Introduction
The role of nursing in the management of acute decompensated heart failure (ADHF) in the hospital environment is fundamental to achieving therapeutic goals, adherence to treatment, and self-care [1-3]. According to data from the National Health and Nutrition Examination Survey (NHANES) for 2015-2018, approximately 6 million individuals aged 20 years or older in the United States had heart failure (HF). It is also estimated that the prevalence of HF will increase by 46% between 2012 and 2030, affecting over 8 million people aged 18 and above [4,5]. Consequently, the use of health services in this population is increasing, with an average hospitalization rate for HF of 11.6 cases per 1000 individuals per year in people over 55 years old [6].
Considering the high burden of morbidity and mortality associated with HF, the nursing care process (NCP), through its structure and scientific basis, allows comprehensive and practical resolution of problems and decision-making from its different phases. In the assessment phase, a diagnosis is identified (Nursing Diagnoses from the NANDA International - NANDA); in the planning phase, interventions are established (Nursing Interventions Classification - NIC); and in the evaluation phase, an outcome is based (Nursing Outcome Classification-NOC) to monitor the efficacy of the interventions executed, under the implementation of a standardized language recognized by the American Nursing Association (AAN) [7,8].
Standardized language is expected to improve the consistency, content, and format of nursing communication and enhance the effectiveness and efficiency of information shared among nurses and other healthcare professionals [8,9]. Additionally, this process promotes autonomy and leadership within the nursing profession, particularly in the care of hospitalized patients, based on the clinical reasoning employed by the nurse. This standardized terminology also provides strategies for patient engagement, care plan implementation, change monitoring, and clinical decision-making that enhance the quality of nursing care across clinical contexts [10-12]. In the context of HF, the literature supports that using standardized language leads to high-quality care by prescribing evidence-based interventions, ensuring patient safety [13].
While previous research has documented the prevalence of NANDA-NIC-NOC interactions in HF patients in other settings [14], there is a lack of consolidated data in Colombia regarding nursing records that utilize standardized language for managing patients with ADHF. This is notable despite the existence of multiple specialized heart failure units with a high volume of patients, where nursing plays a key role in patient care [15].
These studies are primarily conducted in controlled settings such as intensive care units and not in heart failure centers of excellence, where they address populations from different hospital services. Furthermore, most do not systematically integrate the NANDA-NOC-NIC taxonomies to describe the nursing care process.
This lack of local evidence makes it difficult to identify patterns and care priorities in the care of patients with heart failure in a specialized cardiovascular center and restricts comparisons with international standards.
Therefore, this study aimed to address this gap by analyzing real-world data from routine clinical practice in Colombia. This study aimed to determine the prevalence of diagnoses, outcomes, and nursing interventions in patients with ADHF in a specialized cardiovascular center.
Materials and methods
A prospective cohort study was conducted based on the Institutional aCute decompensAted HeaRt FailUre Registry (ICARUS) [16]. Patients with a medical diagnosis of ADHF who were treated at the emergency department in a cardiovascular center in Colombia between June 2022 and June 2023 were included. Eligible patients were 18 years or older, hospitalized in any department, and had undergone the nursing care process (NCP). No sample size calculation was considered; thus, all patients meeting the inclusion criteria during the study period were included.
It is important to note that the healthcare institution where these patients were treated has specialized centers of excellence for managing various pathologies, all of which adhere to the highest quality standards. One is the Heart Failure Center of Excellence, accredited by the Joint Commission International (JCI). The center provides comprehensive care for ADHF, including advanced therapies such as heart transplantation and long-term ventricular assist devices.
Demographic data such as sex, age, marital status, education level, social security coverage, and area of residence were collected, along with clinical information related to HF, such as left ventricular ejection fraction (LVEF), functional class (according to the New York Heart Association - NYHA scale), HF etiology, vital signs (heart rate and blood pressure), key clinical laboratories (serum potassium level, glomerular filtration rate), refractory vs. non-refractory HF status, palliative management, type of cardiovascular devices, medical history, and treatment at admission. The primary, secondary, and tertiary NANDA-NIC-NOC taxonomies were also recorded.
At the Center of Excellence, the nursing professional applies a structured NCP within 24 hours of patient admission, including an initial assessment based on NANDA II taxonomy, identifying a NANDA diagnosis, NOC objectives, and NIC interventions. The team also utilizes a standardized and prioritized nursing care matrix specific to ADHF patients, developed based on a literature review and institutional standards to streamline the care process.
A descriptive analysis was performed, and quantitative variables that presented a normal distribution were described with the mean and standard deviation; otherwise, the median, first, and third quartiles (Q1-Q3) were reported. For categorical variables, the NCP absolute and relative values were also reported. The statistical analysis was performed using Stata v15 (StataCorp LLC). This research was approved by the Scientific Technical Committee and the Research Ethics Committee of the Institution (act code CEI2022-05104).
Results
A total of 1397 patients with ADHF were included, with a median age of 67 years (Q1 = 58; Q3 = 76), of whom 69.22% were male. Regarding marital status, 39.44% were married, 76.08% were illiterate or had basic schooling, 67.36% were covered by subsidized social security, and 90.98% resided in urban areas (Table 1).
Table 1 Sociodemographic characteristics of patients with ADHF (n = 1397).
| Variables | n (%) |
|---|---|
| Age (years) | 67 (58-76)* |
| Sex | |
| Men | 967 (69.22) |
| Women | 430 (30.78) |
| Marital status | |
| Married | 551 (39.44) |
| Single | 339 (24.27) |
| Unmarried | 223 (15.96) |
| Widowed | 167 (11.95) |
| Separated | 85 (6.08) |
| Not stated | 32 (2.29) |
| Level of schooling | |
| None - illiterate | 220 (15.74) |
| Primary | 843 (60.34) |
| Secondary | 233 (16.68) |
| Technical-professional-graduate | 101 (7.24) |
| Social Security | |
| Subsidized | 941 (67.36) |
| Contributory | 363 (25.98) |
| Other | 93 (6.65) |
| Area of residence | |
| Urban | 1271 (90.98) |
| Rural | 126 (9.02) |
Note. *Median (first and third quartile).
The most common comorbidities were hypertension (55.91%), atrial fibrillation (24.27%), and diabetes mellitus (24.12%). The etiology of HF was ischemic in 61.63% of patients. The median LVEF was 30% (Q1 = 20; Q3 = 43), and 58.77% (n = 821) had NYHA functional class III/IV. had NYHA functional class III/IV. Refractory ADHF was present in 4.72% of patients, and 3.79% received palliative management. A prior implantable cardiovascular device was present in 16.25% of patients, with an implantable cardioverter-defibrillator (ICD) being the most common (8.38%). At admission, 49.61% of patients were on receiving angiotensin-converting enzyme (ACE) inhibitors, Angiotensin 2 Receptor Blockers (ARBs), or Angiotensin receptor neprilysin inhibitors (ARNIs), 45.45% were on beta-blockers, 37.80% on mineralocorticoid receptor antagonists, 34.00% on SGLT2 inhibitors, and 2.22% required inotropes (Table 2).
Table 2 Clinical characteristics of patients with ADHF (n = 1397).
| Characteristics | n (%) |
|---|---|
| Comorbidities | |
| Arterial hypertension | 781 (55.91) |
| Atrial fibrillation | 339 (24.27) |
| Diabetes mellitus | 337 (24.12) |
| Chronic renal disease | 240 (17.18) |
| Dyslipidemia | 191 (13.67) |
| Hypothyroidism | 182 (13.03) |
| Vital signs | |
| Heart rate | 74 (64-85)* |
| SBP (mmHg) | 118 (101-136)* |
| DBP (mmHg) | 70 (61-82)* |
| Etiology of ADHF | |
| Ischemic | 861 (61.63) |
| Non-ischemic | 536 (38.37) |
| LVEF (%) | 30 (20-43)* |
| NYHA functional class | |
| Functional class I-II | 576 (41.23) |
| Functional class III-IV | 821 (58.77) |
| Patient in palliative care (yes) | 53 (3.79) |
| Patient with refractory ADHF (yes) | 66 (4.72) |
| Previous devices | 227 (16.25) |
| Type of device | |
| ICD | 117 (8.38) |
| Cardio resynchronizer | 28 (2.00) |
| ICD+ Cardio resynchronizer | 16 (1.15) |
| Pacemaker | 66 (4.72) |
| Admission treatment | |
| IECA - ARAII - ARNI | 693 (49.61) |
| Beta blockers | 635 (45.45) |
| ARM | 528 (37.80) |
| iSGLT2 | 475 (34.00) |
| Inotropic | 31 (2.22) |
Notes. SBP: systolic blood pressure; DBP: diastolic blood pressure; LVEF: left ventricular ejection fraction; NYHA: New York Heart Association; ICD: implantable cardioverter-defibrillator; ACEIs: angiotensin-converting enzyme inhibitors; ARBs: Angiotensin II receptor antagonists; ARNI: Dual neprilesin and angiotensin receptor inhibitor; MRA: Mineralocorticoid receptor antagonists; iSGLT2: sodium-glucose cotransporter type 2 inhibitors. *Median (first and third quartiles).
Regarding the NANDA-NOC-NIC interaction, the most prevalent diagnosis was “deficient knowledge” (24.05%), with the outcome “knowledge disease control” (22.98%) and the intervention “teaching: disease process (31.16%). The second diagnosis was “decreased cardiac output” (17.11%), with NOC “cardiac pump effectiveness” (16.96%) and NIC “fluid management” (14.18%); the third most prevalent diagnosis was “decreased activity tolerance” (10.95%), with NOC “fatigue level” (13.10%) and NIC “encouragement of exercise” (12.75%). Table 3 shows the Prevalence of diagnoses, outcomes and nursing interventions in patients with ADHF.
Table 3 Prevalence of diagnoses, outcomes, and nursing interventions in patients with ADHF (n = 1397).
| NANDA nursing diagnosis | n (%) | NOC | n (%) | NIC | n (%) |
|---|---|---|---|---|---|
| Deficient knowledge [00126] | 336 (24.05) | Knowledge disease control [1830] | 321 (22.98) | Teaching: disease process [5602] | 435 (31.16) |
| Decreased cardiac output [00029] | 239 (17.11) | Effectiveness of cardiac pump [0400] | 237 (16.96) | Fluid management [4120] | 198 (14.18) |
| Decreased activity tolerance [00298] | 153 (10.95) | Fatigue level [0007] | 183 (13.10) | Exercise promotion [0200] | 178 (12.75) |
| Willingness to improve self-management [00293] | 122 (8.73) | Knowledge: management of heart failure [1835] | 137 (9.81) | Cardiac care [4040] | 127 (9.10) |
| Excess fluid volumen [00026] | 105 (7.52) | Compliance behavior [1601] | 132 (9.45) | Common goal setting [4410] | 82 (5.87) |
| Tendency to adopt health-risk behaviors [00188] | 90 (6.44) | Water balance [0601] | 104 (7.44) | Improved coping [5230] | 54 (3.87) |
| Acute Pain [00132] | 80 (5.73) | Pain level [2102] | 74 (5.30) | Agreement on conduct [4420] | 46 (3.30) |
| Ineffective health maintenance behaviors [00292] | 50 (3.58) | Self-management: heart failure [3106] | 61 (4.37) | Active listening [4920] | 44 (3.15) |
| Willingness to improve knowledge [00161] | 50 (3.58) | Coping [1302] | 25 (1.79) | Pain management: acute [1410] | 38 (2.72) |
| Impaired ambulation [00088] | 24 (1.72) | Psychosocial modification: life change [1305] | 24 (1.72) | Praise [4364] | 33 (2.36) |
| Ineffective coping [00069] | 21 (1.50) | Knowledge: infection management [1842] | 17 (1.22) | Protection against infections [6550] | 18 (1.29) |
| Risk of infection [00004] | 18 (1.29) | Social climate of the family [2601] | 12 (0.86) | Teaching: individual [5606] | 16 (1.15) |
| Risk of situational low self-esteem [00153] | 17 (1.22) | Nutritional status: food and fluid intake [1008] | 11 (0.79) | Help with self-care [1800] | 14 (1.00) |
| Willingness to improve self-care [00182] | 14 (1.00) | Severity of loneliness [1203] | 9 (0.64) | Teaching: Prescribed Diet [5614] | 13 (0.93) |
| Nutritional imbalance: intake below needs [00002] | 13 (0.93) | Therapeutic conduct: illness or injury [1609] | 6 (0.43) | Improving support systems [5440] | 12 (0.86) |
| Risk of loneliness [00054] | 13 (0.93) | Teaching: disease process [5602] | 5 (0.36) | Fluid monitoring [4130] | 12 (0.86) |
| Sleep pattern disorder [00198] | 10 (0.72) | Medication administration: intraspinal [2319] | 5 (0.36) | Nutrition management [1100] | 12 (0.86) |
| Chronic grief [00137] | 9 (0.64) | Liquid management [4120] | 3 (0.21) | Improved sleep [1850] | 10 (0.72) |
| Interruption of family processes [00060] | 7 (0.50) | Fear level [1210] | 3 (0.21) | Give hope [5310] | 8 (0.57) |
| Ineffective health management [00078] | 5 (0.36) | Compliance conduct [1601] | 3 (0.21) | Behavior modification [4360] | 7 (0.50) |
| Anxiety [00146] | 5 (0.36) | Adherence behavior: prescribed activity [1632] | 3 (0.21) | Health education [5510] | 6 (0.43) |
| Fear [00148] | 4 (0.29) | Cardiac care [4040] | 2 (0.14) | Teaching: Prescribed Medications [5616] | 5 (0.36) |
| Ineffective thermoregulation [00008] | 2 (0.14) | Sleep[0004] | 1 (0.07) | Weight management [1260] | 4 (0.29) |
| Constipation [00011] | 2 (0.14) | Anxiety level [0040] | 1 (0.07) | Knowledge: Heart Disease Management [1830] | 4 (0.29) |
| Caregiver fatigue [00061] | 2 (0.14) | Self-management: liver disease [3126] | 1 (0.07) | Teaching: prescribed exercise [5612] | 3 (0.21) |
| Diarrhea [00013] | 1 (0.07) | Ambulate [0200] | 1 (0.07) | Environmental management: safety [400] | 2 (0.14) |
| Activity intolerance [00092] | 1 (0.07) | Mobility [0208] | 1 (0.07) | Compliance conduct [1601] | 2 (0.14) |
| Provision to improve comfort [00183] | 1 (0.07) | Blood clotting [0409] | 1 (0.07) | Emotional support [5270] | 2 (0.14) |
| Risk of bleeding [00206] | 1 (0.07) | Decision making [0906] | 1 (0.07) | Conservation of energy [0002] | 1 (0.07) |
| Self-care deficit: bathing/hygiene [01211] | 1 (0.07) | Anxiety level [1211] | 1 (0.07) | Electrolyte management: hypokalemia [2007] | 1 (0.07) |
| Impaired physical mobility [04040] | 1 (0.07) | Stress level [1212] | 1 (0.07) | [29] | 1 (0.07) |
| Dignified death [1307] | 1 (0.07) | Electrolyte management: hypokalemia [0601] | 1 (0.07) | ||
| Auditory compensation behavior [1610] | 1 (0.07) | Wound healing [1102] | 1 (0.07) | ||
| Knowledge: health behavior [1805] | 1 (0.07) | [1206] | 1 (0.07) | ||
| Knowledge: Asthma Management [1832] | 1 (0.07) | Therapeutic conduct [1609] | 1 (0.07) | ||
| Knowledge: management of anticoagulant treatment [1845] | 1 (0.07) | Help with self-care: IADL [1805] | 1 (0.07) | ||
| Caregiver well-being [2508] | 1 (0.07) | Prevention of bleeding [4010] | 1 (0.07) | ||
| [4008] | 1 (0.07) | Support in decision-making [5250] | 1 (0.07) | ||
| Knowledge: Pain management [4360] | 1 (0.07) | Support for the primary caregiver [7040] | 1 (0.07) | ||
| Circulatory status [4410] | 1 (0.07) | ||||
| Agreement with the patient [4420] | 1 (0.07) | ||||
| Teaching: prescribed exercise [5612] | 1 (0.07) |
Notes. NANDA = Nursing Diagnoses from the NANDA; NOC = Nursing Outcome Classification; NIC = Nursing Interventions Classification.
Discussion
This study determined that the diagnosis “deficient knowledge” was the primary NANDA-NOC-NIC interaction, with the outcome “knowledge and control of the disease” and the intervention “teaching: disease process” in a cohort of hospitalized patients with ADHF attended by a Center of Excellence, which oriented nursing care.
Several studies in the scientific literature have corroborated the results of our research. Thus, Park H et al. agree with the results found, where the diagnosis of deficient knowledge (14.95%) and decreased cardiac output (12.31%) were the most prevalent diagnoses [10]. However, decreased activity tolerance, willingness to improve self-management, and excess fluid volume did not make part of the most frequent diagnoses; these differences could be explained by the hospitalization units where the patients were captured, that are related to health status (intensive care unit vs various services, in less frequency ICU) [17]. At the same time, the interventions were similar to those in our study, where fluid monitoring, cardiac care, and teaching procedures/treatments were identified as the main ones.
The longitudinal study conducted by Pereira J et al., involving two heart failure centers sharing similar sociodemographic and clinical characteristics with our population, showed that the most prevalent diagnosis was decreased cardiac output (62.5%), followed by activity intolerance (4.2%) and fatigue (1.4%) [18]. Likewise, Cavalcanti and Pereira, in their systematic review of 24 studies that included hospitalized, ambulatory, and home care populations, identified the eight most frequent nursing diagnoses in HF patients, among which the three most prevalent were decreased cardiac output (58.3%), excess fluid volume (33.3%), and activity intolerance (33.3%) [19]. It is essential to highlight that some nursing diagnoses are also part of specific defining characteristics (DC) that make up the NANDA-I taxonomy, as is the case with “fatigue,” which is described as a DC of “activity intolerance.” Therefore, they identify very similar human reactions.
Paneque-Sánchez-Toscano et al., in their meta-analysis, focused on the 16 most prevalent nursing diagnoses, identified a greater focus on the perception/cognition domain (deficient knowledge), followed by physiological problems with the activity/rest and nutrition domain (activity intolerance, excess fluid volume) [20]. There was discordance with the results of the study conducted in the Intensive Care Unit in Rio de Janeiro, where the most prevalent diagnosis corresponding to NANDA was risk of infection (74.8%), decreased cardiac output (55.1%), and excess fluid volume (49.5%); the NIC interventions performed in IC were vital signs monitoring, fluid monitoring and change of position [21]. Likewise, the most prevalent NOC outcomes in the study by Park et al. did not coincide with our results, as it addressed knowledge: therapeutic regimen, followed by fall prevention behavior, tissue integrity: skin and mucous membranes, and cardiac pump effectiveness [10].
HF patients require complex pharmacological and non-pharmacological treatment that includes different self-care behaviors. Thus, the mistake of adopting these behaviors has been related to various aspects, such as difficulty in care, inadequate follow-up by health services, and inadequate knowledge about the disease and treatment [22]. Evidence from randomized clinical trials show that when patients with HF are well-educated and followed up, they adhere more to treatment and improve knowledge about the disease and self-care [23-25].
It is also important to highlight that the nurse's role at the Heart Failure Center of Excellence is to educate the patient and family to improve adherence to treatment, quality of life, and self-care. This could contribute to prioritizing the diagnosis of deficient knowledge and the interventions and results related to the education and teaching process [26].
At the international level, continual efforts are being made to enhance the quality of nursing care and professional practices. The American Nurses Association has sanctioned the use of standardized nursing languages to promote evidence-based nursing care within the profession. Applying these languages has been shown to improve decision-making efficiency and critical thinking throughout the nursing process [27]. These results guide the standardization of processes and evidence-based decision-making, facilitating the development of care plans and innovative educational activities for patients with heart failure [12]. Furthermore, they are the key to prioritizing nursing interventions and distributing the workload across the multidisciplinary team. The nursing process facilitates ongoing communication between nursing professionals and efficient documentation of care through standardization in the electronic medical record [28].
Based on these findings, several lines of research have been identified for future studies. One of these is the creation of predictive models to estimate the risk of knowledge and/or self-care deficits in patients with heart failure, based on clinical and sociodemographic characteristics. Additionally, the development and validation of tools or instruments aimed at measuring the level of disease knowledge, thus facilitating the implementation and monitoring of educational interventions, is being considered.
Our study presents some strengths and limitations. Among its strengths, the information was routinely collected on patients with ADHF in a homogeneous way that reflects the reality of the application of ECP in this population and is of great relevance in the nursing profession [29]. Another strength is the large sample size is highlighted, which, although it was not randomly selected, all records were included consecutively, making it representative and adequate. As a limitation, the variability in the nurses' ability to execute care plans is evident, given that several nursing professionals performed this, and they may have different perceptions of the judgment produced by the nursing assessment due to experience and knowledge of pathology, among others; however, this was minimized with a standardized application of the nursing process as mentioned in the methodology.
Conclusions
The results indicate that deficient knowledge regarding acute decompensated heart failure in hospitalized patients is the most prevalent diagnosis, directing the nursing professional to establish a care plan to teach the process and control of the disease to improve adherence to treatment and self-care.














