Evidence map›Paper›PMID 28254738›Full record

ArticleJournal of medical Internet research2017

Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study.

Jiaping Zheng, Hong Yu

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Jiaping ZhengCollege of Information and Computer Sciences, University of Massachusetts, Amherst, MA, United States.ORCID 0000-0001-7662-810X
Hong YuBedford Veterans Affairs Medical Center, Center for Healthcare Organization and Implementation Research, Bedford, MA, United States.ORCID 0000-0001-9263-5035

Funding

Resource Curation and Evaluation for EHR Note ComprehensionR01LM012817 · NLM · UNIVERSITY OF MASSACHUSETTS LOWELL · PI YU, HONG · 2018 to 2020
$1.0M
Systems for Helping Veterans Comprehend Electronic Health Record NotesI01HX001457 · VA · NORTHAMPTON VA MEDICAL CENTER · PI YU, HONG · 2015 to 2020
–
HSRD VA I01 HX001457NLM NIH HHS R01 LM012817
6 · The paper itself

Abstract

backgroundElectronic health records (EHRs) are a rich resource for developing applications to engage patients and foster patient activation, thus holding a strong potential to enhance patient-centered care. Studies have shown that providing patients with access to their own EHR notes may improve the understanding of their own clinical conditions and treatments, leading to improved health care outcomes. However, the highly technical language in EHR notes impedes patients' comprehension. Numerous studies have evaluated the difficulty of health-related text using readability formulas such as Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning-Fog Index (GFI). They conclude that the materials are often written at a grade level higher than common recommendations.

objectiveThe objective of our study was to explore the relationship between the aforementioned readability formulas and the laypeople's perceived difficulty on 2 genres of text: general health information and EHR notes. We also validated the formulas' appropriateness and generalizability on predicting difficulty levels of highly complex technical documents.

methodsWe collected 140 Wikipedia articles on diabetes and 242 EHR notes with diabetes International Classification of Diseases, Ninth Revision code. We recruited 15 Amazon Mechanical Turk (AMT) users to rate difficulty levels of the documents. Correlations between laypeople's perceived difficulty levels and readability formula scores were measured, and their difference was tested. We also compared word usage and the impact of medical concepts of the 2 genres of text.

resultsThe distributions of both readability formulas' scores (P<.001) and laypeople's perceptions (P=.002) on the 2 genres were different. Correlations of readability predictions and laypeople's perceptions were weak. Furthermore, despite being graded at similar levels, documents of different genres were still perceived with different difficulty (P<.001). Word usage in the 2 related genres still differed significantly (P<.001).

conclusionsOur findings suggested that the readability formulas' predictions did not align with perceived difficulty in either text genre. The widely used readability formulas were highly correlated with each other but did not show adequate correlation with readers' perceived difficulty. Therefore, they were not appropriate to assess the readability of EHR notes.

Indexed as

ComprehensionElectronic Health RecordsHealth LiteracyHumansInternetelectronic health recordspatientsreadability

Identifiers

PMID28254738
PMCPMC5355629

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Registered trials

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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.