ArticleSpine surgery and related research2022
Predictive Analysis of Healthcare Resource Utilization after Elective Spine Surgery.
Article in Spine surgery and related research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed, 9 citations in OpenAlex.
- Predictive Analysis of Social Determinants of Health in Posterior Cervical Spine Surgery.Journal of clinical medicine · 2026Article
- Prediction of primary admission total charges following lumbar disc arthroplasty utilizing machine learning.Journal of spine surgery (Hong Kong) · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The management of degenerative spine pathology continues to be a significant source of costs to the US healthcare system. Besides surgery, utilization of healthcare resources after spine surgery drives costs. The responsibility of managing costs is gradually shifting to patients and providers. Patient-centered predictors of healthcare utilization after elective spine surgery may identify targets for cost reduction and value creation. Therefore, our study aims to quantify patterns of healthcare utilization and identify risk factors that predict high healthcare utilization after elective spine surgery. Methods: A total of 623 patients who underwent elective spine surgery at a tertiary academic medical center by one of three fellowship-trained orthopedic spine surgeons between 2013 and 2018 were identified in this retrospective cohort study. Healthcare utilization was quantified including advanced spine imaging, emergency and urgent care visits, hospital readmission, reoperation, PT/OT referrals, opioid prescriptions, epidural steroid injections, and pain management referrals. Patient variables, namely, the Charlson comorbidity index (CCI) and the American Society of Anesthesiologists (ASA) classification system, were assessed as potential predictors for healthcare utilization. Results: Among all patients, a wide range of health utilization was identified. Age, body mass index, Charlson Comorbidity Index, and American Society of Anesthesiology class were identified as positive predictors of postoperative healthcare utilization including emergency department visits, spine imaging studies, opioid and nerve blocker prescriptions, inpatient rehabilitation, any referrals, and pain management referrals. Conclusions: Markers of patient health-such as CCI and ASA class-may be used to predict healthcare utilization following elective spine surgery. Identifying at-risk patients and addressing these challenges prior to surgery is an important step to deliver efficient postoperative care. Level of Evidence: 3.
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Registered trials
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 OpenQuestion graph.