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2 pages/≈550 words
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APA
Subject:
Health, Medicine, Nursing
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Essay
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English (U.S.)
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Data Processing Health, Medicine, Nursing Essay Paper (Essay Sample)

Instructions:

The purpose of this assignment is to explore the challenges associated with abstracting, normalizing, and reconciling clinical data from multiple disparate sources. In a 500-750 word paper address the following:
How are data abstracted from clinical records?
Describe the process of normalizing data.
Describe the process of reconciling data.
What are the challenges associated with using data from different sources?
This assignment requires two or three scholarly sources.
Prepare this assignment according to the guidelines found in the APA Style Guide

source..
Content:


Data Processing
Student’s Name
Institutional Affiliation

Data Processing
Data processing is vital in a clinical setting. Indeed, it enables clinicians to understand the number of patients affected by a particular illness and come up with an effective strategy to prevent it from spreading. Some of the most significant data processes that will be discussed in this paper include abstraction, reconciliation, and normalization.
Data abstraction entails providing crucial information to people and hiding the background details. With the implementation of the electronic health record (EHR), the processing of clinical records has become easy where healthcare professionals get the information that they want about their patients. For instance, when they want to know the number of patients affected by a specific disease, clinicians search the name of the illness on the database and the actual statistics (Zozus et al., 2015). When a doctor wants to know whether a particular patient has been admitted, one can use the patient code. Data abstraction enables clinicians to obtain the information they want from the EHR systems without knowing the internal processes that happen for them to get exactly what they want. Consequently, clinical records are abstracted to ensure that doctors obtain relevant information without understanding the calculations at the background of an EHR system.

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