Removing the roadblocks to promoting health equity: finding the social determinants of health addressed in standardized nursing classifications

Abstract

Providing 80% of healthcare worldwide, nurses focus on physiologic and psychosocial aspects of health, which incorporate social determinants of health (SDOH). Recognizing their important role in SDOH, nurse informatics scholars included standardized measurable terms that identify and treat issues with SDOH in their classification systems, which have been readily available for over 5 decades. In this Perspective, we assert these currently underutilized nursing classifications would add value to health outcomes and healthcare, and to the goal of decreasing disparities. To illustrate this, we mapped 3 rigorously developed and linked classifications: NANDA International (NANDA-I), Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) called NNN (NANDA-I, NIC, NOC), to 5 Healthy People 2030 SDOH domains/objectives, revealing the comprehensiveness, usefulness, and value of these classifications. We found that all domains/objectives were addressed and NNN terms often mapped to multiple domains/objectives. Since SDOH, corresponding interventions and measurable outcomes are easily found in standardized nursing classifications (SNCs), more incorporation of SNCs into electronic health records should be occurring, and projects addressing SDOHs should integrate SNCs like NNN into their ongoing work.

BACKGROUND AND SIGNIFICANCE

Nurses comprise the majority of health care personnel in the world¹ and provide up to 80% of health care worldwide.² In providing holistic care, nurses focus on both the physiological and psychosocial aspects of health. Importantly, this includes the social determinants of health (SDOH), such as food insecurity, housing instability, lack of education, lack of social support, unemployment, and lack of transportation.^3–8 Recognizing nurses’ important role in SDOH, nursing informatics scholars developed standardized measurable terms to assess and treat issues with SDOH. Within their groundbreaking research they developed classification systems for problems that nurses address (nursing diagnosis), activities nurses do to address problems (nursing interventions) and measurable nursing-care-sensitive outcomes. These classification systems have been readily available for over 5 decades.^9–13

More recently, other groups such as the Gravity Project¹⁴ and the Social Interventions Research and Evaluation Network (SIREN),¹⁵ have been developing standardized guidelines that capture a person’s social needs during a healthcare visit, for the electronic health record (EHR). In addition, the Office of the National Coordinator for Health Information Technology (ONC) has developed a toolkit for SDOH information exchange¹⁶ to contribute to better health outcomes.¹⁷

Although these efforts are making important progress, drawing from the existing nursing evidence-based classifications that include SDOH could streamline and enhance this process. This existing nursing work should not only be acknowledged but should be included in ongoing efforts to incorporate SDOH in the EHR. We believe that existing standardized nursing terminologies provide a coded and interoperable way to identify SDOH, choose appropriate evidence-based interventions and measure the outcomes of the interventions over time. Importantly, the opportunity costs associated with not including these classifications in the EHR will delay efforts to eliminate health disparities. Therefore, the purpose of this paper is to highlight 3 of the well-developed standardized nursing classifications (SNCs): NANDA International (NANDA-I), Nursing Outcomes Classification (NOC), and Nursing Interventions Classification (NIC); and to illustrate their usefulness in the EHR, including an enhanced ability to track and impact SDOH outcomes when these classifications are incorporated into EHR documentation systems.

NURSING CLASSIFICATIONS AND THE SOCIAL DETERMINANTS OF HEALTH

To have terms that can demonstrate the value of nursing care, nursing informaticists began developing SNCs for health care documentation needs in the 1970s.^9–13,18 Some of the SNCs currently in use work synergistically. For example, the NANDA-I diagnoses are used to diagnose a person’s health problems, NOC are used to set goals and desirable health outcomes for those diagnoses, and the NIC provide the needed nursing care or interventions to achieve the NOC outcomes. Collectively referred to as NNN (NANDA-I, NIC, and NOC), these SNCs were selected for this project as they have been used most often in research and secondary data analysis worldwide,^19–21 are suitable for use in secondary analysis of EHR data,²¹ and have sound taxonomic nursing structures (including definitions on all classification levels).^13,22,23 Finally, since the NNN are classifications, not terminologies, their descriptors are observable or measurable,^13,24,25 making them more amenable to mapping.

Although originally developed by nursing informatics scholars, these classifications are applicable to many health care disciplines, and are well-suited to the development of interprofessional and nursing-focused plans of care. Importantly, these classifications not only name and enable tracking of SDOH, but provide evidence-based interventions²⁴ and standardized ways to document progress on achieving patients’ goals.²⁵

NANDA International (NANDA-I), Nursing Interventions Classification (NIC), Nursing Outcomes Classification (NOC)

Created in the 1970s, the NANDA-I Classification of Nursing Diagnoses contains health problems that can be applied at the individual, family, or community level. The NANDA-I includes a taxonomy of 13 domains, 47 classes, and 267 diagnoses, which contain definitions, clinical indicators, and etiological elements that are research-based and support accurate diagnoses. NANDA-I is a clinically validated classification with the number of NANDA-I diagnoses found to be a strong independent predictor of hospital length of stay and hospital mortality, while use of the classification adds accuracy to predictive models of mortality that include traditional predictive data like demographics, diseases, disease severity, and morbidity indexes.^26–28 Studies conducted as early as the 1990s indicated the value of NANDA-I diagnoses, demonstrating relationships with hospital length of stay, Intensive Care Unit (ICU) length of stay, and total charges, and increased explanatory power when added to models with diagnosis related groups (DRGs) or all patients refined DRGs (APR-DRGs).²⁹

The NIC, first published in 1992, provides a way to exchange comparable information about the treatments that address health concerns (social and other). It contains 7 domains, 30 classes and 614 interventions, which are researched, have been effectively implemented in multiple settings worldwide, and are able to be used by multiple disciplines.^24,30–33

The NOC, first published in 1997, provides terms that capture changes in status after intervention. The NOC is measured on a 5-point Likert-type scale that allows clinicians to track their patient’s progress, or lack thereof, over time. It contains 7 domains, 34 classes and 540 outcomes. Like the NIC, it is researched, has been effectively implemented worldwide, and can be used by multiple disciplines.^25,34–37

It is important to note that, although NNN are not widely used by EHR vendors in the United States (US), they are broadly used in multiple settings worldwide (see Figure 1). Their usefulness in predictive health care models is documented in multiple studies from countries such as Italy, Spain, China, Brazil, and Turkey.^{26–28,38–42} Research conducted in health care organizations that use NNN produces meaningful data that are a valid representation of nursing care and amenable to efficient processing and analysis,⁴³ demonstrate relationships between nursing care plan components and patient outcomes,^28,44 and assist the care provider in targeting areas of need, such as SDOH.⁴⁵

Figure 1.

Countries using NANDA-I, NIC, and NOC. International use of NIC and NOC in education, practice, and/or research. Countries are Brazil, Canada, China, Colombia, Estonia, France, Germany, Greece, Iceland, Indonesia, Israel, Iran, Italy, Japan, Mexico, Netherlands, Nigeria, Norway, Peru, Portugal, Slovakia, South Korea, Spain, Switzerland, Turkey, United Kingdom, United States, and Wales.

Social determinants of health

Though there are many categories of SDOH, the population disease prevention and health promotion work from the Healthy People 1990 publication⁴⁶ provides a foundation for subsequent efforts, in conjunction with the World Health Organization.⁴⁷ Currently in its 5th iteration, Healthy People 2030 has 42 priority areas and 1300+ objectives aimed at improving overall population health.^{17,46,48–51} Influenced by the WHO’s publications and ongoing discussions of the effects of SDOH worldwide,⁴⁷ critical target areas were added to the existing Healthy People objectives to include an area of SDOH domains and objectives in the Healthy People 2030 iteration.¹⁷ There are 5 SDOH domains of interest in the Healthy People 2030 publications: Health Care Access and Quality, Social and Community Context, Economic Stability, Neighborhood and Built Environment, and Education Access and Quality.⁵² These SDOH are also a focus in The Future of Nursing 2020–2030: Charting a Path to Achieve Health Equity,⁵³ which is a blueprint created by members of the National Academies of Sciences, Engineering and Medicine, and intended as a set of “bold recommendations to strengthen the capacity, education, and critical role of the nursing workforce” (p. ix). The Healthy People 2030 SDOH, coupled with the Future of Nursing recommendations, have influenced the direction of several nursing research studies^54,55 and nursing educational efforts.⁵⁶ These influences directed our selection of SDOH for this project.

Mapping of NNN with SDOH

To assess the usefulness of the NNN to SDOH care delivery, we formed a team of 5 nurse experts to identify socially relevant NNN terms that connect to the Healthy People 2030 SDOH domains and their corresponding targeted objectives, using the following method: (1) 2 authors (CMW, CTL) mapped NNN labels to each SDOH objective, using the textbooks’ taxonomies and reviewing page by page, while examining corresponding definitions, defining characteristics, activities, and indicators; (2) these initial mappings were placed into tables organized by SDOH domains and objectives; (3) a team of 3 authors (KDL, EAMM, GAJ) independently marked each mapping for agreement or disagreement; (4) a team of 4 authors met to develop consensus. During the consensus process, 305 decisions were changed and 99 terms were added.

Figure 2 is a representation of the mapping data in the form of a heat map or diagram in which data values are represented as colors that indicate ranges of data. Red indicates no terms matched the objective, yellow indicates 1–2 terms matched, and green indicates more than 2 terms of each individual NNN matched to an SDOH objective. The mapping revealed that all objectives in all domains are addressed by at least one set of NNN, and that multiple terms of the NNN mapped to more than one of the objectives in the domains. When duplicated terms were accounted for, a total of 109 unique NANDA-I, 159 unique NIC, and 173 unique NOC labels were found to address objectives in the Healthy People 2030 SDOH Domains.

Figure 2.

Heat map connecting NNN concepts by healthy people domains.

Figure 2.

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Figure 2.

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Figure 2.

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DISCUSSION

The value of using SNCs in nursing care documentation is demonstrated in many international research publications and several from the US.^{26–28,38–42,44,57–59} These rigorously developed classification systems address a broad array of aspects of patient care and include SDOH evidence-based interventions and measurable outcomes. Nonetheless, for those making efforts to develop EHR terms that address SDOH, it may be a surprise that many terms suitable for interprofessional care documentation have already been developed, linked to evidence, and validated by nursing informatics experts. While we have focused in this Perspective on NNN, other classifications include SDOH, such as the Omaha System.^58,59 When these classifications are used in the EHR, the ability to track and address a person’s SDOH becomes simplified. Once a problem or a need is identified (using NANDA-I) in a nursing or interdisciplinary care plan, it is incumbent upon the clinicians to provide a means of addressing the issue. Multiple evidence-based interventions (at the individual, family, and public health level) that can address the problem (diagnosis) can be found in NIC with measurable outcomes in NOC. Therefore, NNN goes beyond naming and tracking SDOH, to intervening and monitoring progress toward goals over time.

Selected examples of multidisciplinary care plans addressing the Healthy People SDOH objectives and using the NNN are noted in Table 1. In practice, the use of these particular care plan components or any of the other unique NNN terms mapped to the SDOH would indicate that there is an SDOH need and the clinicians would be alerted to choose appropriate interventions in this area, thus promoting health equity.⁶⁰

Table 1.

Selected examples link healthy people domain objectives to NNN

Examples of objective mappings
Economic stability domain
Reduce work-related injuries resulting in missed work days—OSH—02
NANDA—I (diagnosis)	NOC 6th edition (outcome)	NIC 8th edition (intervention)
12th edition
Risk for occupational injury	Personal safety behavior	Body mechanics promotion
	Risk control: environmental hazards
Social and community context
Reduce anxiety and depression in family caregivers of people with disabilities—DH—D01
Caregiver role strain	Caregiver well-being	Caregiver support
Education access and quality
Increase the proportion of children who are developmentally ready for school—EMC—D01
Risk for delayed child development	Knowledge: parenting	Child care
		Parental education: childrearing family
		Teaching: early childhood development
Neighborhood and built environment
Reduce the amount of toxic pollutants released into the environment—EH—06
Risk for contamination	Community risk control: environmental hazards	Community disaster preparedness
Health care access and quality
Increase the proportion of adults with limited English proficiency who say their providers explain things clearly—HC/HIT—D11
Readiness for enhanced health literacy	Client satisfaction: communication Client satisfaction: cultural needs fulfillment Health literacy behavior	Culture care negotiation Health coaching Health education Health literacy enhancement

So why are these classifications not extensively used in the EHR to assist in focusing health care on SDOH needs? Unfortunately, with the movement toward computerized health care using EHRs in the US, the knowledge of nursing informaticists with expertise in standardized nursing classifications is not always pursued. In addition, unlike many European countries (eg, Italy, Spain, Estonia, Finland), the US has not enacted federal policies for the use of standardized nursing languages. This has resulted in nursing documentation in EHR systems that focuses on flowsheets with check-boxing tasks and assessments.⁶¹ Thus, the intellectual and critical thinking work of nurses to identify patient problems, plan interventions and measure outcomes of those interventions is largely invisible in our current EHRs. Many documentation systems currently implemented by EHR vendors do not contain SNCs,^62–68 thus creating missed opportunities to use NNN to target and address SDOH needs such as those arising from the recent pandemic.^69–72

If assessment and management of SDOHs are easily found in SNCs and these classifications are used regularly as part of the nursing process of care, more incorporation of SNCs into the EHRs should be occurring. The Future of Nursing 2020–2030: Charting a Path to Achieve Health Equity⁵³ recommended that nursing expertise should be used in the design, generation, application, and analyzing of new technology in the workplace and in projects directed at enhancing that technology. The addition of nursing SNC expertise can serve to enhance these projects and further promote understanding of and attention to SDOH and their impact on overall ability to achieve good health.

CONCLUSION

We have demonstrated the promise of NNN to identify and promote health equity. It is clear from existing international research that the use of standardized nursing classifications in documentation provides important insights into health and health outcomes in acute care, illustrating the promise of widespread use to focus on SDOH and health disparities.^{26–28,38–42,44,45,57–59} Importantly, NNN offer not just the identification of SDOH, but evidence-based and actionable interventions that the care team can implement, with measurable outcomes to determine the impact of these interventions. Future work that includes SNC expertise is needed to partner with organizations that focus on developing interoperable EHR terms for SDOH.

FUNDING

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

AUTHOR CONTRIBUTIONS

CMW: Lead on first draft and manuscript revisions; assisted with writing; created mapping; critical review of mappings for consensus; critical review of final draft of article. CTL: Assisted with writing; created mapping; critical review of final draft of article. GAJ: Assisted with writing; critical review of mappings for consensus; critical review of final draft of article. EAMM: Assisted with writing; created tables and figures; critical review of mappings for consensus; critical review of final draft of article. ED: Critical review of final draft of article. KDL: Assisted with writing; critical review of mappings for consensus; critical review of final draft of article.

CONFLICT OF INTEREST STATEMENT

The authors have no competing interests to declare.

DATA AVAILABILITY

Data available on request.