ArticleClinical epidemiology2015
Validation of International Classification of Diseases coding for bone metastases in electronic health records using technology-enabled abstraction.
Article in Clinical epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Electronic health record data quality assessment and tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2023Pooled it
- A Systematic Review of Estimating Breast Cancer Recurrence at the Population Level With Administrative Data.Journal of the National Cancer Institute · 2020Pooled it
- Biomarker Testing Approaches, Treatment Selection, and Cost of Care Among Adults With Advanced Cancer.JAMA network open · 2025Article
- Classifying Stereotactic Radiosurgery Patients by Primary Diagnosis Using Natural Language Processing of Clinical Notes.JCO clinical cancer informatics · 2025Article
- Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.Scientific reports · 2025Article
- Validation of Algorithms to Identify Bone Metastases Using Administrative Claims Data in a Japanese Hospital.Drugs - real world outcomes · 2023Article
- Article
- Chemoimmunotherapy vs. Immunotherapy for First Line Treatment of Advanced Non-small Cell Lung Cancer With a PD-L1 Expression ≥50% or ≥90.Clinical lung cancer · 2023Article
- Development and Use of Natural Language Processing for Identification of Distant Cancer Recurrence and Sites of Distant Recurrence Using Unstructured Electronic Health Record Data.JCO clinical cancer informatics · 2021Article
- Emergency Department Visits for Opioid Overdoses Among Patients With Cancer.Journal of the National Cancer Institute · 2020Article
- An evaluation of the impact of missing deaths on overall survival analyses of advanced non-small cell lung cancer patients conducted in an electronic health records database.Pharmacoepidemiology and drug safety · 2019Observational
- Implementing an Electronic Data Capture System to Improve Clinical Workflow in a Large Academic Radiation Oncology Practice.JCO clinical cancer informatics · 2018Article
- Risk-reducing mastectomy rates in the US: a closer examination of the Angelina Jolie effect.Breast cancer research and treatment · 2018Article
- Incidence of bone metastases in patients with solid tumors: analysis of oncology electronic medical records in the United States.BMC cancer · 2018Article
- Use of bone-modifying agents among breast cancer patients with bone metastasis: evidence from oncology practices in the US.Clinical epidemiology · 2018Article
- Longitudinal patterns of bone-targeted agent use among patients with solid tumors and bone metastases in the United States.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2017Article
- An observational study of concomitant immunotherapies and denosumab in patients with advanced melanoma or lung cancer.OncoimmunologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe accuracy of bone metastases diagnostic coding based on International Classification of Diseases, ninth revision (ICD-9) is unknown for most large databases used for epidemiologic research in the US. Electronic health records (EHR) are the preferred source of data, but often clinically relevant data occur only as unstructured free text. We examined the validity of bone metastases ICD-9 coding in structured EHR and administrative claims relative to the complete (structured and unstructured) patient chart obtained through technology-enabled chart abstraction. PATIENTS AND
methodsFemale patients with breast cancer with ≥1 visit after November 2010 were identified from three community oncology practices in the US. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of bone metastases ICD-9 code 198.5. The technology-enabled abstraction displays portions of the chart to clinically trained abstractors for targeted review, thereby maximizing efficiency. We evaluated effects of misclassification of patients developing skeletal complications or treated with bone-targeting agents (BTAs), and timing of BTA.
resultsAmong 8,796 patients with breast cancer, 524 had confirmed bone metastases using chart abstraction. Sensitivity was 0.67 (95% confidence interval [CI] =0.63-0.71) based on structured EHR, and specificity was high at 0.98 (95% CI =0.98-0.99) with corresponding PPV of 0.71 (95% CI =0.67-0.75) and NPV of 0.98 (95% CI =0.98-0.98). From claims, sensitivity was 0.78 (95% CI =0.74-0.81), and specificity was 0.98 (95% CI =0.98-0.98) with PPV of 0.72 (95% CI =0.68-0.76) and NPV of 0.99 (95% CI =0.98-0.99). Structured data and claims missed 17% of bone metastases (89 of 524). False negatives were associated with measurable overestimation of the proportion treated with BTA or with a skeletal complication. Median date of diagnosis was delayed in structured data (32 days) and claims (43 days) compared with technology-assisted EHR.
conclusionTechnology-enabled chart abstraction of unstructured EHR greatly improves data quality, minimizing false negatives when identifying patients with bone metastases that may lead to inaccurate conclusions that can affect delivery of care.
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.