Impact of Joint Commission International Patient-Centered Standards on Nursing Performance in Sana'a, Yemen Hospitals

Impact of Joint Commission International Patient-Centered Standards on Nursing Performance in Sana'a, Yemen Hospitals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of Joint Commission International Patient-Centered Standards on Nursing Performance in Sana'a, Yemen Hospitals Kamal Ahmed Qabban, Muneer Musleh Al-Wesabi, Haitham Mohammed Jowah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6372401/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction : Yemen’s healthcare system faces challenges such as inadequate training and resource shortages, impacting nursing performance. This study examined the impact of patient-centered standards of the Joint Commission International (JCI) on nursing performance in Sana’a, Yemen, a resource-constrained setting. Methods This cross-sectional study was conducted from August to October 2024 in six hospitals in Sana’a, Yemen. A simple random sample of 526 nurses from emergency, inpatient, intensive care unit, and neonatal units completed a two-part questionnaire assessing JCI standards (42 items) and nursing performance (24 items) on a 7-point Likert scale. Confirmatory factor analysis (CFA) validated the constructs using IBM SPSS AMOS . Regression analyses, t-tests, and descriptive statistics were performed using SPSS 26.0. Results The implementation of JCI standards was moderately high (mean = 4.77, 68.1%), with Access to Care and Continuity highest (mean = 4.95, 70.7%) and International Patient Safety Goals lowest (mean = 4.46, 63.7%). The nursing performance was moderate (mean = 4.64, 66.3%). JCI standards significantly predicted performance (R² = 0.644, p < 0.001) driven by Medication Management and Use (MMU), International Patient Safety Goals (IPSG), and Patient-Centered Care (PCC). Private hospitals outperformed government hospitals in JCI implementation across all standards (p < 0.001), with mean differences ranging from 0.65−0.96. Conclusion JCI standards can enhance the quality of care in Yemen, despite systemic challenges. Targeted training in safety protocols and equitable resource allocation, particularly in governmental hospitals, are recommended to address these gaps and improve healthcare quality. Patient-Centered Care Nursing Performance Hospital Accreditation JCI Standards Healthcare Quality Figures Figure 1 Figure 2 Introduction Healthcare quality is fundamental to effective medical services, driving societal progress, and improving quality of life [ 1 , 2 ]. The World Health Organization (WHO) underscores its importance, particularly in low- and middle-income countries that pursue universal health coverage [ 3 ]. In Yemen, prolonged conflict and economic instability have severely strained the healthcare system, leading to resource shortages, staffing deficits, and infrastructure deterioration [ 4 ]. These challenges have compromised care delivery, heightened medical error risks, and undermined patient safety, necessitating standardized quality frameworks. Nurses, pivotal to healthcare delivery, face significant barriers in Yemen, including inadequate training, heavy workload, and limited resources [ 5 ]. For instance, Al-Jaradi et al. (2021) revealed that only 16.8% of nurses in Sana’a public hospitals had good knowledge of drug administration, with 64.2% at a fair level, highlighting gaps in medication management skills [ 6 ]. A 2021 Ministry of Health assessment further revealed that only 5% of public and private hospitals have achieved high-quality benchmarks, underscoring systemic gaps [ 7 ]. These deficiencies, coupled with low caring efficacy among nurses (mean = 3.99), as reported by Al-Thaifani et al. (2020), emphasize the urgent need for interventions to enhance nursing practice and elevate care standards in Yemen [ 8 ]. The Joint Commission International (JCI) provides a globally recognized framework of patient-centered standards to improve healthcare quality and safety through accreditation [ 9 ]. Previous studies have demonstrated its benefits in several contexts. In South Korea, nurses in JCI-accredited hospitals reported improved patient safety, although gaps in International Patient Safety Goals (IPSG) implementation persist [ 10 ]. In China, JCI standards enhance nursing management and improve patient identification and hand hygiene, thereby increasing patient satisfaction [ 11 ]. However, several challenges remain. Medication management standards such as titration have raised concerns about care delays and documentation burdens [ 12 ], whereas cultural and leadership barriers hinder their adoption in diverse settings [ 13 ]. In the Middle East, JCI standards are linked to better care quality and positive nursing perceptions; however, their application in resource-scarce settings, such as Yemen, is underexplored. Insights from Guatemala highlight the difficulties of implementing JCI standards in low-income contexts, where infrastructure and staffing constraints pose barriers, emphasizing the need for tailored strategies such as staff training and leadership commitment [ 14 , 15 ]. In Yemeni hospitals, nursing performance is hampered by resource constraints and inconsistent standardization, which elevate medical error risks and compromise patient outcomes. This study addresses this gap by examining the implementation of JCI patient-centered standards and their impact on nursing performance in Sana’a, Yemen, a setting marked by severe resource limitations. We hypothesized that JCI standards would positively influence nursing performance. By assessing adherence to key standards, such as IPSG, Access to Care and Continuity (ACC), and Medication Management and Use (MMU), and their effects on performance efficiency, effectiveness, and indicators, this research aims to provide actionable recommendations for improving healthcare quality in resource-constrained environments. Material and methods Study Design This cross-sectional study examined the association between the implementation of Joint Commission International (JCI) patient-centered standards and nursing performance in hospitals in Sana’a, Yemen, from August to October 2024. This design was selected due to its suitability for studying social phenomena, such as the implementation of JCI standards and their impact on nursing performance, allowing for a snapshot of current practices across multiple hospitals. The study was approved by the Ethical Committee of the Center of Business Administration, Sana’a University to ensure compliance with ethical standards. All participants provided written informed consent prior to participation and confidentiality was ensured through anonymous data collection. This study was conducted in compliance with the ethical principles outlined in the Declaration of Helsinki, ensuring the protection of the participants’ rights, safety, and well-being. Setting Data were collected from August to October 2024 across six hospitals in Sana’a, Yemen: Al-Thawra General Hospital and 48 Model Hospitals (governmental; 33.3%), and Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital (private, 42.2%). These urban facilities vary in size and JCI accreditation status, providing diverse samples for assessing JCI standard implementation. Participants Of 1,459 potentially eligible nursing staff across the six hospitals, 847 medically licensed nurses actively employed in emergency departments, inpatient wards, intensive care units (ICUs), or neonatal units were assessed for eligibility. Inclusion criteria required willingness to participate, while exclusion criteria eliminated nurses in outpatient/helper roles, those not in specified departments, or those with incomplete data. Using simple random sampling with proportional representation (Al-Thawra, 32.3%; 48 Model, 25.5%; others in Table 1 ; governmental, 57.8%; private, 42.2%), 558 nurses were confirmed to be eligible. Proportional representation ensured that the sample from each hospital accurately reflected its study population, avoiding overburdening any single hospital and ensuring equitable representation across all facilities. To account for non-responses, 710 questionnaires were distributed, 621 were received (87.5% response rate), and 526 were analyzed after excluding 95 for incomplete data (n = 59), outpatient/helper roles (n = 24), or not being in specified departments (n = 12). All the participants provided informed consent. The selection process is illustrated in Fig. 1 . Variables The independent variable was the implementation level of JCI patient-centered standards, comprising six domains: International Patient Safety Goals (IPSG), Access to Care and Continuity (ACC), Patient-Centered Care (PCC), Assessment of Patients (AOP), Care of Patients (COP), and Medication Management and Use (MMU), as outlined in the conceptual model (Fig. 2 ). The dependent variable was nursing performance, measured across three dimensions: Performance Efficiency, Performance Effectiveness, and Performance Indicators, focusing on the dimensions most relevant to the JCI standards. Hospital type (government vs. private) and years of experience were included as covariates to explore differences in implementation and performance. Data Sources and Measurement Data were collected using a two-part questionnaire developed for this study and administered in Arabic (Supplementary File S1: Study Questionnaire, English translation). The questionnaire targeted nurses’ perspectives on practical field practices, given their extensive involvement in implementing JCI standards and their deeper knowledge compared with other healthcare or administrative staff. It comprised 91 items: Part 1 : Demographic data (25 items), such as hospital name, department, job title, and years of experience. Part 2 : Scored items (66 items) assessing the study variables: JCI Patient-Centered Standards (42 items) : Covered in six domains: International Patient Safety Goals (IPSG, 9 items), Access to Care and Continuity (ACC, 7 items), Patient-Centered Care (PCC, 7 items), Assessment of Patients (AOP, 5 items), Care of Patients (COP, 8 items), and Medication Management and Use (MMU, 6 items)—adapted from JCI (2024), and previous studies [ 16 – 20 ]. Nursing Performance (24 items) : Three dimensions were assessed: Performance Effectiveness (4 items), Performance Efficiency (5 items), and Performance Indicators (15 items), adapted from Schwirian (1978), the National Database of Nursing Quality Indicators (NDNQI), and previous studies [ 21 – 24 ]. Responses were recorded on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). The questionnaire was developed by synthesizing these sources and validated using a two-step process. First, a panel of four experts—two hospital administrators with over 15 years of experience in healthcare management and two nursing researchers with doctoral degrees in healthcare quality—reviewed it for content validity. Second, a pilot test with 40 nurses from two Sana’a hospitals (excluded from the final sample) confirmed its clarity and cultural appropriateness, leading to minor wording revisions for improved comprehension. The psychometric properties of the questionnaire were evaluated using confirmatory factor analysis (CFA) with IBM SPSS AMOS along with reliability and validity metrics (Supplementary File S2). Both the six-factor JCI standards model and the three-factor nursing performance model were validated, with fit indices meeting acceptable thresholds (e.g., RMSEA ≤ 0.08, CFI ≥ 0.90; Supplementary Table S2.3 ) and factor loadings ranging from 0.41 to 0.88 across subscales (Supplementary Figures S2.1 and S2.2). Convergent validity was confirmed, with composite reliability (CR) of 0.885–0.932 and average variance extracted (AVE) of 0.513–0.749, exceeding the thresholds of 0.70 for CR and 0.50 for AVE. Reliability was high, with Cronbach’s alpha values of 0.980 for JCI standards, 0.956 for nursing performance, and 0.982 overall. Detailed psychometric properties, including the subscale-specific CR, AVE, and Cronbach’s alpha values, are provided in Supplementary Table S2.1 . Bias Selection bias was minimized through simple random sampling with proportional representation across hospitals. Non-response bias was reduced by distributing 710 questionnaires, achieving an 87.5% response rate. Information bias was mitigated using a standardized, pre-tested questionnaire with anonymous data collection to reduce social desirability bias. Incomplete responses were excluded to ensure data quality. Potential confounders (e.g., years of experience and hospital type) were addressed by stratifying the sample by hospital type and department and could be controlled for in the statistical analyses. Study Size The study population comprised 847 nurses in emergency departments, inpatient wards, ICUs, and neonatal units across six hospitals, identified from 1,459 human resource records. The sample size of 558 nurses was determined using the Krejcie and Morgan table [ 25 ] (95% confidence level, 5% margin of error) with 80% power to detect a moderate effect size (f² = 0.15) at α = 0.05, based on prior JCI studies [ 18 ]. After exclusion, a simple random sampling resulted in a final sample of 526 nurses. Statistical Methods Data were analyzed using SPSS version 26.0 and IBM SPSS AMOS for confirmatory factor analysis (CFA). Descriptive statistics (means, standard deviations, and percentages) were used to summarize the JCI standard implementation and nursing performance. Data normality was confirmed using skewness and kurtosis (± 2 threshold), justifying parametric tests. Multicollinearity among the JCI standard dimensions was assessed using variance inflation factors (VIF) and Tolerance, with VIF ranging from 3.070 to 5.688 (all 0.10), indicating no significant multicollinearity. The Durbin-Watson statistic (1.78) confirmed the independence of the errors, with no autocorrelation (value between 1 and 3). Hypotheses were tested as follows: (1) simple linear regression assessed the overall impact of JCI standards on nursing performance (H1), reporting R, R², p-values, and 95% confidence intervals; (2) multiple linear regression identified the contributions of individual JCI standards, reporting standardized beta coefficients (β), p-values (p < 0.05), and 95% confidence intervals; (3) independent t-tests comparing JCI implementation and nursing performance by hospital type (H2), with significance at p < 0.05. Missing data (3.2%) were handled using listwise deletion. Multicollinearity was assessed using variance inflation factors (VIF; 3.070–5.688), which indicated moderate multicollinearity, which is a potential limitation. Results Participants This study targeted 847 nursing staff across six hospitals in Sana’a, Yemen: Al-Thawra General Hospital, 48 Model Hospitals (governmental), Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital (private). Of the 710 distributed questionnaires, 621 were returned (87.5% response rate) and 526 were analyzed (62.1% of the study population) after excluding 95 participants for incomplete data (n = 59), outpatient/helper roles (n = 24), and those who did not being in specified departments (n = 12). Simple random sampling, guided by the Krejcie and Morgan table, ensured a proportional representation from each hospital (Table 1 ). Table 1 Study Population and Sample Distribution Across Hospitals in Sana’a, Yemen Hospital Study Population (N) Targeted Sample (N) Distributed Questionnaires (N) Returned Questionnaires (N) Analyzed Questionnaires (N) Analyzed (%) Governmental Hospital Al-Thawra General 320 175 230 196 170 32.3 48 Model 224 140 170 152 134 25.5 Private Hospital Azal Model 150 110 130 120 103 19.6 Modern European 70 59 75 65 51 9.7 Royal 50 44 70 55 40 7.6 Yemeni Health International 33 30 35 33 28 5.3 Total 847 558 710 621 526 100.0 Notes : Sample size determined using the Krejcie and Morgan table for random sampling. Response rate = Returned/Distributed = 621/710 = 87.5%. Analyzed proportion = Analyzed/Study Population = 526/847 = 62.1%. Analyzed (%) reflects the proportion of the final sample (N = 526). Final analyzed sample distribution: Governmental (304, 57.8%), Private (222, 42.2%). No statistical tests applied. Abbreviations: N = number of participants; Targeted Sample (N) = intended sample size; Distributed Questionnaires (N) = questionnaires sent; Returned Questionnaires (N) = questionnaires received; Analyzed Questionnaires (N) = valid responses included in analysis. Characteristics of Study Participants The 526 participants were nursing staff from emergency, inpatient, ICU, and neonatal units in governmental and private hospitals in Sana’a. More than half were from governmental hospitals (57.8%, n = 304) versus private hospitals (42.2%, n = 222), reflecting the larger staff sizes at Al-Thawra and the 48 model hospitals (Table 1). Most participants worked in the general wards (53.2%, n = 280), followed by the ICU (30.4%, n = 160), emergency departments (11.8%, n = 62), and neonatal units (4.6%, n = 24). The sample had a small female majority (52.3%, n = 275; males: 47.7%, n = 251), consistent with Yemen’s nursing workforce. Experience-wise, 37.8% (n = 199) had 3–6 years, 22.8% (n = 120) had over 10 years, 22.1% (n = 116) had less than three years, and 17.3% (n = 91) had 7–10 years. Qualifications included 54.8% (n = 288) with a diploma, 43.5% (n = 229) with a bachelor’s degree, and 1.7% (n = 9) with higher education (e.g., a master’s degree or above), aligned with the Ministry of Health’s shift toward bachelor’s degrees (Table 2). Table 2: Demographic Characteristics of Nursing Staff in Sana’a, Yemen (N = 526) Variable Category Frequency (n) Percentage (%) Hospital Type Governmental 304 57.8 Private 222 42.2 Total 526 100.0 Department ICU 160 30.4 General Ward 280 53.2 Emergency 62 11.8 Neonatal Unit 24 4.6 Total 526 100.0 Sex Male 251 47.7 Female 275 52.3 Total 526 100.0 Experience (Years) 10 120 22.8 Total 526 100.0 Qualification Diploma 288 54.8 Bachelor’s Degree 229 43.5 Higher Studies 9 1.7 Total 526 100.0 Notes: No statistical tests applied. Higher Studies include master’s degrees or above. Abbreviations: ICU = Intensive Care Unit. Implementation Level of Patient-Centered JCI Standards The implementation of JCI standards, assessed on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), showed a moderately high level (mean = 4.77, SD = 1.43, 68.1%). Access to Care and Continuity (ACC) scored the highest (mean = 4.95, SD = 1.38, 70.7%), reflecting robust practices in timely and coordinated care, whereas International Patient Safety Goals (IPSG) scored the lowest (mean = 4.46, SD = 1.48, 63.7%), indicating weaker adherence to safety protocols. The other standards, COP (69.7%), PCC (69.3%), MMU (68.0%), and AOP (67.0%), ranged from 67.0% to 69.7% (Table 3). Table 3: Implementation Levels of JCI Patient-Centered Standards Among Nurses in Sana’a, Yemen (N = 526) Standard Mean SD Percentage (%) ACC 4.95 1.381 70.7 COP 4.88 1.389 69.7 PCC 4.85 1.376 69.3 MMU 4.76 1.464 68.0 AOP 4.69 1.471 67.0 IPSG 4.46 1.482 63.7 Overall 4.77 1.427 68.1 Notes: Means and standard deviations (SD) derived from a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Percentage = (Mean/7) × 100, rounded to one decimal place. No inferential tests applied. Standards are ordered from highest to lowest mean score. Abbreviations: JCI = Joint Commission International; ACC = Access to Care and Continuity of Care; COP = Care of Patients; PCC = Patient-Centered Care; MMU = Medication Management and Use; AOP = Assessment of Patients; IPSG = International Patient Safety Goals; SD = standard deviation. Nursing Performance Levels Nursing performance averaged at a moderate level (mean = 4.64, SD = 1.39, 66.3%). Performance Effectiveness was the highest (mean = 4.86, SD = 1.32, 69.4%), followed by Performance Efficiency (mean = 4.65, SD = 1.45, 66.4%), and the Performance Indicators scored the lowest (mean = 4.41, SD = 1.40, 63.0%) (Table 4). Table 4: Nursing Performance Levels Among Nurses in Sana’a, Yemen (N = 526) Dimension Mean SD Percentage (%) Performance Effectiveness 4.86 1.318 69.4 Performance Efficiency 4.65 1.448 66.4 Performance Indicators 4.41 1.401 63.0 Overall 4.64 1.389 66.3 Notes: Means and standard deviations (SD) derived from a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Percentage = (Mean/7) × 100, rounded to one decimal place. No inferential tests applied. Dimensions are ordered from highest to lowest mean score. Abbreviations: SD = standard deviation. Testing the Study Hypotheses Normality of Data Data normality was confirmed, with skewness and kurtosis values within ±2 for all variables, including JCI standards (e.g., IPSG: skewness = -0.428, kurtosis = -0.426) and nursing performance (e.g., Performance Indicators: skewness = -0.400, kurtosis = 0.093), supporting the use of parametric tests (Table 5). Table 5: Normality Test Results for Key Study Variables (N = 526) Variable Mean SD Skewness Kurtosis JCI Standards (Overall) 4.77 1.427 -0.553 -0.278 ACC 4.95 1.381 -0.525 0.017 COP 4.88 1.389 -0.502 -0.049 PCC 4.85 1.376 -0.564 0.095 MMU 4.76 1.464 -0.507 -0.127 AOP 4.69 1.471 -0.437 -0.265 IPSG 4.46 1.482 -0.428 -0.426 Nursing Performance (Overall) 4.64 1.389 -0.552 0.265 Performance Effectiveness 4.86 1.318 -0.362 -0.023 Performance Efficiency 4.65 1.448 -0.360 -0.346 Performance Indicators 4.41 1.401 -0.400 0.093 Notes: Means and standard deviations (SD) are derived from Tables 3 and 4. Skewness and Kurtosis values within ±1 indicate normal distribution, justifying parametric tests (e.g., regression, t-tests). No significance testing applied. Abbreviations: JCI = Joint Commission International; ACC = Access to Care and Continuity of Care; COP = Care of Patients; PCC = Patient-Centered Care; MMU = Medication Management and Use; AOP = Assessment of Patients; IPSG = International Patient Safety Goals; SD = standard deviation. Hypothesis 1: Impact of JCI Standards on Nursing Performance Simple linear regression revealed that JCI standards significantly predicted nursing performance (R = 0.802, R² = 0.644, p < 0.001), explaining 64.4% of the variance and supporting the conceptual model (Figure 2). Multiple regression analysis identified MMU (β = 0.354, 95% CI [0.28, 0.43], p < 0.001), IPSG (β = 0.247, 95% CI [0.18, 0.31], p 0.05) (Table 6). Table 6: Regression Analysis of JCI Standards’ Impact on Nursing Performance (N = 526) Model/Analysis R R² F p (F) Predictor β T p 95% CI Simple Regression 0.802 0.644 947.037 <0.001 JCI Overall 0.745 30.774 <0.001 [0.68,0.81] Multiple Regression 0.820 0.672 176.993 <0.001 MMU 0.354 7.624 <0.001 [0.28,0.43] IPSG 0.247 5.614 <0.001 [0.18,0.31] PCC 0.161 3.018 0.003 [0.06,0.26] AOP 0.098 1.818 0.070 [0.01,0.20] COP 0.104 1.736 0.083 [0.02,0.23] ACC -0.066 -1.406 0.160 [0.16,0.03] Notes: Simple linear regression tests the overall impact of JCI standards and multiple regression assesses the contributions of individual standards. Statistical significance was set at p ≤ 0.05, T > 1.96, or p < 0.05. The F-test assessed the model fit (p < 0.001, significant). VIF ranged from 3.070–5.688, indicating no severe multicollinearity. Predictors in multiple regressions were ordered from highest to lowest β coefficients. 95% CI = 95% confidence interval for β coefficients. Abbreviations: JCI, Joint Commission International; R, correlation coefficient; R², coefficient of determination; F, F-statistic; β, standardized regression coefficient; T, t-statistic; p, significance level; MMU = Medication Management and Use; IPSG = International Patient Safety Goals; PCC = Patient-Centered Care; AOP = Assessment of Patients; COP = Care of Patients; ACC = Access to Care and Continuity of Care. Hypothesis 2: Differences by Hospital Type Private hospitals (n = 222) outperformed government hospitals (n = 304) in JCI implementation across all standards (p < 0.001). Mean differences ranged from 0.65 (ACC: 5.33 vs. 4.68, 95% CI [0.45, 0.85]) to 0.96 (IPSG: 5.01 vs. 4.05, 95% CI [0.74, 1.18]) (Table 7). Table 7: Differences in JCI Standards Implementation by Hospital Type in Sana’a, Yemen (N = 526) Standard Hospital Type N Mean SD Mean Difference T p 95% CI IPSG Private 222 5.01 0.921 0.96 10.422 <0.001 [0.74,1.18] Governmental 304 4.05 1.173 AOP Private 222 5.19 0.978 0.87 8.622 <0.001 [0.65,1.09] Governmental 304 4.32 1.325 PCC Private 222 5.28 0.974 0.74 7.829 <0.001 [0.53,0.95] Governmental 304 4.54 1.179 COP Private 222 5.29 0.905 0.71 7.690 <0.001 [0.50,0.92] Governmental 304 4.58 1.208 MMU Private 222 5.20 0.982 0.75 7.409 <0.001 [0.53,0.97] Governmental 304 4.45 1.345 ACC Private 222 5.33 0.968 0.65 6.970 <0.001 [0.45,0.85] Governmental 304 4.68 1.181 Overall Private 222 5.15 0.938 0.76 8.614 <0.001 [0.55,0.97] Governmental 304 4.39 1.202 Notes: Independent samples t-tests compare means between hospital types. Mean Difference = Private Mean – Governmental Mean. Significance set at p ≤ 0.05; T > 1.96 or p < 0.001 indicates significant differences, favoring private hospitals. Standards are ordered from largest to smallest mean difference. 95% CI = 95% confidence interval for the mean difference. Abbreviations: JCI = Joint Commission International; IPSG = International Patient Safety Goals; AOP = Assessment of Patients; PCC = Patient-Centered Care; COP = Care of Patients; MMU = Medication Management and Use; ACC = Access to Care and Continuity of Care; SD = standard deviation; T = t-statistic; p = significance level. Discussion This study provides insights into the implementation of Joint Commission International (JCI) patient-centered standards and their impact on nursing performance in Sana’a, Yemen, a resource-constrained setting. The implementation of the JCI standards was moderately high (mean = 4.77, 68.1%) but uneven across domains. Access to Care and Continuity (ACC) scored the highest (mean = 4.95, 70.7%), reflecting robust practices in timely and coordinated care, while International Patient Safety Goals (IPSG) scored the lowest (mean = 4.46, 63.7%), indicating weaker adherence to safety protocols. Other standards—Care of Patients (COP, 69.7%), Patient-Centered Care (PCC, 69.3%), Medication Management and Use (MMU, 68.0%), and Assessment of Patients (AOP, 67.0%)—ranged from 67.0% to 69.7%, suggesting a generally positive but inconsistent adoption. The low IPSG score aligns with regional studies in Yemen, where Al-Jaradi et al. (2018) found that 57.5% of ICU nurses had moderate knowledge of ventilator-associated pneumonia (VAP) prevention, 36.8% had poor knowledge, and Al-Rabeei et al. (2019) reported that 52% of nurses had poor VAP prevention practices, indicating broader deficits in safety practices that may contribute to low IPSG adherence [20, 26]. The high reliability of the IPSG subscale (Cronbach’s alpha = 0.925) supported the robustness of this finding. Conversely, Alraimi and Al-Nashmi (2024) reported higher JCI compliance in Yemeni hospitals seeking accreditation, although their focus was on management standards rather than patient-centered standards [18]. Internationally, similar gaps were noted by Wu et al. (2021), who reported inadequate patient identification in Chinese hospitals, and Innab et al. (2022), who found suboptimal pain management knowledge among nurses in Jordan [27, 28]. These findings suggest that knowledge and practice deficits in patient safety protocols such as infection prevention are global challenges in resource-limited settings. Nursing performance was moderate (mean = 4.64, 66.3%), with the highest Performance Effectiveness (mean = 4.86, 69.4%), reflecting nurses’ focus on timely, team-based care, followed by Performance Efficiency (mean = 4.65, 66.4%), and the lowest Performance Indicators (mean = 4.41, 63.0%). The nursing performance scale was an adapted version of the Schwirian Six Dimension Scale, focusing on three dimensions (Efficiency, Effectiveness, Indicators) relevant to the Yemeni context with high reliability (Cronbach’s alpha: 0.897–0.944; overall: 0.956). This pattern echoes Alraimi and Shelke (2023), who found that job stress and organizational factors moderate nursing performance in Yemeni hospitals, yet nurses maintain moderate to excellent ratings [29]. The low performance indicator score (Cronbach’s alpha = 0.944) suggests that resource constraints and shared responsibilities with hospital leadership may hinder measurable outcomes, which is a trend observed in other developing contexts. Additionally, Al-Thaifani et al. (2020) reported low caring efficacy among nurses in Al-Thawra General Hospital, Sana’a (mean = 3.99), which may explain the moderate implementation of PCC in our study (mean = 4.85, 69.3%) despite its significant impact on performance (β = 0.161, p = 0.003) [8]. The emphasis on effectiveness indicates that nurses prioritize core caregiving duties to compensate for systemic limitations, which is a common adaptation in resource-constrained settings. The JCI standards significantly predicted nursing performance (R = 0.802, R² = 0.644, p < 0.001), explaining 64.4% of the variance, supporting the study’s conceptual model. Multiple regression analysis identified MMU (β = 0.354, p < 0.001), IPSG (β = 0.247, p 0.05). The strong influence of MMU aligns with Al-Jaradi et al. (2021), who found that only 16.8% of nurses in Sana’a had good knowledge of drug administration, with 64.2% at a fair level, indicating the need for structured protocols, such as MMU, to enhance performance [6]. Despite its low implementation rate, the significant role of the IPSG underscores the importance of safety protocols in improving nursing outcomes. This is supported by Day et al. (2013), who reported improved pediatric oncology care in Guatemala through MMU and safety goals [14], and Sun and Shen (2017), who noted enhanced care quality in China through MMU and IPSG [11]. PCC’s impact of PCC on PCC highlights the value of patient-centered communication, even in resource-limited settings. The lack of impact from ACC, AOP, and COP may stem from their indirect influence on daily nursing tasks or contextual barriers, such as staffing shortages in Yemen, which limit their practical application. Private hospitals (42.2% of the sample) outperformed government hospitals (57.8%) in JCI implementation across all standards (p < 0.001), with mean differences ranging from 0.65 (ACC) 0.96 (IPSG). This study included two governmental and four private hospitals (33.3% governmental and 66.7% private), reflecting Yemen’s urban healthcare landscape in which private hospitals often predominate. The better performance of private hospitals may be attributed to greater access to resources, more robust training programs, or stronger management practices, as private facilities in Yemen typically cater to higher-income patients and prioritize accreditation standards to attract clientele members. In contrast, governmental hospitals, which serve a larger proportion of the population, face greater resource constraints, as noted by the Yemen Ministry of Health (2021), with only 5% of hospitals achieving excellent compliance [7]. This disparity underscores the need for targeted interventions in government hospitals to bridge the gap and ensure equitable care quality across hospital types. Lower IPSG implementation and moderate nursing performance highlight the systemic challenges in Yemen’s healthcare system. Training gaps, as noted by Al-noani (2020), with only 26% of nurses trained in basic life support and resource shortages, as per the Yemen Ministry of Health (2021), are likely to hinder progress [7,30]. However, the significant effects of MMU, IPSG, and PCC suggest that these standards are critical leverage points for enhancing the quality of care. Local evidence supports the efficacy of training interventions. Haza et al. (2020) found significant improvements in nurses’ knowledge and practice of emergency care post-training at Al-Thawra General Hospital, Sana’a (p < 0.000) [31], and Alwsaby et al. (2019) reported enhanced knowledge of myocardial infarction care after a training program in Al-Hodeida (p < 0.05) [20]. These findings indicated that structured training programs can address knowledge deficits, particularly in terms of safety protocols (IPSG) and medication management (MMU). Policymakers should prioritize the implementation of MMU protocols, safety-goal training, and patient-centered communication skills while addressing disparities between private and governmental hospitals through equitable resource allocation. Such interventions could enhance nursing performance and ultimately, patient outcomes in Yemen’s urban hospitals. Limitations This study had several limitations. It focuses solely on patient-centered JCI standards and nursing performance, excluding other healthcare standards (e.g., management-focused JCI standards) and broader quality metrics (e.g., patient satisfaction). The sample was limited to six hospitals in Sana’a (two governmental and four private) with potentially missing regional or rural variations and included only nurses from emergency departments, inpatient wards, ICUs, and neonatal units, omitting other healthcare professionals (e.g., physicians and pharmacists). Self-reported data may introduce bias such as social desirability bias, in which nurses may overreport adherence to JCI standards. This cross-sectional design limits causality and trend analysis, preventing the assessment of how JCI implementation affects performance over time. Moderate multicollinearity (VIF: 3.070–5.688) in the regression models may affect the precision of the hospital-type comparisons. However, the high reliability of the questionnaire (Cronbach’s alpha: 0.897–0.980 for subscales, 0.982 overall) mitigated concerns regarding measurement errors. Future research should include rural hospitals, use objective metrics (e.g., medication error rates and infection rates), assess patient outcomes (e.g., mortality and readmission rates), and explore barriers to IPSG implementation and the role of hospital resources in refining interventions. Conclusion This study highlights the positive impact of JCI patient-centered standards on nursing performance in Sana’a, Yemen, despite the resource constraints. Moderately high implementation of JCI standards (mean = 4.77, 68.1%) and moderate nursing performance (mean = 4.64, 66.3%) demonstrated their potential to enhance care quality in urban hospitals (two governmental and four private hospitals; final sample: 57.8% governmental and 42.2% private hospitals). MMU, IPSG, and PCC significantly influenced performance, explaining 64.4% of the variance, although uneven adoption, particularly low IPSG scores (mean = 4.46, 63.7%), revealed gaps in patient-safety practices. Private hospitals outperformed government hospitals in terms of JCI implementation (p < 0.001), highlighting the disparities that need to be addressed. These findings underscore the need for targeted interventions focusing on medication safety protocols (MMU), safety-goal training (IPSG), and patient-centered communication (PCC) to address knowledge and practice deficits. Policymakers should prioritize structured training programs and equitable resource allocation to reduce disparities between private and governmental hospitals, ensuring that governmental facilities that serve a larger population can achieve similar quality of care. While these results may be generalizable to other urban hospitals in Yemen, they may not apply to rural settings because of differing resource availability. Adopting JCI standards offers a viable pathway to improve healthcare quality in Yemen; however, systemic challenges such as training gaps and resource shortages must be addressed to maximize their impact and ensure better patient outcomes. Abbreviations ACC: Access to Care and Continuity AOP: Assessment of Patients COP: Care of Patients ICU: Intensive Care Unit IPSG: International Patient Safety Goals JCI: Joint Commission International MMU: Medication Management and Use PCC: Patient-Centered Care SD: Standard Deviation SPSS: Statistical Package for the Social Sciences WHO: World Health Organization B: Regression Coefficient F: F-statistic N: Number of Participants R: Correlation Coefficient R²: Coefficient of Determination T: t-statistic VIF: Variance Inflation Factor Declarations Ethical Approval and Consent to Participate This study was approved by the Ethical Committee of the Center of Business Administration, Sana’a University. All participants provided written informed consent prior to participation and confidentiality was ensured through anonymous data collection. This study was conducted in compliance with the ethical principles outlined in the Declaration of Helsinki, ensuring the protection of the participants’ rights, safety, and well-being. Consent for Publication This was not applicable because no individual participant data (e.g., images and identifiable information) were included in this study. Availability of Data and Materials The datasets generated and analyzed during this study are not publicly available because of ethical restrictions protecting participant confidentiality, but are available from the corresponding author, (K.A.Q, [email protected] ) upon reasonable request, subject to approval by the Ethics Committee of Sana’a University. Competing Interests The authors declare no competing financial interests that could influence the outcomes or interpretation of this study. Funding This study did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sector. Authors’ Contributions K.A.Q. conceptualized the study, designed the questionnaire, supervised data collection, and drafted the manuscript. M.M.A. contributed to the study design and performed the statistical analyses. H.M.J. drafted the manuscript and reviewed it for critical intellectual content. All the authors have read and approved the final manuscript. Acknowledgements The authors thank the nursing staff of the participating hospitals (Al-Thawra General Hospital, 48 Model Hospital, Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital) for their cooperation. Gratitude has also been extended to hospital administration to facilitate data collection. References Alanazi AM, Almutairi AM, Aldhahi MI, et al. 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Knowledge of nurses toward drugs administration at public hospitals in Sana’a city-Yemen. International Journal of Advance Research in Nursing. 2021;4(2):25–30. doi:10.33545/nursing.2021.v4.i2a.181. Minister of Public Health and Population. Announcing the results of the evaluation of government bodies and hospitals at the level of the Republic. Minister of Public Health and Population. 2021. https://moh.gov.ye/en/news/1416. Accessed 27 Mar 2025. Al-Thaifani AA, Al-Akmar MA, Al-Rabeei NA. Nursing caring efficacy among nurses in Al-Thowrah Hospital in Sana’a city-Yemen. http://repository.alraziuni.edu.ye/123456789/51 (2020). Accessed 12 Apr 2025. Joint Commission International. A global leader for health care quality and patient safety. 2024. https://www.jointcommissioninternational.org/. Accessed 27 Mar 2025. Despotou G, Her J, Arvanitis TN. Nurses’ perceptions of Joint Commission International accreditation on patient safety in tertiary care in South Korea: a pilot study. 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Identifying gaps, barriers, and solutions in implementing pressure ulcer prevention programs. The Joint Commission Journal on Quality and Patient Safety. 2011;37:253–264. doi:10.1016/S1553-7250(11)37033-X. Joint Commission International. JCI accreditation standards for hospitals, 8th edition. 2024. https://www.jointcommissioninternational.org/. Accessed 27 Mar 2025. Al-Ammari A. Evaluation of the quality of health services in Yemeni hospitals in light of Joint Commission International standards. https://studies.yemennic.com/study?id=18022# (2021). Accessed 12 Apr 2025. Alraimi AA, Al-Nashmi MM. The interactive effect of the application of accreditation standards (JCIs) and the practice of administrative control in improving the quality of health services: a study on Yemeni hospitals. BMC Health Serv Res. 2024;24:1403. doi:10.1186/s12913-024-11894-0. Saif N. The impact of the application of accreditation standards in Jordanian private hospitals performance. Arab Journal of Administration. 2021;35. https://digitalcommons.aaru.edu.jo/aja/vol35/iss1/12. Accessed 27 Mar 2025. Alwsaby SA, Al-Rabeei NA, Baalawi A, Floos A. Effect of training program on nurses’ knowledge toward care of patients with myocardial infarction in Al-Thowrah Hospital, Al-Hodeida City, Yemen. http://repository.alraziuni.edu.ye/xmlui/handle/123456789/27 (2019). Accessed 12 Apr 2025. Tsang LF. Self-perceived performance-based training needs of senior nurse managers working in United Christian Hospital: a cross-sectional exploratory study. Int Arch Nurs Health Care. 2017;3. doi:10.23937/2469-5823/1510069. Schwirian PM. Evaluating the performance of nurses: a multidimensional approach. Nurs Res. 1978;27:347–51. Montalvo I. The National Database of Nursing Quality IndicatorsTM (NDNQI®). Online J Issues Nurs. 2008;12. doi:10.3912/OJIN.VOL12NO03MAN02. Ta’an WF, Rababah JA, Al-Hammouri MM, et al. Validation and cross-cultural adaptation of the six-dimension scale of nursing performance-Arabic version. BMC Nurs. 2024;23:1–8. doi:10.1186/S12912-024-01740-3. Krejcie RV, Morgan DW. Determining sample size for research activities. Educ Psychol Meas. 1970;30:607–610. doi:10.1177/001316447003000308. Al-Jaradi AFSM. Knowledge and practice of intensive care unit nurses toward prevention of ventilator-associated pneumonia at public hospitals in Sana’a City-Yemen. https://repository.alraziuni.edu.ye/xmlui/bitstream/handle/123456789/42/%d8%a7%d9%84%d8%b1%d8%b3%d8%a7%d9%84%d8%a9%20%d9%84%d9%84%d8%b7%d8%a8%d8%a 7%d8%b9%d8%a9%20%d8%b9%d8%a8%d8%af%d8%a1%d8%a7%d9%84%d9%81%d8%aa%d8%a1%d8%a7%d8%ad1.pdf?sequence=1&isAllowed=y (2018). Accessed 12 Apr 2025. Wu Y, Wu G, Jiang H. Research on application and effect of nursing risk management in improving patient safety goals. In: 2021 3rd World Congress on Chemistry, Biotechnology and Medicine. Francis Academic Press, UK; 2021. p. 25. Innab A, Alammar K, Alqahtani N, et al. The impact of a 12-hour educational program on nurses’ knowledge and attitudes regarding pain management: a quasi-experimental study. BMC Nurs. 2022;21:250. doi:10.1186/s12912-022-01028-4. Alraimi A, Shelke A. Job stress among nursing staff and its impact on performance in hospitals: a case study. 2023. doi:10.21203/rs.3.rs-3682449/v1. Al-Noani F. Evaluation of basic life support training program on intensive care nurses at Al-Thawra Hospital - Sana’a City-Yemen. https://studies.yemennic.com/study?id=17677 (2020). Accessed 12 Apr 2025. A Haza A, Al-Qubati FA, Mohammed MA, et al. Effect of an educational program on critical care nurses performance regarding emergency care for patients with pulmonary embolism. Assiut Scientific Nursing Journal. 2020;8:31–44. doi:10.21608/asnj.2020.78956. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFileS1StudyQuestionnaire.docx SupplementaryFileS2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6372401","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":450938355,"identity":"22d37fa6-7a11-4794-bf8b-358a96e35e6a","order_by":0,"name":"Kamal Ahmed Qabban","email":"","orcid":"","institution":"Sana’a University","correspondingAuthor":false,"prefix":"","firstName":"Kamal","middleName":"Ahmed","lastName":"Qabban","suffix":""},{"id":450938358,"identity":"f8f9c81c-5fc1-4b5a-b8a7-62c3e04cec89","order_by":1,"name":"Muneer Musleh Al-Wesabi","email":"","orcid":"","institution":"21 September University of Medical and Applied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Muneer","middleName":"Musleh","lastName":"Al-Wesabi","suffix":""},{"id":450938359,"identity":"882eaf51-d527-46db-a672-68779116b226","order_by":2,"name":"Haitham Mohammed Jowah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACAwaGBCB1QA7M4yFFizFJWkDgQGID0VrMGRgePuapuZM+f0YC44O3bQyJ/YS0WDYwJBvzHHuWu+FGArPhXKCWmQ2EHHaAIU06h+1w7gaJBDZpXqCWDQeI0vLvcLr8jAT23yAt+4nSktt2OIHhRgIbM9gWQn4xOAz0y9++w4YbzjxslpxzTsJ4BkFbjvckPpzx7bC8fHvywQ9vymxk+xsIWcPMkwBlMYLUSjgS1MHAwI7qEHvCOkbBKBgFo2CkAQCEAUMIrb03fgAAAABJRU5ErkJggg==","orcid":"","institution":"Sana’a University","correspondingAuthor":true,"prefix":"","firstName":"Haitham","middleName":"Mohammed","lastName":"Jowah","suffix":""}],"badges":[],"createdAt":"2025-04-03 23:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6372401/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6372401/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82161613,"identity":"c29ff43a-2f7e-41f8-baaa-e41e55512b73","added_by":"auto","created_at":"2025-05-07 08:39:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60564,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Participant Selection Process for the Study in Sana’a, Yemen Hospitals (N = 526).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6372401/v1/b68f1b23a41412cd2736bf2c.jpg"},{"id":82160156,"identity":"f6c40ecf-7c09-4bf8-af58-6106ebb2183d","added_by":"auto","created_at":"2025-05-07 08:31:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60126,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Model of the Impact of JCI Patient-Centered Standards on Nursing Performance.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6372401/v1/55e6be7f1d1ddd6af6ea5c91.jpg"},{"id":90890538,"identity":"92701e78-fe1a-4b35-bad3-d644b5e095dc","added_by":"auto","created_at":"2025-09-09 11:01:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1701851,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6372401/v1/88250e28-f2bb-49aa-942d-e20e26e4c28c.pdf"},{"id":82160159,"identity":"cd544001-83eb-428d-be05-40ca91158500","added_by":"auto","created_at":"2025-05-07 08:31:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35016,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileS1StudyQuestionnaire.docx","url":"https://assets-eu.researchsquare.com/files/rs-6372401/v1/e9637f3e6a7f3ce523483b2d.docx"},{"id":82163707,"identity":"a82a37cd-cbe6-4e84-9e9c-0acde0c8ec8c","added_by":"auto","created_at":"2025-05-07 08:55:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":454659,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6372401/v1/82af577fa4247a8ae43e4695.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Joint Commission International Patient-Centered Standards on Nursing Performance in Sana'a, Yemen Hospitals","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHealthcare quality is fundamental to effective medical services, driving societal progress, and improving quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The World Health Organization (WHO) underscores its importance, particularly in low- and middle-income countries that pursue universal health coverage [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In Yemen, prolonged conflict and economic instability have severely strained the healthcare system, leading to resource shortages, staffing deficits, and infrastructure deterioration [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These challenges have compromised care delivery, heightened medical error risks, and undermined patient safety, necessitating standardized quality frameworks.\u003c/p\u003e \u003cp\u003eNurses, pivotal to healthcare delivery, face significant barriers in Yemen, including inadequate training, heavy workload, and limited resources [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For instance, Al-Jaradi et al. (2021) revealed that only 16.8% of nurses in Sana\u0026rsquo;a public hospitals had good knowledge of drug administration, with 64.2% at a fair level, highlighting gaps in medication management skills [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A 2021 Ministry of Health assessment further revealed that only 5% of public and private hospitals have achieved high-quality benchmarks, underscoring systemic gaps [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These deficiencies, coupled with low caring efficacy among nurses (mean\u0026thinsp;=\u0026thinsp;3.99), as reported by Al-Thaifani et al. (2020), emphasize the urgent need for interventions to enhance nursing practice and elevate care standards in Yemen [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Joint Commission International (JCI) provides a globally recognized framework of patient-centered standards to improve healthcare quality and safety through accreditation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Previous studies have demonstrated its benefits in several contexts. In South Korea, nurses in JCI-accredited hospitals reported improved patient safety, although gaps in International Patient Safety Goals (IPSG) implementation persist [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In China, JCI standards enhance nursing management and improve patient identification and hand hygiene, thereby increasing patient satisfaction [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, several challenges remain. Medication management standards such as titration have raised concerns about care delays and documentation burdens [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], whereas cultural and leadership barriers hinder their adoption in diverse settings [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In the Middle East, JCI standards are linked to better care quality and positive nursing perceptions; however, their application in resource-scarce settings, such as Yemen, is underexplored. Insights from Guatemala highlight the difficulties of implementing JCI standards in low-income contexts, where infrastructure and staffing constraints pose barriers, emphasizing the need for tailored strategies such as staff training and leadership commitment [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Yemeni hospitals, nursing performance is hampered by resource constraints and inconsistent standardization, which elevate medical error risks and compromise patient outcomes. This study addresses this gap by examining the implementation of JCI patient-centered standards and their impact on nursing performance in Sana\u0026rsquo;a, Yemen, a setting marked by severe resource limitations. We hypothesized that JCI standards would positively influence nursing performance. By assessing adherence to key standards, such as IPSG, Access to Care and Continuity (ACC), and Medication Management and Use (MMU), and their effects on performance efficiency, effectiveness, and indicators, this research aims to provide actionable recommendations for improving healthcare quality in resource-constrained environments.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis cross-sectional study examined the association between the implementation of Joint Commission International (JCI) patient-centered standards and nursing performance in hospitals in Sana\u0026rsquo;a, Yemen, from August to October 2024. \u003cb\u003eThis design was selected due to its suitability for studying social phenomena, such as the implementation of JCI standards and their impact on nursing performance, allowing for a snapshot of current practices across multiple hospitals.\u003c/b\u003e The study was approved by the Ethical Committee of the Center of Business Administration, Sana\u0026rsquo;a University to ensure compliance with ethical standards. All participants provided written informed consent prior to participation and confidentiality was ensured through anonymous data collection. This study was conducted in compliance with the ethical principles outlined in the Declaration of Helsinki, ensuring the protection of the participants\u0026rsquo; rights, safety, and well-being.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSetting\u003c/h3\u003e\n\u003cp\u003eData were collected from August to October 2024 across six hospitals in Sana\u0026rsquo;a, Yemen: Al-Thawra General Hospital and 48 Model Hospitals (governmental; 33.3%), and Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital (private, 42.2%). These urban facilities vary in size and JCI accreditation status, providing diverse samples for assessing JCI standard implementation.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eOf 1,459 potentially eligible nursing staff across the six hospitals, 847 medically licensed nurses actively employed in emergency departments, inpatient wards, intensive care units (ICUs), or neonatal units were assessed for eligibility. Inclusion criteria required willingness to participate, while exclusion criteria eliminated nurses in outpatient/helper roles, those not in specified departments, or those with incomplete data. Using simple random sampling with proportional representation (Al-Thawra, 32.3%; 48 Model, 25.5%; others in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; governmental, 57.8%; private, 42.2%), 558 nurses were confirmed to be eligible. \u003cb\u003eProportional representation ensured that the sample from each hospital accurately reflected its study population, avoiding overburdening any single hospital and ensuring equitable representation across all facilities.\u003c/b\u003e To account for non-responses, 710 questionnaires were distributed, 621 were received (87.5% response rate), and 526 were analyzed after excluding 95 for incomplete data (n\u0026thinsp;=\u0026thinsp;59), outpatient/helper roles (n\u0026thinsp;=\u0026thinsp;24), or not being in specified departments (n\u0026thinsp;=\u0026thinsp;12). All the participants provided informed consent. The selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eThe independent variable was the implementation level of JCI patient-centered standards, comprising six domains: International Patient Safety Goals (IPSG), Access to Care and Continuity (ACC), Patient-Centered Care (PCC), Assessment of Patients (AOP), Care of Patients (COP), and Medication Management and Use (MMU), as outlined in the conceptual model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The dependent variable was nursing performance, measured across three dimensions: Performance Efficiency, Performance Effectiveness, and Performance Indicators, focusing on the dimensions most relevant to the JCI standards. Hospital type (government vs. private) and years of experience were included as covariates to explore differences in implementation and performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eData Sources and Measurement\u003c/h3\u003e\n\u003cp\u003eData were collected using a two-part questionnaire developed for this study and administered in Arabic (Supplementary File S1: Study Questionnaire, English translation). The questionnaire targeted nurses\u0026rsquo; perspectives on practical field practices, given their extensive involvement in implementing JCI standards and their deeper knowledge compared with other healthcare or administrative staff. It comprised 91 items:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePart 1\u003c/b\u003e: Demographic data (25 items), such as hospital name, department, job title, and years of experience.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePart 2\u003c/b\u003e: Scored items (66 items) assessing the study variables:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eJCI Patient-Centered Standards (42 items)\u003c/b\u003e: Covered in six domains: International Patient Safety Goals (IPSG, 9 items), Access to Care and Continuity (ACC, 7 items), Patient-Centered Care (PCC, 7 items), Assessment of Patients (AOP, 5 items), Care of Patients (COP, 8 items), and Medication Management and Use (MMU, 6 items)\u0026mdash;adapted from JCI (2024), and previous studies [\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNursing Performance (24 items)\u003c/b\u003e: Three dimensions were assessed: Performance Effectiveness (4 items), Performance Efficiency (5 items), and Performance Indicators (15 items), adapted from Schwirian (1978), the National Database of Nursing Quality Indicators (NDNQI), and previous studies [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Responses were recorded on a 7-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree, 7\u0026thinsp;=\u0026thinsp;strongly agree).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe questionnaire was developed by synthesizing these sources and validated using a two-step process. First, a panel of four experts\u0026mdash;two hospital administrators with over 15 years of experience in healthcare management and two nursing researchers with doctoral degrees in healthcare quality\u0026mdash;reviewed it for content validity. Second, a pilot test with 40 nurses from two Sana\u0026rsquo;a hospitals (excluded from the final sample) confirmed its clarity and cultural appropriateness, leading to minor wording revisions for improved comprehension.\u003c/p\u003e \u003cp\u003eThe psychometric properties of the questionnaire were evaluated using confirmatory factor analysis (CFA) with IBM SPSS AMOS along with reliability and validity metrics (Supplementary File S2). Both the six-factor JCI standards model and the three-factor nursing performance model were validated, with fit indices meeting acceptable thresholds (e.g., RMSEA\u0026thinsp;\u0026le;\u0026thinsp;0.08, CFI\u0026thinsp;\u0026ge;\u0026thinsp;0.90; Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2.3\u003c/span\u003e) and factor loadings ranging from 0.41 to 0.88 across subscales (Supplementary Figures \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2.1\u003c/span\u003e and S2.2). Convergent validity was confirmed, with composite reliability (CR) of 0.885\u0026ndash;0.932 and average variance extracted (AVE) of 0.513\u0026ndash;0.749, exceeding the thresholds of 0.70 for CR and 0.50 for AVE. Reliability was high, with Cronbach\u0026rsquo;s alpha values of 0.980 for JCI standards, 0.956 for nursing performance, and 0.982 overall. Detailed psychometric properties, including the subscale-specific CR, AVE, and Cronbach\u0026rsquo;s alpha values, are provided in Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2.1\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBias\u003c/h2\u003e \u003cp\u003eSelection bias was minimized through simple random sampling with proportional representation across hospitals. Non-response bias was reduced by distributing 710 questionnaires, achieving an 87.5% response rate. Information bias was mitigated using a standardized, pre-tested questionnaire with anonymous data collection to reduce social desirability bias. Incomplete responses were excluded to ensure data quality. Potential confounders (e.g., years of experience and hospital type) were addressed by stratifying the sample by hospital type and department and could be controlled for in the statistical analyses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Size\u003c/h3\u003e\n\u003cp\u003eThe study population comprised 847 nurses in emergency departments, inpatient wards, ICUs, and neonatal units across six hospitals, identified from 1,459 human resource records. The sample size of 558 nurses was determined using the Krejcie and Morgan table [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] (95% confidence level, 5% margin of error) with 80% power to detect a moderate effect size (f\u0026sup2; = 0.15) at α\u0026thinsp;=\u0026thinsp;0.05, based on prior JCI studies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. After exclusion, a simple random sampling resulted in a final sample of 526 nurses.\u003c/p\u003e\n\u003ch3\u003eStatistical Methods\u003c/h3\u003e\n\u003cp\u003eData were analyzed using SPSS version 26.0 and IBM SPSS AMOS for confirmatory factor analysis (CFA). Descriptive statistics (means, standard deviations, and percentages) were used to summarize the JCI standard implementation and nursing performance. Data normality was confirmed using skewness and kurtosis (\u0026plusmn;\u0026thinsp;2 threshold), justifying parametric tests. Multicollinearity among the JCI standard dimensions was assessed using variance inflation factors (VIF) and Tolerance, with VIF ranging from 3.070 to 5.688 (all \u0026lt;\u0026thinsp;10) and tolerance ranging from 0.176 to 0.326 (all \u0026gt;\u0026thinsp;0.10), indicating no significant multicollinearity. The Durbin-Watson statistic (1.78) confirmed the independence of the errors, with no autocorrelation (value between 1 and 3). Hypotheses were tested as follows: (1) simple linear regression assessed the overall impact of JCI standards on nursing performance (H1), reporting R, R\u0026sup2;, p-values, and 95% confidence intervals; (2) multiple linear regression identified the contributions of individual JCI standards, reporting standardized beta coefficients (β), p-values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and 95% confidence intervals; (3) independent t-tests comparing JCI implementation and nursing performance by hospital type (H2), with significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Missing data (3.2%) were handled using listwise deletion. Multicollinearity was assessed using variance inflation factors (VIF; 3.070\u0026ndash;5.688), which indicated moderate multicollinearity, which is a potential limitation.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThis study targeted 847 nursing staff across six hospitals in Sana\u0026rsquo;a, Yemen: Al-Thawra General Hospital, 48 Model Hospitals (governmental), Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital (private). Of the 710 distributed questionnaires, 621 were returned (87.5% response rate) and 526 were analyzed (62.1% of the study population) after excluding 95 participants for incomplete data (n\u0026thinsp;=\u0026thinsp;59), outpatient/helper roles (n\u0026thinsp;=\u0026thinsp;24), and those who did not being in specified departments (n\u0026thinsp;=\u0026thinsp;12). Simple random sampling, guided by the Krejcie and Morgan table, ensured a proportional representation from each hospital (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy Population and Sample Distribution Across Hospitals in Sana\u0026rsquo;a, Yemen\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy Population (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTargeted Sample (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDistributed Questionnaires (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReturned Questionnaires (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAnalyzed Questionnaires (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAnalyzed (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernmental Hospital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAl-Thawra General\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48 Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrivate Hospital\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAzal Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModern European\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoyal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYemeni Health International\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e847\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e558\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e710\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e621\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e526\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNotes\u003c/b\u003e: \u003cem\u003eSample size determined using the Krejcie and Morgan table for random sampling. Response rate\u0026thinsp;=\u0026thinsp;Returned/Distributed\u0026thinsp;=\u0026thinsp;621/710\u0026thinsp;=\u0026thinsp;87.5%. Analyzed proportion\u0026thinsp;=\u0026thinsp;Analyzed/Study Population\u0026thinsp;=\u0026thinsp;526/847\u0026thinsp;=\u0026thinsp;62.1%. Analyzed (%) reflects the proportion of the final sample (N\u0026thinsp;=\u0026thinsp;526). Final analyzed sample distribution: Governmental (304, 57.8%), Private (222, 42.2%). No statistical tests applied.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;N = number of participants; Targeted Sample (N) = intended sample size; Distributed Questionnaires (N) = questionnaires sent; Returned Questionnaires (N) = questionnaires received; Analyzed Questionnaires (N) = valid responses included in analysis.\u003c/em\u003e\u003c/p\u003e\u003ch2\u003eCharacteristics of Study Participants\u003c/h2\u003e\n\u003cp\u003eThe 526 participants were nursing staff from emergency, inpatient, ICU, and neonatal units in governmental and private hospitals in Sana\u0026rsquo;a. More than half were from governmental hospitals (57.8%, n = 304) versus private hospitals (42.2%, n = 222), reflecting the larger staff sizes at Al-Thawra and the 48 model hospitals (Table 1). Most participants worked in the general wards (53.2%, n = 280), followed by the ICU (30.4%, n = 160), emergency departments (11.8%, n = 62), and neonatal units (4.6%, n = 24). The sample had a small female majority (52.3%, n = 275; males: 47.7%, n = 251), consistent with Yemen\u0026rsquo;s nursing workforce. Experience-wise, 37.8% (n = 199) had 3\u0026ndash;6 years, 22.8% (n = 120) had over 10 years, 22.1% (n = 116) had less than three years, and 17.3% (n = 91) had 7\u0026ndash;10 years. Qualifications included 54.8% (n = 288) with a diploma, 43.5% (n = 229) with a bachelor\u0026rsquo;s degree, and 1.7% (n = 9) with higher education (e.g., a master\u0026rsquo;s degree or above), aligned with the Ministry of Health\u0026rsquo;s shift toward bachelor\u0026rsquo;s degrees (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Demographic Characteristics of Nursing Staff in Sana\u0026rsquo;a, Yemen (N = 526)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHospital Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDepartment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneral Ward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEmergency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeonatal Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eExperience (Years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u0026ndash;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQualification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBachelor\u0026rsquo;s Degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigher Studies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;No statistical tests applied. Higher Studies include master\u0026rsquo;s degrees or above.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;ICU = Intensive Care Unit.\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eImplementation Level of Patient-Centered JCI Standards\u003c/h2\u003e\n\u003cp\u003eThe implementation of JCI standards, assessed on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), showed a moderately high level (mean = 4.77, SD = 1.43, 68.1%). Access to Care and Continuity (ACC) scored the highest (mean = 4.95, SD = 1.38, 70.7%), reflecting robust practices in timely and coordinated care, whereas International Patient Safety Goals (IPSG) scored the lowest (mean = 4.46, SD = 1.48, 63.7%), indicating weaker adherence to safety protocols. The other standards, COP (69.7%), PCC (69.3%), MMU (68.0%), and AOP (67.0%), ranged from 67.0% to 69.7% (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Implementation Levels of JCI Patient-Centered Standards Among Nurses in Sana\u0026rsquo;a, Yemen (N = 526)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e70.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eCOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e69.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003ePCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e69.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eMMU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e68.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eAOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eIPSG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e63.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.427\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Means and standard deviations (SD) derived from a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Percentage = (Mean/7) \u0026times; 100, rounded to one decimal place. No inferential tests applied. Standards are ordered from highest to lowest mean score.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;JCI = Joint Commission International; ACC = Access to Care and Continuity of Care; COP = Care of Patients; PCC = Patient-Centered Care; MMU = Medication Management and Use; AOP = Assessment of Patients; IPSG = International Patient Safety Goals; SD = standard deviation.\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eNursing Performance Levels\u003c/h2\u003e\n\u003cp\u003eNursing performance averaged at a moderate level (mean = 4.64, SD = 1.39, 66.3%). Performance Effectiveness was the highest (mean = 4.86, SD = 1.32, 69.4%), followed by Performance Efficiency (mean = 4.65, SD = 1.45, 66.4%), and the Performance Indicators scored the lowest (mean = 4.41, SD = 1.40, 63.0%) (Table 4).\u003c/p\u003e\n\u003cp\u003eTable 4: Nursing Performance Levels Among Nurses in Sana\u0026rsquo;a, Yemen (N = 526)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003ePerformance Effectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e69.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003ePerformance Efficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e66.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003ePerformance Indicators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e63.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.389\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e66.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Means and standard deviations (SD) derived from a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Percentage = (Mean/7) \u0026times; 100, rounded to one decimal place. No inferential tests applied. Dimensions are ordered from highest to lowest mean score.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;SD = standard deviation.\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eTesting the Study Hypotheses\u003c/h2\u003e\n\u003ch3\u003eNormality of Data\u003c/h3\u003e\n\u003cp\u003eData normality was confirmed, with skewness and kurtosis values within \u0026plusmn;2 for all variables, including JCI standards (e.g., IPSG: skewness = -0.428, kurtosis = -0.426) and nursing performance (e.g., Performance Indicators: skewness = -0.400, kurtosis = 0.093), supporting the use of parametric tests (Table 5).\u003c/p\u003e\n\u003cp\u003eTable 5: Normality Test Results for Key Study Variables (N = 526)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkewness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKurtosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eJCI Standards (Overall)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eCOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003ePCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eMMU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eAOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eIPSG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003eNursing Performance (Overall)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003ePerformance Effectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003ePerformance Efficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003ePerformance Indicators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Means and standard deviations (SD) are derived from Tables 3 and 4. Skewness and Kurtosis values within \u0026plusmn;1 indicate normal distribution, justifying parametric tests (e.g., regression, t-tests). No significance testing applied.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;JCI = Joint Commission International; ACC = Access to Care and Continuity of Care; COP = Care of Patients; PCC = Patient-Centered Care; MMU = Medication Management and Use; AOP = Assessment of Patients; IPSG = International Patient Safety Goals; SD = standard deviation.\u003c/em\u003e\u003c/p\u003e\n\u003ch3\u003eHypothesis 1: Impact of JCI Standards on Nursing Performance\u003c/h3\u003e\n\u003cp\u003eSimple linear regression revealed that JCI standards significantly predicted nursing performance (R = 0.802, R\u0026sup2; = 0.644, p \u0026lt; 0.001), explaining 64.4% of the variance and supporting the conceptual model (Figure 2). Multiple regression analysis identified MMU (\u0026beta; = 0.354, 95% CI [0.28, 0.43], p \u0026lt; 0.001), IPSG (\u0026beta; = 0.247, 95% CI [0.18, 0.31], p \u0026lt; 0.001), and PCC (\u0026beta; = 0.161, 95% CI [0.06, 0.26], p = 0.003) as significant predictors, whereas ACC, AOP, and COP were non-significant (p \u0026gt; 0.05) (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: Regression Analysis of JCI Standards\u0026rsquo; Impact on Nursing Performance (N = 526)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel/Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep (F)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e947.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJCI Overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.68,0.81]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e176.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMMU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.28,0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIPSG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.18,0.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.06,0.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.01,0.20]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.02,0.23]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.16,0.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Simple linear regression tests the overall impact of JCI standards and multiple regression assesses the contributions of individual standards. Statistical significance was set at p \u0026le; 0.05, T \u0026gt; 1.96, or p \u0026lt; 0.05. The F-test assessed the model fit (p \u0026lt; 0.001, significant). VIF ranged from 3.070\u0026ndash;5.688, indicating no severe multicollinearity. Predictors in multiple regressions were ordered from highest to lowest \u0026beta; coefficients. 95% CI = 95% confidence interval for \u0026beta; coefficients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e JCI, Joint Commission International; R, correlation coefficient; R\u0026sup2;, coefficient of determination; F, F-statistic; \u0026beta;, standardized regression coefficient; T, t-statistic; p, significance level; MMU = Medication Management and Use; IPSG = International Patient Safety Goals; PCC = Patient-Centered Care; AOP = Assessment of Patients; COP = Care of Patients; ACC = Access to Care and Continuity of Care.\u003c/p\u003e\n\u003ch3\u003eHypothesis 2: Differences by Hospital Type\u003c/h3\u003e\n\u003cp\u003ePrivate hospitals (n = 222) outperformed government hospitals (n = 304) in JCI implementation across all standards (p \u0026lt; 0.001). Mean differences ranged from 0.65 (ACC: 5.33 vs. 4.68, 95% CI [0.45, 0.85]) to 0.96 (IPSG: 5.01 vs. 4.05, 95% CI [0.74, 1.18]) (Table 7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7: Differences in JCI Standards Implementation by Hospital Type in Sana\u0026rsquo;a, Yemen (N = 526)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIPSG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.74,1.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.65,1.09]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.53,0.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.50,0.92]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMMU\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.53,0.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eACC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.45,0.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e[0.55,0.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGovernmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Independent samples t-tests compare means between hospital types. Mean Difference = Private Mean \u0026ndash; Governmental Mean. Significance set at p \u0026le; 0.05; T \u0026gt; 1.96 or p \u0026lt; 0.001 indicates significant differences, favoring private hospitals. Standards are ordered from largest to smallest mean difference. 95% CI = 95% confidence interval for the mean difference.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;JCI = Joint Commission International; IPSG = International Patient Safety Goals; AOP = Assessment of Patients; PCC = Patient-Centered Care; COP = Care of Patients; MMU = Medication Management and Use; ACC = Access to Care and Continuity of Care; SD = standard deviation; T = t-statistic; p = significance level.\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides insights into the implementation of Joint Commission International (JCI) patient-centered standards and their impact on nursing performance in Sana’a, Yemen, a resource-constrained setting. The implementation of the JCI standards was moderately high (mean = 4.77, 68.1%) but uneven across domains. Access to Care and Continuity (ACC) scored the highest (mean = 4.95, 70.7%), reflecting robust practices in timely and coordinated care, while International Patient Safety Goals (IPSG) scored the lowest (mean = 4.46, 63.7%), indicating weaker adherence to safety protocols. Other standards—Care of Patients (COP, 69.7%), Patient-Centered Care (PCC, 69.3%), Medication Management and Use (MMU, 68.0%), and Assessment of Patients (AOP, 67.0%)—ranged from 67.0% to 69.7%, suggesting a generally positive but inconsistent adoption. The low IPSG score aligns with regional studies in Yemen, where Al-Jaradi et al. (2018) found that 57.5% of ICU nurses had moderate knowledge of ventilator-associated pneumonia (VAP) prevention, 36.8% had poor knowledge, and Al-Rabeei et al. (2019) reported that 52% of nurses had poor VAP prevention practices, indicating broader deficits in safety practices that may contribute to low IPSG adherence [20, 26]. The high reliability of the IPSG subscale (Cronbach’s alpha = 0.925) supported the robustness of this finding. Conversely, Alraimi and Al-Nashmi (2024) reported higher JCI compliance in Yemeni hospitals seeking accreditation, although their focus was on management standards rather than patient-centered standards [18]. Internationally, similar gaps were noted by Wu et al. (2021), who reported inadequate patient identification in Chinese hospitals, and Innab et al. (2022), who found suboptimal pain management knowledge among nurses in Jordan [27, 28]. These findings suggest that knowledge and practice deficits in patient safety protocols such as infection prevention are global challenges in resource-limited settings.\u003c/p\u003e\n\u003cp\u003eNursing performance was moderate (mean = 4.64, 66.3%), with the highest Performance Effectiveness (mean = 4.86, 69.4%), reflecting nurses’ focus on timely, team-based care, followed by Performance Efficiency (mean = 4.65, 66.4%), and the lowest Performance Indicators (mean = 4.41, 63.0%). The nursing performance scale was an adapted version of the Schwirian Six Dimension Scale, focusing on three dimensions (Efficiency, Effectiveness, Indicators) relevant to the Yemeni context with high reliability (Cronbach’s alpha: 0.897–0.944; overall: 0.956). This pattern echoes Alraimi and Shelke (2023), who found that job stress and organizational factors moderate nursing performance in Yemeni hospitals, yet nurses maintain moderate to excellent ratings [29]. The low performance indicator score (Cronbach’s alpha = 0.944) suggests that resource constraints and shared responsibilities with hospital leadership may hinder measurable outcomes, which is a trend observed in other developing contexts. Additionally, Al-Thaifani et al. (2020) reported low caring efficacy among nurses in Al-Thawra General Hospital, Sana’a (mean = 3.99), which may explain the moderate implementation of PCC in our study (mean = 4.85, 69.3%) despite its significant impact on performance (β = 0.161, p = 0.003) [8]. The emphasis on effectiveness indicates that nurses prioritize core caregiving duties to compensate for systemic limitations, which is a common adaptation in resource-constrained settings.\u003c/p\u003e\n\u003cp\u003eThe JCI standards significantly predicted nursing performance (R = 0.802, R² = 0.644, p \u0026lt; 0.001), explaining 64.4% of the variance, supporting the study’s conceptual model. Multiple regression analysis identified MMU (β = 0.354, p \u0026lt; 0.001), IPSG (β = 0.247, p \u0026lt; 0.001), and PCC (β = 0.161, p = 0.003) as the key predictors, whereas ACC, AOP, and COP were not significant (p \u0026gt; 0.05). The strong influence of MMU aligns with Al-Jaradi et al. (2021), who found that only 16.8% of nurses in Sana’a had good knowledge of drug administration, with 64.2% at a fair level, indicating the need for structured protocols, such as MMU, to enhance performance [6]. Despite its low implementation rate, the significant role of the IPSG underscores the importance of safety protocols in improving nursing outcomes. This is supported by Day et al. (2013), who reported improved pediatric oncology care in Guatemala through MMU and safety goals [14], and Sun and Shen (2017), who noted enhanced care quality in China through MMU and IPSG [11]. PCC’s impact of PCC on PCC highlights the value of patient-centered communication, even in resource-limited settings. The lack of impact from ACC, AOP, and COP may stem from their indirect influence on daily nursing tasks or contextual barriers, such as staffing shortages in Yemen, which limit their practical application.\u003c/p\u003e\n\u003cp\u003ePrivate hospitals (42.2% of the sample) outperformed government hospitals (57.8%) in JCI implementation across all standards (p \u0026lt; 0.001), with mean differences ranging from 0.65 (ACC) 0.96 (IPSG). This study included two governmental and four private hospitals (33.3% governmental and 66.7% private), reflecting Yemen’s urban healthcare landscape in which private hospitals often predominate. The better performance of private hospitals may be attributed to greater access to resources, more robust training programs, or stronger management practices, as private facilities in Yemen typically cater to higher-income patients and prioritize accreditation standards to attract clientele members. In contrast, governmental hospitals, which serve a larger proportion of the population, face greater resource constraints, as noted by the Yemen Ministry of Health (2021), with only 5% of hospitals achieving excellent compliance [7]. This disparity underscores the need for targeted interventions in government hospitals to bridge the gap and ensure equitable care quality across hospital types.\u003c/p\u003e\n\u003cp\u003eLower IPSG implementation and moderate nursing performance highlight the systemic challenges in Yemen’s healthcare system. Training gaps, as noted by Al-noani (2020), with only 26% of nurses trained in basic life support and resource shortages, as per the Yemen Ministry of Health (2021), are likely to hinder progress [7,30]. However, the significant effects of MMU, IPSG, and PCC suggest that these standards are critical leverage points for enhancing the quality of care. Local evidence supports the efficacy of training interventions. Haza et al. (2020) found significant improvements in nurses’ knowledge and practice of emergency care post-training at Al-Thawra General Hospital, Sana’a (p \u0026lt; 0.000) [31], and Alwsaby et al. (2019) reported enhanced knowledge of myocardial infarction care after a training program in Al-Hodeida (p \u0026lt; 0.05) [20]. These findings indicated that structured training programs can address knowledge deficits, particularly in terms of safety protocols (IPSG) and medication management (MMU). Policymakers should prioritize the implementation of MMU protocols, safety-goal training, and patient-centered communication skills while addressing disparities between private and governmental hospitals through equitable resource allocation. Such interventions could enhance nursing performance and ultimately, patient outcomes in Yemen’s urban hospitals.\u003c/p\u003e\n\u003ch2\u003eLimitations\u003c/h2\u003e\n\u003cp\u003eThis study had several limitations. It focuses solely on patient-centered JCI standards and nursing performance, excluding other healthcare standards (e.g., management-focused JCI standards) and broader quality metrics (e.g., patient satisfaction). The sample was limited to six hospitals in Sana’a (two governmental and four private) with potentially missing regional or rural variations and included only nurses from emergency departments, inpatient wards, ICUs, and neonatal units, omitting other healthcare professionals (e.g., physicians and pharmacists). Self-reported data may introduce bias such as social desirability bias, in which nurses may overreport adherence to JCI standards. This cross-sectional design limits causality and trend analysis, preventing the assessment of how JCI implementation affects performance over time. Moderate multicollinearity (VIF: 3.070–5.688) in the regression models may affect the precision of the hospital-type comparisons. However, the high reliability of the questionnaire (Cronbach’s alpha: 0.897–0.980 for subscales, 0.982 overall) mitigated concerns regarding measurement errors. Future research should include rural hospitals, use objective metrics (e.g., medication error rates and infection rates), assess patient outcomes (e.g., mortality and readmission rates), and explore barriers to IPSG implementation and the role of hospital resources in refining interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the positive impact of JCI patient-centered standards on nursing performance in Sana\u0026rsquo;a, Yemen, despite the resource constraints. Moderately high implementation of JCI standards (mean = 4.77, 68.1%) and moderate nursing performance (mean = 4.64, 66.3%) demonstrated their potential to enhance care quality in urban hospitals (two governmental and four private hospitals; final sample: 57.8% governmental and 42.2% private hospitals). MMU, IPSG, and PCC significantly influenced performance, explaining 64.4% of the variance, although uneven adoption, particularly low IPSG scores (mean = 4.46, 63.7%), revealed gaps in patient-safety practices. Private hospitals outperformed government hospitals in terms of JCI implementation (p \u0026lt; 0.001), highlighting the disparities that need to be addressed. These findings underscore the need for targeted interventions focusing on medication safety protocols (MMU), safety-goal training (IPSG), and patient-centered communication (PCC) to address knowledge and practice deficits. Policymakers should prioritize structured training programs and equitable resource allocation to reduce disparities between private and governmental hospitals, ensuring that governmental facilities that serve a larger population can achieve similar quality of care. While these results may be generalizable to other urban hospitals in Yemen, they may not apply to rural settings because of differing resource availability. Adopting JCI standards offers a viable pathway to improve healthcare quality in Yemen; however, systemic challenges such as training gaps and resource shortages must be addressed to maximize their impact and ensure better patient outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACC: Access to Care and Continuity\u003cbr\u003e\u0026nbsp;AOP: Assessment of Patients\u0026nbsp;\u003cbr\u003e\u0026nbsp;COP: Care of Patients\u003cbr\u003e\u0026nbsp;ICU: Intensive Care Unit\u003cbr\u003e\u0026nbsp;IPSG: International Patient Safety Goals\u003cbr\u003e\u0026nbsp;JCI: Joint Commission International\u003cbr\u003e\u0026nbsp;MMU: Medication Management and Use\u003cbr\u003e\u0026nbsp;PCC: Patient-Centered Care\u003cbr\u003e\u0026nbsp;SD: Standard Deviation\u003cbr\u003e\u0026nbsp;SPSS: Statistical Package for the Social Sciences\u003cbr\u003e\u0026nbsp;WHO: World Health Organization\u003cbr\u003e\u0026nbsp;B: Regression Coefficient\u003cbr\u003e\u0026nbsp;F: F-statistic\u003cbr\u003e\u0026nbsp;N: Number of Participants\u003cbr\u003e\u0026nbsp;R: Correlation Coefficient\u003cbr\u003e\u0026nbsp;R\u0026sup2;: Coefficient of Determination\u003cbr\u003e\u0026nbsp;T: t-statistic\u003cbr\u003e\u0026nbsp;VIF: Variance Inflation Factor\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical Approval and Consent to Participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Ethical Committee \u0026nbsp;of the Center of Business Administration, Sana\u0026rsquo;a University. All participants provided written informed consent prior to participation and confidentiality was ensured through anonymous data collection. This study was conducted in compliance with the ethical principles outlined in the Declaration of Helsinki, ensuring the protection of the participants\u0026rsquo; rights, safety, and well-being.\u003c/p\u003e\n\u003ch2\u003eConsent for Publication\u003c/h2\u003e\n\u003cp\u003eThis was not applicable because no individual participant data (e.g., images and identifiable information) were included in this study.\u003c/p\u003e\n\u003ch2\u003eAvailability of Data and Materials\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and analyzed during this study are not publicly available because of ethical restrictions protecting participant confidentiality, but are available from the corresponding author, (K.A.Q, [email protected]) upon reasonable request, subject to approval by the Ethics Committee of Sana\u0026rsquo;a University.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing financial interests that could influence the outcomes or interpretation of this study.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sector.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e\n\u003cp\u003eK.A.Q. conceptualized the study, designed the questionnaire, supervised data collection, and drafted the manuscript. M.M.A.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003econtributed to the study design and performed the statistical analyses. H.M.J. drafted the manuscript and reviewed it for critical intellectual content. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors thank the nursing staff of the participating hospitals (Al-Thawra General Hospital, 48 Model Hospital, Azal Model Hospital, Modern European Hospital, Royal Hospital, and Yemeni Health International Hospital) for their cooperation. Gratitude has also been extended to hospital administration to facilitate data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlanazi AM, Almutairi AM, Aldhahi MI, et al. The intersection of health rehabilitation services with quality of life in Saudi Arabia: current status and future needs. Healthcare. 2023;11:389. doi:10.3390/healthcare11030389.\u003c/li\u003e\n\u003cli\u003eOjogiwa OT, Qwabe BR. The practicability of competing value framework as a stride towards public service delivery improvement in the health sector. Transylvanian Review of Administrative Sciences. 2023;19:101\u0026ndash;117. doi:10.24193/tras.69E.6.\u003c/li\u003e\n\u003cli\u003eOECD/WHO/World Bank Group. Delivering quality health services: a global imperative. World Health Organization; 2018. doi:10.1787/9789264300309-en.\u003c/li\u003e\n\u003cli\u003eGarber K, Fox C, Abdalla M, et al. Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis. Lancet Glob Health. 2020;8. doi:10.1016/S2214-109X(20)30359-4.\u003c/li\u003e\n\u003cli\u003eAl-Rshoud FM, Abujledan HM, ALsanabani NT, et al. Yemen health care crisis: challenges in Yemen during the COVID-19 pandemic. HPHR Journal. 2021. doi:10.54111/0001/cc3.\u003c/li\u003e\n\u003cli\u003eAl-Jaradi A, Hazaa AA, Odhah MA. Knowledge of nurses toward drugs administration at public hospitals in Sana\u0026rsquo;a city-Yemen. International Journal of Advance Research in Nursing. 2021;4(2):25\u0026ndash;30. doi:10.33545/nursing.2021.v4.i2a.181.\u003c/li\u003e\n\u003cli\u003eMinister of Public Health and Population. Announcing the results of the evaluation of government bodies and hospitals at the level of the Republic. Minister of Public Health and Population. 2021. https://moh.gov.ye/en/news/1416. Accessed 27 Mar 2025.\u003c/li\u003e\n\u003cli\u003eAl-Thaifani AA, Al-Akmar MA, Al-Rabeei NA. Nursing caring efficacy among nurses in Al-Thowrah Hospital in Sana\u0026rsquo;a city-Yemen. http://repository.alraziuni.edu.ye/123456789/51 (2020). Accessed 12 Apr 2025.\u003c/li\u003e\n\u003cli\u003eJoint Commission International. A global leader for health care quality and patient safety. 2024. https://www.jointcommissioninternational.org/. Accessed 27 Mar 2025.\u003c/li\u003e\n\u003cli\u003eDespotou G, Her J, Arvanitis TN. Nurses\u0026rsquo; perceptions of Joint Commission International accreditation on patient safety in tertiary care in South Korea: a pilot study. J Nurs Regul. 2020;10:30\u0026ndash;36. doi:10.1016/S2155-8256(20)30011-9.\u003c/li\u003e\n\u003cli\u003eSun T, Shen G. The application of patient safety goals in nursing management at health management center. Chinese Journal of Practical Nursing. 2017;36:2056\u0026ndash;2059. doi:10.3760/CMA.J.ISSN.1672-7088.2017.26.015.\u003c/li\u003e\n\u003cli\u003eDavidson JE, Doran N, Petty A, et al. Survey of nurses\u0026rsquo; experiences applying The Joint Commission\u0026rsquo;s medication management titration standards. American Journal of Critical Care. 2021;30:365\u0026ndash;374. doi:10.4037/ajcc2021716.\u003c/li\u003e\n\u003cli\u003eZhang H, Huang S-T, Bittle MJ, et al. Perceptions of Chinese hospital leaders on Joint Commission International accreditation: a qualitative study. Front Public Health. 2023;11. doi:10.3389/fpubh.2023.1258600.\u003c/li\u003e\n\u003cli\u003eDay SW, McKeon LM, Garcia J, et al. Use of Joint Commission International standards to evaluate and improve pediatric oncology nursing care in Guatemala. Pediatr Blood Cancer. 2013;60:810\u0026ndash;815. doi:10.1002/pbc.24318.\u003c/li\u003e\n\u003cli\u003eJankowski IM, Nadzam DM. Identifying gaps, barriers, and solutions in implementing pressure ulcer prevention programs. The Joint Commission Journal on Quality and Patient Safety. 2011;37:253\u0026ndash;264. doi:10.1016/S1553-7250(11)37033-X.\u003c/li\u003e\n\u003cli\u003eJoint Commission International. JCI accreditation standards for hospitals, 8th edition. 2024. https://www.jointcommissioninternational.org/. Accessed 27 Mar 2025.\u003c/li\u003e\n\u003cli\u003eAl-Ammari A. Evaluation of the quality of health services in Yemeni hospitals in light of Joint Commission International standards. https://studies.yemennic.com/study?id=18022# (2021). Accessed 12 Apr 2025.\u003c/li\u003e\n\u003cli\u003eAlraimi AA, Al-Nashmi MM. The interactive effect of the application of accreditation standards (JCIs) and the practice of administrative control in improving the quality of health services: a study on Yemeni hospitals. BMC Health Serv Res. 2024;24:1403. doi:10.1186/s12913-024-11894-0.\u003c/li\u003e\n\u003cli\u003eSaif N. The impact of the application of accreditation standards in Jordanian private hospitals performance. Arab Journal of Administration. 2021;35. https://digitalcommons.aaru.edu.jo/aja/vol35/iss1/12. Accessed 27 Mar 2025.\u003c/li\u003e\n\u003cli\u003eAlwsaby SA, Al-Rabeei NA, Baalawi A, Floos A. Effect of training program on nurses\u0026rsquo; knowledge toward care of patients with myocardial infarction in Al-Thowrah Hospital, Al-Hodeida City, Yemen. http://repository.alraziuni.edu.ye/xmlui/handle/123456789/27 (2019). Accessed 12 Apr 2025.\u003c/li\u003e\n\u003cli\u003eTsang LF. Self-perceived performance-based training needs of senior nurse managers working in United Christian Hospital: a cross-sectional exploratory study. Int Arch Nurs Health Care. 2017;3. doi:10.23937/2469-5823/1510069.\u003c/li\u003e\n\u003cli\u003eSchwirian PM. Evaluating the performance of nurses: a multidimensional approach. Nurs Res. 1978;27:347\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eMontalvo I. The National Database of Nursing Quality IndicatorsTM (NDNQI\u0026reg;). Online J Issues Nurs. 2008;12. doi:10.3912/OJIN.VOL12NO03MAN02.\u003c/li\u003e\n\u003cli\u003eTa\u0026rsquo;an WF, Rababah JA, Al-Hammouri MM, et al. Validation and cross-cultural adaptation of the six-dimension scale of nursing performance-Arabic version. BMC Nurs. 2024;23:1\u0026ndash;8. doi:10.1186/S12912-024-01740-3.\u003c/li\u003e\n\u003cli\u003eKrejcie RV, Morgan DW. Determining sample size for research activities. Educ Psychol Meas. 1970;30:607\u0026ndash;610. doi:10.1177/001316447003000308.\u003c/li\u003e\n\u003cli\u003eAl-Jaradi AFSM. Knowledge and practice of intensive care unit nurses toward prevention of ventilator-associated pneumonia at public hospitals in Sana\u0026rsquo;a City-Yemen. https://repository.alraziuni.edu.ye/xmlui/bitstream/handle/123456789/42/%d8%a7%d9%84%d8%b1%d8%b3%d8%a7%d9%84%d8%a9%20%d9%84%d9%84%d8%b7%d8%a8%d8%a\u003cbr/\u003e7%d8%b9%d8%a9%20%d8%b9%d8%a8%d8%af%d8%a1%d8%a7%d9%84%d9%81%d8%aa%d8%a1%d8%a7%d8%ad1.pdf?sequence=1\u0026amp;isAllowed=y (2018). Accessed 12 Apr 2025.\u003c/li\u003e\n\u003cli\u003eWu Y, Wu G, Jiang H. Research on application and effect of nursing risk management in improving patient safety goals. In: 2021 3rd World Congress on Chemistry, Biotechnology and Medicine. Francis Academic Press, UK; 2021. p. 25.\u003c/li\u003e\n\u003cli\u003eInnab A, Alammar K, Alqahtani N, et al. The impact of a 12-hour educational program on nurses\u0026rsquo; knowledge and attitudes regarding pain management: a quasi-experimental study. BMC Nurs. 2022;21:250. doi:10.1186/s12912-022-01028-4.\u003c/li\u003e\n\u003cli\u003eAlraimi A, Shelke A. Job stress among nursing staff and its impact on performance in hospitals: a case study. 2023. doi:10.21203/rs.3.rs-3682449/v1.\u003c/li\u003e\n\u003cli\u003eAl-Noani F. Evaluation of basic life support training program on intensive care nurses at Al-Thawra Hospital - Sana\u0026rsquo;a City-Yemen. https://studies.yemennic.com/study?id=17677 (2020). Accessed 12 Apr 2025.\u003c/li\u003e\n\u003cli\u003eA Haza A, Al-Qubati FA, Mohammed MA, et al. Effect of an educational program on critical care nurses performance regarding emergency care for patients with pulmonary embolism. Assiut Scientific Nursing Journal. 2020;8:31\u0026ndash;44. doi:10.21608/asnj.2020.78956.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Patient-Centered Care, Nursing Performance, Hospital Accreditation, JCI Standards, Healthcare Quality","lastPublishedDoi":"10.21203/rs.3.rs-6372401/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6372401/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003e: Yemen\u0026rsquo;s healthcare system faces challenges such as inadequate training and resource shortages, impacting nursing performance. This study examined the impact of patient-centered standards of the Joint Commission International (JCI) on nursing performance in Sana\u0026rsquo;a, Yemen, a resource-constrained setting.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted from August to October 2024 in six hospitals in Sana\u0026rsquo;a, Yemen. A simple random sample of 526 nurses from emergency, inpatient, intensive care unit, and neonatal units completed a two-part questionnaire assessing JCI standards (42 items) and nursing performance (24 items) on a 7-point Likert scale. Confirmatory factor analysis (CFA) validated the constructs \u003cb\u003eusing IBM SPSS AMOS\u003c/b\u003e. Regression analyses, t-tests, and descriptive statistics were performed using SPSS 26.0.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e The implementation of JCI standards was moderately high (mean\u0026thinsp;=\u0026thinsp;4.77, 68.1%), with Access to Care and Continuity highest (mean\u0026thinsp;=\u0026thinsp;4.95, 70.7%) and International Patient Safety Goals lowest (mean\u0026thinsp;=\u0026thinsp;4.46, 63.7%). The nursing performance was moderate (mean\u0026thinsp;=\u0026thinsp;4.64, 66.3%). JCI standards significantly predicted performance (R\u0026sup2; = 0.644, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) driven by Medication Management and Use (MMU), International Patient Safety Goals (IPSG), and Patient-Centered Care (PCC). Private hospitals outperformed government hospitals in JCI implementation across all standards (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with mean differences ranging from 0.65\u0026minus;0.96.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eJCI standards can enhance the quality of care in Yemen, despite systemic challenges. Targeted training in safety protocols and equitable resource allocation, particularly in governmental hospitals, are recommended to address these gaps and improve healthcare quality.\u003c/p\u003e","manuscriptTitle":"Impact of Joint Commission International Patient-Centered Standards on Nursing Performance in Sana'a, Yemen Hospitals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 08:31:21","doi":"10.21203/rs.3.rs-6372401/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05b1dc45-21cd-4e82-9c5d-7a0ba1efc3b1","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-09T10:53:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 08:31:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6372401","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6372401","identity":"rs-6372401","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}