ArticleJournal of the American Medical Informatics Association : JAMIA2013
Using electronic health records data to identify patients with chronic pain in a primary care setting.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03593772 (Mission Reconnect), which is not on this map. Cited by 103 papers, 3 of them syntheses that pooled it.
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.
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.
Mission Reconnect: Delivering a Mobile and Web Based Self Directed Complementary and Integrative Health Program to Veterans and Their Partners to Manage Pain and PTSD
Who cites it
103 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Validity of Algorithms for Identification of Individuals Suffering from Chronic Noncancer Pain in Administrative Databases: A Systematic Review.Pain medicine (Malden, Mass.) · 2020Pooled it
- Identification of validated case definitions for medical conditions used in primary care electronic medical record databases: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
- Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.BMC medical informatics and decision making · 2017Pooled it
- Effect of Changing Electronic Health Record Opioid Analgesic Dispense Quantity Defaults on the Quantity Prescribed: A Cluster Randomized Clinical Trial.JAMA network open · 2021Trial
- A Novel Screening Method to Identify Late-Stage Dementia Patients for Palliative Care Research and Practice.Journal of pain and symptom management · 2018Trial
- Identifying Demographic Predictors of Increased Nonfatal Opioid Overdose Risk Among New York State Medicaid Enrollees After the COVID-19 Pandemic: An Analysis of Heterogeneous Treatment Effects.Epidemiology (Cambridge, Mass.) · 2026Article
- Patient and Clinician Perspectives on Chronic Pain Communication in Advanced Kidney Disease.Journal of the American Geriatrics Society · 2026Article
- Article
- Low bone mineral density and pain impact in adults with sickle cell disease.Blood advances · 2026Article
- Article
- Rural specialty care for Veterans with the chronic overlapping pain conditions: Fibromyalgia, migraine, or irritable bowel syndrome.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2026Article
- Article
- Association of analgesics prescription with incident comorbidities in people with osteoarthritis-a UK primary care database cohort study.Rheumatology advances in practice · 2026Article
- Comorbid Chronic Pain and Posttraumatic Stress Disorder Among Veterans: Approaches to Care.Military medicine · 2025Article
- Article
- Leveraging undecided cases in chart-reviewed phenotypes to enhance EHR-based association studies.Journal of biomedical informatics · 2025Article
- The Combined Relationship of Prescription Drug Monitoring Program Enactment and Medical Cannabis Laws with Chronic Pain-Related Healthcare Visits.Journal of general internal medicine · 2025Article
- Latent class analysis identifies distinct pain phenotypes in newly diagnosed systemic juvenile idiopathic arthritis.Arthritis research & therapy · 2025Article
- Refining chronic pain phenotypes: A comparative analysis of sociodemographic and disease-related determinants using electronic health records.The journal of pain · 2025Article
- Occurrence of Opioid-Related Neurocognitive Symptoms Associated With Long-term Opioid Therapy.The Clinical journal of pain · 2025Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and validate an accurate method to identify patients with chronic pain using electronic health records (EHR) data at a multisite community health center. MATERIALS AND
methodsWe identified patients with chronic pain in our EHR system using readily available data elements pertaining to pain: diagnostic codes (International Classification of Disease, revision 9; ICD-9), patient-reported pain scores, and opioid prescription medications. Medical chart reviews were used to evaluate the accuracy of these data elements in all of their combinations. We developed an algorithm to identify chronic pain patients more accurately based on these evaluations. The algorithm's results were validated for accuracy by comparing them with the documentation of chronic pain by the patient's treating clinician in 381 random patient charts.
resultsThe new algorithm, which combines pain scores, prescription medications, and ICD-9 codes, has a sensitivity and specificity of 84.8% and 97.7%, respectively. The algorithm was more accurate (95.0%) than pain scores (88.7%) or ICD-9 codes (93.2%) alone. The receiver operating characteristic was 0.981. DISCUSSION: A straightforward method for identifying chronic pain patients solely using structured electronic data does not exist because individual data elements, such as pain scores or ICD-9 codes, are not sufficiently accurate. We developed and validated an algorithm that uses a combination of elements to identify chronic pain patients accurately.
conclusionsWe derived a useful method that combines readily available elements from an EHR to identify chronic pain with high accuracy. This method should prove useful to those interested in identifying chronic pain patients in large datasets for research, evaluation or quality improvement purposes.
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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.