2020
DOI: 10.1109/access.2020.3011099
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Secondary Use of Electronic Health Record: Opportunities and Challenges

Abstract: In the present technological era, healthcare providers generate huge amounts of clinical data on a daily basis. Generated clinical data is stored digitally in the form of Electronic Health Record (EHR) as a central data repository of hospitals. Data contained in EHR is not only used for the patients' primary care but also for various secondary purposes such as clinical research, automated disease surveillance and clinical audits for quality enhancement. Using EHR data for secondary purposes without consent or … Show more

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Cited by 56 publications
(48 citation statements)
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References 136 publications
(100 reference statements)
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“…Dealing with these challenges can be done in a manner that does not create unintended ethical breaches such as uncontrolled or unauthorised re-identification or disclosure of participant information. Other challenges and opportunities of an integrated system are presented by Shah and Khan 312 and Jones et al 71 .…”
Section: Resultsmentioning
confidence: 99%
“…Dealing with these challenges can be done in a manner that does not create unintended ethical breaches such as uncontrolled or unauthorised re-identification or disclosure of participant information. Other challenges and opportunities of an integrated system are presented by Shah and Khan 312 and Jones et al 71 .…”
Section: Resultsmentioning
confidence: 99%
“…It might consume more time also increases the probability of erroneous in the final results. To avoid this issue, healthcare records are converted digitally as EHR and stored in a data repository [6]. Feature selection is an important process in healthcare data analysis.…”
Section: Related Workmentioning
confidence: 99%
“…However, as we noted previously, clinical data from local sources like institutional EHRs, which are primarily used to track patient care but can also be used secondarily for clinical research and automated disease surveillance, have great potential for use in modeling AD dementia progression. 88 Data from such raw EHR data sources often have data quality issues and require significant effort for data preprocessing and feature engineering. However, they are a rich source of historical clinical data containing patient-level elements which can be effectively leveraged using ML-based computational techniques for longitudinal analyses of their preclinical phase to identify prognostic clinical phenotypes, thus representing an opportunity to employ precision medicine paradigms in disease states where the current evidence-base precludes such an approach.…”
Section: Reproducibilitymentioning
confidence: 99%