CDS

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.

CDS components

There are several key components of a good clinical decision support system. [1]

Order set

An order set is a group of related orders which a physician can place with a few keystrokes or mouse clicks. An order set allows users to issue prepackaged groups of orders that apply to a specified diagnosis or a particular period of time. Using order sets reduces both time spent entering orders and terminal usage.

Medication decision support

• Adverse drug reactions
• Basic Dosing Guidance for medications in CPOE
• Formulary decision support
• Duplicate Therapy Checking
• Advanced Dosing Guidance in CPOE
• Patient Characteristic dosing support
• Medications to be avoided in the elderly
• Medications requiring dosage adjustments in renal insufficiency
• Medications requiring dosage adjustments in hepatic disease
• Medications to be avoided during pregnancy
• Medications to be avoided while breastfeeding
• Vaccination contraindications
• Common Corollary orders
• Detection of Adverse Mediation-Related Events

Non-medication safety rules

• Diagnosis-Order Rules

CDS benefits

Results indicate the potential of CDS to improve the quality of care. These are good reasons for institutions to adopt CDS, but they should do so at their own pace and volition.

• Better clinical decision making leads to better practices.
• Reduces the medication errors
• Promote preventive screening and use of evidence based recommendations
• Cost reduction and increased patient convenience

Interaction models

An interaction model is a set of rules for making clinical decisions. The rules are based on a large collection of medical knowledge and an accurate computer representation scheme.

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.

Business Intelligence and Data Warehousing

• Business Intelligence
• Data warehouse

Validation and Verification of Clinical Decision Support

• On Validation and Verification Of Decision Support Protocol Subsystems During Implementation-Optimization: Encapsulating P(X)

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") [2]
• Weight-based Heparin Dosing Guidelines
• Flowchart-based decision support sample content
• Preventive care reminders

CDS Implementation

CDS should be designed to provide the right information to the right person in the right format through the right channel at the right time.

At the stage of planning for any new health IT system, there are some considerations and steps that should be followed to guarantee the system success; such as identifying the needs and functional requirements, deciding whether to purchase a commercial system or build the system, planning for encouraging physicians to use CDS, designing a system to evaluate how well the system has addressed the identified needs[1].

Clinical Decision Support overview

• 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

Success criteria estimates

To estimate the success of the system we should look at the following points[3]:

1. System quality.
2. Information quality
3. Usage
4. User satisfaction
5. Individual impact
6. Organizational impact.

Information Resources

• [The HIMSS Clinical Decision Support (CDS) Task Force wiki]
• Alert fatigue
• Alert placement in clinical workflow
• Initial Selection of What to Alert on...
• Alerts versus on-demand CDS
• Sources of clinical decision support content

History of decision support

Main article: History of clinical decision support

References

1. Franklin, MJ, et al, Modifiable Templates Facilitate Customization of Physician Order Entry, [3]
2. Sittig, DF, and Stead, WW, Computer-based Order Entry: The State of the Art, J Am Med Informatics Assoc., 1994;1:108-123. [4]
3. Anderson, JG, et al, Physician Utilization of a hospital information system: a computer simulation model. Pric Annu Symp Compu Appl Med Care, IEEE, 1988;12:858-861. [5]
4. Southern Ohio Medical Center, [6]
5. Clinical Decision Support Systems :State of the Art AHRQ Publication No.09* 0069* EF June 2009
6. Grand challenges in Clinical Decision Support Journal of Biomedical Informatics 41(2008) 387* 392
7. Determinants of Success of Inpatient Clinical Information Systems: A Literature Review. M J van der Meijden, H J Tange, J Troost, et al. JAMIA 2003 10: 235* 243