ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evidence-based Clinical Decision Support Systems for the prediction and detection of three disease states in critical care: A systematic literature review.F1000Research · 2019Pooled it
- A Novel Electronic Medical Record Search Method to Identify Patients With Ketosis-Prone Diabetes: Implications for Discovery of Atypical Diabetes.Diabetes care · 2026Article
- Medical Marijuana Documentation Practices in Patient Electronic Health Records: Retrospective Observational Study Using Smart Data Elements and a Review of Medical Records.JMIR formative research · 2024Observational
- Leveraging Large Language Models for Thyroid Nodule Information Extraction and Matching Across Medical Reports.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Validation of a Smartphone-Based Institutional Electronic Data Capture System for Thumb Carpometacarpal Joint Arthroplasty.Hand (New York, N.Y.) · 2023Article
- Low Vision Rehabilitation Service Utilization Before and After Implementation of a Clinical Decision Support System in Ophthalmology.JAMA network open · 2023Article
- Article
- Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis.Annals of medicine and surgery (2012) · 2022Review
- Review
- Validation of rule-based algorithms to determine colorectal, breast, and cervical cancer screening status using electronic health record data from an urban healthcare system in New York City.Preventive medicine reports · 2021Article
- Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation.Respiratory research · 2021Article
- Comprehensive Complication Index or Clavien-Dindo Classification: Which is Better for Evaluating the Severity of Postoperative Complications Following Pancreatectomy?World journal of surgery · 2021Article
- Amplifying Domain Expertise in Clinical Data Pipelines.JMIR medical informatics · 2020Article
- Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study.JMIR medical informatics · 2019Article
- The Value of Aggregated High-Resolution Intraoperative Data for Predicting Post-Surgical Infectious Complications at Two Independent Sites.Studies in health technology and informatics · 2019Article
- Use of Computerized Provider Order Entry Events for Postoperative Complication Surveillance.JAMA surgery · 2019Article
- Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Article
- Characterizing Functional Health Status of Surgical Patients in Clinical Notes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Characterizing Surgical Site Infection Signals in Clinical Notes.Studies in health technology and informatics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Manual Chart Review (MCR) is an important but labor-intensive task for clinical research and quality improvement. In this study, aiming to accelerate the process of extracting postoperative outcomes from medical charts, we developed an automated postoperative complications detection application by using structured electronic health record (EHR) data. We applied several machine learning methods to the detection of commonly occurring complications, including three subtypes of surgical site infection, pneumonia, urinary tract infection, sepsis, and septic shock. Particularly, we applied one single-task and five multi-task learning methods and compared their detection performance. The models demonstrated high detection performance, which ensures the feasibility of accelerating MCR. Specifically, one of the multi-task learning methods, propensity weighted observations (PWO) demonstrated the highest detection performance, with single-task learning being a close second.
Indexed as
Identifiers
28269941PMC5333220What 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.