Effect of continuity of care on self-management, quality of life, and clinical outcomes in patients with chronic heart failure

Abstract

This research aims to investigate the impact of continuity of care on individuals diagnosed with chronic heart failure (CHF), specifically examining its effects on their self-care capabilities, life quality, mental well-being, and physical condition. A total of 90 patients diagnosed with CHF and treated at our hospital between January and September 2023 were included in this retrospective controlled study. Propensity score matching was used to assign patients into 2 comparable groups: an intervention group and a control group (CG), each consisting of 45 individuals. The intervention group received a comprehensive continuity of care program in addition to standard nursing care, while the CG received standard care alone. The continuity of care model included components such as a collaborative multidisciplinary team, tailored patient education, emotional support, guidance on medication adherence, and consistent follow-up monitoring. The study assessed various outcomes, including patients’ self-care performance, quality of life scores, psychological assessments via the Hamilton Depression and Anxiety Scales, physical health indicators, and the frequency of adverse cardiovascular events. Following the continuity of care intervention, patients in the intervention group demonstrated a significant improvement in their self-care scores, increasing from 73.39 ± 4.02 pre-intervention to 89.41 ± 5.38 post-intervention (P < .05). In terms of quality of life, post-intervention scores were significantly better than those in the CG, indicating a positive shift. Physical capacity, measured by average walking distance, rose from 337.76 ± 23.87 m to 462.53 ± 26.28 m in the intervention group (P < .05). Regarding complication rates, there were no cases of myocardial infarction or sudden cardiac death in the intervention group, with only one case of arrhythmia, reflecting a notably lower complication rate compared to the CG (P < .05). These results suggest that continuity of care may play a key role in reducing adverse outcomes. The implementation of a continuity of care model for patients with CHF significantly improves their ability to manage their condition, enhances their overall quality of life, and contributes to better clinical outcomes. These findings emphasize the necessity of incorporating continuous care strategies into the standard management of CHF, offering important guidance for nursing professionals.

1. Introduction

Heart failure (HF), as an essential public health issue on a global scale, has an increasing prevalence year by year and has become a chronic disease with a profound influence on the quality of life (QoL) of patients.^[1] As a clinical manifestation of severe decline in cardiac pumping function, the treatment and management of HF pose great challenges to the medical system, while also exacerbating the economic burden on patients.^[2] The significant decrease in the QoL of patients, as well as the high recurrence rate and readmission rate, all reveal the urgent need for continuous care of this disease.^[3] In recent years, the role of continuity of care in chronic disease management has been increasingly valued, with the goal of providing patients with continuous and comprehensive medical and psychosocial support. In the field of HF treatment, continuity of care has been partially proven to effectively reduce readmission rates and improve QoL for participants.^[4,5] However, there is no consensus in the academic community on the specific intervention measures, implementation methods, duration, and quantitative evaluation of effectiveness of continuity of care, and research results are also fragile, making it difficult to support widespread clinical applications. There are many limitations in the methodology of existing research, such as small sample size, inadequate research design, and single evaluation indicators, which may lead to doubts about the reliability and universality of research conclusions. In addition, the applicability and effectiveness of continuity of care vary greatly among patient groups from different cultural backgrounds and health systems, which also limits its widespread promotion. In view of this, exploring continuity of care models and their therapeutic effects for specific populations has become a major trend in current research. On the grounds of the concepts of precision medicine and personalized treatment, this study aims to integrate existing evidence and adopt a retrospective controlled study design combined with multidimensional evaluation indicators to obtain more reliable and comprehensive research results. By analyzing the effects of structured continuity nursing interventions on patients with chronic heart failure (CHF) (in terms of physiological, psychological, and QoL outcomes) the study seeks to provide more refined and personalized nursing strategies for the comprehensive management of HF. This approach may contribute positively to improving patient health, enhancing quality of life, and reducing the burden on the healthcare system.

2. Materials and methods

2.1. General information

This study was approved by the Ethics Committee of Huanggang Central Hospital. It is a retrospective controlled study based on the clinical records of 90 patients with CHF who were admitted to the cardiology department of our hospital between January and September 2023. To reduce selection bias and ensure comparability between groups, propensity score matching was employed to allocate participants into an experimental group (EG) and a control group (CG), with 45 patients in each group after matching. The EG received continuity of care, while the CG received routine care. In the EG, there were 23 male patients and 22 female patients, aged 51 to 69 years, with an average age of (61.41 ± 2.13) years. The disease course was 0.5 to 8 years, with an average course of (3.88 ± 0.97) years. There were 21 New York Heart Association (NYHA) grade II patients, 13 grade III patients, and 9 grade IV patients. In the CG, there were 24 male patients and 21 female patients, aged 52 to 71 years, with an average age of (60.37 ± 1.86) years and a disease course of 0.5 to 7.5 years and an average disease course of (3.92 ± 1.02) years. There were 22 NYHA grade II patients, 14 grade III patients, and 8 grade IV patients. There was no statistically significant difference in the baseline characteristics between the 2 groups (P > .05), indicating comparability. The inclusion criteria for patients are as follows: (1) diagnosed as CHF in terms of the American Heart Association HF Diagnosis and Treatment Guidelines, with a clinical classification of NYHA II to IV. (2) Between the ages of 40 and 80. (3) The course of the disease exceeds 6 months. (4) Be able to comprehend the research content and sign an informed consent form. The exclusion criteria for patients are as follows: severe liver or kidney dysfunction, that is, liver function testing or blood creatinine levels exceeding the normal range by >3 times. There have been significant cardiovascular events in the past 3 months, such as acute myocardial infarction or stroke. Chronic infectious diseases or active malignant tumors. Has participated in other HF treatment studies that may affect the results of this study. History of cardiac surgery or other major systemic diseases that may affect the diagnosis of HF. The general information of the patient is showcased in Table 1.

Table 1.

General information of participants.

Group	Experimental group (n = 45)	Control group (n = 45)	t	P
Gender (male/female)	23/22	24/21	/	/
NYHA heart function grade II	21	22	/	/
NYHA heart function grade III	13	14	/	/
NYHA heart function grade IV	9	8	/	/
Age (yr)	61.41 ± 2.13	60.37 ± 1.86	2.4671	.0156
Course of disease (yr)	3.88 ± 0.97	3.92 ± 1.02	0.1906	.8493

NYHA = New York Heart Association.

2.2. Research methods and observation indicators

2.2.1. Research method

The CG patients received routine nursing interventions that included standard HF treatment guidelines, including medication treatment, lifestyle education, and standard procedures for monitoring heart function. Drug therapy follows the current guidelines for the treatment of HF, including diuretics, angiotensin-converting enzyme inhibitors, β-receptor blockers, and other drug treatment options that may be added on the grounds of the patient’s specific condition. Lifestyle education mainly focuses on dietary adjustments, such as limiting salt intake, managing weight, and engaging in moderate physical activity. The program for monitoring cardiac function includes regular cardiac function assessments, such as echocardiography and electrocardiogram examinations.

In addition to receiving the same routine care as the CG, the EG patients will also receive a series of structured continuity of care measures. This is to provide more comprehensive support for strengthening the long-term health status and QoL of patients. Specific continuity of care interventions include: forming nursing teams. Organize a nursing team consisting of one cardiologist, nurse, pharmacist, nutritionist, and mental health professional each to regularly evaluate the patient’s treatment plan and provide collaborative and consistent nursing services. Personalized health education. Develop personalized health education plans on the grounds of the specific condition, cognitive level, and educational background of each patient. The content includes the pathophysiology of HF, disease monitoring, medication knowledge, the importance of diet and exercise, and how to identify early signs of disease deterioration. Psychological and social support. Provide psychological assessment and necessary psychological intervention, including assessment of anxiety and depression, as well as training in psychological support and stress management skills. Drug management. Regularly evaluate the patient’s medication treatment plan to ensure rational use of medication and adherence to medical practices. Pharmacology professionals will regularly review patient prescriptions, adjust medication doses, and provide medication education to patients to ensure they understand the effects, side effects, and correct usage of drugs. Regular tracking and monitoring. Through regular outpatient follow-up, remote monitoring, and telephone support, closely monitor the health status of patients and adjust treatment plans in a timely manner. This includes monitoring the patient’s weight, blood pressure, heart rate, and symptoms to evaluate treatment effectiveness and the patient’s self-management ability. Promote self-management. Encourage patients to participate in self-management activities, such as self-monitoring of heart function and symptoms, self-regulation of lifestyle, etc. Provide necessary tools and resources, such as HF diaries, self-monitoring devices, etc, to promote active patient participation.

2.2.2. Outcome measures

To evaluate the efficacy of continuity of care measures, this study used the following observation indicators: physiological indicators, including the results of the 6-minute walk test (6MWT), self-efficacy, and left ventricular ejection fraction (LVEF). QoL assessment, assessed using the Minnesota HF QoL Scale (MLHFQ) score. Negative emotion assessment, using the Self Rating Depression and Anxiety Scale (such as the Hamilton Depression Scale [HAMD] and the Hamilton Anxiety Scale [HAMA]) to assess the patient’s mental health status. The incidence of complications, including cardiovascular complications.

In addition, to reduce detection bias, outcome assessments such as self-management scores, quality of life, and psychological scales were based on standardized and validated tools. Whenever possible, data collection and scoring were performed by researchers who were not involved in the intervention process, and objective clinical outcomes (e.g., LVEF, 6MWT, and complications) were extracted from the hospital’s electronic medical records.

2.2.3. Statistics

The study used SPSS 22.0 statistical software package (IBM Corp., Armonk) for data analysis. For quantitative data, if it conforms to a normal distribution, mean and standard deviation ($\overline{x}\pm s$) are utilized for representing it, and independent sample t tests are utilized for comparing the differences between the EG and the CG. If the data distribution does not follow a normal distribution, the median and quartile are used to represent it, and a nonparametric Mann–Whitney U test is utilized for comparing the differences among the participants. For qualitative data, frequency and percentage (%) are used to represent and Chi square test is utilized for comparing the proportional differences among the participants. P > .05 indicates no statistically standard deviation (SD) and comparability. A statistically significant difference was observed when P < .05.

There were no cases of loss to follow-up, dropout, or patient withdrawal due to severe complications or death during the observation period. Missing data accounted for <5% of the total dataset and were handled using mean imputation for continuous variables and mode imputation for categorical variables. A sensitivity analysis was also performed to confirm that the imputation method did not materially affect the study outcomes. These measures were taken to ensure data integrity and enhance the credibility of the findings.

3. Experimental result

3.1. Comparison of self-management abilities among the EG and the CG

To verify the impact of continuity of care measures on the self-management capability of patients with CHF, a self-management scale was used for evaluation in the study. The scale includes self-care ability, self-responsibility, and self-concept. The comparison results between the EG and the CG are shown in Table 2.

Table 2.

Changes in self-management scores before and after intervention.

Group	Self-care agency		Self-responsibility		Self-conception
	Before intervention	After intervention	Before intervention	After intervention	Before intervention	After intervention
Experimental group (n = 45)	73.39 ± 4.02	89.41 ± 5.38	70.73 ± 4.67	90.37 ± 5.73	72.14 ± 4.93	89.34 ± 5.73
Control group (n = 45)	73.42 ± 3.94	76.47 ± 3.26	70.77 ± 4.66	73.21 ± 3.71	71.92 ± 5.07	74.26 ± 3.32
t	0.0358	13.7990	0.0407	16.8634	0.2087	15.2755
P	.9716	.0000	.9676	.0000	.8352	.0000

Table 2 shows that before intervention, the SD did not exist in the scores of self-care ability, self-responsibility, and self-concept among the EG and the CG, with P-values >.05. There was no statistically significant difference in self-management ability between the 2 groups before the intervention, indicating comparability. After intervention, the scores of the EG on these 3 indicators significantly increased, from 73.39 ± 4.02 to 89.41 ± 5.38, 70.73 ± 4.67 to 90.37 ± 5.73, and 72.14 ± 4.93 to 89.34 ± 5.73, respectively, with P values <.05, demonstrating statistically SDs. This indicates that continuity of care measures significantly enhance the self-management ability of patients with CHF.

3.2. Comparison of MLHFQ among the participants

To evaluate the impact of continuity of care measures on the QoL of participants with CHF, the MLHFQ scale was used to score the participants. The MLHFQ scale is a widely used QoL assessment tool for participants with HF, which includes 3 dimensions: physical activity, emotion, and symptoms, and can comprehensively reflect changes in the QoL of participants. The comparison results are shown in Fig. 1.

Figure 1.

(A and B) Comparison of QoL between the EG and the CG. CG = control group, EG = experimental group, QoL = quality of life.

Figure 1A showcases that after intervention, the scores of physical activity, emotion, and symptoms in the CG were significantly reduced. Figure 1B showcases that the scores of the EG in the 3 dimensions also went down after intervention, and the decrease was markedly more excellent than the CG. Meanwhile, through t test calculations, it was found that the EG and the CG had a P > .05 before intervention, and the statistically SD exists, indicating comparability. After intervention, P < .05, there was a SD among the participants. The continuity of care measures has a positive impact on the overall health status and QoL of patients.

3.3. Comparison of negative emotion scores among the participants

In the development of CHF patients, negative emotions, which can possess a serious influence on their mental health and QoL. Therefore, this study evaluated the psychological status of the participants using HAMD and HAMA before intervention, 1 month after intervention, and 2 months after intervention, to further reveal the positive effects of continuity of care measures on the overall health status and QoL of participants. The comparison results of the HAMD scale are showcased in Table 3.

Table 3.

HAMD of CG and EG.

Group	Before intervention	Intervention for 1 month	Intervention for 2 months
Experimental group (n = 45)	57.04 ± 3.23	50.68 ± 3.07	41.46 ± 1.83
Control group (n = 45)	56.92 ± 3.54	54.36 ± 2.99	52.15 ± 2.94
t	0.1679	5.7604	20.7076
P	.8670	.0000	.0000

CG = control group, EG = experimental group, HAMD = Hamilton Depression Scale.

Table 3 shows that before intervention, with a P-value >.05, the statistically SD did not exist in HAMD scores between the EG and the CG, indicating comparability. After 1 month and 2 months of intervention, the P-values were both <.05, and the difference in HAMD scores among the participants possessed statistical significance. This indicates that the EG showed significant improvement in depressive symptoms after receiving continuity of care. The comparison results of the HAMA scale are shown in Fig. 2.

Figure 2.

Comparison of HAMA scales between EG and CG. CG = control group, EG = experimental group, HAMA = Hamilton Anxiety Scale.

Figure 2 showcases that the HAMA scores of the EG and the CG show a decreasing trend with increasing intervention duration. According to the t test calculation, the statistically SD did not exist in HAMA scores among the participants before intervention (P > .05), indicating comparability. After 1 and 2 months of intervention, the HAMA score of the EG was markedly below the CG, and the P-values were all <.05. This demonstrates that the anxiety symptoms of the EG patients have significantly improved after receiving continuity of care. The above conclusion proves that continuity of care measures can effectively alleviate negative emotions in patients.

3.4. Comparison of physiological indicators between the EG and the CG

To comprehensively evaluate the effectiveness of continuity of care measures, a comparative analysis was conducted on the physiological indicators of the subjects. These physiological indicators include 6MWT, self-efficacy, and left heart ejection fraction, which can reflect the patient’s cardiac function and daily activity ability. 6MWT is a simple exercise endurance test widely used to evaluate heart function and physical endurance in patients with HF. This test reflects the patient’s exercise ability and cardiovascular health status by measuring the maximum distance they can walk within 6 minutes. Therefore, this study considers 6MWT as an important observational indicator. It tests patients before intervention, 1 month after intervention, and 2 months after intervention to quantitatively evaluate and compare the physical function changes of the EG and the CG after receiving different nursing interventions. The results are showcased in Table 4.

Table 4.

Comparison of 6MWT between EG and CG (m).

Group	Before intervention	Intervention for 1 month	Intervention for 2 months
Experimental group (n = 45)	337.76 ± 23.87	397.48 ± 24.46	462.53 ± 26.28
Control group (n = 45)	337.49 ± 23.83	363.97 ± 24.41	417.78 ± 26.27
t	0.0537	6.5051	8.0787
P	.9573	.0000	.0000

6MWT = 6-minute walk test, CG = control group, EG = experimental group.

Table 4 shows that before intervention, the 6MWT results of the EG were 337.76 ± 23.87 m, while the 6MWT results of the CG were 337.49 ± 23.83, P > .05, demonstrating that the difference among the participants did not possessed statistical significance and comparable. After 1 month and 2 months of intervention, the 6MWT results of the EG exceeded the CG, and there was a SD among the participants (P < .05). These results indicate that patients in the EG who received continuity of care showed significant improvements in cardiac function and physical endurance, proving its effectiveness in supporting patients in physical activity and enhancing cardiac function. Self-efficacy refers to an individual’s level of belief and confidence in being able to complete a task or achieve a certain goal. The higher the score, the stronger the self-efficacy, as showcased in Table 5.

Table 5.

Comparison of self-efficacy among the EG and the CG.

Group	Before intervention	Intervention for 1 month	Intervention for 2 months
Experimental group (n = 45)	23.45 ± 3.52	27.68 ± 4.19	31.53 ± 6.17
Control group (n = 45)	23.52 ± 3.24	24.97 ± 3.54	26.79 ± 5.92
t	0.0982	3.3142	3.7186
P	.9220	.0013	.0003

CG = control group, EG = experimental group.

Table 5 shows the SD did not exist in GSES scores between the EG and the CG before intervention (P > .05), indicating that the 2 groups were comparable in terms of initial self-efficacy levels. After 2 months of intervention, the self-efficacy score of the EG markedly exceeded the CG, and this difference possessed statistical significance (P values were all <.05). This demonstrates that the EG of patients achieved significant improvement in self-management ability and confidence in disease control by receiving continuity of care intervention. The enhancement of self-efficacy has played a positive role in the self-management and long-term health maintenance of patients with CHF. LVEF is an essential indicator for evaluating cardiac function, and its decrease is usually positively correlated with the severity of HF. The study compared the left ventricular ejection fraction of patients in the EG and CG before intervention, 1 month after intervention, and 2 months after intervention through echocardiography. The results are shown in Fig. 3.

Figure 3.

(A and B) Comparison of LVEF between the EG and the CG. CG = control group, EG = experimental group, LVEF = left ventricular ejection fraction.

Figure 3 showcases that before intervention, a P-value >.05 demonstrates that the statistically SD did not exist in LVEF among the participants, indicating comparability. As the intervention progressed, the LVEF of the EG increased to 55.63 ± 3.23 and 59.89 ± 5.57 after 1 and 2 months, respectively, while the LVEF of the CG increased to 53.89 ± 3.67 and 55.25 ± 5.21. The improvement of LVEF in the EG after intervention markedly exceeded that in the CG, and the P-values were all <.05. The above results indicate that continuity of care has a positive impact on improving cardiac function.

3.5. Comparison of prognostic complications among the participants

The occurrence of complications is one of the important prognostic indicators for CHF, which not only affects the QoL of patients, but also increases their readmission rate and medical costs. Therefore, through retrospective analysis, the study collected data on 3 complications of myocardial infarction, arrhythmia, and sudden cardiac death in the participants within 3 months after intervention. This is for estimating and comparing the long-term effects of continuity of care measures, as showcased in Table 6.

Table 6.

Comparison of prognostic complications among the participants [n (%)]

Group	n	Myocardial infarct	Arrhythmias	Sudden cardiac death	Total
Experimental group	45	0	1 (2.22)	0	1 (2.22)
Control group	45	2 (4.44)	3 (6.67)	2 (4.44)	7 (15.56)
χ 2	/	/	/	/	4.9390
P	/	/	/	/	.0263

Table 6 shows that the number of myocardial infarction and sudden cardiac death events in the EG was 0, and the number of arrhythmia events was 1 (2.22%). The total number of complications in the EG within 3 months after intervention was significantly lower than that in the CG. By calculating the Chi square value to be 4.9390 and the P-value to be .0263, it indicates that the difference in the incidence of complications among the participants possesses statistical significance (P < .05). This means that continuity of care measures can help decrease the risk of complications in patients with CHF.

3.6. Comparison of nursing satisfaction among the participants

In medical care, patient satisfaction is one of the important indicators for measuring nursing quality and effectiveness. Satisfaction not only reflects the personal feelings and evaluations of patients towards nursing services, but also is a key factor for medical institutions to improve services, enhance patient compliance, and promote health outcomes. Therefore, the study compared the nursing satisfaction of the participants, and the results are showcased in Table 7.

Table 7.

Comparison of prognostic complications among the participants [n (%)]

Group	n	Very satisfied	Relatively satisfied	Dissatisfied	Satisfaction
Experimental group	45	28 (62.2)	14 (31.1)	3 (6.7)	42 (93.3)
Control group	45	14 (31.1)	17 (37.8)	14 (31.1)	31 (68.9)
χ 2	/	/	/	/	8.7752
P	/	/	/	/	.0031

Table 7 shows that 62.2% of patients in the EG were very satisfied, 31.1% were relatively satisfied, and only 6.7% were dissatisfied. The satisfaction of the EG markedly exceeded the CG. The chi square value calculated through chi square test is 8.7752, with a P-value of .0031, indicating a statistically SD in nursing satisfaction among the participants (P < .05). This means that the EG of patients who implemented continuity of care measures had a higher overall satisfaction with nursing services.

4. Discussion

CHF is a heart disease characterized by the inability of the heart to effectively pump blood, leading to hypoxia and circulatory disorders in various organs of the body. Its causes are diverse, including heart valve disease, cardiomyopathy, and arrhythmia. As the disease progresses, patients may experience repeated acute exacerbations, which not only damage their QoL but also increase the burden on medical resources. The study by Bakitas et al suggests that the causes of CHF are usually associated with ventricular remodeling, myocardial cell dysfunction, and activation of the neuroendocrine system. This condition can be attributed to underlying conditions such as coronary artery disease, hypertension, valvular disease, cardiomyopathy, or arrhythmia, as well as genetic, environmental, and lifestyle factors. Zou et al’s study suggests that ventricular remodeling in patients with HF is a compensatory response to myocardial injury, but in the long term, it can lead to further reduction in cardiac pumping efficiency. And neuroendocrine activation, especially excessive activation of the sympathetic nervous system and renin angiotensin aldosterone system, is also a factor in the development of CHF.^[6] The study by scholars such as McDonagh et al suggests that the levels of inflammatory factors in patients with HF increase, suggesting a possible connection between systemic inflammatory response caused by myocardial injury and the development of CHF.^[7] Researchers such as Tsutsui et al believe that dysfunction of endothelial cells may lead to abnormal vasomotor function, affecting local blood flow status, and thus participating in the causal chain of CHF.^[8] Regarding the care of patients with CHF, Chan et al’s study suggests that continuous and comprehensive nursing interventions can improve self-management ability, reduce readmission rates, and improve QoL for patients with CHF.^[9] Singh et al believe that for patients with CHF, channels and referral systems for palliative treatment resources are crucial.^[10] Therefore, implementing personalized and structured interventions for patients with CHF can significantly enhance their health status, thereby enhancing their QoL and reducing the burden on the healthcare system.

Continuing care, as a long-term comprehensive management nursing model for patients with chronic diseases, is increasingly receiving attention in the treatment and management of CHF.^[11–13] However, there is no consensus on the quantitative evaluation of specific intervention measures, implementation methods, duration, and effectiveness of continuity of care.^[14,15] In this context, the study explored the application effect of continuity of care in patients with CHF. It compares the therapeutic effects of implementing structured continuity of care measures with conventional care in patients with CHF through randomized controlled trials. The outcomes showcased that the EG showed essential enhancement in self-management ability, QoL, negative emotions, and physiological indicators after receiving continuity of care. Specifically, after receiving continuity of care, the scores of self-care ability, sense of responsibility, and self-concept in the EG increased from 73.39 ± 4.02, 70.73 ± 4.67, and 72.14 ± 4.93 before intervention to 89.41 ± 5.38, 90.37 ± 5.73, and 89.34 ± 5.73 after intervention. The difference possessed statistical significance relative to the CG (P < .05), proving the effectiveness of continuity of care in improving patient self-management. The score of the EG in MLHFQ significantly decreased relative to the CG after intervention, indicating an enhancement in the QoL of patients and a positive impact of continuity of care on the QoL of patients with CHF. Additionally, the performance of the EG in 6MWT was also better than that of the CG. After intervention, it increased from 337.76 ± 23.87 m to 462.53 ± 26.28 m, while the CG only increased from 337.49 ± 23.83 m to 417.78 ± 26.27 m. The difference between groups was statistically significant (P < .05), suggesting that continuity of care improved patients’ physical and cardiac functions. Meanwhile, the study also pointed out that continuity of care can help reduce negative emotions in patients. After intervention, the HAMD and HAMA scores of the EG were markedly below the CG, indicating an improvement in the mental health status of patients.

5. Limitations

Despite the positive findings, this study has several limitations that should be acknowledged. First, as a retrospective controlled study conducted in a single center, the generalizability of the results may be limited. Multicenter studies with larger sample sizes are needed to validate these findings. Second, although propensity score matching was used to balance baseline characteristics, potential unmeasured confounding factors may still exist. Third, the duration of follow-up was relatively short, and long-term effects of continuity of care on clinical outcomes such as mortality and rehospitalization rates remain to be investigated. Finally, some outcome assessments relied on self-reported questionnaires, which may be subject to response bias. Future prospective studies with longer follow-up periods and objective outcome measures are warranted to strengthen the evidence.

6. Conclusion

In summary, continuity of care has a positive impact on improving self-management ability, quality of life, psychological well-being, and physical health in patients with CHF, while also reducing the risk of complications and enhancing patient satisfaction. These findings provide valuable evidence to support the integration of continuity of care into the comprehensive management of heart failure. Moreover, this nursing model shows promising potential for broader application in primary care and grassroots community follow-up management. By offering ongoing support and early intervention, it may help lower hospital readmission rates and reduce long-term healthcare burdens. Future research should further explore its scalability, cost-effectiveness, and adaptability across various clinical contexts, to strengthen its practical value and promote wider adoption in chronic disease care.

Author contributions

Conceptualization: Pengjun Wang, Yanwen Zhou, Li Wang, Mei Lin.

Data curation: Pengjun Wang, Yanwen Zhou, Li Wang, Rong Liu, Fei Qian, Mei Lin.

Formal analysis: Pengjun Wang, Li Wang, Fei Qian, Mei Lin.

Validation: Rong Liu, Mei Lin.

Visualization: Pengjun Wang, Li Wang, Rong Liu, Mei Lin.

Writing – original draft: Pengjun Wang, Yanwen Zhou, Fei Qian, Mei Lin.

Writing – review & editing: Pengjun Wang.