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

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

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.

Study Overview

• Status: Enrolling by invitation
• Conditions: Low Back Pain; Neck Pain; Radiculopathy; Spinal Stenosis; Disc Degeneration; Disc Herniation

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 165000

Contacts and Locations

Study Locations

• Norway
  • Norge
    • Oslo, Norge, Norway, 0130
      • Oslo Metropolitan University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 80 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

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

Description

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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Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Treatment cohort; Surgical vs conservative treatment. Surgery procedures are based on the NOMESCO Classification of Surgical Procedures (NCSP). Conservative treatment includes all non-surgical treatment methods such as pharmaceutical treatment, physical medicine and physiotherapy modalities (information, patient education, exercise, manual therapy etc), cognitive-behavioural therapy, multidisciplinary treatment, acupuncture, and others (e.g. chiropractic treatment, homeopathy, naprapathy, osteopathy). The results will be described for important spinal subgroups (specific diagnoses, nerve-root affections, and non-specific conditions).

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Patient-reported outcomes	Patient-reported outcome measures included in clinical registers	depends upon the registry data, but in general between 2008 and 2022
Unfavourable outcomes	Healthcare utilization, reoperation, infection, or other complications after surgery.	depends upon the registry data, but in general between 2008 and 2022
Prescribed medication	High use of prescribed medication (dispensed drugs)	depends upon the registry data, but in general between 2008 and 2022
Sickness absence	Sickness absence and disability pension	depends upon the registry data, but in general between 2008 and 2022

Collaborators and Investigators

• Sponsor: Oslo Metropolitan University

Study record dates

Study Major Dates

• Study Start (Actual): December 1, 2021
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): December 31, 2028

Study Registration Dates

• First Submitted: February 1, 2023
• First Submitted That Met QC Criteria: February 15, 2023
• First Posted (Actual): February 27, 2023

Study Record Updates

• Last Update Posted (Actual): February 20, 2024
• Last Update Submitted That Met QC Criteria: February 16, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Keywords: prognosis; risk factors; prediction model; prognostic factors; prognostic model; trajectories; health outcomes; work outcomes
• Additional Relevant MeSH Terms: Nervous System Diseases; Pain; Neurologic Manifestations; Musculoskeletal Diseases; Neuromuscular Diseases; Peripheral Nervous System Diseases; Pathological Conditions, Anatomical; Bone Diseases; Hernia; Back Pain; Low Back Pain; Intervertebral Disc Displacement; Neck Pain; Intervertebral Disc Degeneration; Radiculopathy; Spinal Diseases; Spinal Stenosis
• Other Study ID Numbers: 371282

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No