high frequency: treatment priority nursing diagnoses in critical care

High Frequency: Treatment Priority Nursing Diagnoses in Critical Care

Marjory Gordon, PhD, RN, FAAN, and Elizabeth Hiltunen, MS, RN, CS

The purpose of this study was to identify high frequency-treatment priority nursing diagnoses in critical care nursing using survey research methods. Through a mailed suvvey the prevalence of 135 nursing diagnoses from the NANDA

Diagnostic Taxonomy and other diagnoses was rated by a national, random sample of 678 critical care nurses. Six important diagnostic areas were: sleep-rest, activity, nutritional-metabolic, cognitive-perceptual, self-perception (mood state), and health management (risk ) patterns. Twenty diagnoses were rated as nearly always or frequently present in their practice by 70% or more of the nurses. Findings can be used to focus clinical studies of the highly prevalent diagnoses. Key words: Critical care, nursing diagnosis

Marjo y Gordon, PhD, RN, FAAN, is Professor, School of Nursing, Boston College, Boston, M A . Elizabeth Hiltunen, M S , RN, CS, is Clinical Nurse Specialist, Beth Israel Hospital, Boston, M A .

T h e development of nursing diagnoses and a diagnostic classification system by NANDA (1995) has stimu- lated questions about the prevalence of the conditions diagnosed and treated by nurses. Identification of highly prevalent diagnoses has relevance for developing computerized clinical information systems, a knowledge base for practice, essential content in education, and clinical research.

Prevalence studies identify the frequency and distribution of nursing diagnoses, changes in distributions, and, eventually predisposing antecedent conditions that can be used as a basis for causal inferences (Leighton, 1990). Mormation on the base rate occurrence of a diagnosis can enhance clinicians’ clinical judgments by pro- viding data on populations susceptible to particular health problems and factors associated with a greater likelihood of these problems. Also, systematic repetition of prevalence studies permits surveillance of conditions described by nursing diagnoses. Rantz and her colleagues’ reports (Rantz & Miller, 1987; Rantz, Vinz- Miller, & Matson, 1995) on how diagnoses changed between 1984 and 1993 in long-term care provide an example. In these samples nursing diagnoses associated with greater dependency increased, as did nutritional problems and cognitive impairments. Prevalence data explained the increased functional dependency and acuity of patients that required more nursing staff and changes in staff education. In addition, data suggested important diagnostic areas that would require in-depth assessment.

Prevalence Studies

Prevalence studies of diagnoses in nursing specialties have focused on various populations; many have been directed toward establishing the clinical validity of the

Nursing Diagnosis Volume 6, No. 4, October-December, 1995 193


categories in long-term care (Hardy, Maas, & Akins, 1989; Hoskins et al., 1984), adult care (Gordon, 19851, rehabllitation nursing (Sawin & Heard, 19921, renal nursing (Hoffman, 1986), oncological nursing (MacAvoy & Moritz, 1992), ambulatory care (Collard, Jones, Murphy, & Fitzmaurice, 19871, public health nursing in Canada (Lambert & Jones, 1989) and community nursing in the United States (Saba, 19921, obstetrical nursing (McKeehan & Gordon, 19841, and neonatal intensive care (Herdman, 1990). Dracup (1987), in a review of research on critical care nursing issues, identified patient stressors in intensive care units that suggested diagnoses, such as poiorrlessiiess, sensory oiwload (noise), sleep deprisvtioii , soc-id isolntioii, iinniobility, and pain, some of which contribute to the higher cost of critical care.

The American Association of Critical Care Nurses (AACN) identified nursing diagnoses that could be the focus for developing outcome criteria (1990). A group of 25 experts judged the frequency and priority of nursing diagnoses (“how life threatening or critical”). Table 1 contains the ratings of three sets: high frequency-high priority, low frequency-high priority, and high frequency-low priority diagnoses. When the high frequency-high priority diagnoses are grouped using a functional health patterns typology (Gordon, 1994) the diagnostic areas that emerge are activity (11 = 51, nutritional-metabolic (12 = 3), health (risk) management (17 = 21, and perceptual patterns (77 = 2). Tlus grouping reveals important areas for assessment and diagnosis.

Large, geograplucally representative, epidemiologcal studies using the currently accepted nursing nomencla- ture (NANDA, 1995) will contribute to knowledge development in critical care nursing. Descriptive epidemiological investigations usually start by observing and recording patterns of occurrence. The first step is to identik diagnoses with high prevalence rates (Gordon & Sweeneq; 1979). The traditional methodology employed in prevalence studies is review of reports or case records (Kurland & Molgaard, 1981). These recordings represent clinician’s judgments during patient care (as opposed to reflection and recall of observations and judgments at a later ddte), Yet, from a practical perspective, clinical doc-

Table 1. Three Categories of Diagnosis Identified at AACN Consensus Conference

High Frequency, High P Alterahons in fluid volume/dynamics Ineffective thermoregulation Impawd gas exchange Impaired breathing pattern Alterations in tissue perfusion Potential for injury Ineffective airway clearance Potential for mfection Alterahoiis in nutrition Impaired slun integnty Alterahom in comfort Activity intolerance Sensory-perceptual alterations Impaired physical mobility

Low Frequency, High Priority Importance Impalred breathmg pattern Decreased adaphve capacity

- High Frequency, Low Priority Importance Anxiety Iiieffective Communication Ineffective Coping Self-care deficit Fear Altered Famdy Process Altered Role Performance

From Outcorw Striiufnrds for Nursing Car(> of ‘kr Crzticnlly 111, by AACN, Newport Beach, CA: AACN, 1990 Adapted with per- mission

umentation may not always reflect all diagnostic judgments or national Standards of Care (American Nurses Association [ANAI, 1991). As Brykczynski (1989) suggests, nurses may not document things they take for granted or consider routine. In addition, and of most concern, conditions diagnosed and treated by nurses may not be coded uniformly or may not be easily accessed for research purposes. Lacking indexed records or computerized information systems in most health care delivery settings, nurse researchers have turned to surveys using nurses as informants. Careful focusing of

144 Nursing Diagnosis Volume 6, No. 4, October-December, 1995

nurses’ recall of situations can provide prevalence ratings. Findings from surveys of this type can suggest priorities for funding nursing diagnosis research and content for more complex, epidemiological investigations. As Hardy and her colleagues (1989) comment, these studies will identdy ”the organizing structure for extension of nursing knowledge through clinical research, for assignment of clinical and administrative program priorities, and for communicating nursing to policy makers” (p. 213).

Objective

The objective of the current study was to identify patient conditions described by nursing diagnoses that occur with hgh frequency and are treated in critical care nursing practice. This study was part of a larger research program to describe diagnosis-intervention-outcome links.

Definition of Terms

Nursing diagnoses were defined as diagnostic categories from the NANDA Taxonomy I, May 1990 (Carroll-Johnson, 1991) and other diagnostic categories that met specified criteria. Critical care nurse-experts were defined as members of the American Association of Critical Care Nurses (AACN) and the NANDA Critical Care Special Interest Group. Important diagnostic areas and high frequency diagnoses were defined by a mean of 3.0 or above on a 4-point rating scale.

Methods

Survey methodology was employed to study nurse- experts’ ratings of the prevalence of currently identified nursing diagnoses in critical care.

Sample

A computer-based random, stratified selection procedure was used to obtain 2000 subjects from the AACN

membership that had a) baccalaureate or higher degrees, b) two years, or more, experience in critical care nursing, and c) practiced 10 hours or more per week in direct care. One hundred-fifty subjects representing the total membership of the NANDA Critical Care Nursing Special Interest Group also were included in the sample. Twenty responses were not usable, mainly because of address changes or returned without responses. A 32 percent response rate to the mailed survey with no follow up provided a study sample of 678. Respondents had the distribution of characteristics, such as education and position, required by the study design. Support for geographical representation (48 of the 50 states) was seen in the separately returned postcards stating consent to continue in the project.

The sample was biased toward users of nursing diagnosis or those interested in the concept. This is supported by a background data item asking if subjects used nursing diagnosis as a basis for nursing intervention. The ratio was approximately 5:1, users to non-users. In this study it was considered a positive factor; users would have more familiarity with the diagnostic concepts. Another explanation is the socially acceptable response. National Standards of Care for professional nurses include the use of nursing diagnosis as a basis for nursing intervention (ANA, 1991). In addition, the AACN outcome standards are based on nursing diagnoses.

The sample represented a wide range of experience above the two years required in sample selection. As may be seen in Table 2, the mean was 12 ( S D = 6.6) with a range of 2-41 years. Forty-nine per cent of the 678 subjects were staff nurses. Table 2 contains the percentages for the remaining 51 percent; most were in clinical posi- tions. The sample worked an average of 27 hours in direct care but had a wide range of 15-80 hours; the modal report was 40. There were multiple responses to sub-specialty area indicating that the nurses may have worked on combined units or floated among critical care units. Major subspecialties were nearly equally represented in the 863 multiple responses from the 678 nurses, with 22% (n = 191) indicating coronary care as their specialty area, 18% (n = 158) medical intensive care, and 23%



Table 2. Employment and Experience Characteristics Total Sample (N = 678)

- Position Staff nurse 49 %

Head Nurse 11% Clinical Director 4% Educator 15% Other 7%

Clinical Speclallst 14%

Years of Clinical Experience Mean 12 years SD 6.6 years Range 2-41 years

* Direct Care HoursWeek Mean 27 hours SD 14.1 hours Range 12-80 hours

(12 = 200) surgical intensive care; the remainder were in other subspecialties.

A 53 ratio in the distribution of nurses prepared at the baccalaureate (56%) and master’s degree level ( 37%) may be seen 111 Table 3. Farmllarity with the concept of nursing diagnosis was indicated by three items related to previous education in nursing diagnosis (college, continuing education, and inservice) and reported usage of nursing diagnosis. Approximately one-half were taught nursing diagnosis 111 college; in-service and continuing education programs contributed to subps’ familiarity with diagnoses. Ten per cent had none of these three learning experiences, 29% had one, 32% had two, and 28% had the three learning experiences. As may be .seen in Table 3,82% responded Yes to the Item, ”1 currently base my nursing interventions on nursing diagnoses.” These indicators suggested the sample was famhar with nursing diagnoses.

Instrument

A 13.5-item survey instrument was developed that included the 108 nationally accepted, specific, NANDA

Table 3. Education and Competency Characteristics (N = 678)

Highest Education BS/BSN 56% MS/MSN 37% Doctorate 2% Other 5%

- Competency Indicators Past Education in Nursing Diagnosis

College Course 53%

Continuing Education 55% Inservice 68%

Base Nursing Intervention on ND Yes 82% No 18%

diagnostic categories (Carroll-Johnson, 1991). In addition, 27 other diagnoses published in manuals or critical care nursing journals were included. The additional diagnoses met the criteria that nursing intervention for the condition can lead to problem resolution and that diagnostic outcomes can be acheved by nursing interventions.

Diagnostic labels can have various personal mean- ings. Therefore, the definition of the diagnostic concept preceded the label in order to focus subjects’ attention on the condition and its conceptual definition. Extraneous words in the NANDA definitions were deleted; caution was exercised so as not to alter the conceptual meaning of the diagnosis.

Procedure

The survey instrument was reviewed for clarity and comprehensive representation of practice by a local, five- member, critical care clinical specialist advisory panel prior to a pilot study using 30 critical care nurses in one medical center. The instrument contained a 4-point, forced choice Likert scale for rating the 135 diagnostic concepts and their definitions. Subjects were asked to thnk of a representative sample of critical care patients and rate how frequently each diagnosis was present in their practice. In descending numerical order, the ratings


were: almost always present, frequently present, occasionally present, and rarely present.

It is possible that a diagnosis could be nearly always present, but the treatment of the condition was not appro- priate, nor advisable, in the critical care setting. Following the intervention and outcome phases of the project, subjects were asked to designate which nursing diagnoses were not a treatment priority in critical care nursing.

The survey materials consisted of a letter to participants, a background data sheet, the survey instrument (a half- page size booklet containing 15 pages with reduced-size type), and a return envelope. Surveys were mailed through a m a h g house and requested sub- to participate in the survey and to continue in the project (three additional surveys). Consent for continued participation was returned separately. Due to the large sample cost and anonymity- assurance, there was no follow up of non-responders.

Means and standard deviations were calculated for each diagnosis, and then they were analyzed within the functional health patterns (Gordon, 1994) to identify important diagnostic areas. Important areas had a mean of 3.0 or above; this was consistent with the nearly always or frequently present ratings on the 1-4 scale.

Similarly, high frequency-treatment priority diagnoses had a mean rating of 3.0 or above, equivalent to the almost always or frequently present ratings. A second criterion for individual diagnoses, a 50% simple majority (mean = 2.5 or greater), was applied to identlfy a larger pool of prevalent diagnoses that also were rated as a treatment priority in this setting.

Ethical standards were applied. The research project was approved by a university institutional review board. Subjects were assured anonymity, that results would be reported as pooled data, and that return of the instrument indicated their informed consent. Use of a mailing service protected anonymity of the nurse-subjects.

Results

Descriptive statistics were used to identify important diagnostic areas and high frequency nursing diagnoses in critical care nursing practice.

Diagnostic Areas

The distribution of 135 nursing diagnoses within the 11 functional areas ranged from one diagnosis in the sleep rest pattern to 24 diagnoses in the activity pattern area. Table 4 contains the rankings, means, and standard deviations for the diagnostic areas when all diagnoses were included. Means for the areas ranged from 3.3 for the sleep pattern (3.0 = frequently present) to 2.2 for the diagnoses in the value-belief pattern (2 = occasionally present). Standard deviations ranged from 0.89 to 0.43; homogeneity of responses was apparent when the area with one diagnosis (SD = 0.89) was excluded.

In order to identify important diagnostic areas, low- rated diagnoses (means less than 3.0, the occasionally or rarely present range) were removed from the pattern areas. When the remaining 20 high frequency diagnoses that are starred in Table 5 were considered alone, six important diagnostic areas emerged. They were health (risk) management, nutritional-metabolic (both general nutrition and nutrient supply to tissues), activity, sleep, cognitive-perceptual, and self-perception (emotional) pattern. The diagnostic areas that contained no high

Table 4. Ranks, Means, Standard Deviations of Functional Health Pattern Areas Containing Diagnoses

Rank FHPAreas #of dx X SD in area

1. Sleep-Rest 1 3.3 0 89 2. Activity-Exercise 24 2.7 0.47 3. Nutritional-Metabolic 19 2.5 0.45 4. Coping-Stress Tolerance 9 2.3 0.53 4. Self Perception-Self-Concept 11 2.3 0.52 5. Health Perception-

Health Management 12 2.2 0.45 5. Cognitive-Perceptual 18 2.2 0.49 5. Value-Belief 2 2.2 0.79 6. Elimination 13 2.0 0.49 7. Role-Relationship 21 1.8 0.43

Total 135



Table 5. Frequently Occurring Nursing Diagnoses: Percentages, Mean Ratings, and Standard Deviations*

Mean% Mean Functional Health Patterns Nurses Rating

Health Perception-Health Management Pattern

*High Risk tor Infection 92 At risk for being invaded by pathogens

*High IGsk for Injury (specify type) 7-1 At risk for harm as a result of interaction between environment and individual‘s adaptive and defensive resoiirces

At risk for entry of secretions, food, or fluids into tracheobronchial passages in the absence of iiormal protective mechanisms

High Risk tor Aspiration 70

Nutritional-Metabolic Pattern

*High Ibsk for Impaired Skin Integritv 90 At risk for break in skin

*Fluid Volume Excess 89 Fluid retention and edema

“Altered C“wliopu1monary Tissue I’ertusion 88

Decreaied cardiopulmonary cellular nutntioii and oxvgenahon related to a dehcit in capillarv blood supply

*High Risk for Fluid Volume Deficit At risk for decrease in total body fluid, mtravasdar, intracellular, or Intershtial

Decrease iii total body fluid intrai a%cular, intracellular, interstitial

Break in skin

81

*Fluid x olume deficit 78

“Impaired Skin IntegritL 77

requirements) 71 2iitritional Deficit (less thm bodv

liisutficient nutrient intake to meet metabolic needs

Altered Peripheral Tissue Perfusion 71 Decreased peripheral cellular nutrihon and ow genatioii related to a deficit in capillan blood supplv

3.6

3.1

2.9

3.5

3.2

3.2

3.1

3.0

3.0

2.9

1.9

SD

.68

.91

.81

.74

.65

.72

.78

.75

.M

.85

.n

Mean % Functional Health Patterns Nurses

Altered Cerebral Tissue Perfusion 62 Decreased cerebral cellular nutrition and oxygenation related to a deficit in capillary blood supply

Altered Renal Tissue Perfusion 61 Decreased renal cellular nutrition and oxygenation related to a deficit in capillary blood supply

Hyperthermia 61 Body temperature elevated above normal range

Damage to mucous membrane, corneal, integumentary, or subcutaneous tissue

At risk for failure to maintain body temperature within normal range

Impaired Xssue Integrity 58

High Risk for Altered Body Temperature 54

- Elimination Pattern

Diarrhea 64 Frequent loose, fluid, unformed stools

Involuntary passage of stool

Decrease in frequency and/or passage of hard dry stools

Bowel Incontinence 59

Constipation 50

- Activity-Exercise Pattern

+Impaired Gas Exchange 92 Decreased passage of oxygen/carbon dioxide between alveoli and vascular system

*Decreased Cardiac Output 91 Insufficient amount of blood pumped by heart to meet body tissue needs

“Ineffective Airway Clearance 87 Inability to clear secretions or obstructions from respiratory tract to maintain airway patency

Mean Rating

2.7

2.7

2.7

2.7

2.6

2.7

2.6

2.5

3.3

3.4

3.3

SD

.80

82

.82

.87

.86

.77

.85

.80

.h5

.fl7

73


Table 5. Continued

*Ineffective Breathing Pattern 81 Inhalation and exhalation patterns inadequate for pulmonary inflation or emptying

At risk for insufficient energy for required or desired daily activities

Insufficient energy for required or desired daily activities

Limitation of independent body movement

Inability to perform or complete bathing/hygiene activities for self

Dressing /Grooming Self-care Deficit 67 Inability to perform or complete dressing and grooming activities for self

Total Self-care Deficit 61 Inability to complete feeding, bathing, toileting, dressing, or grooming of self

Inability to perform or complete toileting activities for self

Inability to perform or complete feeding activities for self

*High Risk for Activity Intolerance 73

*Activity Intolerance 73

Impaired Mobility 71

*Bathing/Hygiene Self-Care Deficit 70

Toileting Self-care Deficit 59

Feeding Self-care Deficit 58

Sleep-Rest Pattern

*Sleep-Pattern Disturbance 81 Disruption of sleep time causing discomfort or interfering with desired life-style

- Cognitive-Perceptual Pattern

*Pain (Specify Location) 93

"Sensory Overload 75

Experience and report of severe discomfort

Environmental and social stimuli greater than usual and/or monotonous stimuli

3.1

3.0

3.0

2.9

3.0

2.9

2.8

2.7

2.6

3.3

3.4

3.1

.74

.95

.92

81

.95

1 .oo

.99

.96

.93

.89

.66

.97

*Knowledge Deficit 70 Inability to explain information or demonstrate a required skill needed to manage health care

At risk for impairment of memory, reasoning, judgement and decision making abilities

- Self Perception-Self-concept Pattern

High Risk for Cognitive Impairment 55

*Anxiety 84

Fear (Specify) 64

Vague uneasy feeling associated with a nonspecific or unknown source

Feeling of dread related to an identifiable source

Anticipatory Anxiety 62 Increased level of arousal associated with a perceived future threat (unfocused)

Powerlessness 55 Perceived lack of control over a situation and inability to sigruficantly affect an outcome

Role-Relationship Pattern

Impaired Verbal Communication 54 Decreased, or absent, ability to speak or understand language in human interaction

- Coping-Stress Tolerance Pattern

Impaired Adjustment 55 Inability to modify lifestyle/behaviors in a manner consistent with a change in health status

Denial 55 Conscious or unconscious attempt to disavow knowledge or meaning of an event to reduce anxiety or fear to the detriment of health

Impaired adaptive behaviors and problem solving abilities to meet life demands and roles

Ineffective Coping 49

3.0

2.6

3.3

2.8

2.8

2.6

2.6

2.5

2.5

2.5

.89

.87

.82

.93

.96

.96

.87

.83

33

.78

* Percentages are based on nurses' ratings of "nearly always" and "hquently present" in their practice; high frequency diagnoses are marked with an asterisk.



frequency diagnoses were elimination, sexuality /repro- ductive, role relationship, coping/stress tolerance and the value/belief pattern.

Nursing Diagnoses

Specific diagnoses within diagnostic areas were of interest. Table 5 contains the 44 diagnoses that met the criteria for prevalent diagnoses (mean = 2.5 or greater and 50R or more of 678 nurses). These diagnoses represent 33% of the 135 currently identified diagnoses used in the survey. The standard deviations of the diagnoses in Table 5 ranged from 0.65 to 1.00.

Consider first the 20 high frequency diagnoses that are starred in Table 5. Five of these conditions were rated as nearly always or frequently present in their practice by 90% or more of the 678 nurses: pain (93%), impaired gas exchange (927~c), high risk for infection (927~1, decreased cardiac output (91 %), and high risk for impaired skin iiifegrify (90%). All of the 20 high frequency diagnoses starred in Table 5 were designated as a treatment priority in the critical care setting. These diagnoses represent 15% of the 135 nursing diagnoses in the study.

Five of the 20 high frequency diagnoses describe potential problems: high risk for infection, inju y, fluid uol- iinie dcficif, impaired skin integrity, and high risk for activity i r z f o l t w k f . As could be expected in ths specialty, the five diagnoses lowest in rank (130 to 135) were the three types of r a p traicina syiidronrc (3.4-2.6%7 of the nurses), intJffectizie breastfeeding (4.3%), and weak parent- infant attachment (4.9%). All but four of the prevalent diagnoses in Table 5 were designated as a priority for treatment in critical care: drEssirtg-cqrooming self-cart. deficit, toiletiizg self- mw drf i i i t , inqxiiwd ndj i is fmcnt , aiid denial. None of the currently identified conditions in the sexuality-reproduc- ti\re pattcrn (r7 = .5) and the value-belief pattern ( n = 2) met the criterion for prevalent diagnoses.

A set of ten diagnoses from the NANDA Taxonomy were col1abc)rative treatment problems (primarily require rnedical evaluation and treatment to resolve). Eight of these met the criterion for high frequency or prevalent diagnoses in critical care: impaired gas excliaiigc ( 9 2 7 ~ ) ~

decreased cardiac output (91%), fluid volume excess (89%) and deficit (78%), and impaired tissue perfision (cardiopulmonary 88%, peripheral 71%, cerebral 62%, renal 61%).

Discussion and Implications

The nurse-experts in this national study of nursing diagnoses in critical care reported previous education in diagnosis and use of diagnoses as a basis for nursing interventions. All belonged to AACN, a specialty organi- zation that had based its outcome standards on nursing diagnoses. The effect of heterogeneity in knowledge of diagnostic terms, which can influence consistency of responses across nurses, was reduced by placing clinical descriptions before the diagnostic term in the survey instrument (see dehtions, Table 5).

Important Diagnostic Areas

Knowing important diagnostic areas increases sensi- tivity to cues to dysfunctional patterns and can result in early case finding. From an educational perspective, important diagnostic areas suggest essential content for a curriculum. In addition, these areas suggest priorities for clinical studies that contribute to the development of nursing science.

When only one functional area with a single diagnosis met criterion, it was evident that low frequency problems (e.g., breastfeeding and stress incontinence) reduced area means and masked important information. When just high frequency diagnoses were analyzed, six important diagnostic areas emerged: sleep-rest, nutritional- metabolic (both general nutrition and nutrient supply to tissues), activity, cognitive-perceptual, health (risk) management, and self-perception (mood) patterns. These patterns are commonly affected during the critical phase of an Illness; five were represented in the high frequency diagnoses identified by the AACN Consensus Panel (Table 1).

The single high frequency diagnosis in the sleep-rest pattern, sleep pattern disturbance, inflated the area mean. Yet number of diagnoses and means were not

Nursing Diagnosis Volume 6, No. 4, October-December, ‘1995

directly related in other areas, such as the value-belief pattern that had two diagnoses.

Findings suggest that these six areas should be the focus of in-depth, rather than screening, assessment to avoid diagnostic errors of omission. In addition, because functional patterns are interdependent, it is likely that relationships exist between areas: sleep pattern disturbance related to anxiety is an example of a diagnostic statement that forms the basis for judgments about outcomes and interventions.

There are many types of sleep pattern disturbances. This diagnosis has been cited as a problem in critical care units by others (Dracup, 1987) but was not included in the high frequency-high importance listing by AACN (Table l), perhaps because of its lack of specificity. Specific ”disturbances” in sleep need to be identified, developed, and submitted to NANDA for classification (e.g., sleep pattern reversal, sleep onset delay, interrupted sleep pattern, etc.). Broad diagnostic concepts such as these encourage low precision in diagnostic judgments. Development of a taxonomy of sleep disturbances treated by nurses should precede further study of prevalence rates.

A lower, “simple majority” criterion for defining important diagnostic areas may be useful in situations where a broad perspective on practice is desired. When prevalence was defined as 50% or more of the nurses rating the condition as nearly always or frequently present, the elimination pattern (bowel problems), the role-relationship pattern (communication problems), and coping-stress tolerance (adjustment and denial) were three additional diagnostic areas that emerged.

The lessor importance of the two remaining functional areas may be due to the setting. Unless they impact on the physiological instability, sexuality-repro- ductive problems are not ”seen” frequently or treated in critical care. The value-belief area may not have achieved high importance due to a number of factors: the level of development of the diagnoses in the area (spiritual dis- tress, value conflict), the level of consciousness of critically ill patients, the fairly recent attention to advanced

directives, and conflicts that arise due to competing val- ues, or lastly, a combination of these factors.

High Frequency-Treatment Priority Nursing Diagnoses

The 44 diagnoses representing 33% of the 135 used in the study (Table 5) represent a broad scope of practice in this specialty and the need for both a nursing and medical science base. Five diagnoses had the highest agree- ment, as reflected by the 90% or more of 678 nurses rating the diagnoses as nearly always or frequently present in their practice. This finding suggests that these diagnoses may be useful as quality assurance tracers, as a focus for clinical guideline development, and for clinical research. Risk management could be monitored using the five high risk conditions included among the 20 high frequency diagnoses.

Ninety-three percent of nurses rated pain as a highly prevalent condition in critical care. Possibly chest pain and incisional pain are two types of pain encountered in the subspecialties that predominated in the sample (coronary care, medical intensive care, and surgical intensive care). High risk for infection and high risk for impaired skin integrity were also among the top five conditions. When these two diagnoses are combined with six other high risk problems (Table 5), the role of risk management and health promotion in critical care is clearly visible. Intravenous administration of drugs and fluids, monitoring equipment, and surgical procedures all break the skin barrier and place patients with physiological instability at risk for infection. Similarly, acuity of the illness and impaired bed mobility combine to increase the risk for impaired skin integrity; pressure ulcer is a condition that can develop within 24 hours. High risk for injury, activity intolerance, aspiration, altered body temperature, fruid volume deficit, and cognitive impairment are other risk states that were rated as prevalent. In an extension of this study involving 408 nurses in neonatal intensive care (Herdman, 1990), seven of these high risk states were among the 20 highest ranked. In contrast, no high risk conditions were identified by nurses in a small study by Kim and her colleagues (Kim et al., 1984) that



included some adult critical care, cardiovascular patients. They found alteration in coronary circulatioii, decreased cnrdiiic oiityiit, alteratioii in comfort, decreased activity tolcw2nce, niixiefy, knozuledge drfzczt, and iirobilify iinpairmcnf were the most frequently used diagnoses by a group of nurses caring for cardiovascular patients. Similar to findings in this study, a review of clinical studies in acute adult care ( n = 1,100 cases) demon- strated that pain, niixiety, impairid skin integrit!y, high risk for irnpnirerl skiii integrity, and self-care deficit were com- mon (Gordon, 1985).

Anticipatory anxiety was the only prevalent diagnosis that was not in the NANDA Taxonomy (Carroll- Johnson, 1991 ). Other non-NANDA-approved diagnoses, such as support system deficit, and high risk for joint contractures, did not meet the prevalence criterion.

Diagnostic statements contain a problem and proba- ble cause(s). It is interesting to note that many of the hghly prevalent-treatment priority diagnoses (Table 5) are the focus for intervention (etiological or related factors). For example, nurses intervene to change iiiefiecctizv breatli in~ pattern, knowledge deficit, sensor!/ or~erload, actio- ity intolemiice, anxiety, and pain. Left untreated these conditions continue to produce other problems.

Nine of the 10 collaborative-treatment problems listed by NANDA as nursing diagnoses in 1990 were prevalent in critical care. These include f l i i id volume deficits and excesses, various types of tissue perfusion defined at the cellular nutritional l e ~ e l , decreased cardiac output, and impaired y17s esclzai~~qe. In both this study and the neonatal intensive tare study (Herdman, 1990), these latter two diagnoses were among the highest frequency, collaborative conditions. Except for decreased mrdiac oirtpzit, these diagnoses were listed by AACN (Table 1 ). The definitions of these diagnoses suggest that they are collaborative treatment problems and require medical evaluation and treatment, as well as nursing evaluation and intervention (e.g., preventive intervention, surveillance, and the implementation of physician-initiated treatments). In most instances nurses are not held professionally accountable for the primary plan of care, outcomes of treatment, or for research on these conditions. It may be

that ineffective lirenthing pattern, rather than impaired gas exchange, is the nursing focus for immediate nurse-initiated treatments, such as stimulation, positioning, or clearance of secretions (AACN, 1990). Impaired gas excliatige or decreased cardiac output are the context in which functional problems occur (e.g., activity intolerance, kiiowledge dPficit, self-cure deficit, or anxiety (AACN).

When patients in critical care become aware of the seriousness of their condition, the ever-present lugh tech- nology and monitoring, and the concern of their families, ths awareness can lead to emotional reactions. Fifty per cent or more of the nurses rated anticipat-oy anxiety, f e u , iinpaired ndjus frnenf , denial and pozoerlessness as frequently present and a treatment priority. Ineffective coping (49% of nurses ; mean rating 2.5 ) was on the criterion border; denial was rated as prevalent but was not a treatment priority, reflecting knowledge of the protective nature of denial early in a crisis. Fear also was frequently present in neonatal intensive care nursing, particularly fear of attachment and separation (Herdman, 1990). In contrast to these critical care studies it can be noted in

Table 1 that anxiety, fear, and ineffective coping were rated as h g h frequency but low priority (importance) by the AACN panel. It is possible that the panel was influ- enced by the relative importance (comparisons with more life-threatening conditions) and in the current study each diagnosis was rated individually.

The high frequency of sensory overload can be explained by the increased or monotonous stimuli in a critical care unit. Knozuledge deficit met the criterion for a prevalent diagnosis but less than 50% of the nurses tles- ignated it as a treatment priority. Generally, the extent of teaching when a patient is critically ill is restricted to explanations that enhance coping and understanding.

Self-care deficits were frequently present but only bathing-hygiene deficit was a treatment priority in this setting. In many instances as patients progress, sQme degree of self-bathing is gradually introduced. Many diagnoses related to elimination such as altered urinary elitiiinatioii (45%), firncfional incontinence (37%), and others, did not meet the prevalence criterion possibly because of indwelling catheters.


The AACN identified altered family process as a high frequency but low priority diagnosis but the three family coping diagnoses were not in their listing. In the present study no family diagnoses reached the criterion for frequently occurring conditions. It may be that famihes frequently have concerns but most do not develop altered family processes or compromised or disabling levels of ineffective coping. Alternatively if risk factors are routinely addressed and the condition prevented, perhaps the risk state is not consciously recognized. No language exists to describe risk for ineffective family coping, family anxiety or family powerlessness and thus the conditions and their treatment remain invisible. Development of these conditions as diagnostic categories requires identification of risk factors that can be facilitated by examination of related factors (the causes of the adual problem) (NANDA, 1995).

Decisional conflict (24% of nurses rated as almost always or frequently present) is a good example of a diagnosis that would be expected to be rated as a treatment priority (but perhaps not high frequency) in an area where patients, their families, or both have to make life or death decisions. Hiltunen (1994) proposes that the physiological, communication, and cognitive problems of the critically ill may explain why this diagnosis was not rated higher. Lack of recognition or lack of differen- tial diagnosis by nurses, as well as other competing treatment priorities, also may explain this finding (Hiltunen).

Some caution has to be exercised in generalizing from the prevalence estimates in this study generated by recall (subject’s generalizations about base rates), in comparison to prevalence data obtained during patient care (sta- tistical generalization based on actual base rates). Recall and rating a diagnosis depends on the ability of nurses to develop generalizations from their practice and then recall the base rate occurrence of conditions described by nursing diagnoses. In this study the predominance of experienced nurses and, in particular, their current involvement in direct patient-care increased the recency of their recall. The human tendency to generalize from multiple experiences, combined with the large percent- age (82%) claiming to use nursing diagnoses, and their years in practice, increased the likelihood that they had

stored knowledge of frequency-estimates. The tendency to recall more instances of salient, highly visible phe- nomena than actually occur could also influence ratings. This may elevate diagnoses, such as abuse, rape trauma syndrome, or high risk for violence. None were rated as hgh frequency, suggesting saliency of events did not influence recall of the frequency of diagnostic events.

The study was based on the diagnostic hting of 1990. Since that time other conditions have been added to the classification system (NANDA, 1995). For example, disuse syndrome, inability to sustain spontaneous ventilation, and dysfunctional ventilato y weaning response may be prevalent in critical care settings. Additional prevalence studies of these conditions and other biopsychosocial responses of critically ill patients are needed. Critical defining characteristics of the high frequency diagnoses are the focus of a second study in this project and further analyses of the influence of demographic variables on nurses’ prevalence ratings will be needed to determine, for example, if prevalence rates vary across specialized critical care units.

Conclusions

In summary, six important diagnostic areas were identified that contained 20 high frequency diagnoses. These areas were sleep-rest, nutritional-metabolic, activity, cognitive-perceptual, health (risk) management, and self-perception (mood) patterns. All were a treatment priority in this setting. The 20 diagnoses within these areas can be the focus of further research and development to increase clinical usefulness and provide a focus for education, treatment planning, and quality monitoring. The 10 highest ranked diagnoses were: (1)pain ; (2) high risk for infection; (3) risk for impaired skin integrity; (4) ingective ainoay clearance; (5) anxiety; (6) sleep pattern disturbance; (7) risk for fluid volume deficit; (8) ineffective breathing pattern; (9) senso y overload; and (10) high risk for injury. impaired gas exchange and decreased cardiac output, two collaborative diagnoses, also were of high rank. A broad scope of practice in critical care was revealed by these findings, suggesting that physiological instability is only one dimension of the nursing perspective in critical care.

Nursing Diagnosis Volume 6, No. 4, OdoberDecember, 1995 153

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1% Nursing Diagnosis Volume 6, No. 4, October-December, 1995

high frequency: treatment priority nursing diagnoses in critical care

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