          "role": "SHA-256 of normalized original case data"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers.",
            "replication": {
              "produced_by": [
                "AI stroke imaging with results available to the admitting team immediately after the scan",
                "A regional transfer pathway from primary stroke center to a thrombectomy center"
              ],
              "must_hold": [
                "Rapid ambulance transfer and an available thrombectomy team",
                "Clinicians act on the AI-supported read without waiting for a separate specialist report"
              ],
              "echoes": [
                {
                  "date": "2025-12-02",
                  "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)",
                  "outcome": "recurred",
                  "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 29,
      "reviewed": 0,
      "record_mapped": 29,
      "not_assessed": 62,
      "complete": false,
      "by_state": {
        "value_present": 29,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 62,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}