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Este documento especifica un modelo independiente de la plataforma y un modelo específico de la plataforma para servicios web XML que definen las capacidades e interfaces de un servicio de soporte
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How to fill out Clinical Decision Support Service (CDSS)

01
Step 1: Gather patient data including medical history, symptoms, and any laboratory results.
02
Step 2: Access the Clinical Decision Support Service (CDSS) platform or software.
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Step 3: Enter the collected patient data into the CDSS system.
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Step 4: Review the clinical guidelines or recommendations provided by the CDSS.
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Step 5: Analyze the alerts, reminders, or recommendations offered by the system.
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Step 6: Make clinical decisions based on the CDSS output, considering individual patient context.
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Step 7: Document the decision made and any relevant information in the patient's medical record.

Who needs Clinical Decision Support Service (CDSS)?

01
Healthcare providers who seek guidance in diagnosis and treatment.
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Clinicians aiming to improve patient safety and care quality.
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Facilities looking to standardize clinical practices.
04
Researchers who require data-driven insights for their studies.
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Healthcare organizations that want to enhance their decision-making processes.
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can be classified based on their analytical capabilities into three categories -predictive, descriptive, and prescriptive (Figure 2). Predictive CDSS is based on predictive analytics and provides a reasonable prediction about the risk for desired diseases or outcomes.
The three components of a** Decision Support System** (DSS) are Data Management, Model Management, and Communication System. Data Management involves handling data, Model Management uses models to process that data for aiding decision-making, and the Communication System helps in communicating about these decisions.
For example, an alert may appear when a clinician orders amoxicillin, warning that the patient is allergic to penicillin-class medications. The clinician may accept the alert and cancel the order.
can be classified based on their analytical capabilities into three categories -predictive, descriptive, and prescriptive (Figure 2). Predictive CDSS is based on predictive analytics and provides a reasonable prediction about the risk for desired diseases or outcomes.
An example is a digoxin order. If the clinical task would be starting a patient on digoxin therapy, the CDSS should advice the prescriber on ordering serum potassium levels, perform therapeutic drug monitoring and review new drug-drug interactions.
Epic, Oracle Cerner, and Change Healthcare hold approximately 81% of the overall clinical decision support system market. Outside of the top three vendors, market share drops considerably for the remaining vendors on the list.
Types of decision support systems Data-driven DSS. A data-driven DSS is a computer program that makes decisions based on data from internal or external databases. Model-driven DSS. Communication-driven and group DSS. Knowledge-driven DSS. Document-driven DSS.
A clinical decision support system is an active knowledge system that uses variables of patient data to produce advice regarding health care. This implies that a CDSS is simply a decision support system focused on using knowledge management.
These include substituted judgment decision-making, patient-controlled decision-making, and supported decision-making. This article explores autonomous decision-making by looking at the benefits and limitations of these three models.

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Clinical Decision Support Service (CDSS) is a health information technology system that is designed to provide healthcare providers with clinically relevant knowledge and patient-specific information to enhance clinical decision-making.
Healthcare providers, including physicians, hospitals, and clinics that utilize a CDSS within their practice are typically required to file Clinical Decision Support Service (CDSS) reports.
Filling out a Clinical Decision Support Service (CDSS) usually involves entering patient information, clinical data, and inputting any necessary decision support tools provided by the system, following the specific guidelines set by the healthcare organization.
The purpose of Clinical Decision Support Service (CDSS) is to improve patient outcomes by assisting healthcare providers in making informed clinical decisions based on evidence-based guidelines and patient-specific data.
The information that must be reported on Clinical Decision Support Service (CDSS) typically includes patient demographics, clinical history, results of tests and procedures, recommended actions, and any alerts or reminders generated by the system.
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