2015
DOI: 10.1111/acem.12639
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What Big Data Can and Cannot Tell Us About Emergency Department Quality for Urolithiasis

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Cited by 6 publications
(8 citation statements)
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“…Empirical research evidence indicates that although big data is beneficial in case finding or as an indicator of the need to undertake further assessments, it is not accurate in determining the quality of care delivered to patients in emergency medical setting. This was demonstrated in a research study conducted by Meltzer and Pin [7] in emergency department of an organization in California, whereby serious health conditions of patients visiting it were not diagnosed using the technique. In this case, data analytics failed to identify potentially lethal conditions in vulnerable patients, such as cardiac infarction, fractures and internal hemorrhage among patients making several visits to the emergency department [7].…”
Section: Introductionmentioning
confidence: 99%
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“…Empirical research evidence indicates that although big data is beneficial in case finding or as an indicator of the need to undertake further assessments, it is not accurate in determining the quality of care delivered to patients in emergency medical setting. This was demonstrated in a research study conducted by Meltzer and Pin [7] in emergency department of an organization in California, whereby serious health conditions of patients visiting it were not diagnosed using the technique. In this case, data analytics failed to identify potentially lethal conditions in vulnerable patients, such as cardiac infarction, fractures and internal hemorrhage among patients making several visits to the emergency department [7].…”
Section: Introductionmentioning
confidence: 99%
“…A study conducted by Meltzer and Pin [7], on the potential benefits and limitations of big data in emergency medical services generated several interesting findings. One of the strengths of using big data analytics that enhance its application in emergency medicine is its ability to identify various relations and association of patients' information or data over period of time.…”
Section: Introductionmentioning
confidence: 99%
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