ArticleHealth services research2018
Comparison of Electronic Health Record-Based and Claims-Based Diabetes Care Quality Measures: Causes of Discrepancies.
Article in Health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Enhanced access to healthcare utilization data through medical record review: Lessons learned from a community-based, multi-site project.Research in nursing & health · 2021Trial
- Article
- PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings.medRxiv : the preprint server for health sciences · 2025Article
- Analyzing the medical record homepages quality in a Chinese EMR system.BMC medical informatics and decision making · 2025Article
- Harnessing Electronic Medical Records in Cardiovascular Clinical Practice and Research.Journal of cardiovascular translational research · 2023Review
- Outcome evaluation of capacity building and mentorship partnership (CBMP) program on data quality in the public health facilities of Amhara National Regional State, Ethiopia: a quasi-experimental evaluation.BMC health services research · 2021Article
- Novel Data Linkages to Characterize Palliative and End-Of-Life Care: Challenges and Considerations.Journal of pain and symptom management · 2019Article
- Validity of acute cardiovascular outcome diagnoses in European electronic health records: a systematic review protocol.BMJ open · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo investigate magnitude and sources of discrepancy in quality metrics using claims versus electronic health record (EHR) data. STUDY
designAssessment of proportions of HbA1c and LDL testing for people ascertained as diabetic from the respective sources. Qualitative interviews and review of EHRs of discrepant cases. DATA COLLECTION/EXTRACTION: Claims submitted to Rhode Island Medicaid by three practice sites in 2013; program-coded EHR extraction; manual review of selected EHRs. PRINCIPAL
findingsOf 21,030 adult Medicaid beneficiaries attributed to a primary care patient at a site by claims or EHR data, concordance on assignment ranged from 0.30 to 0.41. Of patients with concordant assignment, the ratio of patients ascertained as diabetic by EHR versus claims ranged from 1.06 to 1.14. For patients with concordant assignment and diagnosis, the ratio based on EHR versus claims ranged from 1.08 to 18.34 for HbA1c testing, and from 1.29 to 14.18 for lipid testing. Manual record review of 264 patients discrepant on diagnosis or testing identified problems such as misuse of ICD-9 codes, failure to submit claims, and others.
conclusionsClaims data underestimate performance on these metrics compared to EHR documentation, by varying amounts. Use of claims data for these metrics is problematic.
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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.