Clinical decision support systems are tools designed to enhance patient care by providing computer-generated clinical knowledge and relevant patient health information at appropriate times. A recent review of 70 studies evaluating CDS systems found that they are significantly associated with improved clinical practice.
Although CDS systems are increasingly used to guide providers toward established protocols and best practices to improve patient care, use of CDS for infection prevention is not widespread. A study published in the American Journal of Infection Control suggests that, in regards to infection control, CDS systems are most often used for antimicrobial stewardship, but that the data demand for many infection preventionists has led to the adoption of such systems for a wider range of use.
Here are the "'10 commandments' for Successful Design, Implementation and Use of Clinical Decision Support Systems," included in the study and adapted from an earlier Journal of the American Medical Informatics Association article.
1. The CDS system must be fast. The time it takes for the CDS system to gather and process data and return meaningful information or actionable recommendations to the end user is key.
2. Keep the CDS system simple. Guidelines can be complicated and not readily adaptable to automated systems. Overly complicated systems are more susceptible to technologic fails, and too much information may overburden the end user.
3. Require the user to enter data only when it is essential. Asking end users to enter data already documented in an EHR or elsewhere is double documentation and is poorly received. If it is necessary, get end user acceptance early in the design process by explaining the necessity and the inability to gather the data elsewhere.
4. Routinely maintain and evaluate the CDS system. When guidelines change, the CDS tool built on those recommendations needs to change as well. Retire CDS tools when they no longer needed.
5. Identify latent needs and inform the end user. Latent needs are supplemental recommendations in the CDS tool. For example, if the primary output of CDS is to recommend an antibiotic for treating a specific infection, a latent need to order therapeutic drug monitoring can be provided at the same time.
6. Build the CDS system to fit the existing workflow and seek input from end users early in the design process to understand their natural workflows better.
7. Understand that usability is essential and nuances matter to end users. Professionals that design or customize CDS tools and clinician end users may both use the same computer program but in very different ways. End users must be involved in the design and development phase from concept to completion.
8. Do not stop or change course during the CDS.
9. Physicians will not 'stop.' Stopping refers to not allowing the end user to complete their desired course of action. Offering clinically appropriate alternatives, such as one drug over another, and override options allows the end user to complete their task.
10. Measure and share success. When a CDS tool is implemented it inherently changes how end users do their job. Measuring how end users are responding to the CDS tool and sharing data on clinical outcomes reinforces the value in their efforts and builds trust for future development.