Evidence map›Paper›PMID 41562120›Full record

ArticlePain reports2026

Predicting high health care use in patients with spinal disorder in secondary care: model development and validation.

Lise Grethe Kjønø, Karin Magnusson, Marianne Bakke Johnsen, Kjersti Storheim, Stine Haugaard Clausen, Maja Wilhelmsen, Søren O'Neill, Are Hugo Pripp, Bjørnar Berg, Christian Volmar Skovsgaard and 3 more

Abstract read
In one paragraph

Article in Pain reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Lise Grethe KjønøDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.ORCID https://orcid.org/0009-0005-4095-9667
Karin MagnussonCluster for Health Services Research, Norwegian Institute of Public Health, Oslo, Norway.
Marianne Bakke JohnsenDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
Kjersti StorheimDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
Stine Haugaard ClausenCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Maja WilhelmsenFaculty of Health Sciences, Department of Clinical Medicine, UiT-The Arctic University of Norway, Tromsø, Norway.
Søren O'NeillMedical Spinal Research Unit, Spine Centre of Southern Denmark, Lillebaelt Hospital - University Hospital of Southern Denmark, Kolding, Denmark.
Are Hugo PrippFaculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
Bjørnar BergDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
Christian Volmar SkovsgaardDepartment of Public Health, Danish Centre for Health Economics, University of Southern Denmark, Odense, Denmark.
Jan HartvigsenCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Margreth GrotleDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
Ørjan Nesse VigdalDepartment of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Spinal disorders are among the biggest contributors to health care utilization (HCU). Objective: To develop and externally validate a prediction model for high all-cause HCU (75th percentile during 1 year after the index date) among patients with spinal disorders visiting multidisciplinary secondary care clinics. Methods: We developed and internally validated the model using the Norwegian Neck and Back Registry, including patients registered between January 1, 2016, and December 31, 2020, linked with national health registries (N = 9092). For external validation, we used data from the Danish SpineData Registry, linked with national registries, for the same period (N = 34,853). We assessed Nagelkerke Results: The final model included sex, nationality, education, physical activity, smoking, prior HCU, work status, disability, health-related quality of life, medicine use, diagnosis, kinesiophobia, and comorbidity. It demonstrated acceptable discrimination (AUC 0.78, 95% confidence interval [CI], 0.77-0.78), an Conclusion: Overall, the model shows promise in predicting high HCU in patients with spinal disorders referred to secondary care but requires further testing and validation in implementation settings before recommendation.

Indexed as

EpidemiologyHigh health care utilizationPrediction modelRegistry dataSpinal disordersValidation

Identifiers

PMID41562120
PMCPMC12815531

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.