Abstract

BackgroundPatient portals are widely adopted in the United States and allow millions of patients access to their electronic health records (EHRs), including their EHR clinical notes. A patient’s ability to understand the information in the EHR is dependent on their overall health literacy. Although many tests of health literacy exist, none specifically focuses on EHR note comprehension.ObjectiveThe aim of this paper was to develop an instrument to assess patients’ EHR note comprehension.MethodsWe identified 6 common diseases or conditions (heart failure, diabetes, cancer, hypertension, chronic obstructive pulmonary disease, and liver failure) and selected 5 representative EHR notes for each disease or condition. One note that did not contain natural language text was removed. Questions were generated from these notes using Sentence Verification Technique and were analyzed using item response theory (IRT) to identify a set of questions that represent a good test of ability for EHR note comprehension.ResultsUsing Sentence Verification Technique, 154 questions were generated from the 29 EHR notes initially obtained. Of these, 83 were manually selected for inclusion in the Amazon Mechanical Turk crowdsourcing tasks and 55 were ultimately retained following IRT analysis. A follow-up validation with a second Amazon Mechanical Turk task and IRT analysis confirmed that the 55 questions test a latent ability dimension for EHR note comprehension. A short test of 14 items was created along with the 55-item test.ConclusionsWe developed ComprehENotes, an instrument for assessing EHR note comprehension from existing EHR notes, gathered responses using crowdsourcing, and used IRT to analyze those responses, thus resulting in a set of questions to measure EHR note comprehension. Crowdsourced responses from Amazon Mechanical Turk can be used to estimate item parameters and select a subset of items for inclusion in the test set using IRT. The final set of questions is the first test of EHR note comprehension.

Highlights

  • Background and SignificanceProviding patients access to their medical records through personal health records (PHRs) is becoming more common as physicians move to electronic health record (EHR) systems

  • The ComprehENotes question set is an instrument for measuring EHR note comprehension

  • During a pilot version of our Amazon Mechanical Turk (AMT) task, we asked participants to complete the Short Test of Functional Health Literacy in Adults (STOFHLA) as well as our test and found that all the respondents scored a perfect score (36) or answered 1 question wrong on the STOFHLA and were considered to have Adequate Health Literacy according to the STOFHLA scoring

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Summary

Introduction

Background and SignificanceProviding patients access to their medical records through personal health records (PHRs) is becoming more common as physicians move to electronic health record (EHR) systems. The Veterans Health Administration offers the My HealtheVet PHR through a Web-based patient portal, which allows millions of veterans to view their EHRs [5]. These records include both structured (eg, patient vitals) and unstructured data (eg, discharge summaries and clinical notes). Questions were generated from these notes using Sentence Verification Technique and were analyzed using item response theory (IRT) to identify a set of questions that represent a good test of ability for EHR note comprehension. A follow-up validation with a second Amazon Mechanical Turk task and IRT analysis confirmed that the 55 questions test a latent ability dimension for EHR note comprehension. The final set of questions is the first test of EHR note comprehension

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