Electronic Medical Records

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Recommended: Current status of electronic health records

The adoption of Electronic Health Records (EHR) systems offers a number of substantial benefits, including increased quality of care, better efficiency and productivity, and financial incentives. Now a days it has become extremely important for healthcare organizations to acquire the appropriate tools, infrastructure, and techniques to manage and use the electronic medical data effectively. The existing medical surveillance systems use EHR to reach a deeper understanding of the medical problems and improve the accuracy of the diagnosis. In the literature, EHR is also referred as Electronic Medical Records (EMR), Electronic Patient Records (EPR), and Personal Health Record (PHR). Although there are technical differences between EHR, EMR, EPR …show more content…

So the format and schema of the structured data is well organized by the vendors. The studies discussed is this research are based on structured EHR mostly. 3.1.2. Semi-structured data Semi-structured EHR refers to clinical data stored in XML, CSV, or other basic text formats, which require pre-processing before querying. This format lies in-between two extremes (structured and unstructured). Generally semi-structured format is more flexible than the structured format because the users are able to define new metric based on their requirements. One example of semi-structured data is flow sheet which contains information regarding patient’s condition (e.g. blood pressure, blood sugar) under clinical care. It offer expandability to EHR systems because it provides detailed information about the speciality care. For example flow sheet provides information regarding how a particular measure is obtained (i.e. the blood sugar was measured after/before meal). 3.1.3. Unstructured …show more content…

surgical notes, radiology report). Unstructured data offers maximum flexibility among the three formats. It may also contain information regarding patient’s environmental exposures, lifestyle, or familial history of disease. Unstructured data requires an exhaustive pre-processing before querying. Natural language processing tools and techniques are required to extract knowledge and make the unstructured data ready for analysis. The scope of this research doesn’t cover the analysis techniques of unstructured EHR. 3.2. Data-Related Challenges EHR based research platform poses various challenges including data integration, interoperability across different platforms, and management of higher dimensional data. In this research, we discuss the key challenges involved in developing a clinical decision support system using EHR. In the next four section we discuss the challenges with missing data, irregular temporal data, censored data and distributed data source. 3.2.1. Missing

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