Importance in Clinical Setting

The tool is a health information application that has proven to be quite useful in guiding the pharmaceutical procedure. It has found use in dosing, ordering, sending notifications at the point of caregiving, and assisting with workflow planning (Beeler, Bates, & Hug, 2014). The applications have enhanced pharmaceutical and caregiving issues such as prescription adherence. Similarly, the documented data can be mined to research patients’ medical histories, which clinicians can use to investigate adverse drug effects as well as patient-specific issues such as probable consequences.

Types of Information Generated by CDSS

Dosing Point-of-care reminders and alerts Adherence guidelines Drug Indications & Contraindication Adverse issues such as incompatible medications Cost-Benefit Views of CDSS

According to a recent report on the implementation of CDSS the installation costs US$23,316 while the training of a single user is US$1,060 (Dalaba et al., 2014). While the financial tag may be high, the overall consideration indicates that the intervention makes economic sense. Some devices with artificial intelligence have automated the delivery of medical care, where they utilize patient data to make informed decisions. The use is critical in addressing human resource shortages that are being experienced in the primary care settings. CDSS also have unlimited potential to offset the public health burden of medications errors through supporting the preparation and review of diagnosis (Beeler, Bates, & Hug, 2014).

Limitations

One of the main limitations of the CDSS is the huge financial implication, as the system is expensive to install and maintain (Dalaba et al., 2014). Its potential of shaping clinical decisions can also be realized only through integrating into existing clinical workflows, an issue that has been a challenge because of the complexity. The current system is already strained and incorporating new tools may result in infrastructural strain. The problem is aggravated by the fact that the informatics resource can be a source of medication errors because of human resource-linked aspects.

References

Beeler, P., Bates, D., & Hug, B. (2014). Clinical decision support systems. Swiss Medical Weekly. http://dx.doi.org/10.4414/smw.2014.14073

Dalaba, M. A., Akweongo, P., Williams, J., Saronga, H. P., Tonchev, P., Sauerborn, R., ... & Loukanova, S. (2014). Costs associated with implementation of computer-assisted clinical decision support system for antenatal and delivery care: case study of Kassena-Nankana district of northern Ghana. PLoS One, 9(9), e106416.