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We discuss an analysis pattern that describes some aspects of a patient treatment instance. Each encounter within a medical facility must be documented. Our pattern describes the breakdown of each treatment instance, or chart into categories for a patient stay or visit in a hospital. Our pattern categorizes this information with a methodology many...
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... Several suggestions have been made for the order the information is presented such as History-Objective-Plan-Evaluation (HOPE) and Assessment-Subjective-Objective-Plan (ASOP). Additional information and rationale can be found in [28][29][30]. ...
Information extraction applications that extract structured event and entity information from unstructured text can leverage knowledge of clinical report structure to improve performance. The Subjective, Objective, Assessment, Plan (SOAP) framework, used to structure progress notes to facilitate problem-specific, clinical decision making by physicians, is one example of a well-known, canonical structure in the medical domain. Although its applicability to structuring data is understood, its contribution to information extraction tasks has not yet been determined. The first step to evaluating the SOAP framework's usefulness for clinical information extraction is to apply the model to clinical narratives and develop an automated SOAP classifier that classifies sentences from clinical reports. In this quantitative study, we applied the SOAP framework to sentences from emergency department reports, and trained and evaluated SOAP classifiers built with various linguistic features. We found the SOAP framework can be applied manually to emergency department reports with high agreement (Cohen's kappa coefficients over 0.70). Using a variety of features, we found classifiers for each SOAP class can be created with moderate to outstanding performance with F(1) scores of 93.9 (subjective), 94.5 (objective), 75.7 (assessment), and 77.0 (plan). We look forward to expanding the framework and applying the SOAP classification to clinical information extraction tasks.
Patient Record System is a blockchain application that is poised to revolutionize the healthcare industry. This application provides a secure ledger that centralizes all patient information, making it easily accessible to healthcare providers such as doctors, pharmacists, clerks, and managers. It eliminates the current challenges of working in silos and separate systems, ensuring that patient records are readily available for any medical event. In addition, Patient Record System provides a secure and tamper-proof platform that guarantees the confidentiality of patient information. ii
Analysis patterns seem to be a promising approach supporting software analysis. However, the usefulness of this approach has not been proved. This paper presents a 'big picture' of issues related to application of analysis patterns in software development process from practitioner's perspective. It examines several aspects of analysis patterns and their application in software development. Then, it provides a method of system analysis with analysis patterns. And finally, it presents a case study of analysis with analysis patterns for a system supporting a small real medical centre.
