Nursing Diagnoses in a Brazilian Intensive Care Unit

International Journal of Nursing Terminologies and Classifications Volume 17, No. 3, July-September, 2006 139

Blackwell Publishing IncMalden, USAIJNTInternational Journal of Nursing Terminologies and Classifications1541-5147© 2006 Blackwell Publishing Ltd.73Original Article

Nursing Diagnoses in a Brazilian Intensive Care Unit


Amália de Fátima Lucena and Alba Lúcia Bottura Leite de Barros

PURPOSE.

To identify the nursing diagnoses and

their most frequent related factors or risk factors

in patients admitted to an intensive care unit

(ICU).

METHOD.

Descriptive cross-sectional study with

information from 991 admissions to an ICU

during a 6-month period.

FINDINGS.

Sixteen nursing diagnoses resulting

from hospitalization were most frequently

identified; six had percentages greater than 40%

with 29 related/risk factors. The resulting

averages were 6.9 diagnoses per hospitalization and

1.2 related/risk factors per nursing diagnoses.

CONCLUSIONS.

The nursing diagnoses identified

seemed to be common to the clinical practice of

nursing and their fundamental related/risk factors

to precise clinical judgment, thus providing a basis

for interventions for a desired outcome.

PRACTICE IMPLICATIONS.

The findings have

contributed to the development of the

standardized nursing language usage in Brazilian

nursing practices.

Diagnósticos de Enfermagem em uma

Unidade de Terapia Intensiva Brasileira

OBJETIVO.

Identificar os diagnósticos de

enfermagem e os seus fatores relacionados/risco

mais freqüentemente estabelecidos aos pacientes

internados numa unidade de terapia intensiva (UTI).

MÉTODO.

Estudo descritivo, transversal, com

informações de 991 admissões numa UTI, durante

seis meses.

RESULTADOS.

Dezesseis diagnósticos de

enfermagem foram mais freqüentes, seis deles com

percentuais acima de 40% por internação e com

29 fatores relacionados ou de risco. As médias

foram de 6,9 diagnósticos de enfermagem por

internação e 1,2 fatores relacionados ou de risco

por diagnóstico de enfermagem.

CONCLUSÕES.

Os diagnósticos de enfermagem

identificados parecem ser comuns à prática clínica

de enfermagem e os seus fatores relacionados ou de

risco fundamentais ao julgamento clínico preciso,

que subsidia à escolha da intervenção para um

resultado esperado.

IMPLICAÇÕES PARA A PRÁTICA.

Os resultados

têm colaborado para o desenvolvimento do uso

da linguagem padronizada de enfermagem no

Brasil.

140 International Journal of Nursing Terminologies and Classifications Volume 17, No. 3, July-September, 2006


Amália de Fátima Lucena is Assistant Professor at the School of Nursing, Federal University of Rio Grande do Sul, and a doctorate degree candidate in the Nursing Department, Federal University of São Paulo, Brazil. Alba Lúcia Bottura Leite de Barros is Head Professor and Research Advisor in the Nursing Department, Federal University of São Paulo, Brazil.

I

n Brazil the first generation of nursing process wasintroduced in the 1970s using the Horta (1979) model.Today, the nursing process has not yet been used to itsfullest. The diagnosis step has not been used frequently.Studies point out that among the factors that havemade nursing diagnoses difficult to implement are thelack of data to determine a diagnosis, lack of technicaland scientific nursing knowledge, nurses’ resistance toaccept the terminology, a lack of standardization ofnursing language, and a lack of the right conditions toallow professionals to implement the process properly(Crossetti, 1989; Farias, Nóbrega, Pérez, & Coler, 1990).

NANDA International was organized to elaborateand develop a diagnostic terminology that evolved intoa taxonomic classification that continues to undergoconstant improvement (NANDA, 2005). The need tostandardize the other elements of the nursing processhas also emerged, giving rise to the development ofclassification systems for interventions (McCloskey &Bulecheck, 2004) and outcomes (Moorhead, Johnson,& Maas, 2004).

In Brazil, the study and utilization of nursinglanguage classifications began in the 1980s, and theNANDA taxonomy was one of the first to be trans-lated into Portuguese (Farias et al., 1990). However,their use in nursing practice has not led to furtherstudies in this field (Lucena & Barros, 2005).

The nursing staff at Hospital de Clínicas in PortoAlegre (HCPA), Brazil, a university hospital of theFederal University of Rio Grande do Sul (UFRGS), hasbeen working with the nursing process for more than20 years. The need to improve the use of nursing pro-cess in this institution, the evolution of nursing knowl-

edge, and the changes of the informatics system in thehospital gave rise to new studies and discussionsconcerning the references and strategies in order tomake the needed changes toward implementing acomputerized system of nursing care plans that tookinto consideration the nursing diagnosis stage, whichup to that time had been absent.

A work group made up of nurses from the hospitaland professors in the School of Nursing at UFRGS wasorganized and, with the help of the institution’s sys-tem analysts, a computerized model of nursing careplans was created and implemented between 1998 and2000 with a focus on nursing diagnoses. The modelwas based on the work of Benedet and Bub (2001),which is structured after Taxonomy I of NANDA(2000) and related to the theory of basic human needsused by Horta (1979). Furthermore, ideas of otherauthors were used along with the practical clinicalexperience of the nurses at the hospital (Carpenito,1999; Doenges & Moorhouse, 1999).

The implementation of the new model took placeinitially in an intensive care unit (ICU) and was slowlyapplied to the other units in the hospital. We currentlywork with a computerized nursing process in thestages of nursing diagnosis and planning care (inBrazil we call this last stage “Nursing Prescriptions”), butassessment and nursing evaluation are still addedmanually to the records.

The computerized system of nursing care at HCPAmakes it possible to view a list of correspondingactions/interventions that can be selected dependingon the nurse’s clinical evaluation for each nursingdiagnosis identified. This system currently contains152 nursing diagnoses, 559 etiologies (related/riskfactors), 565 signs and symptoms, and approximately883 nursing care procedures (Crossetti & Dias, 2002;Crossetti, Rodegheri, D’Ávila, & Dias, 2002).

Preliminary evaluations show that this model hasassisted in solving patient health problems by individ-ualizing nursing diagnoses and care planning therebyimproving the quality of the care provided (Crossettiet al., 2002). Despite these advances, there is an ongoing


need to update and evaluate the model in order toimprove it through discussions, studies, and research.

With this as a background, an investigation into thefrequency of nursing diagnoses and their related/riskfactors for patients admitted to the ICU was under-taken to contribute to the work already begun in thehospital as well as to expand knowledge in the areaand improve the functioning of nurses in Brazil.

We hoped, in addition, that these results wouldprovide further progress in the knowledge of applica-bility and validity of the terminology in nursing diag-noses in Brazilian clinical practice and favor theidentification of strategies for improving the quality ofthe interventions offered, as well as make it possible touse these results in new research about diagnosticprecision and the development of computerized infor-mation systems.

Methods

This descriptive cross-sectional study was carriedout in the ICU of HCPA. The unit cares for critically illadults of clinical or surgical services and has 34 bedsdivided into two large areas—Area 1 and Area 2—both of which provide the same services. However,Area 1 includes specific facilities for the recovery ofpatients after heart surgery in the Cardiac Care Unit(CCU). The research project was approved by theresearch ethical committees of the institutions involved.

Data consisted of information contained in the data-base of the hospital’s computerized system of nursingcare plans related to the patients admitted to ICU dur-ing a period of 6 months. The most frequently made

nursing diagnoses were identified along with theirrelated/risk factors. Being admitted to the unit wasthe only inclusion criterion.

Data gathering was retrospective. Information wasentered on spreadsheets using Excel for Windows. Thedata analysis included descriptive statistics, with thehelp of two programs: Excel for Windows and Statisti-cal Package for the Social Sciences (SPSS) 12.0 forWindows

.

The cutoff point for identifying the mostfrequent nursing diagnoses used the measurement oforder and quartile as a reference. A distribution wasdone of the diagnoses identified in increasing order offrequency. This list was then divided into four quar-tiles. The diagnoses found to be in between the thirdand the fourth quartile corresponded to 25% of themost frequently identified diagnoses. The significancelevel was set at

α

= 0.05 (Motta & Wagner, 2003;Wagner, Motta, & Dornelles, 2005).

Findings

There was a total of 991 hospital admissions to theICU during the selected timeframe; 345 of these to theCCU, 336 in Area 2, and 310 in Area 1. The admissionsinvolved 841 different patients. These admissionsgenerated a total of 6,845 nursing diagnoses with 63different diagnostic categories for which 39,947 nurs-ing interventions were prescribed with an average ofsix interventions prescribed per diagnosis for eachadmission. The average number of nursing diagnosesper admission in an ICU was 6.9 (see Table 1).

The 16 most frequently identified nursing diagnosesare listed in Table 2. These comprised 6,001 of the

Table 1. Average Nursing Diagnoses Identified per Admission in the ICU

ICU area Admissions Diagnoses Mean number of diagnoses per admission

1 310 2,481 8.02 336 2,174 6.5CCU 345 2,190 6.3Total 991 6,845 6.9



diagnoses made (88%). Six of the diagnoses wereassigned greater than 40% of the time. They included

bathing/hygiene self-care deficit

,

risk for infection

,

impairedphysical mobility

,

ineffective breathing pattern

,

impairedspontaneous ventilation

, and

risk for impaired skin integ-rity

. They accounted for 3,834 (56%) of the nursingdiagnoses made, which represented more than half ofthe total of nursing diagnoses in the period analyzed.For these six nursing diagnoses, 4,493 related/riskfactors (etiologies) were identified, divided into 29different types, an average of 1.2 etiologies per nursingdiagnosis (see Table 3).

Discussion

This investigation revealed use of 63 diagnosticcategories, a number that is similar to those describedin some of the studies carried out with patients comingfrom various clinical and surgical units (Barros, 1998;

Camiá, Marin, & Barbieri, 2001; Guerriero, Guimarães,& Maria, 2000; Maria, 1997; Soares, Pinelli, & Abrão,2005; Yom, Chi, & Yoo, 2002). Our ICU admits patientsfrom a variety of types of clinics and surgeries, whichmay have favored the diversity of the nursing diag-noses identified.

The average of 6.9 nursing diagnoses per patientadmitted was also similar to those described in studieswith patients in critical care (Maria, 1997; Pasini,Alvim, Kanda, Mendes, & Cruz, 1996). As the nursesbecame accustomed to using nursing diagnoses andincreasing their expertise, the average number of nurs-ing diagnoses per patient tended to drop and becomemore precise as the nurses became more selective intheir choices.

The analyses of the 16 most frequent nursing diag-noses revealed that although this ICU has specificfacilities for the recovery of patients after heart sur-gery, the nursing diagnoses of greatest frequency are

Table 2. Most Frequent Nursing Diagnoses Identified in the ICU

Nursing diagnosis

Frequency Percentage ofadmissions (n = 991)

Percentage ofdiagnoses(n = 6,845)CCU Area 1 Area 2 Total

Bathing/hygiene self-care deficit 342 301 329 972 98.1 14.2Risk for infection 330 303 317 950 95.9 13.9Impaired physical mobility 240 157 191 588 59.3 8.6Ineffective breathing pattern 170 171 153 494 49.8 7.2Impaired spontaneous ventilation 144 142 141 427 43.1 6.2Risk for impaired skin integrity 142 126 135 403 40.7 5.9Imbalanced nutrition: less than body requirements 119 139 137 395 39.9 5.8Risk for altered respiratory function 162 81 148 391 39.5 5.7Impaired urinary elimination 93 96 80 269 27.1 3.9Impaired tissue integrity 107 70 86 263 26.5 3.8Acute pain 122 65 35 222 22.4 3.2Ineffective tissue perfusion: peripheral 115 31 21 167 16.9 2.4Risk for deficient fluid volume 75 39 21 135 13.6 2Impaired swallowing 13 44 75 132 13.3 1.9Deficit fluid volume 32 47 23 102 10.3 1.5Impaired skin integrity 11 48 32 91 9.2 1.3Total 2,217 1,860 1,924 6,001 — 87.5

Note: The six nursing diagnoses that have a frequency of occurrence per admission higher than 40% are displayed in boldface.


Table 3. Related or Risk Factors Identified in the ICU of

HCPA

for the Six Most Frequently Identified Nursing Diagnoses

Related or risk factors Frequency Percentage of admission Percentage of etiology

Bathing/hygiene self-care deficit (

n

= 972) (

n

= 1,288)Limited therapies 328 33.7 25.5Neuromuscular activity impaired 231 23.8 17.9Evolution of the disease 222 22.8 17.2Immobility 192 19.8 14.9Pain 152 15.6 11.8Fatigue 81 8.3 6.3Trauma 49 5.0 3.8Mental confusion 25 2.6 1.9Effects of medications 5 0.5 0.4Visual deficit 3 0.3 0.2Total 1,288 — 100

Risk for infection (

n

= 950) (

n

= 989)Invasive procedure 948 99.8 95.9Immunosuppression 16 1.7 1.6Contact with infectious/contagious disease 11 1.2 1.1Use of immunosuppression medication 7 0.7 0.7Traumatized tissues 6 0.6 0.6Prolonged hospital stay 1 0.1 0.1Total 989 — 100

Impaired physical mobility (

n

= 588) (

n

= 694)Limited therapies 235 40.0 33.9Impaired neuromuscular activity 193 32.8 27.8Pain 140 23.8 20.2External equipment 87 14.8 12.5Trauma 28 4.8 4.0Effects of medications 8 1.4 1.2Inflammatory processes 2 0.3 0.3Depression 1 0.2 0.1Total 694 — 100

Ineffective breathing pattern (

n

= 494) (

n

= 635)Impaired neuromuscular activity 183 37.0 28.8Pain 130 26.3 20.5Congestion 100 20.2 15.7Infectious process of airways 65 13.2 10.2Fatigue 52 10.5 8.2Trauma 41 8.3 6.5Bronchospasm 27 5.5 4.3Thick and/or excessive secretions 19 3.8 3.0Effects of medications 14 2.8 2.2Anxiety 4 0.8 0.6Total 635 — 100



Impaired spontaneous ventilation (

n

= 427) (

n

= 459)Impaired neuromuscular activity 374 87.6 81.5Infectious process of airways 70 16.4 15.3Bronchospasm 15 3.5 3.3Total 459 — 100

Risk for impaired skin integrity (

n

= 403) (

n

= 428)Immobility 279 69.2 65.2Mechanical factors 102 25.3 23.8Nutritional state 18 4.5 4.2Change in metabolism and/or increased caloric requirements 14 3.5 3.3Vascular change 9 2.2 2.1Extremes of age 6 1.5 1.4Total 428 — 100

Related or risk factors Frequency Percentage of admission Percentage of etiology

Table

3.

Continued

similar to those attributed to the other patients admittedinto the unit. Of the 16 most frequent diagnoses theones that could be considered more specific forpatients with cardiovascular degeneration or post-operative heart surgery such

as ineffective tissue perfusion:peripheral

,

risk for deficient fluid volume

, and

deficient fluidvolume

were evident in much lower percentages inrelation to the others. This may indicate difficulty onthe part of some nurses to diagnose with precision, atask that requires scientific knowledge and skill in theprocess of diagnostic reasoning and making clinicaldecisions.

Some authors also say that good diagnosing mustinclude both technical as well as interpersonal skills.Technical skills include intellectual skills such as scien-tific knowledge and critical thinking, which should beused to make precise interpretations in such a way sothat the interventions are appropriate and their resultspositive. The interpersonal skills have to do with thecapacity that the nurse must have in relating well withthe patients and family members in order to confirmthe data gathered and the interpretation of those data.Efforts directed at helping nurses increase their diagnos-ing skills will result in more precise diagnoses (Levin,Lunney, & Krainovich-Miller, 2004; Lunney, 2004).

As for the types of NANDA diagnoses identified, ofthe 16 most frequent diagnoses, 12 of them reflectedactual problems and four identified potential prob-lems. Of the six most frequently identified diagnoses,four were actual and two were “at risk.” The fact thatmost of the diagnoses are categorized as actual is evi-dence that nursing care in ICUs should be focused onregaining health. However, the identification of therisk diagnoses also indicates that there are concerns onthe part of the nurses concerning preventive aspectswhen caring for patients. Thus, the concept of riskpointed out in the epidemiologic model can be identi-fied, demonstrating that prevention is a part of thenursing care actions at the secondary and tertiary levelsof health care (Barros, 1998).

The 16 most common nursing diagnoses analyzedaccording to the Horta Model are all related to psycho-biologic needs. None related to psychosocial or psy-chospiritual needs were identified. On the one hand,this could be expected considering the fact that ICUpatients are in serious condition in imminent risk oftheir lives, which would indicate their psychobiologicneeds are a priority. However, the absence of diag-noses related to the other two types of needs must bequestioned because we know that many of the patients


from this type of unit experience difficulties related tocommunication, social isolation, anxiety, and spiritualsuffering.

Corroborating this idea, some studies also describethe large number of nursing diagnoses linked to thepsychobiologic needs and refer to the difficulty somenurses have in making emotional and spiritual prob-lems of the patients a priority in relation to physicalproblems (Carmagnani, Cunha, & Behlau, 2003; Maria,1997). Could this difficulty of the nurses in makingdiagnoses linked to psychosocial or psychospiritualneeds also be linked to the strong influence of the bio-medical model under which we continue to work? Orare these nursing diagnoses simply encountered lessfrequently in an ICU? Independently considering thereasons leading to these results, it is important toemphasize that nurses must remain aware of theentire set of needs demonstrated by the patient andnot just one or another aspect.

In relation to the six most frequent nursing diag-noses identified in the ICU, they are also described inthe literature as being the most common, which wouldlikely indicate that they are common to the clinicalnursing practice as a whole and therefore deservegreater attention and knowledge about them (Barros,1998; Canero, Carvalho, & Galdeano, 2004; Galdeano,Rossi, Nobre, & Ignácio, 2003; Guerriero, et al., 2000;Killen, Kleinbeck, Golar, Takahashi Schuchardt, &Uebele, 1997; Maria, 1997; Pasini et al., 1996; Ventura,2001). As for the related/risk factors (etiologies), it isimportant to reinforce the idea that to know them andidentify them correctly is fundamental to preciseclinical judgment that forms the basis for choosing thebest intervention and activities to help the patient witha certain diagnosis and eventually reach the expectedoutcome.

Conclusions and Implications

The results of this study made it possible to identifythe most frequent nursing diagnoses and their related/risk factors in the clinical nursing practice in an ICU in

Brazil. These results have served as a basis for imple-menting new practices, helped in the training ofnursing assistants, and guided the continued educa-tion and teaching process for nurses and others collab-orating in the development of standardized nursinglanguage usage.

Of the 152 nursing diagnoses that currently exist inour hospital’s computer system, 63 different categorieswere identified in the ICU. Of these 16 most frequentones, six were identified in more than 40% of thepatients admitted. The elevated frequency of these sixnursing diagnoses is similar to those found in litera-ture, which confirms that they are common to clinicalpractice and, therefore, it is essential that they beexplored through studies and practices that increaseour understanding.

The identification of the different related/risk fac-tors was also important inasmuch as these increasediagnostic precision and provide guidance for the bestchoice of interventions and the expected nursing out-come. This facilitates the provision of quality care.Finally, we believe that this study has contributedknowledge concerning the task of diagnosing withprecision and helping to prioritize diagnoses for clinicalstudies and development of information technologysystems in nursing.

Author contact: [email protected]

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Documents

Nursing Diagnoses in a Brazilian Intensive Care Unit