Nursing Informatics for Advanced Practice
Clinical decision support systems (CDSS) augment or supplement the process of decision-making by clinicians in today’s health technological world. The use of CDSS can be traced back to the 1970s and since then there have been advancements in this health technology (Sutton et al., 2020)Nursing Informatics for Advanced Practice. Various pros and cons have been documented. The table below summarizes some of the pros and cons of CDSS.
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| Pros | Cons | Rationale/Remarks |
| CDSS improves patient safety by minimizing medical and medication errors through timely reminders and prompt decision-making. The provision of alerts makes the process of making decisions timely and programmed. (Sutton et al., 2020) | The programmed alerts can cause alert fatigue. Sometimes the alerts can be several but their significance in initiating taking clinical actions is doubtable. Getting used to these repetitive ‘annoying’ alerts can be paradoxical in that they may lead to errors of omission. | To err is human. Therefore, we may need assistive technology to aid our decision-making and reduce lags in decision making. This assistance may come at a cost. The solution to repetitive alerts can be achieved by prioritizing the alerts |
| CDSS improves the efficiency of decision-making. The time and human effort pumped into decision-making are decreased by CDSS. The overall costs of clinical decision-making are reduced. (Sutton et al., 2020; Harada et al., 2021)Nursing Informatics for Advanced Practice | Clinicians may see CDSS as a threat to their clinical autonomy (Muhiyaddin et al., 2020). Automated decision-making can, in some, impair clinical decision-making as not all patients are ‘programmed’ to present and be managed in the same way. | I selected this item because of the automation of decisions. As the saying in information technology goes ‘garbage in garbage out.’ The process of seeking a decision may go wrong in the input thus providing unintended output due to automation. |
| CDSS use can improve cost containment in the health system. Reducing the amount of time and financial input in decision-making is improved by reducing the duplication of tests and interventions (Jankovic & Chen, 2020). | Reduction in cost of care is paradoxically expensive. The cost-effectiveness of CDSS is still doubtable (Harada et al., 2021). Startup, maintenance, and usability costs may be higher to achieve higher efficiency. | I selected this item because higher the aim of using technology is to cut care costs but paradoxically it can also increase the overall costs to the health care institution |
| Automated documentation has been easier with CDSS. Tracking the history and records of interventions is easier through their search engines and printable logs (Sutton et al., 2020) | New knowledge makes the set system redundant and may need regular system updates. During these update times, backups or alternative decision support may be required. | Security and data security of patient formation has been some of the care priority per the HIPAA rules. I selected this item due to medicolegal and ethical reasons |
Patient Case Scenario
Situations, where I have wished to have CDSS at my disposal, have been numerous. Working in the unit during shifts when the shift nurses are fewer against the constant number of patients has always made me long for CDSS. In the inpatient units, the various patient may need similar interventions at different times of the day during the shift. For example hourly turning or change of tubes. The need to abide by the protocol of nurses has necessitated that I follow my care plans strictly and timely to avoid making medical errors of omission and commission. Therefore, timely reminders about similar patient conditions and interventions have needed in the application decisions to ensure that I provide these interventions in their correct times and dosages Nursing Informatics for Advanced Practice.
References
Harada, T., Miyagami, T., Kunitomo, K., & Shimizu, T. (2021). Clinical decision support systems for diagnosis in primary care: A scoping review. International Journal of Environmental Research and Public Health, 18(16), 8435. https://doi.org/10.3390/ijerph18168435
Jankovic, I., & Chen, J. H. (2020). Clinical decision support and implications for the clinician burnout crisis. Yearbook of Medical Informatics, 29(1), 145–154. https://doi.org/10.1055/s-0040-1701986
Muhiyaddin, R., Abd-Alrazaq, A. A., Househ, M., Alam, T., & Shah, Z. (2020). The impact of clinical Decision Support Systems (CDSS) on physicians: A scoping review. Studies in Health Technology and Informatics, 272, 470–473. https://doi.org/10.3233/SHTI200597
Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. npj Digital Medicine, 3, 17. https://doi.org/10.1038/s41746-020-0221-y Nursing Informatics for Advanced Practice
