Applying Artificial Intelligence in Developing Personalized and Sustainable Healthcare for Spinal Disorders

Официальное название

Applying Artificial Intelligence in Developing Personalized and Sustainable Healthcare for Spinal Disorders (AID-Spine, Part I)

Обзор

The primary objective is to use machine learning methods on large survey and health register data to identify participants with different treatment trajectories and health outcomes after surgical and/or conservative treatment for spinal disorders. Secondary objectives are to 1) conduct external validation of the prediction models, and 2) explore how the prediction models can be implemented into AI-based clinical co-decision tools and interventions.

Подробное описание

Three work packages are conducted. In the first, the investigators will use data from three general population surveys in Norway (HUNT, Tromsø, and Ullensaker) linked to administrative health registry data (Norwegian Patient Registry (for secondary care) and Norwegian Registry for Primary Health Care) and clinical registers on spinal disorders (the Norwegian registry for spine surgery, NorSpine, and the Norwegian registry for neck and back pain) to explore treatment trajectories and health outcomes following an episode of back and/or neck pain. The investigators will use different combinations of these data sets to assess the impact of a wide range of risk/ prognostic factors and to develop prognostic models for different health and welfare outcomes.

Four major outcomes will be adressed; a) unfavourable outcomes, b) use of prescribed medication, c) use of sickness absence and other disability benefits, and d) patient-reported outcomes.

In the second work package, the investigators will conduct external validation studies of the prediction models by using Danish and Swedish data. There is a large overlap and similarities in health and welfare registers across the Nordic countries.

In the third work package the investigators will first conduct a feasibility study in a secondary care hospital setting in which surgeons examine and assess referred patients with disc herniation and spinal stenosis for surgical treatment (or not). Qualitative interviews will be used to gain a better understanding of today's clinical decision-making process.

Первичные конечные точки

• Patient-reported outcomes [Срок оценки: depends upon the registry data, but in general between 2008 and 2022]
• Unfavourable outcomes [Срок оценки: depends upon the registry data, but in general between 2008 and 2022]
• Prescribed medication [Срок оценки: depends upon the registry data, but in general between 2008 and 2022]
• Sickness absence [Срок оценки: depends upon the registry data, but in general between 2008 and 2022]

Критерии участия

Inclusion Criteria: patients referred to secondary care for assessment of surgery or not due to disc herniation (lumbar or cervical).

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Exclusion Criteria: ambulant cases who needs immediate treatment

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Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Другое

Центры проведения

Норвегия · 1 центр

• Oslo Metropolitan University — Oslo

Публикации

• Zouch JH, Berg B, Pripp AH, Storheim K, Ashton-James CE, Ferreira ML, Grotle M, Ferreira PH. Reducing strain on primary healthcare systems through innovative models of care: the impact of direct access physiotherapy for musculoskeletal conditions-an interrupted time series analysis. Fam Med Community Health. 2024 Sep 24;12(3):e002998. doi: 10.1136/fmch-2024-002998. PMID 39317459

Идентификаторы

NCT: NCT05745129 · 371282

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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