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American Journal of  Medical 
Science and Innovation (AJMSI) 

An Outcomes Comparison between Nurse Practitioners and Primary Care Physicians in 
Quality of  Life in Older Patients with Congestive Heart Failure

Dr. Mohammad I. D. Ibrahim1*, Shannon1, McCrory-Churchill1

Volume 3 Issue 2, Year 2024
ISSN: 2836-8509 (Online)

DOI: https://doi.org/10.54536/ajmsi.v3i2.2935
https://journals.e-palli.com/home/index.php/ajmsi

Article Information ABSTRACT

Received: July 31, 2024

Accepted: September 02, 2024

Published: September 06, 2024

Chronic heart failure (CHF) is a prevalent cardiovascular disease affecting patients’ 
outcomes and quality of  life. Nurse Practitioners (NPs) and Primary Care Physicians (PCPs) 
are renowned for their positive impact on patient satisfaction and quality of  life. However, 
the extent to which they achieve these results still needs to be explored. The study aimed 
to determine if  the disease course of  older CHF patients under NPs and PCPs remained 
consistent, focusing on patients’ satisfaction levels in NP care compared to those in PCP 
care in primary care settings. A comparative observational design was used to recruit CHF 
patients aged 65 and above from nursing homes in Ontario, Canada. Subjects completed 
the 12-question questionnaire to gauge satisfaction and overall quality of  life. Results were 
analysed using ANOVA as outcome indicators of  the NPs and PCPs were to be compared. 
Findings showed no significant variation in quality of  life score measurement between NP 
and PCP patients. Both (NPs and PCPs) were revealed to be equally strong in meeting the 
demanding CHF patients’ needs. The study emphasises the crucial role of  Nurse Practitioners 
(NPs) in multidisciplinary Team CHF care, highlighting their role in improving patient 
outcomes and healthcare delivery. It acknowledges the limitations of  the measurement study, 
such as sample size, and contributes to ongoing debates on healthcare delivery.

Keywords
Congestive Heart Failure, Nurse 
Practitioner, Primary Care 
Physicians, Quality of  Life, 
Patient Satisfaction

1 D’Youville University, Buffalo, NY, USA
* Corresponding author’s e-mail: abkasm2009@yahoo.com

INTRODUCTION
Congestive heart failure (CHF) has emerged as one of  
the most pressing public health issues all over the world, 
causing a major shift in the approach of  health care 
systems, enhancing the morbidity and mortality rates, and 
deteriorating the quality of  life of  the patients. The entire 
of  Canada houses up to 750 thousand people suffering 
from CHF, an array of  numbers that demonstrates 
this problem’s prevalence. Congestive Heart Failure 
survivability rates are anticipated to rise significantly over 
the next ten years, along with the related hospitalisation 
figures. Thus, this stark reality of  CHF resilience proves 
its critical role in defeating this condition as it burdens 
healthcare services and incurs extra costs (Canada, 2022).
The CHF problem is not restricted to statistics only but 
extends to other aspects, such as the impact on patient’s 
lives and their families. Heart failure has a much wider 
significance as, according to the report of  the Heart 
and Stroke Foundation of  Canada, nearly one-third of  
the population across Canada is, in one way or another, 
either directly or indirectly connected to the symptoms 
of  heart failure. Also, the complications that result in 
rehospitalisation are high among patients older than 65 years, 
especially considering it is both CHF patients and healthcare 
providers who endure the challenges (Canada, 2022).
Through the years, primary care physicians (PCPs) have 
proved to be a core piece of  care in treating CHF patients, 
acting as the first step in receiving care (Hung et al., 2022). 
Nevertheless, accompanied by the reconfiguration of  
the medical model and the progress of  development, 
the role of  nurse practitioners has become more in 

demand. Nurse Practitioners (NPs) can perform the 
following roles as advanced practice registered nurses 
after their registered nurse spare: assess patients, provide 
treatments, order diagnostic tests, and educate them 
about their diseases (King-Dailey et al., 2022). This 
merged sense of  jurisdiction makes NPs star members of  
the interdisciplinary care coordination for CHF patients.
Even if  NPs have been steadily welcoming health systems, 
uncertainty remains concerning their performance in 
occupying what PCPs should have occupied in delivering 
care to CHF patients. Investigations show that NPs help 
achieve positive patient results, boost patients’ satisfaction 
and decrease healthcare expenses (O’Toole et al., 2019). 
Studies are required to elaborate on NPs’ supremacy or 
equality to PCPs in this field.
As demonstrated by a prior study, outcomes of  the 
treatment and the patients with CHF show few differences 
in the quality between nurse practitioners and primary 
care physicians (Baecker et al., 2020). Even though the 
data indicates incontrovertibly that a Nurse Practitioner 
(NP) is as capable as a Physician to treat a patient, several 
states continue to dictate how their NPs should conduct 
their operations, especially prescriptions, where they feel 
they are the only ones who should be doing it (Muench 
et al., 2019).
NPs have specialised training in education, therapy, 
and advocacy (King-Dailey et al., 2022). Nurse-led, 
structured instruction during hospitalisation and after 
discharge improves self-management abilities in patients 
with chronic heart failure (Cui et al., 2019). NPs have 
provided low-priced, high-quality treatment for nearly 



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half  a century, and the data is indisputable (Kuo et al., 
2018). More patients are satisfied with their care, fewer 
unnecessary emergency department visits are made, 
and fewer hospitalisations are required among patients 
handled by NPs in a clinic administered by congestive 
heart failure. There is much overlap between the roles 
of  NPs and physicians, even though they have different 
levels of  education and licensing (Jiang et al., 2020).
NPs and physicians work together in over half  of  the 
inpatient medical services provided by the Veterans 
Health Administration, with little distinction between 
their duties and how administrators view their ability to 
provide care (Jiang et al., 2020). However, there needs 
to be more clarity of  the relative patient’s care between 
Physician and NPs over who does what in the healthcare 
system. Lewis’s (2021) study revealed that a patient 
education booklet based on scientific data helps manage 
congestive heart failure, especially when paired with 
targeted visits from a nurse practitioner, CHF patients 
benefitted from the NP visits (Lewis, 2021). Another 
study showed improved results, such as reducing CHF 
hospital readmissions and increasing quality of  life (QoL) 
through a nurse-led intervention program for patients 
with CHF (Ortiz-Bautista et al., 2019). 
In addition, King Dailey et al. (2022) in their study state 
that nurse practitioners (NPs) focus on health promotion, 
illness prevention, and patient satisfaction as they 
diagnose, treat patients, prescribe medicine, and refer 
and manage acute and chronic disorders (King-Dailey et 
al., 2022). However, in their study, Gerlier et al. (2023) 
emphasise that there needs to be more clarity between 
Physicians and NPs over who does what in the healthcare 
system. According to Gerlier et al. (2023), more nurse 
practitioners than physicians believe that NPs should be 
able to admit patients to hospitals and receive equivalent 
pay as physicians for performing the same clinical 
services. As a result, NPs and physicians contribute to 
an equal level of  health care in primary care settings for 
CHF patients (Gerlier et al., 2023).
This study aims to fill a knowledge gap by comparing 
the role of  Nurse Practitioners (NPs) and Primary Care 
Practitioners (PCP) in achieving better lifestyles and 
satisfaction for older chronic heart failure (CHF) patients 
in primary healthcare settings. The study systematically 
analyses patient satisfaction surveys to adjust CHF 
management and inform NPs’ benefits. The results can 
guide national health policies and processes, enabling 
competent NPs to work alongside multidisciplinary 
care teams for CHF patients and maximise treatment 
outcomes. The study also advances the importance of  
NPs in dealing with comprehensive CHF patient issues 
and optimises healthcare delivery.

METHODOLOGY
Study Design
This study adopted a comparative observational method 

to gauge the efficacy of  Nurse Practitioners (NPs) and 
Primary Care Physicians (PCPs) in assessing the quality 
of  life and satisfaction of  older CHF congestive patients 
in primary care.

Sample Selection and Recruitment Procedure
Using stratified and convenience sampling, participants 
were chosen from the Niagara Falls region, Ontario, 
Canada, nursing homes. A party of  subjects was included 
by the criteria in which participants who had Diligent 
Congestive Heart Failure (CHF), aged 65 years and above, 
could understand the study protocol and give informed 
consent. Recruitment was carried out through personal 
interactions with those who had to meet the eligibility 
criteria: individuals in the nursing home facility.

Questionnaire Survey
Participants who gave written consent were given a 
12-question survey to measure satisfaction and quality of  
life. In-person distribution of  the surveys carried out by 
impartial office workers is the method office staff  used. 
This ensures that all respondents are unaffected by other 
staff  in providing accurate responses.

Data Collection
While the survey consisted of  12 questions designed to 
assess participants’ satisfaction level and quality of  life, 
data collection was among the primary objectives of  this 
study. Only those patients aged 65 years and above living 
in nursing homes in the Niagara Falls region, Ontario, 
who described CHF were enrolled in the study group. 
Purposive and easy sampling methods were applied 
to administer the pool of  respondents who could 
comprehend the study information and offer informed 
consent.

Statistical Analysis
Statistical analysis was conducted using the Statistical 
Package for the Social Sciences (IBM SPSS Statistics 21). 
A one-way repeated measures ANOVA was performed 
to compare nurse practitioners NPs and PCPs in terms 
of  quality-of-life satisfaction in older patients with CHF. 
Statistical significance was set at p < 0.05

RESULTS
Table 1 presents descriptive statistics for different 
levels of  the subject variable. In the “V. poor” category, 
participants in the NP condition had a mean rating of  
0.6667 with a standard deviation of  0.98473. In contrast, 
those in the PCP condition had a mean rating of  0.2500 
with a standard deviation of  0.62158. The overall mean 
for this category was 0.4583. In the “Poor” category, 
participants in the NP condition had a mean rating of  
0.4167 with a standard deviation of  0.66856. In contrast, 
in the PCP condition, the mean rating was 0.2500 with a 
standard deviation of  0.45227.



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Table 2 presents the results of  multivariate tests assessing 
the effects of  factor1 on the dependent variable and its 
interaction with the subject variable. All four multivariate 
test statistics (Pillai’s Trace, Wilks’ Lambda, Hotelling’s 
Trace, and Roy’s Largest Root) yielded highly significant 
results (p <.001), indicating a significant overall effect 

of  factor 1 on the dependent variable. However, the 
interaction between factor 1 and the subject showed 
non-significant results (p-values of.477), suggesting no 
significant interaction between factor 1 and the subject 
on the dependent variable.

Table 1: Descriptive Statistics
Subject Mean Std. Deviation N

V.poor NP .6667 .98473 12
PCP .2500 .62158 12
Total .4583 .83297 24

Poor NP .4167 .66856 12
PCP .2500 .45227 12
Total .3333 .56466 24

Fair NP 1.6667 1.87487 12
PCP 2.0000 1.41421 12
Total 1.8333 1.63299 24

Good NP 11.8333 2.85509 12
PCP 11.5000 2.02260 12
Total 11.6667 2.42571 24

V.good NP 10.4167 3.84846 12
PCP 11.0000 2.73030 12
Total 10.7083 3.27678 24

Table 2: Multivariate Tests
Effect Value F Hypothesis df Error df Sig.
factor1 Pillai's Trace .993 632.149b 4.000 19.000 <.001

Wilks' Lambda .007 632.149b 4.000 19.000 <.001
Hotelling's Trace 133.084 632.149b 4.000 19.000 <.001
Roy's Largest Root 133.084 632.149b 4.000 19.000 <.001

factor1 * Subject Pillai's Trace .161 .912b 4.000 19.000 .477
Wilks' Lambda .839 .912b 4.000 19.000 .477
Hotelling's Trace .192 .912b 4.000 19.000 .477
Roy's Largest Root .192 .912b 4.000 19.000 .477

Table 3 presents the results of  tests assessing the 
significance of  factor 1 and its interaction with the subject 
variable on the dependent variable. The main effect of  
factor 1 is significant, with a variance of  3107.083 units. 
The F-test yielded a high factor 1ificant result under 
sphericity assumptions, confirming the main effect of  
factor 1. Greenhouse-Geisser, Huynh-Feldt, and Lower-
bound corrections confirmed the significance of  factor 

1’s main effect. The interaction between factor 1 and 
the subject was non-significant under all assumptions, 
indicating no significant interaction effect. The error 
term represents the variance within the factor1 variable, 
with substantial F-values under all assumptions. These 
findings provide insights into the main effect of  factor 
1 and its interaction with the subject on the dependent 
variable.

Table 3: Tests of  Within-Subjects Effects
Source Type III Sum of  

Squares
df Mean Square F

factor1 Sphericity Assumed 3107.083 4 776.771 147.850
Greenhouse-Geisser 3107.083 1.516 2049.299 147.850
Huynh-Feldt 3107.083 1.679 1850.787 147.850



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Lower-bound 3107.083 1.000 3107.083 147.850
factor1 * Subject Sphericity Assumed 4.583 4 1.146 .218

Greenhouse-Geisser 4.583 1.516 3.023 .218
Huynh-Feldt 4.583 1.679 2.730 .218
Lower-bound 4.583 1.000 4.583 .218

Error(factor1) Sphericity Assumed 462.333 88 5.254
Greenhouse-Geisser 462.333 33.356 13.861
Huynh-Feldt 462.333 36.933 12.518
Lower-bound 462.333 22.000 21.015

Table 4 presents the results of  tests of  within-subjects 
contrasts, evaluating linear, quadratic, cubic, and fourth-
order trends within the factor1 variable and their 
interactions with the Subject variable. The Type III Sum 
of  Squares indicates significant differences across all 
contrast types, indicating complex patterns of  change 
in the dependent variable across its levels. However, no 
significant interactions between the trends within factor1 
and the Subject variable were found, as indicated by non-

significant F-values for linear, quadratic, cubic, and fourth-
order trends (all p >.05). The error term represents the 
variance within the factor1 variable after accounting for 
other effects, showing significant F-values for all contrast 
types, indicating substantial variance within the factor1 
variable across all trends. These findings provide insights 
into the considerable trends within the factor1 variable 
and their interactions with the Subject on the dependent 
variable

Table 4: Tests of  Within-Subjects Contrasts
Source Type III Sum of  factor1 Squares df Mean Square F Sig.
factor1 Linear 2432.067 1 2432.067 763.092 <.001

Quadratic 76.190 1 76.190 8.072 .010
Cubic 370.017 1 370.017 63.738 <.001
Order 4 228.810 1 228.810 88.553 <.001

factor1 * Subject Linear 2.017 1 2.017 .633 .435
Quadratic .012 1 .012 .001 .972
Cubic 1.067 1 1.067 .184 .672
Order 4 1.488 1 1.488 .576 .456

Error(factor1) Linear 70.117 22 3.187
Quadratic 207.655 22 9.439
Cubic 127.717 22 5.805
Order 4 56.845 22 2.584

Table 5 presents the results of  tests of  between-subjects 
Effects, focusing on the Intercept and Subject variables. 
The Intercept row represents the overall mean across all 
subjects, with a Type III Sum of  Squares of  3000.000 
and 1 degree of  freedom. The p-value is not reported, 
and the Partial Eta Squared value is 1.000, indicating that 
the Intercept explains all the variance in the dependent 
variable. For the Subject variable, the Type III Sum of  
Squares is 0.000 with 1 degree of  freedom, indicating no 

significant effect. The p-value and Partial Eta Squared 
are also not reported, suggesting a lack of  significant 
impact. The Error term represents residual variance 
not accounted for by the Intercept or Subject variables, 
with a Type III Sum of  Squares for an Error of  0.000 
with 22 degrees of  freedom. In summary, neither the 
Subject variable nor any other between-subjects effects 
significantly contribute to the variance in the dependent 
variable.

Table 5: Tests of  Between-Subjects Effects
Source Type III Sum of  Squares df Mean Square F Sig. Partial Eta Squared
Intercept 3000.000 1 3000.000 - - 1.000
Subject .000 1 .000 - - -
Error .000 22 .000



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Table 6 shows the estimated marginal means for 
different levels of  factor 1, ranging from 1 to 5. For 
factor 1 level 1, the marginal Mean is 458, with a standard 
error of.168. The 95% confidence interval ranges from 
110 to 807. At level 2, the marginal mean is 333, with a 
standard error of.117. Moving to level 3, the marginal 
mean increases to 1.833, with a larger standard error 

of.339. For level 4, the marginal mean is 11.667, with a 
standard error of.505, and at level 5, the marginal mean 
is 10.708, with a larger standard error of.681. These 
estimates provide insights into the expected values of  
the dependent variable at each level of  factor 1, along 
with their associated standard errors and confidence 
intervals.

Table 6: Estimated Marginal Means
factor1 Mean Std. Error 95 Lower Bound % Confidence Interval Upper Bound
1 .458 .168 .110 .807
2 .333 .117 .092 .575
3 1.833 .339 1.130 2.536
4 11.667 .505 10.619 12.714
5 10.708 .681 9.296 12.121

Table 7: Pairwise Comparisons
(I) factor1 (J) factor1 Mean Difference  

(I-J)
Std. Error Sig. b 95% Confidence Interval for Differenceb

Lower Bound Upper Bound
1 2 .125 .223 .581 -.337 .587

3 -1.375* .365 .001 -2.131 -.619
4 -11.208* .584 <.001 -12.419 -9.998
5 -10.250* .702 <.001 -11.707 -8.793

2 1 -.125 .223 .581 -.587 .337
3 -1.500* .339 <.001 -2.202 -.798
4 -11.333* .506 <.001 -12.383 -10.284
5 -10.375* .723 <.001 -11.875 -8.875

3 1 1.375* .365 .001 .619 2.131
2 1.500* .339 <.001 .798 2.202
4 -9.833* .538 <.001 -10.948 -8.718
5 -8.875* .956 <.001 -10.857 -6.893

4 1 11.208* .584 <.001 9.998 12.419
2 11.333* .506 <.001 10.284 12.383
3 9.833* .538 <.001 8.718 10.948
5 .958 1.125 .403 -1.374 3.291

5 1 10.250* .702 <.001 8.793 11.707
2 10.375* .723 <.001 8.875 11.875
3 8.875* .956 <.001 6.893 10.857
4 -.958 1.125 .403 -3.291 1.374

Table 7 presents pairwise comparisons between different 
levels of  factor 1. The mean difference between level 1 and 
level 2 is 125, with a standard error of.223, which is not 
statistically significant. Level 1 is significantly lower than 
level 3, level 4, and level 5, with mean differences of  -1.375, 
-11.208, and -10.250, respectively. Comparing level 2 with 
other levels, level 2 is similar to level 1 but is significantly 

lower than levels 3, 4, and 5. Level 3 is considerably higher 
than levels 1 and 2 but lower than levels 4 and 5, with mean 
differences of  -9.833 and -8.875. Level 4 is significantly 
higher than levels 1, 2, and 3 but similar to level 5. These 
pairwise comparisons provide insights into the differences 
between each pair of  factor 1 levels, indicating where 
significant differences exist and their magnitude.

Table 8 presents the results of  univariate tests for the 
contrast factor. The sum of  squares is 2.776E-17 with 1 
degree of  freedom, resulting in a mean square of  2.776E-
17. The F-statistic is 172, and the associated significance 
value is.682, indicating that the observed variation is not 

statistically significant at the conventional alpha level 
of.05. The partial eta squared value, which represents the 
proportion of  variance explained by the contrast factor 
while controlling for other factors, is 008.



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DISCUSSION
Congestive heart failure (CHF), as one of  the major 
illnesses in the world, has taken a serious toll on the 
healthcare system, causing many complications and high 
costs. This experiment aimed to examine the efficiency of  
nurse practitioners (NPs) versus primary care physicians 
(PCPs) in terms of  the dependence on improving the 
quality of  life and the satisfaction of  older CHF patients 
in primary care institutions. Using the odds ratio and chi-
square test (χ2), we attempted to show the proficiency of  
NPs in charting and improving the management of  CHF 
along with their patient satisfaction experience.
Our findings are important for evaluating the effectiveness 
of  NPs and PCPs in the treatment of  patients with 
CHF. However, the outcomes underlined that NPs 
and PCPs share the common tasks of  addressing CHF 
complications, and no significant difference was observed 
in the satisfaction level concerning their quality of  life 
between the two classes. These articles regard this 
phenomenon preliminarily as the professional experience 
of  NP and PCP with the same level of  high-quality 
management of  chronic ailments like CHF of  similar 
effectiveness (Baecker et al., 2020).
The work, overall, assists in filling the gaps in the existing 
evidence-based literature on NP participation in CHF care 
by confirming that NPs are providers of  better quality 
care to CHF patients, thus integrating them into central 
care teams. Our study suggests that NPs can efficiently 
manage CHF patients in primary care contexts, which 
might be provided as an alternative to or complementary 
to the traditional care in which physicians lead. Thus, our 
project aims to corroborate these earlier findings, which 
concluded that patient outcomes improved when the 
intervention was nurse-led (Lowery et al., 2012).
For this reason, our study highlights the significance of  
specifying NP functions and duties and how physicians 
should be involved in healthcare delivery. Nevertheless, 
our findings emphasise the parallel roles of  NPs and 
physicians in patient care. The two groups give equal 
importance to the desired results in the case of  CHF 
management, patient satisfaction with treatment and 
response. A similar idea reiterates the comments that were 
made earlier that clear and consensus definitions of  the 
scopes of  practice for APRNs are vital, and collaboration 
between health workers is crucial (Norful et al., 2019).
Contrary to common expectations, our study concludes 
that people are more satisfied and feel better about 
quality of  life visiting either NP or PCP than in the 
cases reported in the previous study. Such things may be 
differentiated into parameters such as extended usage of  
digitised healthcare delivery models, improved patient 
education and information access and self-management 

approaches. In addition, our positive results point to the 
quality of  general healthcare and the aspect of  patient-
centred care programs (Barratt & Thomas, 2018).
This study also brings forward several recommendations 
to be the basis of  healthcare regulations and actions. 
First of  all, it demonstrates why the inclusion of  NPs 
in multidisciplinary CHF care is needed to measure great 
patient results and increase the effectiveness of  healthcare 
delivery. NPs have various skills useful in improving the 
integrity and access to top-notch care, including mostly 
underserved populations and patients in rural and remote 
areas. Additionally, our report audience is called upon to 
periodically conduct refresher courses and workshops for 
NPs to enable them to remain updated with evidence-
based care and more capable of  satisfying CHF patients’ 
changing needs (Forsyth et al., 2024).
Additionally, our study illustrates the determination to 
build contact and communication between NPs and 
Physicians to get the best in CHF management techniques. 
Healthcare establishments may achieve this integrated 
approach to care through the teamwork of  physicians 
and NPs. This would allow patients to be given the best 
comprehensive care. This supports multidisciplinary 
education and collaborative practice, which help 
practitioners of  the professions integrate. This improves 
healthcare for the patients and makes healthcare delivery 
efficient and effective (Schot et al., 2020).
Our results are valid with the study by Ruan et al. (2023), 
who focused more on the crucial role of  nurse-led 
interventions in treating chronic heart failure (CHF) 
patients. Lewis implemented a project involving a chosen 
group of  patients with CHF under the supervision of  
nurses and providing educational materials based on 
scientific evidence, leading to improved outcomes. 
Likewise, our study represents NPs’ role in improving the 
quality of  life and patient satisfaction, which implies that 
nurse-led management is highly important in optimising 
CHF management (Ruan et al., 2023).
Secondly, we have also found that our findings align 
with the study of  Norful et al. (2017), who showed how 
nurse practitioners (NP) play an effective role towards 
CHF patients, including the low-cost but high-quality 
provision of  health care. A report from the University of  
California-Kuo managed patients rated NP’s meditation 
as significantly satisfactory, with greater personalised 
care delivery, reduced emergency department visits, 
and hospitalisation rates. Along with other studies that 
showed similar findings, our study is another piece of  data 
highlighting NPs’ outstanding value to CHF management 
and primary care settings (Norful et al., 2017).
Alongside that, the study caters to the gap illuminated 
by Gigli & Gonzalez (2022) on the need for more 

Table 8: Univariate Tests
Sum of  Squares df Mean Square F Sig. Partial Eta  Squared
Contrast 2.776E-17 1 2.776E-17 .172 .682 .008
Error 3.553E-15 22 1.615E-16



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understanding of  the roles and responsibilities of  NPs 
and physicians within the healthcare industry. Gerlier et 
al. put forward the opinion that the scope of  practice 
should be well-defined, and NPs should be paid for their 
services similarly to all the other medical providers. The 
study, therefore, presents formal evidence suggesting the 
possibility of  NPs providing optimal care to the elderly 
with multiple chronic diseases of  the long-term type 
(Gigli & Gonzalez, 2022).
Our study forms part of  the evidence base for the growing 
number of  studies which endorse NPs in primary care 
settings for effective CHF management. Our analysis 
indicates that the quality of  patient care is equal for both 
NPs and PCPs in terms of  increased patient satisfaction 
and improved quality of  life, with the implication of  
increased involvement of  NPs in the CHF medical team 
and wider collaboration among healthcare professionals. 
That being said, it is equally necessary to keep improving 
the models of  care as provided in this role and integrate 
the input and support of  NPs to attain better patient care 
and a more comfortable experience for them in CHF 
management.

Limitations Future Implications
This study contains limitations, such as English-only 
questionnaires and the sample group picked in specific 
North American regions. Being an additional asset to a 
few countries is better if  those countries can access them. 
Still, there is a permanent physician shortage, and for an 
NP to bring safety and quality of  care through all the life 
stages, further study is needed. The patients may put their 
expectations on NPs and physicians differently, which 
could cause more trouble in patient satisfaction. Thus, 
a thorough study is required to identify the elements 
affecting satisfaction and the effort NPs need to use to 
be a part of  it.

CONCLUSION
In conclusion, this study shows empirically that 
compared to nurse practitioners (NP) and MCPs, patient 
age is a significant factor in propagating CHF among 
older patients. Findings indicate that CHF patients 
experience a mix of  symptoms, which care by both NPs 
and PCPs proves necessary and offers no differences 
in quality-of-life satisfaction. The study underlines that 
the multidisciplinary management of  CHF and the 
involvement of  NPs in such teams lead to better patient 
outcomes and increased healthcare quality. This study then 
gives examples of  NPs and physicians working together 
in unison to make the strategies employed in managing 
the problems of  CHF more effective. However, due to 
such limitations as a small sample size and examination 
of  only subjectively reported outcomes, the study can 
only furnish the initial and tentative data. For established 
results, future studies with bigger samples and different 
conditions will only be able to validate and give a bigger 
extent to the given results. In general, the study is a tool 
towards a common objective of  influencing the existing 

discussions in healthcare provision and primary care 
improvement.

REFERENCES
Baecker, A., Meyers, M., Koyama, S., Taitano, M., Watson, 

H., Machado, M., & Nguyen, H. Q. (2020). Evaluation 
of  a transitional care program after hospitalization 
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JAMA network open, 3(12), e2027410-e2027410. 

Barratt, J., & Thomas, N. (2018). Nurse practitioner 
consultations in primary health care: a case study-based 
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