Background
Healthcare providers globally face multiple pressures from financial, social, technological, political, and other sources. These pressures necessitate evaluating and enhancing healthcare quality to ensure consistent, high-standard service delivery. Adopting standardized healthcare accreditation and certification processes is a critical response to these needs, helping to regulate healthcare practices and improve patient safety and care quality [1, 2]. The Agency for Healthcare Research and Quality (AHRQ) emphasizes the importance of systematic evaluation and continuous improvement processes in healthcare, which are integral to achieving these goals [3].
Accreditation is a systematic evaluation process that helps healthcare organizations improve their services based on specific standards essential for quality improvement efforts [4]. Studies have shown that hospital accreditation can significantly enhance patient experience, underscoring the need for longitudinal evidence from diverse healthcare settings [4, 5].
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Since the 1980s, accreditation has become essential for inducing transformative changes in healthcare systems across approximately 70 countries. It involves systematic evaluations by accredited agencies like the joint commission international (JCI), which assess healthcare providers based on rigorous standards concerning their structure, operations, and care results [1, 6]. Achieving accreditation signifies meeting the highest international healthcare standards and serving as a global quality and safety stamp [7].
However, the impact of hospital accreditation on healthcare quality is not universally positive, and the literature presents mixed findings regarding its effectiveness. A study on the impact of accreditation in Malaysia revealed that while accreditation might enhance certain aspects of healthcare quality, such as reducing patient and family complaints about the high cost of care and alleviating fears among nurses regarding the reporting of incidences, it does not uniformly improve all safety results [8]. For instance, there were no significant differences in perceived overall patient safety, nosocomial infection rates, pressure ulcers, patient falls, medication errors, readmissions, or patient and family complaints between nurses working in accredited versus non-accredited hospitals [8]. These findings suggest that accreditation alone may not be sufficient to drive comprehensive quality improvements across all dimensions of patient care.
The global healthcare landscape increasingly recognizes the importance of accreditation as a mechanism to enhance the quality and safety of patient care. Among various accreditation standards, those set by JCI are notably rigorous, aiming to elevate healthcare services to global standards [6]. The effectiveness of such accreditation processes, particularly from the perspectives of healthcare providers, has been the subject of extensive research [9].
JCI is pivotal in promoting quality and safety in healthcare internationally, offering advisory and continuous improvement services to health organizations and public health agencies. It addresses the unique cultural, religious, and legal challenges faced by healthcare institutions across different countries [6].
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A systematic review highlighted the impact of hospital accreditation on various dimensions of healthcare quality, confirming the positive results associated with such processes [10]. However, the literature also points to challenges in measuring the complex effects of hospital accreditation, suggesting the need for more nuanced investigations into its impacts [1, 10]. In the context of nursing perceptions of quality care, research indicates that hospital accreditation influences nurses’ views of quality care provision, with notable variations based on the accreditation status of their workplaces [11, 12]. This variation underscores the significance of exploring specific accreditation impacts within distinct healthcare environments [13].
This research is necessary because the literature lacks information on the effects of JCI accreditation in conflict-affected regions like Palestine, where healthcare delivery is subject to additional external pressures. By examining the perceptions of nursing staff, which are integral to implementing quality care practices, this study contributes valuable insights into the operationalization of accreditation standards in challenging environments. It also aims to inform policy and practice, providing evidence-based recommendations for leveraging accreditation as a tool for quality enhancement in similar contexts [9, 14].
In Palestine, several hospitals have achieved JCI accreditation, marking significant milestones in healthcare quality and safety within the region. Specifically, two hospitals in East Jerusalem have been pioneers in attaining this prestigious accreditation, setting a benchmark for healthcare standards. In the West Bank, two hospitals, including NNUH, have earned JCI accreditation. This achievement reflects a growing commitment across Palestinian healthcare institutions to adhere to international standards despite the unique challenges posed by the region’s complex socio-political environment.
The NNUH, a notable institution in Palestine, achieved international accreditation in 2020, reflecting its commitment to international healthcare quality and safety standards. However, Palestinian nurses’ perceptions about the impact of accreditation vary significantly. Some view it as a crucial enhancer of care quality, while others regard it as a burdensome administrative process without clear benefits to care quality.
Aims of the study
This study aims to assess nursing perceptions regarding the impact of applying JCI accreditation standards on the quality of health services within a Palestinian hospital setting. By focusing on a context fraught with unique operational challenges, the research seeks to contribute to a broader understanding of accreditation’s role in healthcare quality improvement.
Methods
Study design
The study adopted a quantitative, descriptive, cross-sectional design to assess nurses’ perceptions of the impact of hospital accreditation on patient care quality.
Study setting
This study was conducted at NNUH. A tertiary university hospital located in Nablus - Palestine. This hospital was selected as the main center for the study because it obtained accreditation from the JCI twice, an international accreditation body. Additionally, it is the only accredited university hospital in the West Bank in Palestine that focuses on the quality of care since it is a teaching hospital for different specialties.
Sample and sampling method
The hospital was reaccredited in 2023. A convenience sampling method was utilized in this study due to its efficiency and practicality. The sample comprised nurses directly involved in patient care, with inclusion criteria mandating at least one year of professional experience to ensure familiarity with the hospital’s accreditation processes. Nurses on leave during the study period were excluded to maintain data integrity. The sample size was determined to be 180 nurses out of a total nursing staff of 275, calculated using Raosoft software with a 95% confidence level and a 5% margin of error, ensuring the study’s findings would be statistically significant within the predefined parameters.
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Instruments
This study’s primary research instrument was a structured questionnaire based on the Donabedian model, designed to rigorously evaluate the process and results dimensions of healthcare quality influenced by JCI accreditation at NNUH. The questionnaire used in this study was adapted from scales used in prior research [10, 11, 15]. The author granted permission to use the questionnaire. The questionnaire was methodically divided into two main sections: the first section assessed the respondents’ perception of the quality process, and the second section focused on the quality results. The quality process section was subdivided into eight sub-sections, including quality measurement and analysis, leadership commitment and support, use of data, strategic quality planning, human resources education and training, quality management (operation focus), staff involvement, and benefits of accreditation. Meanwhile, the quality results sub-section included four questions to assess the respondents’ perception of patient satisfaction, patient safety, staff satisfaction, and staff performance [16, 17]. Responses were captured using a five-point Likert scale, ranging from “strongly disagree (1)” to “strongly agree (5),” to allow detailed insights into nurses’ perceptions of the accreditation’s impact on hospital operations and patient care standards to measure each subscale the mean value was used for each item as well as the total for each subscale. To calculate the mean score for each subscale, the mean for each statement was calculated first. The total mean of all statements in each subscale was calculated by summing all means and dividing by the number of statements.
To evaluate the survey tool’s internal consistency, Cronbach’s alpha analysis was conducted on the organized subscales derived from individual survey items. As detailed in Table 1, the results demonstrate high Cronbach’s alpha values across all subscales, exceeding 0.90, indicating a high reliability level. This robust internal consistency, surpassing the recommended alpha threshold of > 0.70, underscores the tool’s suitability for assessing perceptions in this context.
Table 1
Cronbach alpha, Means, and standard deviations for study sub-scales
Variables | |||
|---|---|---|---|
Number of items | Mean ± SD | Cronbach Alpha | |
Quality Results | 4 | 4.18 ± 0.67 | 0.92 |
Benefit Of Accreditation | 8 | 4.16 ± 0.57 | 0.92 |
Quality Management (Operation Focus) | 4 | 4.12 ± 0.62 | 0.92 |
Staff Involvement | 5 | 4.07 ± 0.55 | 0.92 |
Quality Measurement and Analysis | 4 | 4.03 ± 0.81 | 0.92 |
Use of Data (Patient Focus) | 4 | 4.01 ± 0.75 | 0.91 |
Strategic Quality Planning | 4 | 3.96 ± 0.75 | 0.91 |
Human Resources Education and Training | 4 | 3.88 ± 0.83 | 0.92 |
Leadership, Commitment, and Support | 4 | 3.78 ± 0.80 | 0.92 |
Total quality process subscales | 0.96 | ||
Pilot study
A pilot study involving 18 nurses refined the questionnaire’s clarity and relevance, ensuring the data captured were pertinent to the study’s objectives. The high internal consistency of the questionnaire was confirmed with a Cronbach’s alpha score of 0.93, affirming its reliability and validity for this research. The pilot test demonstrated the tool’s effectiveness, with no modifications required post-pilot, thus ensuring its readiness for the main study deployment.
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Data collection
Following the necessary approvals from the Institutional Review Board (IRB) and hospital administration at NNUH, the data for this study was collected using a structured questionnaire. The distribution process commenced in October 2023 and concluded in December 2023. Questionnaires were administered both electronically and in person to ensure comprehensive participation. Nurses received the surveys during their shifts at various departments within the hospital to facilitate ease of access and immediate completion. This method helped achieve a high response rate by accommodating the nurses’ availability and work schedules. After distribution, completed questionnaires were collected promptly to maintain data integrity and minimize potential loss or non-response.
Statistical analysis
The data analysis in this study was designed to assess the relationships between various quality process variables and quality results, as well as to explore differences in nurses’ perceptions based on demographic variables. The analysis utilized both descriptive and inferential statistical methods to provide a comprehensive understanding of the data collected.
At the outset, IBM SPSS software, version 21.0, was used for data analysis. The data were first entered and subjected to rigorous cleaning procedures to ensure accuracy. Descriptive statistics, including means, standard deviations, and percentages, were used to summarize the survey data and provide an overview of the respondents’ characteristics and their general perceptions of the quality processes and results influenced by JCI accreditation. For example, Table 1 details the means and standard deviations for each of the subscales related to quality processes and results, allowing for an assessment of the central tendency and variability of the respondents’ perceptions. Additionally, demographic characteristics of the respondents, such as age, gender, education level, and years of experience, are summarized using percentages in Table 2, providing insight into the composition of the sample.
Table 2
Demographic characteristics
Variables | Range | N | N% | |
|---|---|---|---|---|
Gender | ||||
Male | 98 | 54.4 | ||
Female | 82 | 45.6 | ||
Age | ||||
Below 30 | 24–30 | 103 | 57.2 | |
31–40 | 31–40 | 70 | 38.9 | |
41–50 | 41–50 | 7 | 3.9 | |
More than 51 | 51–60 | 0 | 0 | |
Educational Qualification | ||||
Diploma | 9 | 5.0 | ||
Baccalaureate | 139 | 77.2 | ||
Master’s | 30 | 16.7 | ||
Doctorate | 2 | 1.1 | ||
Year of experiences | ||||
3 to 6 years | 3–6 | 88 | 48.9 | |
More than 6 years | 6–10 | 92 | 51.1 | |
Department | ||||
Cardiology | 24 | 13.3 | ||
ER | 5 | 2.8 | ||
Pediatrics | 19 | 10.6 | ||
ICU | 37 | 20.6 | ||
Medical | 16 | 8.9 | ||
PICU | 5 | 2.8 | ||
Dialysis | 27 | 15.0 | ||
Surgical | 23 | 12.8 | ||
Oncology clinic | 4 | 2.2 | ||
Vascular | 2 | 1.1 | ||
Radiology | 2 | 1.1 | ||
Outpatient clinics | 5 | 2.8 | ||
CCU | 6 | 3.3 | ||
Endoscopy | 5 | 2.8 | ||
Marital status | ||||
Single | 65 | 36.1 | ||
Married | 115 | 63.9 | ||
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Inferential statistical techniques were then employed to explore deeper relationships within the data. Pearson correlation coefficients were utilized to assess the relationships between quality process variables (independent variables) and quality results (dependent variables). This analysis helped identify the strength and direction of the associations between different aspects of the quality processes and the resulting results. Stepwise regression analysis was subsequently conducted to determine which specific quality process variables served as significant predictors of the quality results, providing insight into the factors most influential in improving healthcare quality. Additionally, Analysis of Variance (ANOVA) was used to examine the differences in nurses’ perceptions based on demographic variables, such as age, gender, and years of experience, allowing the study to explore how these factors might influence the perceived impact of JCI accreditation.
To evaluate the internal consistency of the survey tool, Cronbach’s alpha was calculated, revealing high reliability with values exceeding 0.90 across all subscales. Furthermore, a power analysis was performed using Raosoft software, indicating that the sample size was adequate to achieve the desired statistical power.
Results
The study targeted 180 nurses at NNUH to evaluate the impact of JCI accreditation on quality of care. The response rate was 65%, with 180 nurses completing the survey. A breakdown of demographic details in Table 2 revealed that 54.4% of participants were male (98), and 45.6% were female (82). Participants ranged in age from 21 to 55 years, with an average age of approximately 30 years.
Most respondents, 77.2% (139 nurses), held a Baccalaureate degree, demonstrating a highly educated workforce. Regarding professional experience, 48.9% of the nurses had worked for 3 to 6 years at the hospital, while 51.1% had more than six years of experience.
The nurses worked various hours weekly, most reporting between 40 and 50 h. Their tenure at the hospital varied, with 50.5% having worked there from 1 to 5 years and a significant number (49.5%) reporting a longer tenure of 6 to 10 years.
Nursing perception of the quality process
The study results revealed strong positive perceptions of the quality processes influenced by JCI accreditation, as detailed in Table 3. Most respondents affirmed the effective collection and utilization of quality data, with 93.3% agreeing on the hospital’s data collection breadth and 85% on continual data usage improvements. Leadership commitment was robust, with over 81.6% noting active participation by senior executives in quality initiatives. Patient-focused data usage was also rated highly, with 88.3% acknowledging effective assessment of patient needs. Strategic planning, human resources training, and quality management received high marks for promoting clear quality goals, appropriate training, and rigorous quality checks, respectively. Staff involvement in accreditation processes was strong, with over 92.2% participating in implementing recommended changes. Overall, 92.8% recognized the benefits of accreditation, including enhanced collaboration and improved patient care, illustrating a comprehensive endorsement of JCI accreditation’s positive impact on hospital operations and quality care standards.
Table 3
Respondents’ perception of the quality process
Item # | Process Standards Subscales | Strongly disagree N (%) | Disagree N (%) | Neither N (%) | Agree N (%) | Strongly agree N(%) | Mean | SD |
|---|---|---|---|---|---|---|---|---|
Subscale 1: Quality Measurement and Analysis | ||||||||
This hospital collects a wide range of data and information about quality. | 0 (0.0) | 9 (5.0) | 3 (1.7) | 87 (48.3) | 81 (45.0) | 4.33 | 0.74 | |
This hospital continually tries to improve how it uses data and information on quality. | 15 (8.3) | 9 (5.0) | 3 (1.7) | 81 (45.0) | 72 (40.0) | 4.03 | 1.17 | |
Hospital employees are involved in determining which data are collected for improving quality. | 11 (6.1) | 9 (5.0) | 14 (7.8) | 93 (51.7) | 53 (29.4) | 3.93 | 1.06 | |
This hospital compares its data to data on quality at other hospitals. | 14 (7.8) | 8 (4.4) | 23 (12.8) | 84 (46.7) | 51 (28.3) | 3.83 | 1.12 | |
Subscale 2: Leadership, Commitment and Support | ||||||||
The hospital manager is a primary driving force behind quality improvement efforts. | 12 (6.7) | 24 (13.3) | 40 (22.2) | 75 (41.7) | 29 (16.1) | 3.47 | 1.11 | |
The senior executives consistently participate in activities to improve quality. | 9 (5.0) | 6 (3.3) | 18 (10.0) | 105 (58.3) | 42 (23.3) | 3.92 | 0.95 | |
The senior executives have articulated a clear vision for improving quality. | 11 (6.1) | 7 (3.9) | 19 (10.6) | 102 (56.7) | 41 (22.8) | 3.86 | 1.01 | |
Senior executives have a thorough understanding of how to improve quality. | 9 (5.0) | 4 (2.2) | 30 (16.7) | 94 (52.2) | 43 (23.9) | 3.88 | 0.96 | |
Subscale 3: Use of Data (Patient Focus) | ||||||||
This hospital does a good job of assessing patient needs and expectations. | 8 (4.4) | 5 (2.8) | 8 (4.4) | 99 (55.0) | 60 (33.3) | 4.10 | 0.94 | |
Hospital employees promptly resolve patient complaints. | 4 (2.2) | 7 (3.9) | 15 (8.3) | 117 (65.0) | 37 (20.6) | 3.97 | 0.80 | |
This hospital uses data from patients to improve services. | 5 (2.8) | 6 (3.3) | 12 (6.7) | 106 (58.9) | 51 (28.3) | 4.06 | 0.85 | |
Data on patient satisfaction are widely communicated to hospital staff. | 10 (5.6) | 10 (5.6) | 14 (7.8) | 95 (52.8) | 51 (28.3) | 3.92 | 1.04 | |
Subscale 4: Strategic quality planning | ||||||||
Hospital employees are given adequate time to plan for and test quality improvements. | 9 (5.0) | 12 (6.7) | 12 (6.7) | 112 (62.2) | 35 (19.4) | 3.84 | 0.97 | |
Each department and workgroup within this hospital maintains specific goals to improve quality. | 6 (3.3) | 4 (2.2) | 12 (6.7) | 114 (63.3) | 44 (24.4) | 4.03 | 0.83 | |
The hospital’s quality improvement goals are known throughout your department. | 8 (4.4) | 3 (1.7) | 9 (5.0) | 110 (61.1) | 50 (27.8) | 4.06 | 0.89 | |
Hospital employees are involved in developing plans for improving quality. | 10 (5.6) | 4 (2.2) | 18 (10.0) | 109 (60.6) | 39 (21.7) | 3.90 | 0.94 | |
Subscale 5: Human Resources Education and Training | ||||||||
Hospital employees are given training on how to identify and act on quality improvement opportunities. | 8 (4.4) | 9 (5.0) | 17 (9.4) | 106 (58.9) | 40 (22.2) | 3.89 | 0.95 | |
Hospital employees are given training in statistical and other quantitative methods that support quality improvement. | 11 (6.1) | 15 (8.3) | 19 (10.6) | 100 (55.6) | 35 (19.4) | 3.73 | 1.05 | |
Hospital employees are given the needed training to improve performance. | 10 (5.6) | 4 (2.2) | 12 (6.7) | 116 (64.4) | 38 (21.1) | 3.93 | 0.93 | |
The results of training are well evaluated by the personnel department to achieve hospital objectives. | 11 (6.1) | 5 (2.8) | 11 (6.1) | 107 (59.4) | 46 (25.6) | 3.95 | 0.99 | |
Subscale 6: Quality Management (Operation Focus) | ||||||||
This hospital regularly checks equipment and supplies to make sure they meet quality requirements. | 4 (2.2) | 2 (1.1) | 7 (3.9) | 108 (60.0) | 59 (32.8) | 4.20 | 0.75 | |
This hospital has effective policies to support improving quality. | 4 (2.2) | 1 (0.6) | 10 (5.6) | 109 (60.6) | 56 (31.1) | 4.17 | 0.74 | |
This hospital tries to design quality into new services as they are being developed. | 4 (2.2) | 4 (2.2) | 10 (5.6) | 119 (66.1) | 43 (23.9) | 4.07 | 0.76 | |
This hospital encourages employees to keep records of quality measurement. | 5 (2.8) | 1 (0.6) | 21 (11.7) | 107 (59.4) | 46 (25.6) | 4.04 | 0.80 | |
Subscale 7: Staff Involvement | ||||||||
During the preparation for the last survey, important changes were implemented at the hospital. | 5 (2.8) | 2 (1.1) | 7 (3.9) | 108 (60.0) | 58 (32.2) | 4.17 | 0.79 | |
You participated in the implementation of these changes. | 4 (2.2) | 5 (2.8) | 12 (6.7) | 125 (69.4) | 34 (18.9) | 4.00 | 0.75 | |
You learned of the recommendations made to your hospital since the last survey. | 4 (2.2) | 6 (3.3) | 19 (10.6) | 113 (62.8) | 38 (21.1) | 3.97 | 0.80 | |
These recommendations were an opportunity to implement important changes at the hospital. | 3 (1.7) | 6 (3.3) | 14 (7.8) | 112 (62.2) | 45 (25.0) | 4.05 | 0.78 | |
You participated in the changes that resulted from accreditation recommendations. | 2 (1.1) | 2 (1.1) | 10 (5.6) | 119 (66.1) | 47 (26.1) | 4.15 | 0.66 | |
Subscale 8: Benefits of Accreditation | ||||||||
Accreditation enables the improvement of patient care. | 2 (1.1) | 8 (4.4) | 13 (7.2) | 116 (64.4) | 41 (22.8) | 4.03 | 0.76 | |
Accreditation enables the development of values shared by all professionals at the hospital. | 2 (1.1) | 3 (1.7) | 9 (5.0) | 108 (60.0) | 58 (32.2) | 4.20 | 0.70 | |
Accreditation enables the hospital to better use its internal resources. | 4 (2.2) | 3 (1.7) | 6 (3.3) | 119 (66.1) | 48 (26.7) | 4.13 | 0.74 | |
Accreditation enables the hospital to better respond to the population’s needs. | 3 (1.7) | 2 (1.1) | 11 (6.1) | 104 (57.8) | 60 (33.3) | 4.20 | 0.74 | |
Accreditation enables the hospital to better respond to its partners (other hospitals, diverse hospitals, private clinics, etc.) | 4 (2.2) | 1 (0.6) | 10 (5.6) | 114 (63.3) | 51 (28.3) | 4.15 | 0.73 | |
Accreditation contributes to the development of collaboration with partners in the healthcare system. | 3 (1.7) | 3 (1.7) | 7 (3.9) | 111 (61.7) | 56 (31.1) | 4.18 | 0.73 | |
Accreditation is a valuable tool for the hospital to implement changes. | 2 (1.1) | 5 (2.8) | 6 (3.3) | 111 (61.7) | 56 (31.1) | 4.18 | 0.72 | |
The hospital’s participation in accreditation enables it to be more responsive when changes are to be implemented. | 3 (1.7) | 2 (1.1) | 8 (4.4) | 112 (62.2) | 55 (30.6) | 4.18 | 0.71 | |
Nursing perception of quality results
The results from Table 4 highlight the respondents’ perceptions of quality results, showing a positive consensus on the hospital’s progress in several areas. Specifically, 93.3% (n = 168) of respondents agreed that there have been steady, measurable improvements in patient satisfaction over the past few years. Similarly, 92.2% (n = 166) affirmed improvements in the quality of services provided by the administration. Additionally, 91.7% (n = 165) observed measurable advancements in patient care quality, and another 92.2% (n = 166) noted improvements in services provided by clinical support departments. These findings underscore the hospital’s consistent progress in enhancing various aspects of healthcare quality, reflecting positively on its accreditation results and operational standards.
Table 4
Respondent’s perception of quality results
Item # | Subscale | Strongly disagree N(%) | Disagree N (%) | Neither N (%) | Agree N (%) | Strongly agree N(%) | Mean | SD |
|---|---|---|---|---|---|---|---|---|
Quality Results | ||||||||
Over the past few years, this hospital has shown steady, measurable improvements in the quality of patient satisfaction. | 6 (3.3) | 3 (1.7) | 3 (1.7) | 108 (60.0) | 60 (33.3) | 4.18 | 0.82 | |
Over the past few years, this hospital has shown steady, measurable improvements in the quality of services provided by the administration. | 6 (3.3) | 3 (1.7) | 5 (2.8) | 106 (58.9) | 60 (33.3) | 4.17 | 0.83 | |
Over the past few years, this hospital has shown steady, measurable improvements in the quality of care provided to patients. | 4 (2.2) | 2 (1.1) | 9 (5.0) | 106 (58.9) | 59 (32.8) | 4.18 | 0.76 | |
Over the past few years, this hospital has shown steady, measurable improvements in the quality of services provided by clinical support departments. | 5 (2.8) | 2 (1.1) | 7 (3.9) | 108 (60.0) | 58 (32.2) | 4.17 | 0.79 | |
The quality process sub-scales and quality results sub-scale
In terms of the Likert scale scores, the subscale ‘Quality Results’ scored the highest mean at (4.18), followed closely by ‘Benefit of Accreditation’ at (4.16) and ‘Quality Management (Operation Focus)’ at (4.123). Additional subscale means include ‘Staff Involvement’ at (4.04), ‘Quality Measurement and Analysis’ at (4.03), ‘Use of Data (Patient Focus)’ at (4.01), ‘Strategic Quality Planning’ at (3.96), and ‘Human Resources Education and Training’ at (3.88), with ‘Leadership, Commitment, and Support’ registering the lowest mean score of (3.78).
Pearson correlation measurements were utilized to explore the relationships between various quality process variables and the quality results variable, as perceived by respondents. The results in Table 5 reveal significant positive correlations for all variables, with correlation coefficients exceeding 0.4, indicating robust associations between the quality processes and results. Specifically, the strongest correlation was observed with Quality Management (Operation Focus), which had a correlation coefficient of r (178) = 0.762, p < 0.000. The lowest, yet still substantial, correlation was with Quality Measurement and Analysis, at r (178) = 0.492, p < 0.000. These findings highlight the impact of dedicated and supportive leadership, alongside other quality processes, in achieving superior quality results in the healthcare setting.
Table 5
Pearson correlations between the quality process and quality results sub-scales
95.0% Confidence Interval | ||||
|---|---|---|---|---|
Quality results | Lower | Upper | p-value | |
Quality Management (Operation Focus) | 0.76 * | 0.61 | 0.86 | 0.000 |
Staff Involvement | 0.76 * | 0.61 | 0.86 | 0.000 |
Benefit of Accreditation | 0.68 ** | 0.42 | 0.84 | 0.000 |
Strategic Quality Planning | 0.60 ** | 0.35 | 0.77 | 0.000 |
Use of Data (Patient Focus) | 0.59 ** | 0.38 | 0.75 | 0.000 |
Human Resources Education and Training | 0.56 ** | 0.35 | 0.71 | 0.000 |
Leadership, Commitment, and Support | 0.50 ** | 0.32 | 0.66 | 0.000 |
Quality Measurement and Analysis | 0.49 *** | 0.33 | 0.62 | 0.000 |
Step-wise regression analysis results of the quality process on quality results
The stepwise regression analysis conducted between various quality process subscales and the “quality results” subscale offers a clear understanding of what drives healthcare quality in a hospital setting. The analysis, detailed in Table 6, explored how factors like “Quality Management (Operation Focus),” “Staff Involvement,” and “Use of Data” impact the overall quality results, with the latter being treated as the dependent variable. The unstandardized coefficients (B) in the table provide a straightforward interpretation. For instance, a one-unit increase in the “Quality Management (Operation Focus)” subscale is associated with a 45% increase in quality results. At the same time, “Staff Involvement” has an even greater impact, with a coefficient of 0.533. This suggests that actively engaging staff in quality processes leads to significantly better outcomes. The model’s R² value of 0.71 is particularly telling, as it shows that these subscales can explain 71% of the variability in quality results. This strong explanatory power highlights the effectiveness of focusing on these key areas to enhance overall healthcare quality.
Table 6
Step-wise regression analysis results of the quality process on quality results
Predictor | 95.0% Confidence Interval | ||||||
|---|---|---|---|---|---|---|---|
β | b | t | p-value | Lower | Upper | VIF | |
Constant | -0.233 | -1.08 | 0.280* | -0.659 | 0.192 | ||
Quality management (operation focus) | 0.451 | 0.418 | 7.23 | 0.001* | 0.328 | 0.574 | 2.038 |
Staff involvement | 0.533 | 0.434 | 7.95 | 0.001* | 0.401 | 0.666 | 1.818 |
Use of data | 0.095 | 0.106 | 2.02 | 0.044* | 0.002 | 0.188 | 1.665 |
One-way ANOVA test between demographic data and quality result
Data analysis for this study was conducted using IBM SPSS software, where data were first entered and subjected to rigorous cleaning procedures to ensure accuracy. The statistical analysis encompassed both descriptive and inferential techniques. Descriptive statistics, including means, standard deviations, and percentages, summarized the survey data. Inferential analyses were applied extensively: Pearson correlation coefficients assessed the relationships between quality process variables and results, multiple regression analysis determined predictors of quality results, and ANOVA along with t-tests were used to examine differences in perceptions based on demographic variables. A Cronbach’s Alpha of 0.93 verified the high internal consistency of the survey items. Additionally, a power analysis performed using Raosoft software indicated that a sample size of 180 was adequate to achieve a power level of 0.95 with an expected medium effect size (f^2 = 0.15) and an alpha of 0.05, ensuring the study was well-powered to detect significant effects and validating the reliability and comprehensiveness of the statistical evaluations used.
The ANOVA results presented in Table 7 reveal significant differences in perceptions of quality results across different age groups. A Tukey HSD post-hoc test further pinpointed these differences, showing the most substantial disparities between the youngest group (below 30 years) and the oldest group (41–50 years), as well as between the 31–40 years group and the 41–50 years group. The “41–50” age group exhibited notably lower quality results, and it was significantly different from the age groups (31–40) (below 30).
Table 7
One-way ANOVA test between age and quality result
Categories | N | Mean ± SD | Homogeneous Subsets | df | Sig |
|---|---|---|---|---|---|
Below 30 years (a) | 103 | 4.2112 ± 0.486 | A – B | 2 | 0.024* |
31–40 (b) | 70 | 4.2036 ± 0.093 | 177 | ||
41–50 (c) | 7 | 3.5000 ± 0.514 | 179 |
Discussion
This study aimed to assess nurses’ perceptions of the impact of international accreditation on healthcare quality at NNUH, which is JCI-accredited. To address this, the study investigated nurses’ views on key aspects of quality healthcare, focusing on quality processes and results. It then examined the relationship between nurses’ evaluations of these processes and results to determine the effect of hospital accreditation on healthcare quality.
Nurses’ perception of quality processes
The study revealed that nurses at NNUH highly value the hospital’s efforts in collecting and utilizing quality data. Most nurses reported that the hospital gathers extensive quality data and continuously seeks improvement, a finding supported by previous studies [18]. This consistent collection and analysis of quality data are crucial for maintaining high patient care standards and identifying areas that require improvement. Integrating data-driven decision-making processes aligns with the broader literature emphasizing the importance of quality indicators in healthcare [19].
Positive leadership support emerged as a significant factor in successfully implementing quality improvement initiatives. Nurses noted that senior executives at NNUH actively participate in quality improvement efforts, which aligns with findings from previous studies [11, 20]. Effective leadership is essential for fostering a culture of continuous improvement and ensuring that quality initiatives are prioritized and adequately supported [21].
Nurses highly rated the effective use of patient data to improve healthcare services. This involves assessing patient needs, promptly resolving patient complaints, and using patient feedback to enhance service quality. Studies have shown patient-centered data utilization is critical for improving healthcare results [22]. Nurses in this study recognized the hospital’s efforts in this area, highlighting the importance of a patient-focused approach in achieving high-quality care.
Strategic quality planning involves setting clear goals and providing adequate time and resources for quality improvement initiatives. Nurses at NNUH reported that the hospital maintains specific quality goals within departments and involves staff in developing improvement plans. This finding is consistent with previous research indicating that strategic planning is vital for sustaining quality improvement efforts [23, 24].
Training and education are critical components of quality improvement. Nurses at NNUH reported receiving effective training on quality improvement opportunities, statistical methods, and performance enhancement. This aligns with previous studies emphasizing the role of education and training in improving nurses’ engagement with quality and safety initiatives [36].
Regular checks of equipment and supplies, effective policies for quality improvement, and the design of quality into new services were highlighted by nurses as key factors in maintaining high-quality healthcare services. The findings support the importance of robust quality management practices in achieving superior healthcare results [20, 25].
Another significant finding was the staff’s active involvement in quality improvement initiatives. Nurses reported participating in implementing changes recommended by accreditation bodies, learning from accreditation feedback, and engaging in quality improvement activities. This involvement is critical for fostering a sense of ownership and commitment to quality among healthcare providers [18, 23].
Nurses’ perception of quality results
Nurses perceived steady improvements in patient satisfaction, a crucial indicator of healthcare quality. Studies have shown that patient satisfaction is strongly influenced by the quality of care provided, and accreditation can play a significant role in enhancing patient experiences [26].
The quality of administrative services was also seen to improve significantly. Effective administration is essential for the smooth operation of healthcare facilities and directly impacts the overall quality of care [15].
Improvements in clinical support services were noted by nurses, underscoring the importance of a comprehensive approach to quality improvement that includes all aspects of healthcare delivery [11].
The link between nurses’ perceptions of quality processes and their assessments of quality results
This study found a positive relationship between quality process sub-scales (use of data, staff involvement, quality management) and quality results. These findings are consistent with studies [8], which highlighted the importance of quality management, data use, and employee engagement in achieving better quality results [27, 28].
However, unlike other studies, this research did not find evidence of some quality process sub-scales significantly impacting quality results. Nurses acknowledged the hospital’s quality measurement and analysis efforts, human resources education and training, and leadership commitment. Yet, these efforts did not show a significant positive impact on quality results.
The study underscored the need for leadership commitment and continuous quality improvement to sustain high-quality care. Previous research has demonstrated that leadership is pivotal in driving quality initiatives and ensuring their successful implementation [29].
The complexity of measuring the impact of accreditation on healthcare quality is well-documented in the literature. The findings of this study suggest that while accreditation processes positively influence certain aspects of quality care, the relationship between accreditation and overall quality results can be challenging to quantify [1]. This underscores the need for continuous and comprehensive evaluations to capture the full impact of accreditation [10].
In reflecting on the findings of our study, which suggest significant improvements in various quality indicators at NNUH following JCI accreditation, it is important to consider the broader implications of accreditation on healthcare quality. A previous study [8], provides valuable insights into the mixed effects of accreditation across different hospital settings. Their research found that while accreditation did not result in significant differences in perceived overall patient safety or in rates of nosocomial infections, pressure ulcers, patient falls, and medication errors, it did contribute to reduced concerns among nurses about incident reporting and lower patient and family complaints regarding the cost of care in accredited hospitals. These nuanced findings underscore the complexity of accreditation’s impact, suggesting that while accreditation can alleviate certain administrative and financial pressures, it may not be sufficient on its own to address all aspects of patient safety and care quality. This aligns with our observation that accreditation, while beneficial, must be part of a broader, continuous effort to enhance healthcare outcomes across multiple dimensions.
Study limitations
This study, the first to evaluate the impact of JCI accreditation on healthcare quality at NNUH in Palestine, encounters several limitations. Primarily, it relies on the subjective perceptions of nurses, which may not accurately reflect the objective reality of patient results, limiting the robustness of the findings. Conducted in a single JCI-accredited hospital, its scope is restricted, thus hindering the generalizability of the results across other accredited hospitals. The cross-sectional design restricts temporal analysis, preventing the assessment of changes in perceptions pre- and post -post-accreditation. Additionally, excluding nurses on leave during the study and, focusing solely on nurses, omitting other healthcare providers may introduce bias and limit the comprehensiveness of the insights gathered. Lastly, the quantitative nature of the study may not capture the depth of nurses’ perceptions as effectively as qualitative methods would.
Recommendations
The recommendations provided in the study are aimed at enhancing the effectiveness and sustainability of healthcare services, particularly in the context of JCI accreditation. First, the study emphasizes the importance of hospital leaders adopting a mindset of continuous preparedness. This involves integrating quality improvement into daily operations rather than viewing it as a task only for accreditation purposes, and it highlights the need for ongoing leadership and management development to support this cultural shift. Secondly, the study recommends that hospitals should create and implement strategies to ensure that the improvements achieved through accreditation are maintained and further developed over time. This includes regular reviews and updates to quality practices, continuous staff training, and the institutionalization of quality initiatives.
Moreover, the study suggests that future research should take a broader approach by including all healthcare professionals, not just nurses, to gain a more comprehensive understanding of accreditation’s impact. Assessing patient results is also recommended as it provides direct evidence of the benefits of accreditation, making the quality improvement process more data-driven. The study also proposes expanding research to include a variety of hospitals, both accredited and non-accredited, across different regions. This would help in understanding whether the positive impacts of accreditation observed in one context can be generalized to others. Finally, the study underscores the importance of hospitals consistently using and monitoring quality measures and indicators. By doing so, hospitals can better identify areas that need improvement and ensure that quality standards are upheld. Furthermore, openly reporting these findings to the public and stakeholders is crucial for maintaining transparency, building trust, and encouraging a culture of continuous quality improvement.
Conclusions
This study provides compelling evidence that specific quality management processes, particularly those involving staff involvement and the effective use of data, have a profound impact on healthcare quality outcomes. The analysis revealed that focusing on these areas is crucial for achieving sustained improvements in patient care and operational efficiency.
To build on these findings, it is recommended that healthcare institutions prioritize the enhancement of quality management practices by embedding a strong operational focus into their daily activities. This can be accomplished through continuous training, monitoring, and evaluation of quality initiatives. Furthermore, actively engaging staff in these processes is essential; fostering a culture of shared responsibility and recognizing the vital role that staff play in quality improvement can significantly bolster these efforts.
The use of data in decision-making processes should also be emphasized. Investments in robust data management systems that allow for the timely collection and analysis of data will enable more informed and effective quality improvements. Additionally, while accreditation remains a valuable tool for enhancing quality, it should be integrated into a broader strategy that includes leadership commitment, strategic planning, and ongoing staff education.
By implementing these recommendations, healthcare organizations can more effectively leverage their resources to drive meaningful improvements in quality outcomes, ultimately leading to higher standards of patient care and overall operational excellence.
Acknowledgements
The authors want to thank Dana Radwan, Hamzeh Jabali, and Ward Bawaqneh for their support. They are also grateful for Prof. Saed Zyoud’s guidance and help. Special thanks go to all nurses who participated in this study and to the hospital administration for facilitating its conduct.
Declarations
Ethics approval and consent to participate
The Institutional Review Board (IRB) of An-Najah National University approved the current study under the reference number (Oct. 2023/53). Permission was granted to use the adopted questionnaire. Ethical measures were strictly observed to uphold participant autonomy, privacy, and confidentiality, with informed written consent obtained from all participants. Information regarding voluntary participation and the right of withdrawal was included on the cover page of the questionnaire. The cover page also explained the study objectives and the method of answering the questions. The information gathered was used solely for research purposes and was kept anonymous and confidential. No incentives were provided to participants for completing the survey.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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