Disc Degeneration, Disc Herniation, Low Back Pain, Neck Pain, Radiculopathy, Spinal Stenosis
Conditions
Keywords
prognosis, trajectories, risk factors, prognostic factors, prognostic model, prediction model, health outcomes, work outcomes
Brief summary
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.
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.
Interventions
None listed
Sponsors
Oslo Metropolitan University
Study design
Observational model
OTHER
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
patients referred to secondary care for assessment of surgery or not due to disc herniation (lumbar or cervical). \-
Exclusion criteria
ambulant cases who needs immediate treatment \-
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Patient-reported outcomes | depends upon the registry data, but in general between 2008 and 2022 | Patient-reported outcome measures included in clinical registers |
| Unfavourable outcomes | depends upon the registry data, but in general between 2008 and 2022 | Healthcare utilization, reoperation, infection, or other complications after surgery. |
| Prescribed medication | depends upon the registry data, but in general between 2008 and 2022 | High use of prescribed medication (dispensed drugs) |
| Sickness absence | depends upon the registry data, but in general between 2008 and 2022 | Sickness absence and disability pension |
Countries
Norway
Outcome results
None listed