Evidence map›Paper›PMID 38054107›Full record

ArticleOphthalmology science

The Impact of Documentation Workflow on the Accuracy of the Coded Diagnoses in the Electronic Health Record.

Thomas S Hwang, Merina Thomas, Michelle Hribar, Aiyin Chen, Elizabeth White

Abstract read
In one paragraph

Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Thomas S HwangCasey Eye Institute, Oregon Health and Science University, Portland, OR.
Merina ThomasCasey Eye Institute, Oregon Health and Science University, Portland, OR.
Michelle HribarCasey Eye Institute, Oregon Health and Science University, Portland, OR.
Aiyin ChenCasey Eye Institute, Oregon Health and Science University, Portland, OR.
Elizabeth WhiteCasey Eye Institute, Oregon Health and Science University, Portland, OR.

Funding

Proteomics CoreP30EY010572 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Kate E Keller · 1995 to 2026
$19.4M
Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic EfficiencyR01LM013426 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI HRIBAR, MICHELLE · 2020 to 2023
$1.3M
Identifying and understanding drivers of selection bias and information bias in clinical COVID-19 dataR21LM013645 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI WEISKOPF, NICOLE GRAY · 2021 to 2022
$368k
Improving Quality of Electronic Health Record Ophthalmic Data for Big Data AnalyticsR21EY031443 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI HRIBAR, MICHELLE · 2020 to 2020
$231k
Improving Quality of Electronic Health Record Ophthalmic Data for Big Data AnalyticsR21LM013937 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI WEISKOPF, NICOLE GRAY · 2021 to 2021
$187k
NEI NIH HHS P30 EY010572NEI NIH HHS R21 EY031443NLM NIH HHS R01 LM013426NLM NIH HHS R21 LM013645NLM NIH HHS R21 LM013937
6 · The paper itself

Abstract

Objective: To determine the impact of documentation workflow on the accuracy of coded diagnoses in electronic health records (EHRs). Design: Cross-sectional study. Participants: All patients who completed visits at the Casey Eye Institute Retina Division faculty clinic between April 7, 2022 and April 13, 2022. Main Outcome Measures: Agreement between coded diagnoses and clinical notes. Methods: We assessed the rate of agreement between the diagnoses in the clinical notes and the coded diagnosis in the EHR using manual review and examined the impact of the documentation workflow on the rate of agreement in an academic retina practice. Results: In 202 visits by 8 physicians, 78% (range, 22%-100%) had an agreement between the coded diagnoses and the clinical notes. When physicians integrated the diagnosis code entry and note composition, the rate of agreement was 87.9% (range, 62%-100%). For those who entered the diagnosis codes separately from writing notes, the agreement was 44.4% (22%-50%, Conclusion: The visit-specific agreement between the coded diagnosis and the progress note can vary widely by workflow. The workflow and EHR design may be an important part of understanding and improving the quality of EHR data. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Data qualityElectronic health recordsProblem-oriented charting

Identifiers

PMID38054107
PMCPMC10694743

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.