ArticleInternational journal of medical informatics2018
Electronic medical records as a replacement for prospective research data collection in postoperative pain and opioid response studies.
Article in International journal of medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Assessing the readiness of digital data infrastructure for opioid use disorder research.Addiction science & clinical practice · 2020Pooled it
- An anonymization-based privacy-preserving data collection protocol for digital health data.Frontiers in public health · 2023Article
- Development and testing of data infrastructure in the American College of Emergency Physicians' Clinical Emergency Data Registry for opioid-related research.Journal of the American College of Emergency Physicians open · 2022Article
- Using Electronic Medical Record Data for Research in a Healthcare Information and Management Systems Society (HIMSS) Analytics Electronic Medical Record Adoption Model (EMRAM) Stage 7 Hospital in Beijing: Cross-sectional Study.JMIR medical informatics · 2021Article
- Opioid Misuse and Dependence Screening Practices Prior to Surgery.The Journal of surgical research · 2020Article
- Electronic medical record-based cohort selection and direct-to-patient, targeted recruitment: early efficacy and lessons learned.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Providers' Perceptions of the Effectiveness of Electronic Health Records in Identifying Opioid Misuse.Journal of healthcare management / American College of Healthcare ExecutivesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
BACKGROUND AND
aimMany clinical research studies claim to collect data that are also captured in the electronic medical record (EMR). We evaluate the potential for EMR data to replace prospective research data collection.
methodsUsing a dataset of 358 surgical patients enrolled in a prospective study, we examined the completeness and agreement of EMR and study entries for several variables, including the patient's stay in the post-operative care unit (PACU), surgical pain relief and pain medication side effects.
resultsFor all variables with a completeness percentage, values were greater than 96%. For the adverse event variables, we found slight to substantial agreement (Cohen's kappa), ranging from 0.19 (nausea) to 0.48 (respiratory depression) to 0.73 (emesis).
conclusionThe potential to use EMR data as a replacement for prospective research data collection shows promise, but for now, should be evaluated on a variable-by-variable basis.
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.