Clinical nursing information systems based on standardized nursing terminologies: How are we doing?

Historically, the most significant feature of a profession is its unique body of knowledge, or the foundation of common information that guides its practitioners in their activities. Terminologies in nursing are essential for describing nursing-related phenomena and are part of a scientific and constantly updated body of knowledge. More generally, a standardized terminology, as defined by the World Health Organization (WHO), is “a compilation of terms used in the clinical assessment, management and care of patients, which includes agreed definitions that adequately represent the knowledge behind these terms and link with a standardized coding and classification system” (Fennelly et al., 2021). Therefore, standardized nursing terminologies (SNTs) offer a unique opportunity to make nursing practice more visible, generate valuable knowledge, and provide essential data for decision-making and research.

The idea behind creating SNTs was to organize the knowledge of nursing discipline by developing a vocabulary that could explain nurses' clinical judgments (e.g., nursing diagnoses) and the consequences of their detection (e.g., nursing actions). The movement began in the 1970s, and today several widely recognized nursing classification systems are in use because no single universal SNT has been adopted. Among these, 12 nursing-specific SNTs have been officially recognized by the American Nurses Association (ANA): Clinical Care Classification (CCC), Alternative Billing Concepts (ABC) Codes, International Classification for Nursing Practice (ICNP), Logical Observation Identifiers Names and Codes (LOINC), NANDA International (NANDA-I), Nursing Interventions Classification System (NIC), Nursing Outcomes Classification (NOC), Nursing Minimum Data Set, Nursing Management Minimum Data Set (NMMDS), Omaha System, Perioperative Nursing Data Set (PNDS), SNOMED Clinical Terms (SNOMED CT) (Chae et al., 2020). Due to their ability to represent vital information about patients' health and the overall value of nursing care, all of these languages are potentially necessary. The use of SNTs to document nursing care in electronic health records (EHRs) can encourage nursing participation in big data research, thereby advancing knowledge of the multifaceted effects of nursing on public health, regardless of the specific SNT used in clinical practice.

SNTs can thus enhance patient knowledge by improving the quality of professional evaluation, raising the visibility of nursing, and producing data that reflects the impact of nursing care on patient outcomes. However, several challenges complicate this process. SNTs are not widely used in clinical practice, and a global issue persists due to the insufficient collection and encoding of nursing data with SNTs in EHRs. Additionally, managing and analyzing unstructured textual data—often found in paper-based nursing documentation—presents significant difficulties. As a result, there is an urgent need for a “call to action” to promote the use of SNTs in clinical practice. This crucial step will facilitate semantic data interoperability, enable nurses to communicate using a common language, and better assess the impact of nursing care on patient outcomes (Fennelly et al., 2021).

When nurses use the same SNT, regardless of the hospital or region, they can communicate in a unified language, which leads to an overall improvement in patient care. Moreover, giving nurses the opportunity to use a SNT in clinical practice—whether or not it is the same SNT across different settings—will enhance the definition of the complexity of care, which, in turn, will improve patient care and benefit healthcare organizations. Additionally, the application of SNTs can impact health managers' forecasting abilities (e.g., definition of staffing levels) and facilitate sustainability analyses over short, medium, and longtime horizons (D'Agostino et al., 2012).

Unfortunately, the complexity of care remains largely unrecognized in many countries today, with few health institutions able to define it accurately. As a result, nurses—and their patients, along with their responses to nursing care—often remain invisible. This deficiency affects not only healthcare but also the economic system and societal perceptions of nursing. Currently, care payments are primarily based on medical diagnoses and their groupings (such as Diagnosis Related Groups—DRGs), with SNTs not being integrated into this framework (Cesare et al., 2023). This troubling scenario, particularly in light of ongoing demographic and epidemiological transitions, underscores the urgent need for a standardized language to ensure a solid and reliable data flow. With an increasing proportion of non-hospital care (such as home care and community services) being nurse-managed in the future, establishing this data flow will be essential for evaluating the quality and costs of care provided.

Over the past 12 years, Italy has begun to define the complexity of care using clinical nursing information systems (CNISs) based on SNTs. The implementation of effective CNISs was crucial, as they positively impact various aspects of nursing practice, including the accuracy of nursing documentation, management, quality and safety of care, communication, and the administration of healthcare resources.

The Professional Assessment Instrument (PAI) and its pediatric and neonatal version (PAIped) were the first CNISs introduced in Italy, adopted by the EHRs of the largest general university hospital in Rome, in 2012 and 2016, respectively. Numerous facilities and primary care centers have requested the Board of Nursing (OPI) of Rome, which holds the material rights to the PAI system, to share the scientific algorithm it contains. This algorithm is freely available upon request, making it possible for numerous organizations to implement the system and reap its extensive benefits.

So, what happen when the PAI is adopted in clinical practice? The effectiveness of PAI lies in its ability to support nurses in the choice of standardized nursing diagnoses, interventions, and actions. The system provides suggestions based on the data entered during nursing assessments, which are scientifically structured and based on signs and symptoms gathered using Marjory Gordon's Functional Health Patterns Model (Gordon, 1994). The PAI suggestions are supported by a validated scientific algorithm (Zega et al., 2014), which has been the basis for multiple published scientific papers over time (Cesare et al., 2023; D'Agostino et al., 2017, 2019; Sanson et al., 2019). This algorithm is not intended to replace nurses; rather, it offers suggestions for optimal strategies to support patients and achieve the best outcomes during and after hospitalization. Nurses can accept or reject these suggestions, thus preserving their decision-making autonomy and ensuring the care plan's completeness and high quality. Since its implementation, the system has reduced the nursing documentation burden, facilitating the planning and reporting of care for over 800,000 patients. It has also enhanced legal protection for nurses and other healthcare workers by documenting evaluations, clinical issues, and the care provided, thus improving patient outcomes (Cesare et al., 2023; Cocchieri et al., 2018; D'Agostino et al., 2012). Furthermore, the use of PAI has resulted in significant cost savings, as hospitalization events in Italy—and other countries— are financially covered by the Ministry of Health only if nursing documentation meets accuracy and completeness standards.

The adoption of systems like the PAI, will be crucial in addressing demographic and epidemiological transitions that are making patients increasingly complex, vulnerable, and challenging to treat. Health services will struggle to adapt to these changes unless they recognize the urgent need to integrate SNTs into CNIS. By promoting their use and demonstrating the real impact of nursing care on patient outcomes, as well as integrating these systems into health facilities' EHRs, nursing will become more visible and relatable to other disciplines. This will help nursing gain the appropriate financial and social recognition and improve the standards and effectiveness of care (Cesare et al., 2023).

When, if not now? To support the necessary changes, we must first believe in our own specific language and the core principles of our profession. If we do not believe in these ourselves, we cannot expect others to. By dedicating the necessary financial and human resources to implement CNISs based on SNTs, we will achieve substantial savings over time and our patients will benefit from this shift in perspective. However, a multifaceted approach is required, including a well-defined university strategy. Nurses' knowledge, confidence, and attitudes toward SNTs and their use in CNISs can be enhanced through proper training and demonstrations during their education. This would improve the acceptability and long-term sustainability of this approach within health systems. Yet, the impetus for change must come from us.

So, how are we doing? We need to ask ourselves this question since we are, and will continue to be, an active part of this change. Using SNTs and integrating them into effective CNISs able to support nurses, such as the PAI, will be crucial. However, it is also imperative to remember, as Marjory Gordon noted, that even with the adoption of standardized technology and systems, the nurse remains the most sensitive measuring device (Gordon, 1994). Therefore, our goal should be to provide the best possible CNIS to support this professional, who must receive advanced education to make a significant impact on nursing worldwide.

For this purpose, we are ready to share our knowledge and provide your organizations with our algorithm—this “secret” formula that enables everyone to communicate in the same language—if you are ready for this transition. The greatest source of interest and satisfaction will be hearing from nurses about their experiences and perspectives after using the PAI.

We cannot wait any longer; the time to speak the same language has come.

This work was supported by the Center of Excellence for Nursing Scholarship (CECRI), Board of Nursing (OPI) of Rome, Italy [Correction added on September 2, 2024 after first online publication: Funding section has been included].