Patient safety is the key priority of all health care professionals since no mistakes are allowed in this area. Regardless of the level of technological support of the unit, safety policies require ongoing improvement as they must respond to the ever-changing environment (Healy, 2016). The problem is that the issue of safety is too complex to reduce it to physical security and protection from emergency situations. Each hospital needs its own set of safety regulations, reflecting its peculiarities.
The overwhelming majority of patient complications occur owing to the growing number of medical errors of judgment, which are both harmful to relationships and resource-demanding. Medical errors, if neglected, may lead to the appearance and aggravation of HIV/AIDS, cancer, and other terminal conditions (Healy, 2016). Thus, there is a need for new technological solutions that would make it easier to identify and eliminate errors.
CDSS (Clinical Decision Support System) is one of the most innovative health care technologies, which is aimed to assist medical specialists on their way to quality and safety improvement. The system is computer-based and relies on real case studies in order to obtain arguments for decision making (Nanji et al., 2014). Thus, it is proposed to implement the system in both general and intensive care units in order to increase safety levels. In case the offered solution is successfully implemented, CDSS will allow performing disease status assessment, diagnosis statement, and therapy selection. Another crucial implication is that with the help of CDSS, medication errors will be considerably reduced, which will improve patient outcomes and increase their satisfaction level.
However, it must be remembered that patient safety is not limited to the prevention of medical errors. It is also highly important to make existing errors visible and to mitigate their consequences in case patients have already been affected. Since CDSS provides numerous modes of safety support, including reminders, recommendations, warnings, alters, and suggestions, it makes it possible to deal with safety threats by improving health care professionals’ behaviors, the quality of therapy, and follow-up actions (Nanji et al., 2014). Moreover, the system of alerts also allows collecting data from a large number of patients, which makes it easier to conclude what strategies are the most beneficial both for patients and health care units after safety has already been undermined.
In order to ensure that CDSS is truly improving patient outcomes in terms of safety, it is required to perform regular measurements of its impact. Here are the examples of measures that can be demonstrative in this respect (Nanji et al., 2014):
- satisfaction levels and usability (feedback from the staff and patients);
- impact of the workflow and efficiency (time to complete tasks and resolve various safety concerns before and after CDSS implementation).
- the use of alerts (alert firing rates, the ability to react on time);
- the level of adherence to safety guidelines and patient awareness;
- the occurrence of safety-related problems (emergency factors that increase the length of the state and may potentially lead to future readmissions);
- unintended consequences of CDSS application (redundant safety alerts and adverse events caused by overprotection).
In order to start implementing the change, it is highly important to select appropriate strategies that would allow communicating its importance to all stakeholders involved. These are the most effective ways of dissemination that allow approaching both academic and non-academic public (Moule, Aveyard, & Goodman, 2016):
- E-mail. Since safety issues are connected with a great number of human lives, delayed forms of communication are not preferable but still can be used for reaching policy-makers.
- Telephone. This is a perfect way of communicating with non-academic stakeholders.
- Flyers and posters. The visibility of the problem can be increased with posters.
- Newsletter. This method is effective for informing both non-academic and academic partners when some results have already been achieved.
- Publications in peer-reviewed journals. This dissemination tool is applied for communicating the importance of the issue to the academic community. It also helps ensure the long-lasting impact of the change implemented.
- Publication of policy documents. At the beginning of project implementation, it is too early to speak about this communication strategy since there is nothing to present to policymakers. However, when the effectiveness of the methods has already been proven, funding agencies can be addressed using this method.
- Press releases and mass media. When positive results have been obtained, there is a possibility to resort to mass media to share them with the health care community.
- Workshops. Scheduling workshops makes it possible for all participants to exchange their opinions and introduce changes if necessary.
- Social media. This channel can also help popularize the change.
The adoption of innovative technologies does not always run smoothly due to human factors. They may include fear of making a mistake, lack of understanding, and general resistance to change. In order to overcome these obstacles, it is highly important to take into consideration all questions that the staff may have during the process of change implementation. The problem is that no change is stable in its nature, which implies that its success is unpredictable. Misunderstanding, misuse, or unwillingness may bring to naught even the most impressive improvements. Thus, the staff must receive proper instructions and be encouraged to cooperate in order to ensure that CDSS is properly installed and operated.
Healy, J. (2016). Improving health care safety and quality: Reluctant regulators. Abingdon-on-Thames, UK: Routledge.
Moule, P., Aveyard, H., & Goodman, M. (2016). Nursing research: An introduction. Thousand Oaks, CA: Sage.
Nanji, K. C., Slight, S. P., Seger, D. L., Cho, I., Fiskio, J. M., Redden, L. M.,… Bates, D. W. (2014). Overrides of medication-related clinical decision support alerts in outpatients. Journal of the American Medical Informatics Association, 21(3), 487-491.