Difference between revisions of "CDS"
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* Symptom Triage Decision Support for Consumers (example: "Chest Pain") [http://www.freemd.com/fmdTriage.html?e=Chest%20Pain] | * Symptom Triage Decision Support for Consumers (example: "Chest Pain") [http://www.freemd.com/fmdTriage.html?e=Chest%20Pain] | ||
* [[Weight-based Heparin Dosing Guidelines]] | * [[Weight-based Heparin Dosing Guidelines]] | ||
+ | * [[Flowchart-based decision support sample content]] |
Revision as of 19:45, 4 January 2010
Contents
- 1 Clinical Decision Support -- CDS
- 1.1 Overview
- 1.2 Modes of Interaction
- 1.3 Order Sets
- 1.4 Information Resources
- 1.5 Artificial intelligence
- 1.6 Business Intelligence and Data Warehousing
- 1.7 Medication-Based Safety Rules
- 1.8 Non-Medication-Based Safety Rules
- 1.9 Validation and Verification of Clinical Decision Support
- 1.10 Sample Decision Support Content
Clinical Decision Support -- CDS
Overview
Clinical Decision Support (CDS) refers broadly to providing clinicians or patients with clinical knowledge and patient-related information, intelligently filtered or presented at appropriate times, to enhance patient care. Clinical knowledge of interest could range from simple facts and relationships to best practices for managing patients with specific disease states, new medical knowledge from clinical research and other types of information.
For an overview of the process that healthcare organizations can use to begin, or improve, a clinical decision support (CDS) initiative interested parties can follow the guidelines described in Improving Outcomes with Clinical Decision Suppport: An Implementer's Guide to measurably improve key healthcare outcomes such as the quality, safety, and cost-effectiveness of care delivery.
- National Roadmap for Clinical Decision Support
- History of decision support
- General system features associated with improvements in clinical practice
- Support Decisions with Diagnostic Aids
- Clinical Decision Support Liability
Modes of Interaction
Order Sets
- Personal Order Sets
- Functional Specifications
- Criteria for creating new order sets
- A Process for Creating and Maintaining Order Sets
- Most commonly used Order Sets in In-patient Setting
Information Resources
- [The HIMSS Clinical Decision Support (CDS) Task Force wiki]
- Alerts and Reminders
- Alert Fatigue?
- Alert placement in clinical workflow
- Initial Selection of What to Alert on...
- Alerts versus on-demand CDS
Artificial intelligence
Artificial intelligence is a system that was developed by a team of system engineers and clinicians. The system would take some of the workload from medical teams by assisting the physicians with tasks like diagnosis & Therapy recommendations. An AI system could be running within electronic medical record system, and alert a clinician when it detects a contraindication to a planned treatment. It could also alert the clinician when it detected patterns in clinical data that suggested significant changes in a patient’s condition. The definition of artificial intelligence has changed over the years, since 1956 till now. It is mostly found in data rich areas like intensive care settings There are many different types of clinical task to which Artificial intelligence can be applied. 1. Monitoring patients vital signs and then evaluating and administering the right amounts of different drugs needed 2. Planning an adequate nutritional support for maintaining the metabolic needs of newborn infants. Control of the level of pressure support ventilation. 3. Reading of the electrocardiogram (ECG).
There are numerous reasons why more expert systems are not in routine use. Some require the existence of an electronic medical record system to supply their data and most institutions do not yet have all their working data available electronically. Much of the difficulty has been the poor way in which they have fitted into clinical practice, which required additional effort from already busy individuals.
Examples of AI that are still in practice samrtcare/pc ventilator manager, 2004. VIE-PNN Neo-natal parentral nutrition 1993. Examples of decommissioned AI are: N‘eoGaneshVentilator manager, 1992. ACORN Coronary care admission ,1987. By Bassima Hammoud
Business Intelligence and Data Warehousing
Medication-Based Safety Rules
- Potentially Inappropriate Medication (PIM) Use in Older Adults:65 years and older (Based on 2000 updated Beers Criteria)
- Medications to be avoided in the elderly
- Medications requiring dosage adjustments in renal insufficiency
- Common Corollary orders
- Drug-Laboratory Interactions
- Drug-Drug interaction
- Drug-Allergy Interactions
- Detection of Adverse Mediation-Related Events
- Drug-Food Interactions
- Drug-Tobacco Interactions
- Medications requiring dosage adjustments in hepatic disease
- Medications to be avoided during pregnancy
- Medications to be avoided while breastfeeding
- Vaccination contraindications
- List of 39 Warning Messages Targeting Prescribing Decisions Designed to Prevent Adverse Drug Events in Long-Term Care
Non-Medication-Based Safety Rules
Validation and Verification of Clinical Decision Support
Sample Decision Support Content
- Diabetes CDS Content
- Drug-Drug Interaction Rules
- Clinical Reminders from Beth Israel/Deaconess Medical Center in Boston
- Symptom Triage Decision Support for Consumers (example: "Chest Pain") [1]
- Weight-based Heparin Dosing Guidelines
- Flowchart-based decision support sample content