Nursing Decision Support Tools

Decision-Making Support Tools

Clinical decision support tools are complex systems that serve as decision-making support tools and are mostly an extension of electronic health records or patient record systems (Healthit.gov, 2013). Over time nurses have increasingly got new, extended roles and responsibilities which, however, have recently been made much easier by the introduction of clinical decision support systems. There is a range of decision tools that are available for clinicians that aid them in decision making. These tools are majorly computer-based programs, though they can also be paper-based, which helps in integrating information that has been obtained from an extensive collection of highly reliable studies. The information is then combined with the characteristics of individual patients from which the clinicians can then get substantive advice (Berner, 2009).

There is a myriad of forces that have an influence on healthcare, but more than ever technology is at the forefront of the development of nursing practices. The decision-making tools serve a general purpose in the whole healthcare system where they help provide timely and relevant information to those involved. The result is that they assist the clinicians, staff, patients and other interested stakeholders in making decisions, preventing errors, and, finally, in enhancing the way healthcare is performed (Berner, 2009). However, more particular is the impact the tools have on the nursing profession where, contrary to some opinions that technology is taking away the art of clinical judgment for the practice, they have standardized approaches to decision-making eliminating individualized and holistic approaches. Many of the studies conducted refer to the use of the tools by medical doctors, however, one review of how the methods are used by the nurses revealed that most of the instances of employing the tools focus on telephone triage and dosage assistance as well as anticoagulation management recommendations (Randell, Mitchell, Dowding, Cullum, & Thompson, 2007). Although it is believed that most of the nurses are non-medical prescribers, they might be using the clinical decision support tools to perform drug dosing and prescribing.

Examples of Decision-Making Support Tools

Mostly, the clinical decision support systems (CDSS) are categorized based on their functionality, which includes both passive and active systems. The former provide information to a clinician only upon request, whereas the latter give specific recommendations concerning a patient to a medical professional automatically (Dowding et al., 2009). The computerized provider order entry (CPOE) is one example of an active clinical decision tool. It is an information system that is used by clinicians and others in the healthcare profession to bypass both written and verbal orders, and instead allows using computer aided entries for making orders either for medication, lab works, procedures or radiology tests (American Sentinel University – Healthcare, 2011). The orders are then sent automatically to the departments or the individuals that have the responsibility of carrying them out. Examples of the passive CDSS are EMR (electronic medical record) or EHR (electronic health record) that are the systematized collections of patients’ or populations’ information which is stored electronically in a digital format. The data in the system is available upon request by the clinician, who can retrieve it. As for EMR, it contains information derived from one provider’s office, however, when it comes to EHR, the information provided goes further beyond one medical facility and contains more elaborate information concerning a patient’s history. Electronic health record, which is more broadly used, is designed as an all-round system where it stores information that can be shared among all of the patient’s care providers. Health records created under EHR are highly mobile and move with the patients to any health care providers, hospitals, or across states (Hughes, 2008).

Personal Experiences in Cases of Interactions with Decision-Making Support Tools

During a regular visit to the doctor’s when I went for a medical check-up, my doctor was out of town, and I had to see another physician. However, the new doctor read my EMR record which provided her with the documentation of the last visit that included recent laboratory results and a list of medications I had been given. She was updated on my condition, and it was easy for her to enter then another prescription order that I needed to complete my dosage. My experience underscores that using clinical decision-making tools is essential in healthcare, and that EMR as one of them is very critical in ensuring patient safety as well as providing improvements in health care quality. However, while the systems prove to be helpful in some instances, they are a cause for practice dilemmas in conflicted work environments.

As a nursing attaché in an intensive care unit, I witnessed some practicing nurses having to battle with stresses over professional decisions and nursing ethics. In one such case, a nurse was given a do-not-resuscitate order by a doctor after the latter had made a decision based on a Cerner Acute Physiological, Age and Chronic Health Evaluation (APACHE) III system used in the hospital. The patient had been receiving a life-sustaining treatment and the systems query on the mortality of the patient through a series of predictive equations, predicted a 98% mortality. According to the nurse, the system’s information was used to stop providing active care for the person and that the doctor used it as a final tool in his judgment. What the nurse was suggesting is that the system played a significant role in the decision-making process for patient care. To take care of such kind of ethical dilemmas in the use of CDSS, it would be prudent not to allow machine generated reports to be the final decision maker. Clinicians should refer to bioethics and use a human-based approach such as ethics committees in situations regarding validation of withdrawal of critical care support for patients.

Conclusion

Some benefits exist in the use of CDSSs, more particularly in aiding decision-making practices. Nurses and other healthcare professionals have had an opportunity to access current research evidence, which has helped to inform their decisions. However, use of the systems has also led to a diversity of perceptions when it comes to professional practice. There is much to do with the education of those who are expected to make use of the tools, and more importantly when it comes to the utilization of predictions as well as the assumptions arising out of the technology with an underpinning to ethical concerns. There is a need for equity of education regarding CDSS where nurses who are expected to contribute regularly to the system’s database need formal training in its use. Discussions surrounding the systems’ ethical limitations are necessary and must be a part of the training, because they would help to ensure the tool is used together with all other relevant data that include nursing and medical judgment. Such kind of dialogue would help dispel any fears among the clinicians that withdrawal of critical care support for patients would become normal. Furthermore, the future of the development of CDSSs is apparent in that it offers a helping hand in decision making for healthcare professionals; however, a clear rationale for the continued introduction of the systems needs to be ensured. Support and monitoring systems should also be put in place once they are developed properly so that vital issues that exist around the use of the tools can be adequately addressed. Finally, based on the information gathered, it will help in learning how to use patient care technology to communicate effectively with other members of the healthcare team and to employ a range of technologies useful in supporting patient care.