ReviewSpine2012
Identifying neck and back pain in administrative data: defining the right cohort.
Review in Spine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00054847 (CSP #474 - Radial Artery vs. Saphenous Vein Grafts in Coronary Artery Bypass Surgery), which is not on this map. Cited by 18 papers.
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.
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.
CSP #474 - Radial Artery vs. Saphenous Vein Grafts in Coronary Artery Bypass Surgery (Radial Artery)
Who cites it
18 citing papers in PubMed, 40 citations in OpenAlex.
- The association between primary care appointment lengths and opioid prescribing for common pain conditions.BMC health services research · 2024Article
- Spinal pain and major depression in a military cohort: bias analysis of dependent misclassification in electronic medical records.Social psychiatry and psychiatric epidemiology · 2022Article
- Nightmare disorder and low back pain in veterans: cross-sectional association and effect over time.Sleep advances : a journal of the Sleep Research Society · 2022Article
- Impact of reported NSAID "allergies" on opioid use disorder in back pain.The Journal of allergy and clinical immunology · 2021Article
- Identifying cases of chronic pain using health administrative data: A validation study.Canadian journal of pain = Revue canadienne de la douleur · 2020Article
- Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization.Chiropractic & manual therapies · 2020Article
- Assessment of Primary Care Clinician Concordance With Guidelines for Use of Magnetic Resonance Imaging in Patients With Nonspecific Low Back Pain in the Veterans Affairs Health System.JAMA network open · 2020Article
- The bird's-eye view: A data-driven approach to understanding patient journeys from claims data.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Health Care Costs and Opioid Use Associated With High-impact Chronic Spinal Pain in the United States.Spine · 2019Article
- Classifying clinical notes with pain assessment using machine learning.Medical & biological engineering & computing · 2018Article
- Article
- Non-chemical Risk Assessment for Lifting and Low Back Pain Based on Bayesian Threshold Models.Safety and health at work · 2017Article
- Observational
- Classification of patients with incident non-specific low back pain: implications for research.The spine journal : official journal of the North American Spine Society · 2016Article
- Long-term Prescription of Opioids and/or Benzodiazepines and Mortality Among HIV-Infected and Uninfected Patients.Journal of acquired immune deficiency syndromes (1999) · 2015Observational
- Cost-utility of cognitive behavioral therapy for low back pain from the commercial payer perspective.Spine · 2015Article
- Using electronic health records data to identify patients with chronic pain in a primary care setting.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Receipt of opioid analgesics by HIV-infected and uninfected patients.Journal of general internal medicine · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
STUDY
designWe reviewed existing methods for identifying patients with neck and back pain in administrative data. We compared these methods using data from the Department of Veterans Affairs.
objectiveTo answer the following questions: (1) what diagnosis codes should be used to identify patients with neck pain and back pain in administrative data; (2) because the majority of complaints are characterized as nonspecific or mechanical, what diagnosis codes should be used to identify patients with nonspecific or mechanical problems in administrative data; and (3) what procedure and surgical codes should be used to identify patients who have undergone a surgical procedure on the neck or back. SUMMARY OF BACKGROUND DATA: Musculoskeletal neck and back pain are pervasive problems, associated with chronic pain, disability, and high rates of health care utilization. Administrative data have been widely used in formative research, which has largely relied on the original work of Volinn, Cherkin, Deyo, and Einstadter and the Back Pain Patient Outcomes Assessment Team first published in 1992. Significant variation in reports of incidence, prevalence, and morbidity associated with these problems may be due to nonstandard or conflicting methods to define study cohorts.
methodsA literature review produced 7 methods for identifying neck and back pain in administrative data. These code lists were used to search Veterans Health Administration data for patients with back and neck problems, and to further categorize each case by spinal segment involved, as nonspecific/mechanical and as surgical or not.
resultsThere is considerable overlap in most algorithms. However, gaps persist.
conclusionGaps are evident in existing methods and a new framework to identify patients with neck pain and back pain in administrative data is proposed.
Indexed as
Identifiers
What OpenQuestion holds
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.