Computerized Decision Support Systems: A Case Study

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4. DATA STORAGE, MANAGEMENT, AND RETRIEVAL SYSTEMS

4.1 Electronic Health Record Systems (EHRs)

Being the heart of any health information system, electronic health record systems might consist of uncomplicated storage instruments or more complex systems with differing functions included, incorporating the capability of electronic prescribing (e-Prescribing) and using computerized decision support systems (CDSSs). These later are effective knowledge systems that use each patient’s information to produce guidance related to particular situation. Electronic health record systems act as the foundation for e-Health improvements that are happening internationally. It permits to digitally input, store, display, retrieve, print, and share information
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It employs a storehouse of clinical information (knowledge-base) and an inference mechanism (logic) to produce patient particular outcome. These applications differ highly in refinement, outcome and the dimension to which they could merge with other clinical information systems. (Josip Car et al, 2008)
Computerized decision support systems are created to help clinicians in taking decisions and by this improve the quality and safety of healthcare care. (Kathrin Cresswell, 2012)
Kathrin also indicated that computerized decision support systems are in core computer software systems or applications that combine patient data, a database of clinical knowledge and conditional logic (if-then or do while) to produce patient particular advices related to healthcare (Figure below).
Knowledge-base:
Knowledge-base is an arranged storage of knowledge inside a computer system or a firm which could be representing ideas, raw data, goals, requirements, principles, and descriptions.
Its form depends on whether it supports
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These data should be gathered using methods that reduce systematic and random error.
The number of application involving these computerized decision support systems is large and could possibly involve using the whole chain of both clinical and non-clinical activities. Potential usages of computerized decision support systems are presented below:
• Preventive care such as vaccination reminders,
• Ordering investigations such as reminders for previously presented results,
• Interpreting investigations such as computer-aided detection for screening mammography,
• Diagnostics such as proposing a diagnosis of heart disease based on electrocardiogram results in the patient record,
• Disease management such as blood pressure monitoring in people with hypertension,
• Guideline-based and prescribing-related decisions and monitoring such as systems alerting for contraindications and inappropriate medication doses,
• Prognostics such as helping to predict prognoses of malignant tumors, helping to predict risks based on risk-prediction algorithms,
• Public health surveillance such as public health alerts to promote awareness of infectious diseases or environmental

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