Insights into the Allocation of Pharmaceutical Human Resources and Pharmacy Service Development Evidence from Regional Healthcare Institutions

Insights into the Allocation of Pharmaceutical Human Resources and Pharmacy Service Development Evidence from Regional Healthcare Institutions | 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 Insights into the Allocation of Pharmaceutical Human Resources and Pharmacy Service Development Evidence from Regional Healthcare Institutions Jian Yang, Quanzhi Wei, Jingyi Jiao, Xin Yang, Zaixian Yang, Zhiying Wen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5821042/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 Background The allocation of pharmaceutical human resources and the development of pharmacy services are critical to ensuring effective, safe, and rational medication use within healthcare systems. Regional healthcare institutions, especially in resource-constrained settings, face significant challenges, including workforce shortages, uneven skill distribution, and limited integration of advanced pharmacy practices. This study aims to provide evidence-based insights into workforce allocation and pharmacy service development in these settings. Methods A cross-sectional study was conducted across healthcare institutions in Yunnan Province, China, including tertiary, secondary, and primary facilities. Data were collected through a structured questionnaire targeting pharmaceutical personnel actively engaged in service delivery. Variables assessed included demographic and professional characteristics, service participation, and institutional factors. Statistical analyses included descriptive statistics, cluster analysis, multidimensional scaling, and regression analysis to explore patterns and relationships. Results The dataset included 2,905 participants, with 78.24% female and 21.76% male respondents. The majority (78%) were aged 20–40 years, and educational attainment was high, with 77.46% holding a bachelor’s degree, 15.93% a master’s degree or higher, and only 6.61% an associate degree or lower. Service participation varied across activities: 50.36% of respondents were involved in medication reconciliation, 47.23% in clinical consultations, and only 24.68% in medication education. Regression analysis revealed that age and professional title were significant predictors of salary, highlighting disparities in career progression and compensation distribution. Cluster analysis identified distinct participation patterns, segregating respondents into high and low engagement groups, underscoring variability in service involvement. The Gini coefficient for salary distribution was 0.17, indicating a relatively equitable distribution. Conclusions This study highlights critical challenges and opportunities in the allocation of pharmaceutical human resources and the delivery of pharmacy services in regional healthcare institutions. Findings emphasize the need for targeted training programs, equitable resource distribution, and structured career development pathways. These results provide valuable insights for policymakers and healthcare administrators to enhance workforce development and optimize pharmacy services, particularly in resource-constrained settings. Pharmaceutical Human Resources Pharmacy Service Development Regional Healthcare Institutions Workforce Allocation Service Participation Patterns Figures Figure 1 Figure 2 Plain Language Summary This study investigates the allocation of pharmaceutical human resources and the development of pharmacy services within healthcare institutions in Yunnan Province, China. Challenges such as workforce shortages, uneven resource distribution, and limited patient-centered services (e.g., medication education) are identified. Through the analysis of data from over 2,900 pharmaceutical staff, this study underscores the need for targeted training programs, equitable career pathways, and improved access to pharmacy services in underserved areas. The findings provide actionable insights to guide strategies for developing a more effective, sustainable, and equitable health workforce. Implications for Health Workforce Policy This study offers valuable guidance for policymakers to address disparities in pharmaceutical workforce allocation and enhance pharmacy service delivery. Recommendations include ensuring equitable resource distribution, integrating advanced pharmacy practices into routine healthcare, and prioritizing investments in training programs. Strengthening the capacity of primary healthcare institutions, particularly in resource-constrained settings, can improve service accessibility, reduce inequalities, and enhance the overall quality of healthcare delivery. These strategies contribute to building a more robust and inclusive health workforce system, aligned with the goals of achieving universal health coverage and equity in healthcare. 1 Introduction The allocation of pharmaceutical human resources and the development of pharmacy services are critical to ensuring the effective, safe, and rational use of medications within healthcare systems[ 1 ]. The increasing complexity of therapeutic regimens, the rising prevalence of chronic diseases, and the demands of aging populations have amplified the need for a well-structured and adequately resourced pharmaceutical workforce[ 2 ]. This is particularly evident in regional healthcare institutions, which frequently face challenges such as limited resources, workforce shortages, and inequitable distribution of services[ 3 ]. Addressing these issues requires a comprehensive understanding of the factors that influence pharmaceutical human resource allocation and pharmacy service delivery[ 4 ]. Pharmacy services have evolved significantly over the past few decades, transitioning from traditional medication dispensing to include clinical pharmacy practices, medication reconciliation, therapeutic drug monitoring, and patient-centered education[ 5 ]. This expansion necessitates a pharmaceutical workforce with advanced competencies in both technical and interpersonal domains. However, there is a notable gap in the literature concerning the allocation and optimization of pharmaceutical human resources in regional healthcare settings[ 6 ]. These settings, often marked by disparities in infrastructure and access to care, provide a unique lens for examining the dynamics of pharmacy service development and workforce deployment. Understanding these dynamics is crucial for improving access to high-quality pharmacy services in underserved areas[ 7 ]. Globally, optimizing pharmaceutical human resources and expanding pharmacy services have been recognized as fundamental to advancing healthcare systems. In high-income countries such as the United States, Canada, and the United Kingdom, pharmacists have become integral members of multidisciplinary healthcare teams, contributing to chronic disease management, patient education, and medication therapy optimization[ 8 ]. These advancements are supported by robust educational systems, widespread adoption of clinical pharmacy practices, and policies incentivizing the integration of pharmacists into primary care. Conversely, middle- and low-income countries, including India, Brazil, and South Africa, face significant barriers such as workforce shortages, insufficient training opportunities, and limited financial resources for expanding pharmacy services[ 9 ]. Strategies like telepharmacy, task-shifting, and adherence to Good Pharmacy Practice (GPP) guidelines, as recommended by the World Health Organization, have shown potential in addressing these challenges[ 10 ]. In East Asia, Taiwan's pharmacist integration in primary care clinics and Japan's "pharmacist-at-home" model provide regionally adapted solutions for enhancing pharmacy services under resource-constrained conditions[ 11 ]. Regional healthcare institutions play a vital role in delivering healthcare services in underserved areas but face unique barriers that hinder the implementation of advanced pharmacy services. These barriers include an uneven distribution of workforce resources, limited access to professional training, and the insufficient integration of clinical pharmacy practices into routine care[ 12 ]. Nevertheless, these institutions offer critical insights into the interplay between resource allocation and service delivery, revealing strategies to enhance the capacity and quality of pharmacy services. Moreover, regional healthcare settings provide an opportunity to explore how systemic reforms and resource optimization can improve healthcare equity and access[ 13 ]. This study aims to evaluate the current state of pharmaceutical human resources and pharmacy services in regional healthcare institutions, focusing on their allocation, utilization, and service development. By analyzing workforce characteristics and participation in pharmacy services, the study seeks to identify key determinants of effective pharmacy service delivery and propose evidence-based strategies to optimize pharmaceutical human resource allocation. Integrating insights from both national and international contexts, this research emphasizes the importance of aligning workforce strategies with the evolving demands of healthcare systems. The findings of this study will provide valuable guidance for healthcare policymakers, administrators, and practitioners in designing and implementing targeted interventions to improve pharmacy service delivery. Furthermore, the study seeks to contribute to the broader discourse on pharmaceutical workforce management by offering scalable models for service expansion, particularly in resource-constrained and regional contexts. By addressing current gaps in the knowledge base and offering actionable recommendations, this research aims to advance pharmacy practice and improve healthcare outcomes in underserved areas. 2 Methods 2.1 Study Design and Setting This cross-sectional study was designed to evaluate the allocation of pharmaceutical human resources and the current status of pharmacy services in regional healthcare institutions. The research was conducted in Yunnan Province, China, which was selected due to its diverse healthcare infrastructure, demographic composition, and socioeconomic characteristics. These factors reflect common challenges faced by resource-constrained settings, such as workforce shortages, service disparities, and varying institutional capacities. By including tertiary, secondary, and primary healthcare institutions, the study ensured a comprehensive examination of the pharmaceutical workforce and service delivery across different levels of the healthcare system. The focus on Yunnan Province provides a relevant and representative case to analyze how institutional factors and human resource allocation impact pharmacy services in regional contexts, offering insights applicable to other similar settings. 2.2 Sample Size Calculation The sample size for this study was calculated to ensure sufficient power for analyzing the allocation of pharmaceutical human resources and pharmacy service delivery in Yunnan Province. For determining the sample size, the formula used was n = z 2 × p ×(1 − p )/ d 2 , where 'z' is the z-score for a 95% confidence level (1.96), 'p' is the estimated proportion of the population exhibiting the attribute (assumed to be 0.5), and 'd' is the margin of error (set at 0.02), a minimum required sample size of 2,401 participants was calculated. To account for a potential 10% non-response or exclusion rate, the initial target sample size was calculated to be 2,641 participants. Ultimately, 2,905 individuals were surveyed across tertiary, secondary, and primary healthcare institutions. This robust sample size ensures reliable findings and enables detailed analyses of the relationships between human resource allocation, institutional factors, and pharmacy service delivery in resource-constrained settings. 2.3 Data Collection Data were collected using a structured questionnaire distributed to pharmacists and related personnel actively involved in the participating institutions. The questionnaire was developed based on an extensive review of existing literature and refined through consultations with domain experts to ensure content validity and relevance. It comprised sections capturing demographic details, professional qualifications, pharmacy service participation, and institutional characteristics. Questions specifically assessed engagement in pharmacy services, including medication reconciliation, clinical pharmacy consultations, therapeutic monitoring, and patient education. Additional items explored perceived challenges in service implementation, such as workforce shortages, resource limitations, and skill gaps. To ensure accessibility and inclusivity, data collection employed both electronic and paper-based surveys, accommodating participants in varying healthcare settings. Participation was entirely voluntary, with informed consent obtained before survey completion. The multi-modal approach facilitated a robust and diverse dataset for comprehensive analysis. 2.4 Variables and Measures This study analyzed variables related to pharmaceutical human resource allocation and pharmacy service development. Independent variables included demographic and professional characteristics such as age, gender, educational level, professional title, years of experience, and job roles. Pharmacy service participation was measured by involvement in activities like prescription review, medication reconciliation, therapeutic monitoring, and patient education. Institutional characteristics, such as facility type (tertiary, secondary, or primary), resource availability, and workload distribution, were also recorded. Dependent variables focused on the extent of pharmacy service participation and barriers to implementation, such as staffing shortages and resource limitations. This comprehensive variable selection allowed for an in-depth analysis of the factors influencing pharmacy service delivery and workforce optimization. 2.5 Statistical Analysis Statistical analyses were conducted using specialized software to identify patterns and relationships between variables. Descriptive statistics, including frequencies, percentages, means, and standard deviations, summarized participant demographics, professional characteristics, and institutional contexts. Inferential statistics, such as chi-square tests and ANOVA, were applied to examine associations between independent variables (e.g., age, professional title, and years of experience) and dependent variables (e.g., service participation levels and reported barriers). Cluster analysis using the k-means method grouped participants and institutions based on service participation profiles and workforce characteristics, highlighting variations across different healthcare settings. Statistical significance was set at p < 0.05 for all analyses, ensuring rigorous evaluation of factors influencing pharmacy service delivery in resource-constrained environments. 2.6 Ethical Considerations The study was conducted in compliance with the principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board of Kunming Medical University. Participants were informed about the purpose and scope of the study and provided written consent before data collection. Anonymity and confidentiality of all participants and institutions were strictly maintained, and all responses were de-identified prior to analysis. The use of the data was restricted to research purposes, ensuring the privacy and rights of all participants. 3 Results 3.1 Demographic, Educational, and Economic Insights into the Pharmaceutical Workforce in Yunnan Table 1 provides an extensive overview of the demographic and professional attributes of pharmaceutical personnel in Yunnan. The majority of the workforce is female (78.24%), indicating a significant gender imbalance that may influence organizational dynamics and policy development. Age-wise, the workforce is relatively young, with most individuals between 20 and 40 years old, suggesting a dynamic sector with potential for future growth. Table 1 Descriptive Statistics of Demographic and Professional Characteristics of Pharmaceutical Human Resources in Yunnan Description Frequency Proportion (%) Gender Male 632 21.76 Female 2273 78.24 Age 20–30 years old 1004 34.56 31–40 years old 1268 43.65 41–50 years old 502 17.28 Over 51 years old 131 4.51 Education Level High school / Vocational school 70 2.41 College diploma 189 6.50 Bachelor's degree 2250 77.46 Master's degree or above 399 13.73 Years of Experience in Pharmacy Work 0–5 years 871 30.84 6–10 years 715 24.78 11–15 years 567 19.57 More than 16 years 752 25.95 Technical Title No title 306 10.53 Junior title 1429 49.19 Intermediate title 898 30.91 Deputy senior title 228 7.85 Senior title 44 1.52 Monthly Salary ≤ $ 690 USD 1488 51.22 $ 690 - $ 1,380 USD 1336 46.00 $ 1,380 - $ 2,070 USD 72 2.48 ≥ $ 2,070 USD 9 0.31 Educationally, the sector is highly qualified, with over 90% of respondents possessing a college diploma or higher, and a substantial 77.46% holding a bachelor’s degree. This reflects a well-educated workforce poised to handle complex tasks in pharmaceutical services. The technical title distribution shows limited career advancement, as nearly half of the respondents hold junior titles, and only a small fraction (1.52%) achieve senior titles, pointing to potential bottlenecks at higher professional levels. The salary analysis reveals that the vast majority of employees earn below $ 1,380 USD per month, with half earning under $ 690 USD, which may impact employee satisfaction and retention. These findings are crucial for understanding the economic constraints within the healthcare sector and for guiding policy makers in improving compensation and career development opportunities. 3.2 Chi-Square Analysis of Institutional Characteristics, Gender, and Hospital Types in Pharmaceutical Services Chi-square tests applied to various factors in pharmaceutical practices reveal significant associations and insights. The relationship between the level of medical institutions and the types of pharmaceutical services provided yielded a chi-square value of 3156.51, with a p-value significantly below 0.001, indicating that institutional capabilities strongly influence the types of pharmaceutical work performed. Conversely, the analysis of gender versus technical titles showed no significant association, with a p-value of 0.097, suggesting that gender does not influence career progression regarding technical titles in this sector, indicating a gender-neutral environment. Additionally, the study between hospital types and the weekly hours spent on pharmaceutical services revealed a significant relationship, with a chi-square statistic of 260.41 and a p-value below 0.001, demonstrating that the type of medical institution significantly affects the operational hours, likely due to varying workload and operational demands (Table 2 ). These findings are crucial for healthcare administrators and policymakers, emphasizing the need for resource allocation and policy adjustments that consider institutional characteristics and ensure equitable career advancement and operational efficiency across the healthcare sector. Table 2 Chi-Square Test Results for Associations Between Institutional Characteristics, Gender, and Operational Hours in Pharmaceutical Practice Variable Comparison Chi-Square Statistic Degrees of Freedom P-value Conclusion Medical Institution Level vs. Main Work Content 3156.51 2152 < 0.001 Significant association Gender vs. Technical Title 7.85 4 0.097 No significant association Hospital Type vs. Weekly Hours Spent on Pharmaceutical Services 260.41 140 < 0. 0001 Significant association 3.3 Effects of Training and Education on Pharmacists' Professional Metrics: Insights from ANOVA Analysis The ANOVA analysis evaluates the effects of different types of pharmacy service training and varying education levels on pharmacists’ professional metrics, such as hours spent on services and efficiency. The results indicate that neither training types nor education levels have statistically significant impacts, with p-values of 0.076 and 0.197 respectively, both above the conventional significance threshold of 0.05 (Table 3 ). These findings suggest that the expected relationship between these factors and professional performance may be less direct than assumed, highlighting the potential influence of other determinants such as institutional support, workload distribution, or workplace culture. Table 3 Combined ANOVA Results on the Impact of Pharmacy Service Training and Education Level on Pharmacists' Work Metrics Source Sum of Squares Degrees of Freedom F-Statistic P-value Impact of Pharmacy Service Training on Hours 647.21 7 1.84 0.076 Impact of Education Level on Efficiency 455.58 3 1.56 0.197 Residual for Training Impact 145966.01 2897 N/A N/A Residual for Education Impact 282522.16 2901 N/A N/A 3.4 Factor Analysis Reveals Core Dimensions of Pharmacy Service Engagement The factor analysis identify two key latent dimensions that characterize pharmacy service participation. Factor 1 , which explains 63.15% of the total variance, is primarily associated with technical and professional service tasks. The highest loadings on this factor are observed for Participation in Medication Reconciliation Services (-0.2826) and Participation in Pharmaceutical Care Services (-0.2623), indicating a strong focus on technical expertise and professional responsibilities. This dimension is best described as “Core Technical Pharmacy Services” . In contrast, Factor 2 , accounting for 36.85% of the variance, represents roles that emphasize interaction with patients. Positive loadings for Participation in Medication Education Services (0.2667) and Participation in Outpatient Pharmacy Consultation Services (0.0449) suggest that this dimension reflects “Patient Education and Communication” , which highlights the pharmacist's role in providing educational and advisory services to patients (Table 4 ). Table 4 Variable Contributions to Latent Dimensions of Pharmacy Service Participation Variable Factor 1: Core Technical Pharmacy Services Factor 2: Patient Education and Communication Participation in Outpatient Pharmacy Consultation Services -0.2057 0.0449 Participation in Medication Reconciliation Services -0.2826 -0.0802 Participation in Medication Education Services -0.2121 0.2667 Participation in Pharmaceutical Care Services -0.2623 0.0160 The spatial distribution of individual observations further underscores the separation between these two dimensions. Observations plotted along the horizontal axis (Factor 1) exhibit varying levels of engagement in core technical pharmacy tasks, whereas observations along the vertical axis (Factor 2) demonstrate differences in roles emphasizing patient education and communication. For instance, individuals scoring highly on Factor 2 are more likely to prioritize patient interaction and education, while those with high scores on Factor 1 are predominantly engaged in technical service delivery (Fig. 1 ). These findings provide significant insights into the dual nature of pharmacy practice, balancing technical competencies with patient-centered communication. This duality has implications for the training and development of pharmacy professionals, suggesting the need for integrated educational programs that strengthen both technical and interpersonal skills. 3.5 Diverse Profiles of Pharmacy Service Participation: Insights from Clustering Analysis Clustering analysis revealed four distinct profiles of pharmacy service participation, highlighting significant differences in engagement across key categories such as outpatient pharmacy consultation, medication reconciliation, medication education, and pharmaceutical care (Table 5 ). Cluster 1 represents the most comprehensive service providers, with high participation levels across all services, including outpatient pharmacy consultation (1.00) and medication education (1.00). Cluster 0 shows similar engagement in outpatient pharmacy consultation (1.00) and medication reconciliation (0.96) but demonstrates minimal involvement in medication education (0.00). Conversely, Cluster 2 reflects limited engagement across all services, particularly in outpatient pharmacy consultation (0.24) and pharmaceutical care (0.11). Cluster 3 is characterized by strong participation in pharmaceutical care (1.00) and medication reconciliation (0.97), coupled with moderate involvement in medication education (0.16). Figure 2 visualizes the clustering distribution, showing varying engagement levels along two key dimensions: outpatient pharmacy consultation (x-axis) and medication reconciliation (y-axis). Pharmacists in Cluster 1 exhibit exemplary engagement, serving as models for comprehensive service delivery, whereas those in Cluster 0 highlight opportunities for targeted training to improve service participation. These findings underscore the variability in pharmacy service participation and provide actionable insights for designing training programs and policies that address specific service gaps while enhancing overall service quality and patient outcomes. Table 5 Cluster-Specific Characteristics of Pharmacy Service Participation Cluster Outpatient Pharmacy Consultation Medication Reconciliation Medication Education Pharmaceutical Care 0 1.00 0.96 0.00 0.85 1 1.00 0.99 1.00 0.99 2 0.24 0.21 0.02 0.11 3 0.00 0.97 0.16 1.00 3.6 Comprehensive Analysis of Factors Influencing Pharmacists' Monthly Salaries: A Regression, Variance, and Equity Perspective An in-depth analysis was conducted to evaluate factors influencing pharmacists' monthly salaries, including regression analysis, variance testing, and equity assessment. Multivariate regression analysis identified age and professional title as statistically significant predictors of monthly salary. Age (coefficient = 10.37, p < 0.0001) demonstrated a significant positive relationship, with each additional year associated with an increase of 10.37 USD in salary. Similarly, professional title (coefficient = 175.90, p < 0.0001) was a strong positive factor, where each advancement in title level contributed approximately 175.90 USD to monthly earnings. In contrast, years of experience (coefficient = -4.61, p = 0.169) showed no significant impact. The baseline monthly salary, represented by the constant term, was estimated at 477.17 USD. Variance analysis (ANOVA) validated the findings, indicating significant differences in salary levels across groups with varying professional titles (F-statistic = 140.67, p-value < 0.0001). This underscores the critical role of professional title advancement in determining salary disparities. Furthermore, equity in salary distribution was assessed using the Gini coefficient, which yielded a value of 0.17 (Table 6 ). This suggests that the salary distribution among pharmacists is relatively equitable, with limited disparity within the sample population. Table 6 Summary of Factors Influencing Pharmacists' Monthly Salaries, Variance Analysis, and Gini Coefficient Analysis Component Variable/Statistic Value Interpretation Regression Analysis Constant 477.17 Represents the baseline monthly salary in USD. Age 10.37 (p < 0.0001) Exhibits a significant positive effect; each additional year increases monthly salary by 10.37 USD. Years of Experience -4.61 (p = 0.169) Demonstrates no statistically significant impact on monthly salary. Technical Title 175.90 (p < 0.0001) Shows a significant positive effect; every level advancement adds 175.90 USD to monthly salary. ANOVA F-statistic 140.67 Confirms significant differences in monthly salaries across groups with varying technical titles. p-value < 0.0001 Indicates the observed differences in salaries among professional groups are highly significant. Gini Coefficient Salary Distribution Gini 0.17 Reflects a relatively equitable salary distribution among pharmacists. These results highlight the importance of professional title progression as a key determinant of salary increases, with age serving as an additional influential factor. The findings underscore the need for structured career development frameworks and equitable compensation strategies. 4 Discussion 4.1 Workforce Composition and Gender Distribution The pharmaceutical workforce in Yunnan Province demonstrates distinct demographic characteristics, with 78.24% of participants being female and 78% aged between 20 and 40 years. The predominance of female professionals reflects global trends in pharmacy, where women increasingly dominate the sector due to high enrollment rates in healthcare-related education and employment opportunities. However, this gender imbalance warrants further attention, particularly regarding leadership representation. Women remain underrepresented in senior management and decision-making roles, highlighting the need for gender-equitable leadership development initiatives. The relatively young workforce provides a dynamic foundation for growth and adaptability but also underscores the need for structured mentorship and training programs[ 14 ]. These programs are crucial for equipping professionals with the specialized skills necessary for advanced pharmacy roles and ensuring long-term workforce retention. Policymakers should focus on fostering an inclusive and supportive work environment that promotes leadership opportunities and professional growth for women while addressing broader workforce sustainability[ 15 ]. 4.2 Educational Attainment and Service Engagement Educational attainment among the pharmaceutical workforce is encouraging, with 77.46% holding a bachelor’s degree and 15.93% possessing a master’s degree or higher. These qualifications are critical for advancing clinical pharmacy services and addressing the growing complexity of medication management. However, a disconnect exists between educational attainment and participation in key pharmacy services. While 50.36% of respondents were engaged in medication reconciliation and 47.23% in clinical consultations, only 24.68% participated in medication education. This limited involvement in patient-centered services indicates potential gaps in the practical application of advanced training[ 16 ]. Factors such as workload constraints, institutional priorities, and inadequate emphasis on patient education likely contribute to this disparity. Aligning training programs with practical needs is essential to bridging these gaps. Emphasizing patient-centered care, such as medication education, within training curricula and institutional workflows can improve health outcomes and optimize service delivery[ 17 ]. 4.3 Salary Distribution and Career Advancement Salary data revealed notable disparities, with 51.22% of respondents earning less than $ 690 USD per month. This underscores the economic challenges faced by pharmaceutical professionals, particularly those in junior roles or entry-level positions within regional healthcare institutions. Regression analysis identified age and professional title as significant predictors of salary, with higher professional titles correlating with substantial salary increments. Despite this, only 1.52% of respondents held senior titles, highlighting significant barriers to career advancement. These bottlenecks not only affect salary equity but also risk diminishing workforce morale and retention. Addressing these challenges requires transparent and equitable promotion pathways, competitive salary structures, and expanded opportunities for skill enhancement. Revising compensation models to reflect the value of pharmaceutical services and incentivize professional growth will be critical for fostering a motivated and sustainable workforce[ 18 ]. 4.4 Institutional Characteristics and Resource Allocation The disparity in service participation among different healthcare institutions highlights systemic inequities in resource allocation and workforce engagement. Tertiary hospitals reported higher participation in services such as medication reconciliation and pharmaceutical care, supported by superior infrastructure and higher staffing levels[ 19 ]. Conversely, primary healthcare institutions exhibited limited service participation, reflecting resource constraints and fewer training opportunities. Cluster analysis revealed distinct service participation profiles, emphasizing the significant role of institutional characteristics in shaping workforce engagement[ 20 ]. Bridging these gaps requires targeted investments in training programs, technological resources, and equitable resource distribution. Strengthening primary healthcare institutions, which often serve as the first point of contact for patients, is especially critical. Addressing these disparities will improve access to high-quality pharmaceutical care across all healthcare levels, advancing equity in service delivery[ 21 ]. 4.5 Policy Implications and Future Directions This study provides actionable insights into workforce planning and service optimization in regional healthcare institutions. Policymakers should prioritize developing structured career pathways, transparent promotion criteria, and competitive salary frameworks to enhance job satisfaction and retention. Institutions must implement targeted training programs to align workforce capabilities with service demands, particularly in areas like patient education and advanced clinical roles[ 22 ]. Addressing institutional disparities requires coordinated efforts to improve resource allocation and support under-resourced facilities, ensuring equitable access to pharmaceutical care. Future research should focus on evaluating the long-term impacts of these interventions on patient outcomes and the scalability of successful models in other regional and resource-constrained settings. By integrating these findings into actionable strategies, healthcare systems can foster a more equitable and efficient pharmaceutical workforce[ 23 ]. 5 Conclusion This study identifies key challenges and opportunities in pharmaceutical human resource allocation and pharmacy service delivery in regional healthcare institutions. Significant issues include workforce disparities, limited participation in patient-centered services, and inequities in resource allocation between tertiary and primary healthcare facilities. Addressing these gaps requires equitable resource distribution, structured career development pathways, and training programs that align workforce capabilities with service demands. Strengthening primary healthcare institutions is crucial to ensuring consistent access to quality pharmacy services. These findings provide a basis for policy-making and workforce planning to optimize pharmaceutical care and promote healthcare equity in resource-constrained settings. Limitations This study is subject to several limitations. First, the reliance on self-reported data may introduce response bias, as participants may overestimate or underestimate their involvement in certain activities. Second, the study was geographically limited to Yunnan Province, which may affect the generalizability of findings to other regions with different healthcare contexts. Third, the cross-sectional design precludes the establishment of causal relationships between variables. Despite these limitations, the study provides valuable insights into pharmaceutical human resource allocation and pharmacy service participation in regional healthcare settings, offering a foundation for further research and policy development. Abbreviations ANOVA : Analysis of Variance PCA : Principal Component Analysis SPSS : Statistical Package for the Social Sciences K-Means : K-Means Clustering IBM : International Business Machines Corporation Declarations Ethics Approval and Consent to Participate Ethical clearance for this study was granted by the Biomedical Ethics Committee of Kunming Medical University, Yunnan, China [Approval Number: 202400129]. Prior to data collection, participants were thoroughly informed about the study’s purpose, procedures, and their right to withdraw at any stage without consequence. Written consent was secured from all participants, with legal guardians providing consent for individuals under the age of 16. The study adhered strictly to established ethical guidelines and regulatory frameworks to ensure the rights and welfare of all participants were safeguarded. Consent for publication Not Applicable. Availability of Data and Materials The datasets utilized and analyzed during this study are available from the corresponding author upon reasonable request. All data generated or analyzed during the study are included in this published article and its supplementary information files. Competing Interests The authors declare no competing interests. There has been no financial support or relationships that could have influenced the outcomes of this research. Funding This study received support from several grants and projects: (1) First-Class Discipline Team of Kunming Medical University (Pharmaceutical Policy Research and Practice), 2024 (2024XKTDPY21); (2) Kunming Medical University Education and Teaching Research Project, 2023 (2023-JY-Y-090); (3) Undergraduate Teaching Quality and Reform Project, Kunming Medical University, 2024 (Clinical Pharmacokinetics, 2024KCSZSFXM022) ; (4) "Establishing a Model Modern Biomedical Industry College" Project (JG2023001). The funding bodies had no involvement in the study’s design, data collection, analysis, interpretation, or manuscript writing. Authors' contributions Jian Yang and Quanzhi Wei conceived the study, led the study design, data collection, analysis, and manuscript drafting. Xin Yang contributed to the study design, data analysis, and interpretation, and provided critical manuscript revisions. Jingyi Jiao, Zaixian Yang, and Zhiying Wen were involved in data collection, analysis, and interpretation, offering valuable feedback. Fan Li and Jian Yang, as senior authors, provided guidance and oversight throughout the research process. All authors read and approved the final manuscript. Acknowledgements This study was made possible with the support of the Yunnan Provincial Health Commission, the health departments of various prefectures and cities in Yunnan Province, and healthcare institutions at all levels. The authors extend their deepest gratitude to these organizations for their valuable assistance and collaboration throughout the research process. References Hepler, C. D., Strand, L. M. Opportunities and responsibilities in pharmaceutical care. American Journal of Health-System Pharmacy. 1990;47(3):533-543. doi:10.1093/ajhp/47.3.533. International Pharmaceutical Federation (FIP). 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Pharm Educ. 2022;22(1):211–220. doi: 10.46542/pe.2022.221.211220. Akel ME, et al. Experiential education in pharmacy curriculum: the Lebanese International University Model. Pharmacy (Basel) 2020;9(1):5. doi: 10.3390/pharmacy9010005. Zeenny RM, et al. Descriptive assessment of graduates' perceptions of pharmacy-related competencies based on the Lebanese pharmacy core competencies framework. Pharm Pract (Granada) 2021;19(2):2320. doi: 10.18549/PharmPract.2021.2.2320. International Pharmaceutical Federation (FIP). The FIP Development Goals report 2021. 2022 [cited 2022 March 27]; Available from: https://farmaciavirtuale.it/wp-content/uploads/2022/01/3116-Development-Goals-report-2021-Fonte-FIP.pdf Stewart D, Maclure K, Newham R, Gibson-Smith K, Bruce R, Cunningham S, Maclure A, Fry S, Mackerrow J, Bennie M. A cross-sectional survey of the pharmacy workforce in general practice in Scotland. Fam Pract. 2020 Mar 25;37(2):206-212. doi: 10.1093/fampra/cmz052. Obamiro K, Barnett T, Inyang I. The Australian pharmacist workforce: distribution and predictors of practising outside of metropolitan and regional areas in 2019. Int J Pharm Pract. 2022 Aug 9;30(4):354-359. doi: 10.1093/ijpp/riac027. Bader L, Bates I, John C. From workforce intelligence to workforce development: advancing the Eastern Mediterranean pharmaceutical workforce for better health outcomes. East Mediterr Health J. 2018 Dec 9;24(9):899-904. doi: 10.26719/2018.24.9.899. Fitzpatrick KL, Allen EA, Griffin BT, O'Shea JP, Dalton K, Bennett-Lenane H. Exploring career choices of pharmacy graduates over 15 years: A cross-sectional evaluation. Curr Pharm Teach Learn. 2024 May;16(5):307-318. doi: 10.1016/j.cptl.2024.02.010. Epub 2024 Mar 28. Zeenny RM, et al. A cross-sectional survey on community pharmacists readiness to fight COVID-19 in a developing country: knowledge, attitude, and practice in Lebanon. J Pharm Policy Pract. 2021;14(1):51. doi: 10.1186/s40545-021-00327-6. Almaghaslah D, Alsayari A, Almanasef M, Asiri A. A Cross-Sectional Study on Pharmacy Students' Career Choices in the Light of Saudi Vision 2030: Will Community Pharmacy Continue to Be the Most Promising, but Least Preferred, Sector? Int J Environ Res Public Health. 2021 Apr 26;18(9):4589. doi: 10.3390/ijerph18094589. Additional Declarations No competing interests reported. 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. 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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-5821042","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":402007326,"identity":"8dfb184d-7a88-4627-9f21-e102b9b309da","order_by":0,"name":"Jian Yang","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Yang","suffix":""},{"id":402007327,"identity":"619e3d48-ab0d-4893-9dc1-69a8b797f402","order_by":1,"name":"Quanzhi Wei","email":"","orcid":"","institution":"Yunnan Provincial Center for Drug Policy Research","correspondingAuthor":false,"prefix":"","firstName":"Quanzhi","middleName":"","lastName":"Wei","suffix":""},{"id":402007328,"identity":"bb1044a3-9861-4e44-875c-058e1b4860a4","order_by":2,"name":"Jingyi Jiao","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jingyi","middleName":"","lastName":"Jiao","suffix":""},{"id":402007329,"identity":"037b6f45-28cb-4343-acc1-895931cd7677","order_by":3,"name":"Xin Yang","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Yang","suffix":""},{"id":402007330,"identity":"3993b816-d452-4e83-84e8-805f47ae9e5d","order_by":4,"name":"Zaixian Yang","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zaixian","middleName":"","lastName":"Yang","suffix":""},{"id":402007331,"identity":"37d063ab-71cc-4ebc-bab0-2c9f8736dfed","order_by":5,"name":"Zhiying Wen","email":"","orcid":"","institution":"Kunming Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhiying","middleName":"","lastName":"Wen","suffix":""},{"id":402007332,"identity":"6a07077b-8bf0-47d0-86a7-0b92b3b19475","order_by":6,"name":"Fan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYNACHgYGfmbmww9I0yLZzpZmQJpFBud5FCSIU3kj/Zk0j0xd4ubDPAwGDDU20URoSUg25uFhMzY7zHvgAcOxtNwGglpuJxx8zMPDI2d2mC/BgLHhMDFaEhsO8/BI8Bg38xhIEKklmRFoi4GcATOxWiTvP2M2nMOTYCxxGBjICcT4he/M8WcSb3vqEvv7Dx9+8KHGhrAWhQMMDEy8PVBeAiHlICAPNJTxxw9ilI6CUTAKRsGIBQC9QTsBGFxZQwAAAABJRU5ErkJggg==","orcid":"","institution":"Yunnan Provincial Center for Drug Policy Research","correspondingAuthor":true,"prefix":"","firstName":"Fan","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-01-13 15:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5821042/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5821042/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74076450,"identity":"f5096620-cb8b-40a6-bad3-ec2a5f634388","added_by":"auto","created_at":"2025-01-17 13:40:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47317,"visible":true,"origin":"","legend":"\u003cp\u003eBivariate Projection of Pharmacy Service Dimensions in Latent Space\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5821042/v1/3b9dd3d3677a164bccef8cab.png"},{"id":74076451,"identity":"bb0f9deb-0cca-452f-a075-6ce06f3de3cc","added_by":"auto","created_at":"2025-01-17 13:40:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62546,"visible":true,"origin":"","legend":"\u003cp\u003eScatter Plot of Pharmacy Service Participation Clusters\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5821042/v1/1a4ae31982e25bfa062a77b1.png"},{"id":75036711,"identity":"23437983-0691-4ac4-9b70-88e6f12621c8","added_by":"auto","created_at":"2025-01-29 17:16:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1479059,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5821042/v1/db0d0606-dff4-4b86-a3d6-ab1151e354cb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Insights into the Allocation of Pharmaceutical Human Resources and Pharmacy Service Development Evidence from Regional Healthcare Institutions","fulltext":[{"header":"Plain Language Summary","content":"\u003cp\u003eThis study investigates the allocation of pharmaceutical human resources and the development of pharmacy services within healthcare institutions in Yunnan Province, China. Challenges such as workforce shortages, uneven resource distribution, and limited patient-centered services (e.g., medication education) are identified. Through the analysis of data from over 2,900 pharmaceutical staff, this study underscores the need for targeted training programs, equitable career pathways, and improved access to pharmacy services in underserved areas. The findings provide actionable insights to guide strategies for developing a more effective, sustainable, and equitable health workforce.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for Health Workforce Policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study offers valuable guidance for policymakers to address disparities in pharmaceutical workforce allocation and enhance pharmacy service delivery. Recommendations include ensuring equitable resource distribution, integrating advanced pharmacy practices into routine healthcare, and prioritizing investments in training programs. Strengthening the capacity of primary healthcare institutions, particularly in resource-constrained settings, can improve service accessibility, reduce inequalities, and enhance the overall quality of healthcare delivery. These strategies contribute to building a more robust and inclusive health workforce system, aligned with the goals of achieving universal health coverage and equity in healthcare.\u003c/p\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eThe allocation of pharmaceutical human resources and the development of pharmacy services are critical to ensuring the effective, safe, and rational use of medications within healthcare systems[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The increasing complexity of therapeutic regimens, the rising prevalence of chronic diseases, and the demands of aging populations have amplified the need for a well-structured and adequately resourced pharmaceutical workforce[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This is particularly evident in regional healthcare institutions, which frequently face challenges such as limited resources, workforce shortages, and inequitable distribution of services[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Addressing these issues requires a comprehensive understanding of the factors that influence pharmaceutical human resource allocation and pharmacy service delivery[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePharmacy services have evolved significantly over the past few decades, transitioning from traditional medication dispensing to include clinical pharmacy practices, medication reconciliation, therapeutic drug monitoring, and patient-centered education[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This expansion necessitates a pharmaceutical workforce with advanced competencies in both technical and interpersonal domains. However, there is a notable gap in the literature concerning the allocation and optimization of pharmaceutical human resources in regional healthcare settings[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These settings, often marked by disparities in infrastructure and access to care, provide a unique lens for examining the dynamics of pharmacy service development and workforce deployment. Understanding these dynamics is crucial for improving access to high-quality pharmacy services in underserved areas[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlobally, optimizing pharmaceutical human resources and expanding pharmacy services have been recognized as fundamental to advancing healthcare systems. In high-income countries such as the United States, Canada, and the United Kingdom, pharmacists have become integral members of multidisciplinary healthcare teams, contributing to chronic disease management, patient education, and medication therapy optimization[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These advancements are supported by robust educational systems, widespread adoption of clinical pharmacy practices, and policies incentivizing the integration of pharmacists into primary care. Conversely, middle- and low-income countries, including India, Brazil, and South Africa, face significant barriers such as workforce shortages, insufficient training opportunities, and limited financial resources for expanding pharmacy services[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Strategies like telepharmacy, task-shifting, and adherence to Good Pharmacy Practice (GPP) guidelines, as recommended by the World Health Organization, have shown potential in addressing these challenges[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In East Asia, Taiwan's pharmacist integration in primary care clinics and Japan's \"pharmacist-at-home\" model provide regionally adapted solutions for enhancing pharmacy services under resource-constrained conditions[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegional healthcare institutions play a vital role in delivering healthcare services in underserved areas but face unique barriers that hinder the implementation of advanced pharmacy services. These barriers include an uneven distribution of workforce resources, limited access to professional training, and the insufficient integration of clinical pharmacy practices into routine care[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Nevertheless, these institutions offer critical insights into the interplay between resource allocation and service delivery, revealing strategies to enhance the capacity and quality of pharmacy services. Moreover, regional healthcare settings provide an opportunity to explore how systemic reforms and resource optimization can improve healthcare equity and access[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study aims to evaluate the current state of pharmaceutical human resources and pharmacy services in regional healthcare institutions, focusing on their allocation, utilization, and service development. By analyzing workforce characteristics and participation in pharmacy services, the study seeks to identify key determinants of effective pharmacy service delivery and propose evidence-based strategies to optimize pharmaceutical human resource allocation. Integrating insights from both national and international contexts, this research emphasizes the importance of aligning workforce strategies with the evolving demands of healthcare systems.\u003c/p\u003e \u003cp\u003eThe findings of this study will provide valuable guidance for healthcare policymakers, administrators, and practitioners in designing and implementing targeted interventions to improve pharmacy service delivery. Furthermore, the study seeks to contribute to the broader discourse on pharmaceutical workforce management by offering scalable models for service expansion, particularly in resource-constrained and regional contexts. By addressing current gaps in the knowledge base and offering actionable recommendations, this research aims to advance pharmacy practice and improve healthcare outcomes in underserved areas.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Setting\u003c/h2\u003e \u003cp\u003e This cross-sectional study was designed to evaluate the allocation of pharmaceutical human resources and the current status of pharmacy services in regional healthcare institutions. The research was conducted in Yunnan Province, China, which was selected due to its diverse healthcare infrastructure, demographic composition, and socioeconomic characteristics. These factors reflect common challenges faced by resource-constrained settings, such as workforce shortages, service disparities, and varying institutional capacities. By including tertiary, secondary, and primary healthcare institutions, the study ensured a comprehensive examination of the pharmaceutical workforce and service delivery across different levels of the healthcare system. The focus on Yunnan Province provides a relevant and representative case to analyze how institutional factors and human resource allocation impact pharmacy services in regional contexts, offering insights applicable to other similar settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample Size Calculation\u003c/h2\u003e \u003cp\u003eThe sample size for this study was calculated to ensure sufficient power for analyzing the allocation of pharmaceutical human resources and pharmacy service delivery in Yunnan Province. For determining the sample size, the formula used was \u003cb\u003en\u0026thinsp;=\u0026thinsp;z\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e\u0026times;\u003c/b\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e\u0026times;(1\u0026thinsp;\u0026minus;\u003c/b\u003e\u0026thinsp;\u003cb\u003ep\u003c/b\u003e\u003cb\u003e)/\u003c/b\u003e\u003cb\u003ed\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e, where 'z' is the z-score for a 95% confidence level (1.96), 'p' is the estimated proportion of the population exhibiting the attribute (assumed to be 0.5), and 'd' is the margin of error (set at 0.02), a minimum required sample size of 2,401 participants was calculated. To account for a potential 10% non-response or exclusion rate, the initial target sample size was calculated to be 2,641 participants. Ultimately, 2,905 individuals were surveyed across tertiary, secondary, and primary healthcare institutions. This robust sample size ensures reliable findings and enables detailed analyses of the relationships between human resource allocation, institutional factors, and pharmacy service delivery in resource-constrained settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Collection\u003c/h2\u003e \u003cp\u003eData were collected using a structured questionnaire distributed to pharmacists and related personnel actively involved in the participating institutions. The questionnaire was developed based on an extensive review of existing literature and refined through consultations with domain experts to ensure content validity and relevance. It comprised sections capturing demographic details, professional qualifications, pharmacy service participation, and institutional characteristics. Questions specifically assessed engagement in pharmacy services, including medication reconciliation, clinical pharmacy consultations, therapeutic monitoring, and patient education. Additional items explored perceived challenges in service implementation, such as workforce shortages, resource limitations, and skill gaps. To ensure accessibility and inclusivity, data collection employed both electronic and paper-based surveys, accommodating participants in varying healthcare settings. Participation was entirely voluntary, with informed consent obtained before survey completion. The multi-modal approach facilitated a robust and diverse dataset for comprehensive analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Variables and Measures\u003c/h2\u003e \u003cp\u003eThis study analyzed variables related to pharmaceutical human resource allocation and pharmacy service development. Independent variables included demographic and professional characteristics such as age, gender, educational level, professional title, years of experience, and job roles. Pharmacy service participation was measured by involvement in activities like prescription review, medication reconciliation, therapeutic monitoring, and patient education. Institutional characteristics, such as facility type (tertiary, secondary, or primary), resource availability, and workload distribution, were also recorded. Dependent variables focused on the extent of pharmacy service participation and barriers to implementation, such as staffing shortages and resource limitations. This comprehensive variable selection allowed for an in-depth analysis of the factors influencing pharmacy service delivery and workforce optimization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using specialized software to identify patterns and relationships between variables. Descriptive statistics, including frequencies, percentages, means, and standard deviations, summarized participant demographics, professional characteristics, and institutional contexts. Inferential statistics, such as chi-square tests and ANOVA, were applied to examine associations between independent variables (e.g., age, professional title, and years of experience) and dependent variables (e.g., service participation levels and reported barriers). Cluster analysis using the k-means method grouped participants and institutions based on service participation profiles and workforce characteristics, highlighting variations across different healthcare settings. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all analyses, ensuring rigorous evaluation of factors influencing pharmacy service delivery in resource-constrained environments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Ethical Considerations\u003c/h2\u003e \u003cp\u003e The study was conducted in compliance with the principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board of Kunming Medical University. Participants were informed about the purpose and scope of the study and provided written consent before data collection. Anonymity and confidentiality of all participants and institutions were strictly maintained, and all responses were de-identified prior to analysis. The use of the data was restricted to research purposes, ensuring the privacy and rights of all participants.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic, Educational, and Economic Insights into the Pharmaceutical Workforce in Yunnan\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides an extensive overview of the demographic and professional attributes of pharmaceutical personnel in Yunnan. The majority of the workforce is female (78.24%), indicating a significant gender imbalance that may influence organizational dynamics and policy development. Age-wise, the workforce is relatively young, with most individuals between 20 and 40 years old, suggesting a dynamic sector with potential for future growth.\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\u003eDescriptive Statistics of Demographic and Professional Characteristics of Pharmaceutical Human Resources in Yunnan\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\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 \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;30 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 51 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school / Vocational school\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\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster's degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of Experience in Pharmacy Work\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 16 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTechnical Title\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeputy senior title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly Salary\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; \u003cspan\u003e$\u003c/span\u003e690 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e690 - \u003cspan\u003e$\u003c/span\u003e1,380 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e1,380 - \u003cspan\u003e$\u003c/span\u003e2,070 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; \u003cspan\u003e$\u003c/span\u003e2,070 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEducationally, the sector is highly qualified, with over 90% of respondents possessing a college diploma or higher, and a substantial 77.46% holding a bachelor\u0026rsquo;s degree. This reflects a well-educated workforce poised to handle complex tasks in pharmaceutical services. The technical title distribution shows limited career advancement, as nearly half of the respondents hold junior titles, and only a small fraction (1.52%) achieve senior titles, pointing to potential bottlenecks at higher professional levels. The salary analysis reveals that the vast majority of employees earn below \u003cspan\u003e$\u003c/span\u003e1,380 USD per month, with half earning under \u003cspan\u003e$\u003c/span\u003e690 USD, which may impact employee satisfaction and retention. These findings are crucial for understanding the economic constraints within the healthcare sector and for guiding policy makers in improving compensation and career development opportunities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Chi-Square Analysis of Institutional Characteristics, Gender, and Hospital Types in Pharmaceutical Services\u003c/h2\u003e \u003cp\u003eChi-square tests applied to various factors in pharmaceutical practices reveal significant associations and insights. The relationship between the level of medical institutions and the types of pharmaceutical services provided yielded a chi-square value of 3156.51, with a p-value significantly below 0.001, indicating that institutional capabilities strongly influence the types of pharmaceutical work performed. Conversely, the analysis of gender versus technical titles showed no significant association, with a p-value of 0.097, suggesting that gender does not influence career progression regarding technical titles in this sector, indicating a gender-neutral environment. Additionally, the study between hospital types and the weekly hours spent on pharmaceutical services revealed a significant relationship, with a chi-square statistic of 260.41 and a p-value below 0.001, demonstrating that the type of medical institution significantly affects the operational hours, likely due to varying workload and operational demands (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These findings are crucial for healthcare administrators and policymakers, emphasizing the need for resource allocation and policy adjustments that consider institutional characteristics and ensure equitable career advancement and operational efficiency across the healthcare sector.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChi-Square Test Results for Associations Between Institutional Characteristics, Gender, and Operational Hours in Pharmaceutical Practice\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable Comparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChi-Square Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDegrees of Freedom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Institution Level vs. Main Work Content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3156.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificant association\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender vs. Technical Title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo significant association\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital Type vs. Weekly Hours Spent on Pharmaceutical Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e260.41\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\u003e\u0026lt;\u0026thinsp;0. 0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificant association\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Effects of Training and Education on Pharmacists' Professional Metrics: Insights from ANOVA Analysis\u003c/h2\u003e \u003cp\u003eThe ANOVA analysis evaluates the effects of different types of pharmacy service training and varying education levels on pharmacists\u0026rsquo; professional metrics, such as hours spent on services and efficiency. The results indicate that neither training types nor education levels have statistically significant impacts, with p-values of 0.076 and 0.197 respectively, both above the conventional significance threshold of 0.05 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings suggest that the expected relationship between these factors and professional performance may be less direct than assumed, highlighting the potential influence of other determinants such as institutional support, workload distribution, or workplace culture.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCombined ANOVA Results on the Impact of Pharmacy Service Training and Education Level on Pharmacists' Work Metrics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSum of Squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDegrees of Freedom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF-Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpact of Pharmacy Service Training on Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e647.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpact of Education Level on Efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e455.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual for Training Impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e145966.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual for Education Impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e282522.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Factor Analysis Reveals Core Dimensions of Pharmacy Service Engagement\u003c/h2\u003e \u003cp\u003eThe factor analysis identify two key latent dimensions that characterize pharmacy service participation. \u003cb\u003eFactor 1\u003c/b\u003e, which explains 63.15% of the total variance, is primarily associated with technical and professional service tasks. The highest loadings on this factor are observed for \u003cem\u003eParticipation in Medication Reconciliation Services\u003c/em\u003e (-0.2826) and \u003cem\u003eParticipation in Pharmaceutical Care Services\u003c/em\u003e (-0.2623), indicating a strong focus on technical expertise and professional responsibilities. This dimension is best described as \u003cb\u003e\u0026ldquo;Core Technical Pharmacy Services\u0026rdquo;\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, \u003cb\u003eFactor 2\u003c/b\u003e, accounting for 36.85% of the variance, represents roles that emphasize interaction with patients. Positive loadings for \u003cem\u003eParticipation in Medication Education Services\u003c/em\u003e (0.2667) and \u003cem\u003eParticipation in Outpatient Pharmacy Consultation Services\u003c/em\u003e (0.0449) suggest that this dimension reflects \u003cb\u003e\u0026ldquo;Patient Education and Communication\u0026rdquo;\u003c/b\u003e, which highlights the pharmacist's role in providing educational and advisory services to patients (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable Contributions to Latent Dimensions of Pharmacy Service Participation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactor 1: Core Technical Pharmacy Services\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFactor 2: Patient Education and Communication\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in Outpatient Pharmacy Consultation Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in Medication Reconciliation Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.0802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in Medication Education Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in Pharmaceutical Care Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.2623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe spatial distribution of individual observations further underscores the separation between these two dimensions. Observations plotted along the horizontal axis (Factor 1) exhibit varying levels of engagement in core technical pharmacy tasks, whereas observations along the vertical axis (Factor 2) demonstrate differences in roles emphasizing patient education and communication. For instance, individuals scoring highly on Factor 2 are more likely to prioritize patient interaction and education, while those with high scores on Factor 1 are predominantly engaged in technical service delivery (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese findings provide significant insights into the dual nature of pharmacy practice, balancing technical competencies with patient-centered communication. This duality has implications for the training and development of pharmacy professionals, suggesting the need for integrated educational programs that strengthen both technical and interpersonal skills.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Diverse Profiles of Pharmacy Service Participation: Insights from Clustering Analysis\u003c/h2\u003e \u003cp\u003eClustering analysis revealed four distinct profiles of pharmacy service participation, highlighting significant differences in engagement across key categories such as outpatient pharmacy consultation, medication reconciliation, medication education, and pharmaceutical care (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Cluster 1 represents the most comprehensive service providers, with high participation levels across all services, including outpatient pharmacy consultation (1.00) and medication education (1.00). Cluster 0 shows similar engagement in outpatient pharmacy consultation (1.00) and medication reconciliation (0.96) but demonstrates minimal involvement in medication education (0.00). Conversely, Cluster 2 reflects limited engagement across all services, particularly in outpatient pharmacy consultation (0.24) and pharmaceutical care (0.11). Cluster 3 is characterized by strong participation in pharmaceutical care (1.00) and medication reconciliation (0.97), coupled with moderate involvement in medication education (0.16). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e visualizes the clustering distribution, showing varying engagement levels along two key dimensions: outpatient pharmacy consultation (x-axis) and medication reconciliation (y-axis). Pharmacists in Cluster 1 exhibit exemplary engagement, serving as models for comprehensive service delivery, whereas those in Cluster 0 highlight opportunities for targeted training to improve service participation. These findings underscore the variability in pharmacy service participation and provide actionable insights for designing training programs and policies that address specific service gaps while enhancing overall service quality and patient outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCluster-Specific Characteristics of Pharmacy Service Participation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutpatient Pharmacy Consultation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedication Reconciliation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedication Education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePharmaceutical Care\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Comprehensive Analysis of Factors Influencing Pharmacists' Monthly Salaries: A Regression, Variance, and Equity Perspective\u003c/h2\u003e \u003cp\u003eAn in-depth analysis was conducted to evaluate factors influencing pharmacists' monthly salaries, including regression analysis, variance testing, and equity assessment. Multivariate regression analysis identified age and professional title as statistically significant predictors of monthly salary. Age (coefficient\u0026thinsp;=\u0026thinsp;10.37, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) demonstrated a significant positive relationship, with each additional year associated with an increase of 10.37 USD in salary. Similarly, professional title (coefficient\u0026thinsp;=\u0026thinsp;175.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) was a strong positive factor, where each advancement in title level contributed approximately 175.90 USD to monthly earnings. In contrast, years of experience (coefficient = -4.61, p\u0026thinsp;=\u0026thinsp;0.169) showed no significant impact. The baseline monthly salary, represented by the constant term, was estimated at 477.17 USD.\u003c/p\u003e \u003cp\u003eVariance analysis (ANOVA) validated the findings, indicating significant differences in salary levels across groups with varying professional titles (F-statistic\u0026thinsp;=\u0026thinsp;140.67, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This underscores the critical role of professional title advancement in determining salary disparities. Furthermore, equity in salary distribution was assessed using the Gini coefficient, which yielded a value of 0.17 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This suggests that the salary distribution among pharmacists is relatively equitable, with limited disparity within the sample population.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Factors Influencing Pharmacists' Monthly Salaries, Variance Analysis, and Gini Coefficient\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalysis Component\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable/Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eRegression Analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e477.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRepresents the baseline monthly salary in USD.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.37 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExhibits a significant positive effect; each additional year increases monthly salary by 10.37 USD.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYears of Experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.61 (p\u0026thinsp;=\u0026thinsp;0.169)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDemonstrates no statistically significant impact on monthly salary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTechnical Title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175.90 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShows a significant positive effect; every level advancement adds 175.90 USD to monthly salary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eANOVA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF-statistic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConfirms significant differences in monthly salaries across groups with varying technical titles.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndicates the observed differences in salaries among professional groups are highly significant.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGini Coefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSalary Distribution Gini\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReflects a relatively equitable salary distribution among pharmacists.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese results highlight the importance of professional title progression as a key determinant of salary increases, with age serving as an additional influential factor. The findings underscore the need for structured career development frameworks and equitable compensation strategies.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Workforce Composition and Gender Distribution\u003c/h2\u003e \u003cp\u003eThe pharmaceutical workforce in Yunnan Province demonstrates distinct demographic characteristics, with 78.24% of participants being female and 78% aged between 20 and 40 years. The predominance of female professionals reflects global trends in pharmacy, where women increasingly dominate the sector due to high enrollment rates in healthcare-related education and employment opportunities. However, this gender imbalance warrants further attention, particularly regarding leadership representation. Women remain underrepresented in senior management and decision-making roles, highlighting the need for gender-equitable leadership development initiatives. The relatively young workforce provides a dynamic foundation for growth and adaptability but also underscores the need for structured mentorship and training programs[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These programs are crucial for equipping professionals with the specialized skills necessary for advanced pharmacy roles and ensuring long-term workforce retention. Policymakers should focus on fostering an inclusive and supportive work environment that promotes leadership opportunities and professional growth for women while addressing broader workforce sustainability[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Educational Attainment and Service Engagement\u003c/h2\u003e \u003cp\u003eEducational attainment among the pharmaceutical workforce is encouraging, with 77.46% holding a bachelor\u0026rsquo;s degree and 15.93% possessing a master\u0026rsquo;s degree or higher. These qualifications are critical for advancing clinical pharmacy services and addressing the growing complexity of medication management. However, a disconnect exists between educational attainment and participation in key pharmacy services. While 50.36% of respondents were engaged in medication reconciliation and 47.23% in clinical consultations, only 24.68% participated in medication education. This limited involvement in patient-centered services indicates potential gaps in the practical application of advanced training[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Factors such as workload constraints, institutional priorities, and inadequate emphasis on patient education likely contribute to this disparity. Aligning training programs with practical needs is essential to bridging these gaps. Emphasizing patient-centered care, such as medication education, within training curricula and institutional workflows can improve health outcomes and optimize service delivery[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Salary Distribution and Career Advancement\u003c/h2\u003e \u003cp\u003eSalary data revealed notable disparities, with 51.22% of respondents earning less than \u003cspan\u003e$\u003c/span\u003e690 USD per month. This underscores the economic challenges faced by pharmaceutical professionals, particularly those in junior roles or entry-level positions within regional healthcare institutions. Regression analysis identified age and professional title as significant predictors of salary, with higher professional titles correlating with substantial salary increments. Despite this, only 1.52% of respondents held senior titles, highlighting significant barriers to career advancement. These bottlenecks not only affect salary equity but also risk diminishing workforce morale and retention. Addressing these challenges requires transparent and equitable promotion pathways, competitive salary structures, and expanded opportunities for skill enhancement. Revising compensation models to reflect the value of pharmaceutical services and incentivize professional growth will be critical for fostering a motivated and sustainable workforce[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Institutional Characteristics and Resource Allocation\u003c/h2\u003e \u003cp\u003eThe disparity in service participation among different healthcare institutions highlights systemic inequities in resource allocation and workforce engagement. Tertiary hospitals reported higher participation in services such as medication reconciliation and pharmaceutical care, supported by superior infrastructure and higher staffing levels[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Conversely, primary healthcare institutions exhibited limited service participation, reflecting resource constraints and fewer training opportunities. Cluster analysis revealed distinct service participation profiles, emphasizing the significant role of institutional characteristics in shaping workforce engagement[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Bridging these gaps requires targeted investments in training programs, technological resources, and equitable resource distribution. Strengthening primary healthcare institutions, which often serve as the first point of contact for patients, is especially critical. Addressing these disparities will improve access to high-quality pharmaceutical care across all healthcare levels, advancing equity in service delivery[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Policy Implications and Future Directions\u003c/h2\u003e \u003cp\u003e This study provides actionable insights into workforce planning and service optimization in regional healthcare institutions. Policymakers should prioritize developing structured career pathways, transparent promotion criteria, and competitive salary frameworks to enhance job satisfaction and retention. Institutions must implement targeted training programs to align workforce capabilities with service demands, particularly in areas like patient education and advanced clinical roles[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Addressing institutional disparities requires coordinated efforts to improve resource allocation and support under-resourced facilities, ensuring equitable access to pharmaceutical care. Future research should focus on evaluating the long-term impacts of these interventions on patient outcomes and the scalability of successful models in other regional and resource-constrained settings. By integrating these findings into actionable strategies, healthcare systems can foster a more equitable and efficient pharmaceutical workforce[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study identifies key challenges and opportunities in pharmaceutical human resource allocation and pharmacy service delivery in regional healthcare institutions. Significant issues include workforce disparities, limited participation in patient-centered services, and inequities in resource allocation between tertiary and primary healthcare facilities. Addressing these gaps requires equitable resource distribution, structured career development pathways, and training programs that align workforce capabilities with service demands. Strengthening primary healthcare institutions is crucial to ensuring consistent access to quality pharmacy services. These findings provide a basis for policy-making and workforce planning to optimize pharmaceutical care and promote healthcare equity in resource-constrained settings.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study is subject to several limitations. First, the reliance on self-reported data may introduce response bias, as participants may overestimate or underestimate their involvement in certain activities. Second, the study was geographically limited to Yunnan Province, which may affect the generalizability of findings to other regions with different healthcare contexts. Third, the cross-sectional design precludes the establishment of causal relationships between variables. Despite these limitations, the study provides valuable insights into pharmaceutical human resource allocation and pharmacy service participation in regional healthcare settings, offering a foundation for further research and policy development.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eANOVA\u003c/strong\u003e: Analysis of Variance\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePCA\u003c/strong\u003e: Principal Component Analysis\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSPSS\u003c/strong\u003e: Statistical Package for the Social Sciences\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eK-Means\u003c/strong\u003e: K-Means Clustering\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIBM\u003c/strong\u003e: International Business Machines Corporation\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance for this study was granted by the Biomedical Ethics Committee of Kunming Medical University, Yunnan, China [Approval Number: 202400129]. Prior to data collection, participants were thoroughly informed about the study’s purpose, procedures, and their right to withdraw at any stage without consequence. Written consent was secured from all participants, with legal guardians providing consent for individuals under the age of 16. The study adhered strictly to established ethical guidelines and regulatory frameworks to ensure the rights and welfare of all participants were safeguarded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets utilized and analyzed during this study are available from the corresponding author upon reasonable request. All data generated or analyzed during the study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests. There has been no financial support or relationships that could have influenced the outcomes of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received support from several grants and projects: (1) First-Class Discipline Team of Kunming Medical University (Pharmaceutical Policy Research and Practice), 2024 (2024XKTDPY21); (2) Kunming Medical University Education and Teaching Research Project, 2023 (2023-JY-Y-090); (3) Undergraduate Teaching Quality and Reform Project, Kunming Medical University, 2024 (Clinical Pharmacokinetics, 2024KCSZSFXM022) ; (4) \"Establishing a Model Modern Biomedical Industry College\" Project (JG2023001). The funding bodies had no involvement in the study’s design, data collection, analysis, interpretation, or manuscript writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJian Yang and Quanzhi Wei conceived the study, led the study design, data collection, analysis, and manuscript drafting. Xin Yang contributed to the study design, data analysis, and interpretation, and provided critical manuscript revisions. Jingyi Jiao, Zaixian Yang, and Zhiying Wen were involved in data collection, analysis, and interpretation, offering valuable feedback. Fan Li and Jian Yang, as senior authors, provided guidance and oversight throughout the research process. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was made possible with the support of the Yunnan Provincial Health Commission, the health departments of various prefectures and cities in Yunnan Province, and healthcare institutions at all levels. The authors extend their deepest gratitude to these organizations for their valuable assistance and collaboration throughout the research process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHepler, C. D., Strand, L. M. Opportunities and responsibilities in pharmaceutical care. \u003cem\u003eAmerican Journal of Health-System Pharmacy.\u003c/em\u003e 1990;47(3):533-543. doi:10.1093/ajhp/47.3.533.\u003c/li\u003e\n\u003cli\u003eInternational Pharmaceutical Federation (FIP). Pharmacy Education Taskforce: A Global Competency Framework. 2012 [cited 2020 July 24]; Available from: https://www.fip.org/files/fip/PharmacyEducation/GbCF_v1.pdf.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Health Workforce Requirements for Universal Health Coverage and Sustainable Development Goals. WHO; 2016. Available at: https://www.who.int/publications.\u003c/li\u003e\n\u003cli\u003eInternational Pharmaceutical Federation (FIP). FIP Global Advanced Development Framework (GADF): Supporting the advancement of the profession. 2019 [cited 2022 March 27]; Available from: https://www.fip.org/file/4331.\u003c/li\u003e\n\u003cli\u003eInternational Pharmaceutical Federation (FIP) FIP Development Goals. 2021 [cited 2022 March 27]; Available from: https://www.fip.org/search?page=fip-development-goals\u003c/li\u003e\n\u003cli\u003eMeilianti S, Smith F, Kristianto F, Himawan R, Ernawati DK, Naya R, Bates I. A national analysis of the pharmacy workforce in Indonesia. Hum Resour Health. 2022 Sep 29;20(1):71. doi: 10.1186/s12960-022-00767-4.\u003c/li\u003e\n\u003cli\u003eMukhalalati BA, Ibrahim MMME, Al Alawneh MO, Awaisu A, Bates I, Bader L. National assessment of pharmaceutical workforce and education using the International Pharmaceutical Federation\u0026apos;s global development goals: a case study of Qatar. J Pharm Policy Pract. 2021 Feb 22;14(1):22. doi: 10.1186/s40545-021-00305-y.\u003c/li\u003e\n\u003cli\u003eCovvey JR, Cohron PP, Mullen AB. Examining pharmacy workforce issues in the United States and the United kingdom. Am J Pharm Educ. 2015 Mar 25;79(2):17. doi: 10.5688/ajpe79217. \u003c/li\u003e\n\u003cli\u003eBates I, Patel D, Chan AHY, Rutter V, Bader L, Meilianti S, Udoh A. A comparative analysis of pharmaceutical workforce development needs across the commonwealth. Res Social Adm Pharm. 2023 Jan;19(1):167-179. doi: 10.1016/j.sapharm.2022.07.010. Epub 2022 Aug 8. \u003c/li\u003e\n\u003cli\u003eFang Y, Yang S, Zhou S, Jiang M, Liu J. Community pharmacy practice in China: past, present and future. Int J Clin Pharm. 2013 Aug;35(4):520-8. doi: 10.1007/s11096-013-9789-5. Epub 2013 May 10. \u003c/li\u003e\n\u003cli\u003eChen WH, Lee PC, Chiang SC, Chang YL, Chen TJ, Chou LF, Hwang SJ. Pharmacist Workforce at Primary Care Clinics: A Nationwide Survey in Taiwan. Healthcare. 2021 Jul 8;9(7):863. doi: 10.3390/healthcare9070863.\u003c/li\u003e\n\u003cli\u003eBates I, John C, Bruno A, Fu P, Aliabadi S. An analysis of the global pharmacy workforce capacity. Hum Resour Health. 2016 Oct 10;14(1):61. doi: 10.1186/s12960-016-0158-z. \u003c/li\u003e\n\u003cli\u003eSparkmon W, Barnard M, Rosenthal M, Desselle S, Ballou JM, Holmes E. Pharmacy Technician Efficacies and Workforce Planning: A Consensus Building Study on Expanded Pharmacy Technician Roles. Pharmacy (Basel). 2023 Feb 3;11(1):28. doi: 10.3390/pharmacy11010028. \u003c/li\u003e\n\u003cli\u003eTawil S, et al. Pharmacists and continuing education: a cross-sectional observational study of value and motivation. Int J Pharm Pract. 2020;28(4):380\u0026ndash;389. doi: 10.1111/ijpp.12616.\u003c/li\u003e\n\u003cli\u003eHajj A, et al. The Lebanese experience for early career development: Bridging the gap to reach the International Pharmaceutical Federation (FIP) Global Competency Framework. Pharm Educ. 2022;22(1):211\u0026ndash;220. doi: 10.46542/pe.2022.221.211220. \u003c/li\u003e\n\u003cli\u003eAkel ME, et al. Experiential education in pharmacy curriculum: the Lebanese International University Model. Pharmacy (Basel) 2020;9(1):5. doi: 10.3390/pharmacy9010005.\u003c/li\u003e\n\u003cli\u003eZeenny RM, et al. Descriptive assessment of graduates\u0026apos; perceptions of pharmacy-related competencies based on the Lebanese pharmacy core competencies framework. Pharm Pract (Granada) 2021;19(2):2320. doi: 10.18549/PharmPract.2021.2.2320. \u003c/li\u003e\n\u003cli\u003eInternational Pharmaceutical Federation (FIP). The FIP Development Goals report 2021. 2022 [cited 2022 March 27]; Available from: https://farmaciavirtuale.it/wp-content/uploads/2022/01/3116-Development-Goals-report-2021-Fonte-FIP.pdf\u003c/li\u003e\n\u003cli\u003eStewart D, Maclure K, Newham R, Gibson-Smith K, Bruce R, Cunningham S, Maclure A, Fry S, Mackerrow J, Bennie M. A cross-sectional survey of the pharmacy workforce in general practice in Scotland. Fam Pract. 2020 Mar 25;37(2):206-212. doi: 10.1093/fampra/cmz052. \u003c/li\u003e\n\u003cli\u003eObamiro K, Barnett T, Inyang I. The Australian pharmacist workforce: distribution and predictors of practising outside of metropolitan and regional areas in 2019. Int J Pharm Pract. 2022 Aug 9;30(4):354-359. doi: 10.1093/ijpp/riac027. \u003c/li\u003e\n\u003cli\u003eBader L, Bates I, John C. From workforce intelligence to workforce development: advancing the Eastern Mediterranean pharmaceutical workforce for better health outcomes. East Mediterr Health J. 2018 Dec 9;24(9):899-904. doi: 10.26719/2018.24.9.899. \u003c/li\u003e\n\u003cli\u003eFitzpatrick KL, Allen EA, Griffin BT, O\u0026apos;Shea JP, Dalton K, Bennett-Lenane H. Exploring career choices of pharmacy graduates over 15 years: A cross-sectional evaluation. Curr Pharm Teach Learn. 2024 May;16(5):307-318. doi: 10.1016/j.cptl.2024.02.010. Epub 2024 Mar 28. Zeenny RM, et al. A cross-sectional survey on community pharmacists readiness to fight COVID-19 in a developing country: knowledge, attitude, and practice in Lebanon. J Pharm Policy Pract. 2021;14(1):51. doi: 10.1186/s40545-021-00327-6.\u003c/li\u003e\n\u003cli\u003eAlmaghaslah D, Alsayari A, Almanasef M, Asiri A. A Cross-Sectional Study on Pharmacy Students\u0026apos; Career Choices in the Light of Saudi Vision 2030: Will Community Pharmacy Continue to Be the Most Promising, but Least Preferred, Sector? Int J Environ Res Public Health. 2021 Apr 26;18(9):4589. doi: 10.3390/ijerph18094589. \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":"Pharmaceutical Human Resources, Pharmacy Service Development, Regional Healthcare Institutions, Workforce Allocation, Service Participation Patterns","lastPublishedDoi":"10.21203/rs.3.rs-5821042/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5821042/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe allocation of pharmaceutical human resources and the development of pharmacy services are critical to ensuring effective, safe, and rational medication use within healthcare systems. Regional healthcare institutions, especially in resource-constrained settings, face significant challenges, including workforce shortages, uneven skill distribution, and limited integration of advanced pharmacy practices. This study aims to provide evidence-based insights into workforce allocation and pharmacy service development in these settings.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted across healthcare institutions in Yunnan Province, China, including tertiary, secondary, and primary facilities. Data were collected through a structured questionnaire targeting pharmaceutical personnel actively engaged in service delivery. Variables assessed included demographic and professional characteristics, service participation, and institutional factors. Statistical analyses included descriptive statistics, cluster analysis, multidimensional scaling, and regression analysis to explore patterns and relationships.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe dataset included 2,905 participants, with 78.24% female and 21.76% male respondents. The majority (78%) were aged 20\u0026ndash;40 years, and educational attainment was high, with 77.46% holding a bachelor\u0026rsquo;s degree, 15.93% a master\u0026rsquo;s degree or higher, and only 6.61% an associate degree or lower. Service participation varied across activities: 50.36% of respondents were involved in medication reconciliation, 47.23% in clinical consultations, and only 24.68% in medication education. Regression analysis revealed that age and professional title were significant predictors of salary, highlighting disparities in career progression and compensation distribution. Cluster analysis identified distinct participation patterns, segregating respondents into high and low engagement groups, underscoring variability in service involvement. The Gini coefficient for salary distribution was 0.17, indicating a relatively equitable distribution.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study highlights critical challenges and opportunities in the allocation of pharmaceutical human resources and the delivery of pharmacy services in regional healthcare institutions. Findings emphasize the need for targeted training programs, equitable resource distribution, and structured career development pathways. These results provide valuable insights for policymakers and healthcare administrators to enhance workforce development and optimize pharmacy services, particularly in resource-constrained settings.\u003c/p\u003e","manuscriptTitle":"Insights into the Allocation of Pharmaceutical Human Resources and Pharmacy Service Development Evidence from Regional Healthcare Institutions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-17 13:32:22","doi":"10.21203/rs.3.rs-5821042/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":"be277246-d56b-4f4e-8977-0f4f1e92ad9e","owner":[],"postedDate":"January 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-06T08:08:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-17 13:32:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5821042","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5821042","identity":"rs-5821042","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}