Article

Study Protocol: Prognostic Factors of High Healthcare Utilization Costs Among People with Spinal Disorders Using a Spine Registry Linked to Public Healthcare Data

2025-08-06

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Objective</h4> To identify prognostic factors associated with high spine-related healthcare costs among patients referred to secondary care for spinal disorders in Norway. <h4>Study Design and Setting</h4> This prognostic factor study will follow the PROGnosis RESearch Strategy (PROGRESS) framework. We will utilize data from 7,877 patients included in the Norwegian Neck and Back Registry b...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 13501366-db1d-5582-b5b4-fdd1249ccc60
DOI: 10.1101/2025.08.05.25333009

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Study Protocol: Prognostic Factors of High Healthcare Utilization Costs Among People with Spinal Disorders Using a Spine Registry Linked to Public Healthcare DataDOI 10.1101/2025.08.05.25333009Read

Prognostic Prediction Models for Patients with Low Back Pain: Systematic Review ProtocolSemantic proximity Read

Clustering high-cost patients in England using machine learning: a population-based cohort studySemantic proximity Read

Predicting patient-reported outcomes following lumbar spine surgery: development and external validation of multivariable prediction modelsSemantic proximity Read

Identifying cases of chronic pain using health administrative data: A validation studySemantic proximity Read

Predicting pain and function outcomes in people consulting with shoulder pain: The PANDA-S clinical cohort and qualitative study protocol (ISRCTN 46948079)Semantic proximity Read

Development and validation of a risk-prediction nomogram for chronic low back pain using a national health examination surveySemantic proximity Read

Multidimensional analysis of preoperative patient-reported outcomes identifies distinct phenotypes in patients booked for total knee arthroplasty: Secondary analysis of the SHARKS registry in a metropolitan hospital departmentSemantic proximity Read

Identifying patients with a phenotype consistent with chronic postsurgical pain after hip and knee arthroplasty using robust, scalable k-medoids clustering analysisSemantic proximity Read

Phenotypes of patients with symptomatic lumbar spinal stenosis presenting for nonoperative care: baseline data from the Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment Study (PROSPECTS).Semantic proximity Read

Development of prediction models and predictors analysis for axial neck pain in patients undergoing cervical laminoplasty based on machine learningSemantic proximity Read

Development and application of predictive clinical biomarkers for low back pain care: recommendations from the ISSLS phenotype/precision spine focus group.Semantic proximity Read