Insights Into Conducting Audiological Research With Clinical Databases

Dillard, Lauren K; Saunders, Gabrielle H.; Zobay, O.; Naylor, Graham

doi:10.1044/2020_aja-19-00067

Cited by 10 publications

(18 citation statements)

References 29 publications

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“…Data cleaning and preparation involved multiple steps and processes. As further discussed in Dillard et al (2020) , these were completed to avoid biases that can arise when using EHRs for research ( Verheij et al 2018 ). These processes, combined with examination of internal and external validity, give us confidence in the integrity of the data.…”

Section: Discussionmentioning

confidence: 99%

“…However, there is no reason to expect that these differences are systematic. Further, as discussed in Dillard et al (2020) , we attempted to capture all relevant conditions by using multiple codes (as opposed to one) to classify particular diagnoses and by broadening coding categories to account for changes in coding practices over time.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, before concluding that novel associations found in an EHR dataset reflect real effects, it is important to establish confidence in the dataset. See Dillard et al (2020) for additional discussion of issues that can arise when using and interpreting data from EHR datasets.…”

Section: Introductionmentioning

confidence: 99%

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Electronic Health Records As a Platform for Audiological Research: Data Validity, Patient Characteristics, and Hearing-Aid Use Persistence Among 731,213 U.S. Veterans

et al. 2020

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Objectives: This article presents a summary of audiological, general health, and hearing aid (HA) outcome data in a large sample of U.S. Veterans receiving HAs. The current article also provides the foundation for a series of papers that will explore relationships between a wide range of factors and HA outcomes. Design:The patient sample is all (n = 731,213) patients for whom HAs were ordered between April 2012 and October 2014 through the U.S. Veterans Health Administration Remote Order Entry System. For these patients, Veterans Affairs electronic health records (EHRs) stored in various databases provided data on demographics, received diagnostic and procedure codes (2007 to 2017), audiometry, self-reported outcomes up to 6 months postfitting, and HA battery orders (to 2017). Data cleaning and preparation was carried out and is discussed with reference to insights that provide potential value to other researchers pursuing similar studies. HA battery order data over time was used to derive a measure of long-term HA use persistence. Descriptive statistics were used to characterize the sample, comparative analyses against other data supported basic validity assessment, and bivariate analyses probed novel associations between patient characteristics and HA use persistence at 2 years postfitting.Results: Following extensive cleaning and data preparation, the data show plausible characteristics on diverse metrics and exhibit adequate validity based on comparisons with other published data. Further, rates of HA use persistence are favorable when compared against therapy persistence data for other major chronic conditions. The data also show that the presence of certain comorbid conditions (Parkinson's disease, diabetes, arthritis, and visual impairment) are associated with significantly lower HA use persistence, as are prior inpatient admissions (especially among new HA recipients), and that increasing levels of multimorbidity, in general, are associated with decreasing HA use persistence. This is all despite the fact that deriving relevant audiological care-process variables from the available records was not straightforward, especially concerning the definition of the date of HA fitting, and the use of battery ordering data to determine long-term HA use persistence. Conclusions:We have shown that utilizing EHRs in audiology has the potential to provide novel insights into clinical practice patterns, audiologic outcomes, and relations between factors pertaining to hearing and to other health conditions in clinical populations, despite the potential pitfalls regarding the lack of control over the variables available and limitations on how the data are entered. We thus conclude that research using EHRs has the potential to be an integral supplement to populationbased and epidemiologic research in the field of audiology.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Electronic Health Records As a Platform for Audiological Research: Data Validity, Patient Characteristics, and Hearing-Aid Use Persistence Among 731,213 U.S. Veterans

et al. 2020

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“…Additionally, procedural and diagnostic codes were used to identify HA-related appointments. See Dillard et al (2020) and Saunders et al (2020) for a full description of the provenance and processing of the dataset.…”

Section: Methodsmentioning

confidence: 99%

A Measure of Long-Term Hearing Aid Use Persistence Based on Battery Reordering Data

et al. 2021

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Objective: We describe the construction of a hearing aid long-term use persistence measure based on battery reorder data. The measure is derived from the notion that hearing aid users keep using their devices for some time after placing a battery order. Design: A hearing aid user is defined as persistent at time T if they placed a battery order within a time span W preceding T . We characterize and validate this measure using electronic health records from a large sample of US Veterans. Results: We describe how to choose parameters T and W for calculating persistence rates in the patient sample. For validation, the associations of persistence with: (1) the duration over which users received outpatient hearing aid care; (2) self-reported hearing aid use shortly after fitting; and (3) patient age and hearing loss are investigated. In all cases, plausible dependencies are observed. Conclusions: We conclude that our persistence measure is viable and hope this will motivate its use in similar studies.

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“…Finally, on a somewhat unique topic for the meeting, Dillard et al (2020) examine the data integrity issues that arise when using information stored in electronic health records (EHR) for research purposes within the context of an established framework. They note that while there are a multitude of advantages of using EHRs for research, correct interpretation of findings depends on an understanding of the data source and structure, and effort is required to avoid or ameliorate errors and biases.…”

Section: Introductionmentioning

confidence: 99%

Introduction for the 4th International Meeting on Internet and Audiology Special Issue of the American Journal of Audiology

Saunders

Preminger

2020

Am J Audiol

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Insights Into Conducting Audiological Research With Clinical Databases

Cited by 10 publications

References 29 publications

Electronic Health Records As a Platform for Audiological Research: Data Validity, Patient Characteristics, and Hearing-Aid Use Persistence Among 731,213 U.S. Veterans

Electronic Health Records As a Platform for Audiological Research: Data Validity, Patient Characteristics, and Hearing-Aid Use Persistence Among 731,213 U.S. Veterans

A Measure of Long-Term Hearing Aid Use Persistence Based on Battery Reordering Data

Introduction for the 4th International Meeting on Internet and Audiology Special Issue of the American Journal of Audiology

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