ReviewCureus2022
Interfacing With the Electronic Health Record (EHR): A Comparative Review of Modes of Documentation.
Review in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Canadian Paramedic User Requirements for Speech Recognition-Aided Documentation.Applied clinical informatics · 2026Article
- Eliminating Nonvalue-Added Tasks in Health Care: Artificial Intelligence in the Orthopedic Office.Journal of hand surgery global online · 2026Article
- Ambient AI Documentation and Patient Satisfaction in Outpatient Care: Retrospective Pilot Study.JMIR AI · 2026Article
- The Current State of Digital Scribes in Primary Care: A Scoping Review.Journal of medical systems · 2026Article
- Strategies and Tools for Electronic Health Records and Physician Workflow Alignment: Protocol for a Scoping Review.JMIR research protocols · 2025Article
- Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study.JMIR aging · 2024Article
- I'm not burned out. This is how I write notes.JAMIA open · 2023Article
- Time to Put Down the Phone-A Case for Structured Data Entry.JCO clinical cancer informatics · 2023Article
- Generalizability and portability of natural language processing system to extract individual social risk factors.International journal of medical informatics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic health records (EHRs) have provided physicians with a systematic framework for collecting patient data, organizing notes from the healthcare team, and managing the daily workflow in the modern era of healthcare. Despite these advantages, EHRs have proven to be problematic for clinicians. The burdensome regulations requiring increased documentation with the EHR paradigm have led to inefficiencies from data-entry requirements forcing physicians to spend an inordinate amount of time on it, affecting the time available for direct patient care as well as leading to professional burnout. As a result, new modalities such as speech recognition, medical scribes, pre-made EHR templates, and digital scribes [a form of artificial intelligence (AI) based on ambient speech recognition] are increasingly being used to reduce charting time and increase the time available for patient care. The purpose of our review is to provide an up-to-date review of the literature on these modalities including their benefits and shortcomings, to help physicians and other medical professionals choose the best methods to document their patient-care encounters efficiently and effectively.
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.