Effect of Procurement Practices on Medicine Procurement Effectiveness in Tanzania’s Regional Referral Hospitals: Evidence from Mwananyamala, Amana, and Temeke Hospitals

Effect of Procurement Practices on Medicine Procurement Effectiveness in Tanzania’s Regional Referral Hospitals: Evidence from Mwananyamala, Amana, and Temeke Hospitals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of Procurement Practices on Medicine Procurement Effectiveness in Tanzania’s Regional Referral Hospitals: Evidence from Mwananyamala, Amana, and Temeke Hospitals Justine Nangu, Bahati Mabina, Nicholaus Mgawe, Ambali Kitalima This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8141502/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract Background Efficient procurement practices are essential to ensuring the availability, affordability, and quality of medicines in public healthcare systems. Despite various reforms in regulatory frameworks and public procurement systems, Tanzanian regional hospitals continue to face frequent stock-outs and procurement inefficiencies, leading to treatment delay and increased financial burden on patients. This study examined the effect of procurement practices, specifically procurement planning, supplier selection and evaluation, and contract management, on the effectiveness of medicine procurement in regional referral hospitals in Dar es Salaam. Methods A descriptive cross-sectional quantitative design was used, involving 80 respondents from Amana, Temeke, and Mwananyamala regional referral hospitals. Primary data were collected using structured questionnaires and analyzed using SPSS version 31. Correlation and multiple regression analyses tested the relationships between procurement practices and the effectiveness of medicine procurement. Reliability was assessed using Cronbach’s alpha, with all variables exceeding 0.70. Results All three procurement practices positively and significantly influenced medicine procurement effectiveness. Procurement planning had B = 0.298, p < 0.001, showing that improved planning enhances timely and cost-effective medicine availability. Supplier selection and evaluation had B = 0.185, p < 0.001, indicating that effective supplier management improves medicine reliability and quality. Contract management had the strongest effect with B = 0.433, p < 0.001, demonstrating that proper contract oversight, timely payments, and risk management ensure consistent high-quality supply. Together, these practices explained 94.2% of the variation in procurement effectiveness (Adjusted R² = 0.940), highlighting their combined impact on improving hospital medicine procurement if implemented effectively. Conclusions Effective and joint implementation of procurement planning, supplier evaluation, and contract management can improve medicine procurement and reduce stock-outs in regional hospitals. Strengthening accountability, compliance monitoring, and supplier management is key to sustaining improvements in public medicine supply systems. medicine procurement health supply chain medicine stock-out procurement planning contract management supplier evaluation Figures Figure 1 Figure 2 Figure 3 Background Efficient procurement of medicines is fundamental to the functioning of health systems, ensuring timely, affordable, and quality access to essential medicines. Globally, procurement performance directly influences service delivery, patient outcomes, and health system efficiency. The COVID-19 pandemic further exposed vulnerabilities in pharmaceutical procurement systems, particularly in settings with weak planning capacities, limited supplier networks, and fragile forecasting mechanisms, where widespread shortages of critical medicines were experienced ( 1 ). Evidence shows that transparent supplier selection, accurate needs-based planning, and effective contract management significantly improve the availability of medicines while reducing costs and minimizing stock-outs ( 2 ). In high-income countries, innovations such as e-procurement systems and blockchain-enabled contracts have improved accountability, traceability, and efficiency across the procurement cycle ( 3 ) Despite global progress, many low- and middle-income countries (LMICs) continue to face persistent challenges in medicine procurement. The World Health Organization emphasizes that procurement practices affect not only affordability but also the safety and quality of medicines, thereby influencing clinical outcomes and public trust ( 4 ). Inefficiencies such as limited competition, poor contract enforcement, weak monitoring mechanisms, and corruption risks undermine procurement performance in LMICs and contribute to inflated prices, supply disruptions, and circulation of substandard or counterfeit medicines ( 5 ). These weaknesses hinder progress toward Sustainable Development Goal 3 on universal health coverage, particularly in health systems that rely heavily on public procurement as the main source of essential medicines. In Africa, medicine procurement remains one of the most critical health system challenges. Fragmented procurement structures, inadequate governance, and financial constraints often lead to duplication of processes, high transaction costs, and long delays in medicine delivery to public health facilities ( 4 ). Weak forecasting, poor quantification, and unreliable supply chains commonly result in stock-outs of essential medicines, forcing patients to purchase medicines from private pharmacies at significantly higher prices, thereby undermining equity and financial protection. In addition, limited technical capacity within procurement units, such as shortages of trained staff, a lack of digital procurement tools, and weak performance monitoring, further increases vulnerability to inefficiencies and corruption ( 5 ). Although reforms such as African Union-led pooled procurement and national purchasing innovations, including Kenya’s NHIF reforms, have improved supplier accountability and price negotiation power ( 6 ), persistent challenges such as supplier monopolies, fragmented supply chains, and inadequate contract enforcement continue to impede progress. In Tanzania, despite a structured framework and reforms in public procurement systems, public facilities continue to face recurrent stock-outs, procurement delays, and budget limitations, which compromise medicine availability and continuity of care ( 4 ). Weak forecasting practices, untimely disbursement of funds, and inadequate procurement planning limit hospitals’ ability to procure adequate quantities of essential medicines. Patients often turn to private pharmacies where prices are significantly higher. Moreover, limited supplier competition, weak supplier performance monitoring, and inadequate contract management mechanisms contribute to procurement inefficiencies within regional hospitals ( 7 ). Strengthening procurement planning, improving supplier evaluation processes, and enforcing effective contract management, particularly in high-demand regions such as Dar es Salaam, are essential to improving medicine availability, cost-efficiency, and overall quality of healthcare services in Tanzania. Methods Study Design and Setting A descriptive cross-sectional quantitative survey was conducted in three regional hospitals in Dar es Salaam Amana, Temeke, and Mwananyamala. This design was appropriate for assessing the relationship between procurement practices (procurement planning, supplier selection and evaluation, and contract management) and medicine procurement effectiveness at a single point in time (( 8 ); ( 9 )). Study Population and Sampling The target population consisted of 121 staff involved in procurement activities, including procurement officers, pharmacists, finance officers, and hospital administrators. The sample size was determined using Yamane’s (1967) ( 10 ) Whereby: n = Sample size N = Total number of Staff = 121 e = Precision = 5% Therefore; n = 121/ [1 + 121(0.05) 2 ] = 93 With N = 121 and e = 0.05, the minimum sample size was 93, proportionally allocated across departments. Simple random sampling was used to select respondents. A total of 80 participants completed the survey (response rate: 86%), which was adequate for analysis. Data Collection Primary data were collected using structured, self-administered questionnaires consisting of closed-ended Likert-scale items. Secondary data were obtained through documentary reviews of PPRA compliance reports, NAOT audit reports, hospital procurement records, and relevant policy documents to complement primary data ( 11 ) Data Analysis Data were analyzed using SPSS Version 31. Descriptive statistics summarized respondent characteristics, and multiple regression was used to assess the influence of procurement planning, supplier evaluation, and contract management on medicine procurement effectiveness.” Results Respondents Demographic Information The demographic characteristics of participants are presented in Table 1 were nearly evenly split by gender (51.2% female, 48.8% male). Most participants (57.5%) held undergraduate degrees, 33.8% held diplomas, 6.3% had master’s degrees, and 2.5% had certificates. The majority (57.5%) had over five years of work experience. Respondents were evenly distributed across the three hospitals: Temeke (33.8%), Amana (33.8%), and Mwananyamala (32.5%). These figures indicate that the respondents were knowledgeable and experienced in the subject under study, ensuring the credibility and reliability of the collected data. Table 1 Respondents' Demographics Variable Attribute Frequency Percent Gender Male 39 48.8% Female 41 51.2% education Certificate 2 2.5% Ordinary Diploma 27 33.8% Undergraduate/ Degree 46 57.5% Masters 5 6.3% years 0–1 Years 12 15.0% 2–4 Years 22 27.5% 5 Years and above 46 57.5% Hospital you are working Mwananyamala 26 32.5% Temeke 27 33.8% Amana 27 33.8% SPSS, Version 31 Descriptive statistics of the study variable The descriptive analysis of study variables shows that procurement planning practices were moderately implemented in the regional hospitals, with a mean score of 3.73 (SD = 0.481). Supplier selection and evaluation practices also reflected moderate effectiveness, with a mean of 3.44 (SD = 0.444). In contrast, contract management practices were strongly implemented, as indicated by a mean of 4.76 (SD = 0.716). Overall, medicine procurement effectiveness was high, with a mean score of 4.42 (SD = 0.474), suggesting that the hospitals largely achieved their objectives in ensuring timely availability, quality, and cost efficiency of medicines. These figures also indicate that respondents had substantial knowledge of the subject under study. Multiple Regression Analysis Before performing multiple regression analysis, the study tested key assumptions to ensure the validity, reliability, and accuracy of the results. Linearity was confirmed through scatter plots, showing that procurement planning, supplier selection, and contract management each had a linear relationship with medicine procurement effectiveness as summarized in Fig. 1 (Procurement Planning Scatter Plot for linearity test) , Fig. 2 (Supplier Selection and Evaluation Scatter Plot for linearity test) , and Fig. 3 (Contract Management Scatter Plot for linearity test). Normality of residuals was satisfied, as both the Kolmogorov–Smirnov (p = 0.200) and Shapiro–Wilk (p = 0.052) tests indicated no significant deviations, confirming that residuals were approximately normally distributed. Homoscedasticity was verified using the Breusch–Pagan test (p = 0.145), indicating constant variance of residuals across predicted values. Independence of errors was confirmed with a Durbin–Watson statistic of 1.953, showing no autocorrelation among residuals. Multicollinearity was not a concern, as Variance Inflation Factor (VIF) values ranged between 1.373 and 1.964 and Tolerance values exceeded 0.1, confirming that independent variables contributed uniquely to the model. Finally, outlier analysis using Cook’s Distance revealed a low average influence (0.029), with only one case slightly exceeding the threshold, indicating that the regression results were not substantially distorted. Collectively, these tests confirmed that the data met all necessary assumptions for multiple regression analysis, supporting the robustness and reliability of the findings. Model Summary Multiple regression analysis, summarized in Table 2 showed a very strong positive relationship between the combined predictors—procurement planning, supplier selection and evaluation, and contract management—and medicine procurement effectiveness (R = 0.971). The model explained 94.2% of the variation in procurement effectiveness (R² = 0.942; Adjusted R² = 0.940), with a low standard error (0.116), indicating accur 1 Medical Stores Department (MSD) P.O. Box 9081 Dar es Salaam, Tanzania ate and consistent predictions. These results demonstrate that the model fits the data well and that the three factors collectively have a strong and significant influence on medicine procurement effectiveness in regional hospitals. Table 2 Regression Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .971 a .942 .940 .116 a. Predictors: (Constant), Contract Management, Procurement planning, Supplier Selection b. Dependent Variable: Medical Procurement Effectiveness ANOVA ANOVA results confirmed that the regression model predicting medicine procurement effectiveness was statistically significant (F = 414.618, p < 0.001) as shown in Table 3 . This indicates that procurement planning, supplier selection and evaluation, and contract management jointly and individually have a significant impact on procurement effectiveness. Overall, the model provides a good fit, supporting the conclusion that effective planning, supplier management, and contract oversight enhance medicine procurement performance in regional hospitals. Table 3 ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 16.740 3 5.580 414.618 .000 b Residual 1.023 76 .013 Total 17.763 79 a. Dependent Variable: Medical Procurement Effectiveness b. Predictors: (Constant), Contract Management, Procurement planning, Supplier Selection Coefficients Statistics The coefficients analysis shows that procurement planning (B = 0.298, β = 0.302), supplier selection and evaluation (B = 0.185, β = 0.173), and contract management (B = 0.433, β = 0.654), as summarized in Table 4 , have a positive and significant effect on medicine procurement effectiveness (p < 0.05). This indicates that improvements in planning, supplier management, and contract management each contribute significantly to enhancing procurement performance in regional hospitals Table 4 Coefficients Statistics Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .611 .119 5.122 .000 Procurement planning .298 .032 .302 9.357 .000 Supplier Selection .185 .041 .173 4.542 .000 Contract Management .433 .026 .654 16.960 .000 a. Dependent Variable: Medical Procurement Effectiveness Discussion The study demonstrates that procurement planning, supplier selection and evaluation, and contract management all significantly influence the effectiveness of medicine procurement in regional hospitals. Procurement planning was positively associated with procurement effectiveness (B = 0.298, p < 0.001), indicating that structured activities such as needs assessment, budgeting, and adherence to procurement schedules enhance medicine availability, reduce costs, and improve operational efficiency. These findings align with Agency Theory, which emphasizes monitoring and accountability to ensure alignment between agents (procurement officers) and principals (hospital management) (( 12 ). Prior studies in Tanzania, Kenya, and South Africa similarly report that effective procurement planning reduces stock-outs, ensures timeliness, and improves cost control (( 13 ); ( 11 ); ( 4 )). Hospitals should strengthen forecasting, budgeting alignment, and training in data-driven procurement to enhance efficiency and accountability. Supplier selection and evaluation also positively influenced procurement effectiveness (B = 0.185, p < 0.001). Transparent prequalification, regular performance assessment, and compliance monitoring improve medicine quality, timely supply, and cost efficiency. These results support Agency Theory by demonstrating that supplier evaluation acts as a control mechanism to reduce opportunistic behavior and align supplier actions with hospital objectives (( 14 ); ( 11 ); ( 6 )). Hospitals should implement standardized evaluation frameworks and supplier relationship management systems to maintain consistent supply quality and build trust in procurement operations. Contract management emerged as the strongest predictor of procurement effectiveness (B = 0.433, p < 0.001). Effective contract oversight, timely supplier payments, and strategic risk management enhance medicine availability and reliability. These findings corroborate prior evidence showing that well-managed contracts improve procurement predictability and operational efficiency while limiting information asymmetry between principals and agents (( 15 ); ( 16 ); ( 3 ) ). Hospitals should establish dedicated contract monitoring teams, enforce timely payments, and integrate supplier performance scorecards to strengthen accountability and operational efficiency in medicine procurement. Overall, the study confirms that structured procurement planning, rigorous supplier evaluation, and effective contract management collectively enhance the reliability, efficiency, and quality of medicine procurement in resource-limited settings. These findings reinforce Agency Theory principles and provide evidence-based recommendations for improving public sector procurement practices in Tanzanian hospitals. Study Limitation This study focused on three regional referral hospitals in the Dar es Salaam region, highlighting procurement practices within this specific context. Future research could explore hospitals in other regions to provide a broader understanding of medicine procurement across Tanzania. Furthermore, this study used a purely quantitative approach, whereas incorporating qualitative perspectives could offer deeper insights into the experiences and opinions of procurement officers, suppliers, and other stakeholders. Conclusion The study concludes that procurement planning, supplier selection and evaluation, and contract management are critical drivers of medicine procurement effectiveness in regional hospitals. To sustain and enhance these outcomes, hospitals should strengthen planning processes through systematic forecasting, budgeting, and scheduling aligned with organizational priorities. Supplier evaluation mechanisms should be standardized and regularly monitored to ensure accountability, reliability, and quality in the supply chain. Furthermore, effective contract management, including timely payments, compliance monitoring, and risk mitigation, should be institutionalized to minimize disruptions and improve operational efficiency. Policymakers and regulatory authorities, such as the Public Procurement Regulatory Authority (PPRA), are encouraged to provide supportive frameworks, digital tools, and training programs to reinforce these practices, thereby promoting consistent medicine availability and overall healthcare quality. Questionaire The questionnaire used in this study was developed by the research team for the purposes of this project. The full English-language version of the instrument is provided in the Supplementary File named Questionnaire for procurement effectiveness in regional hospitals Abbreviations CAG Controller and Auditor General CPSP Certified Procurement and Supplies Professional MSD Medical Stores Department NAOT National Audit Office of Tanzania PPRA Public Procurement Regulatory Authority PSPTB Procurement and Supplies Professionals and Technicians Board SPSS Statistical Package for the Social Sciences WHO World Health Organization Declarations Availability of Data and Materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics Approval This study did not require formal review or approval by an institutional ethics committee according to national regulations, as it involved minimal-risk and anonymized survey data. Permission to conduct the study and collect data from participating institutions was granted by the Procurement and Supplies Professionals and Technicians Board (PSPTB) (Ref. No. CD.294/574/01A/264). Additional administrative permissions were obtained from Amana, Mwananyamala, and Temeke Regional Referral Hospitals. The study was conducted in accordance with the ethical standards of the Declaration of Helsinki and international guidelines for research involving human participants. All participants provided informed consent before taking part in the study. Participants were informed about the study’s purpose, procedures, potential risks and benefits, their right to withdraw at any time without penalty, and the measures taken to ensure privacy and confidentiality. Consent of Publication Not applicable Competing interests: The author declares no competing interests. Funding: This research received no external funding . Authors’ contributions : JFN, BM, NC, and KM contributed to the study concept and participated in the study design, planning, data interpretation, and reporting. JFN acted as Principal Investigator, supervised data collection, and contributed to reporting. BM contributed to the training and management of data collection, while NC and KM participated in proposal writing and co-supervised data collection. KM and JFN managed data entry and analysis, and together prepared the first draft of the manuscript. Acknowledgements The authors sincerely acknowledge the cooperation and support of Amana, Mwananyamala, and Temeke hospitals during this study. We also extend our gratitude to the entire research team and all individuals who actively participated in and contributed to the successful completion of this work. References van der Kate Bahn, Jennifer Cohen Y. MR. A feminist perspective on COVID-19 and the value of care work globally. 2020;(2020). 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Supplementary Files Questionaireforprocurementeffectivenessinregionalhospitals.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Mar, 2026 Reviews received at journal 13 Mar, 2026 Reviews received at journal 08 Mar, 2026 Reviewers agreed at journal 05 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviews received at journal 26 Feb, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviews received at journal 26 Feb, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers invited by journal 10 Dec, 2025 Editor assigned by journal 04 Dec, 2025 Submission checks completed at journal 03 Dec, 2025 First submitted to journal 03 Dec, 2025 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. 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14:18:17","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":69028,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/d40a050b156397ac5a92df17.html"},{"id":98436687,"identity":"2a90878f-a160-48c6-beef-8be7ef512f40","added_by":"auto","created_at":"2025-12-17 16:56:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25206,"visible":true,"origin":"","legend":"\u003cp\u003eProcurement Planning Scatter Plot for linearity test\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/6ffe6a43e4ba5de2c9df53f7.png"},{"id":98323481,"identity":"c725c3bd-34fe-4010-9386-8be4810fb834","added_by":"auto","created_at":"2025-12-16 14:18:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25738,"visible":true,"origin":"","legend":"\u003cp\u003eSupplier Selection\u003cstrong\u003e \u003c/strong\u003eScatter Plot for linearity test\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/aa7d46b374ee816ec0aa4457.png"},{"id":98436049,"identity":"3b60442c-3693-48bd-8c15-949ad00ac4b9","added_by":"auto","created_at":"2025-12-17 16:54:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25167,"visible":true,"origin":"","legend":"\u003cp\u003eContract Management\u003cstrong\u003e \u003c/strong\u003eScatter Plot for linearity test\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/2231aa6c2fd82565c072d648.png"},{"id":98445299,"identity":"32e4a168-849a-4563-9dc9-06cf697434f0","added_by":"auto","created_at":"2025-12-17 17:19:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":851944,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/fa49abad-e56b-4aa1-a4a1-3e390b05263d.pdf"},{"id":98437584,"identity":"277d54d7-cc86-4985-a0b7-fb294ddcd198","added_by":"auto","created_at":"2025-12-17 16:57:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":41747,"visible":true,"origin":"","legend":"","description":"","filename":"Questionaireforprocurementeffectivenessinregionalhospitals.docx","url":"https://assets-eu.researchsquare.com/files/rs-8141502/v1/68a5faeaca6ab593c6122a1c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of Procurement Practices on Medicine Procurement Effectiveness in Tanzania’s Regional Referral Hospitals: Evidence from Mwananyamala, Amana, and Temeke Hospitals","fulltext":[{"header":"Background","content":"\u003cp\u003eEfficient procurement of medicines is fundamental to the functioning of health systems, ensuring timely, affordable, and quality access to essential medicines. Globally, procurement performance directly influences service delivery, patient outcomes, and health system efficiency. The COVID-19 pandemic further exposed vulnerabilities in pharmaceutical procurement systems, particularly in settings with weak planning capacities, limited supplier networks, and fragile forecasting mechanisms, where widespread shortages of critical medicines were experienced (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Evidence shows that transparent supplier selection, accurate needs-based planning, and effective contract management significantly improve the availability of medicines while reducing costs and minimizing stock-outs (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In high-income countries, innovations such as e-procurement systems and blockchain-enabled contracts have improved accountability, traceability, and efficiency across the procurement cycle (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDespite global progress, many low- and middle-income countries (LMICs) continue to face persistent challenges in medicine procurement. The World Health Organization emphasizes that procurement practices affect not only affordability but also the safety and quality of medicines, thereby influencing clinical outcomes and public trust (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Inefficiencies such as limited competition, poor contract enforcement, weak monitoring mechanisms, and corruption risks undermine procurement performance in LMICs and contribute to inflated prices, supply disruptions, and circulation of substandard or counterfeit medicines (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These weaknesses hinder progress toward Sustainable Development Goal 3 on universal health coverage, particularly in health systems that rely heavily on public procurement as the main source of essential medicines.\u003c/p\u003e \u003cp\u003eIn Africa, medicine procurement remains one of the most critical health system challenges. Fragmented procurement structures, inadequate governance, and financial constraints often lead to duplication of processes, high transaction costs, and long delays in medicine delivery to public health facilities (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Weak forecasting, poor quantification, and unreliable supply chains commonly result in stock-outs of essential medicines, forcing patients to purchase medicines from private pharmacies at significantly higher prices, thereby undermining equity and financial protection. In addition, limited technical capacity within procurement units, such as shortages of trained staff, a lack of digital procurement tools, and weak performance monitoring, further increases vulnerability to inefficiencies and corruption (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although reforms such as African Union-led pooled procurement and national purchasing innovations, including Kenya\u0026rsquo;s NHIF reforms, have improved supplier accountability and price negotiation power (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), persistent challenges such as supplier monopolies, fragmented supply chains, and inadequate contract enforcement continue to impede progress.\u003c/p\u003e \u003cp\u003eIn Tanzania, despite a structured framework and reforms in public procurement systems, public facilities continue to face recurrent stock-outs, procurement delays, and budget limitations, which compromise medicine availability and continuity of care (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Weak forecasting practices, untimely disbursement of funds, and inadequate procurement planning limit hospitals\u0026rsquo; ability to procure adequate quantities of essential medicines. Patients often turn to private pharmacies where prices are significantly higher. Moreover, limited supplier competition, weak supplier performance monitoring, and inadequate contract management mechanisms contribute to procurement inefficiencies within regional hospitals (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Strengthening procurement planning, improving supplier evaluation processes, and enforcing effective contract management, particularly in high-demand regions such as Dar es Salaam, are essential to improving medicine availability, cost-efficiency, and overall quality of healthcare services in Tanzania.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Design and Setting\u003c/p\u003e \u003cp\u003e A descriptive cross-sectional quantitative survey was conducted in three regional hospitals in Dar es Salaam Amana, Temeke, and Mwananyamala. This design was appropriate for assessing the relationship between procurement practices (procurement planning, supplier selection and evaluation, and contract management) and medicine procurement effectiveness at a single point in time ((\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e); (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eStudy Population and Sampling\u003c/p\u003e \u003cp\u003eThe target population consisted of 121 staff involved in procurement activities, including procurement officers, pharmacists, finance officers, and hospital administrators. The sample size was determined using Yamane\u0026rsquo;s (1967) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eWhereby:\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;Sample size\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;Total number of Staff\u0026thinsp;=\u0026thinsp;121\u003c/p\u003e \u003cp\u003ee\u0026thinsp;=\u0026thinsp;Precision\u0026thinsp;=\u0026thinsp;5%\u003c/p\u003e \u003cp\u003eTherefore; n\u0026thinsp;=\u0026thinsp;121/ [1\u0026thinsp;+\u0026thinsp;121(0.05)\u003csup\u003e2\u003c/sup\u003e]\u0026thinsp;=\u0026thinsp;93\u003c/p\u003e \u003cp\u003eWith \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;121 and \u003cem\u003ee\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, the minimum sample size was 93, proportionally allocated across departments. Simple random sampling was used to select respondents. A total of 80 participants completed the survey (response rate: 86%), which was adequate for analysis.\u003c/p\u003e \u003cp\u003eData Collection\u003c/p\u003e \u003cp\u003ePrimary data were collected using structured, self-administered questionnaires consisting of closed-ended Likert-scale items. Secondary data were obtained through documentary reviews of PPRA compliance reports, NAOT audit reports, hospital procurement records, and relevant policy documents to complement primary data (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS Version 31. Descriptive statistics summarized respondent characteristics, and multiple regression was used to assess the influence of procurement planning, supplier evaluation, and contract management on medicine procurement effectiveness.\u0026rdquo;\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eRespondents Demographic Information\u003c/p\u003e \u003cp\u003eThe demographic characteristics of participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were nearly evenly split by gender (51.2% female, 48.8% male). Most participants (57.5%) held undergraduate degrees, 33.8% held diplomas, 6.3% had master\u0026rsquo;s degrees, and 2.5% had certificates. The majority (57.5%) had over five years of work experience. Respondents were evenly distributed across the three hospitals: Temeke (33.8%), Amana (33.8%), and Mwananyamala (32.5%). These figures indicate that the respondents were knowledgeable and experienced in the subject under study, ensuring the credibility and reliability of the collected data.\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\u003eRespondents' Demographics\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable Attribute\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eeducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCertificate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrdinary Diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate/ Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMasters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eyears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;1 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;4 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 Years and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHospital you are working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMwananyamala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTemeke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSPSS, Version 31\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics of the study variable\u003c/p\u003e \u003cp\u003eThe descriptive analysis of study variables shows \u003cb\u003ethat procurement planning practices\u003c/b\u003e were moderately implemented in the regional hospitals, with a mean score of 3.73 (SD\u0026thinsp;=\u0026thinsp;0.481). \u003cb\u003eSupplier selection and evaluation practices\u003c/b\u003e also reflected moderate effectiveness, with a mean of 3.44 (SD\u0026thinsp;=\u0026thinsp;0.444). In contrast, \u003cb\u003econtract management practices\u003c/b\u003e were strongly implemented, as indicated by a mean of 4.76 (SD\u0026thinsp;=\u0026thinsp;0.716). Overall, \u003cb\u003emedicine procurement effectiveness\u003c/b\u003e was high, with a mean score of 4.42 (SD\u0026thinsp;=\u0026thinsp;0.474), suggesting that the hospitals largely achieved their objectives in ensuring timely availability, quality, and cost efficiency of medicines. These figures also indicate that respondents had substantial knowledge of the subject under study.\u003c/p\u003e \u003cp\u003eMultiple Regression Analysis\u003c/p\u003e \u003cp\u003eBefore performing multiple regression analysis, the study tested key assumptions to ensure the validity, reliability, and accuracy of the results. Linearity was confirmed through scatter plots, showing that procurement planning, supplier selection, and contract management each had a linear relationship with medicine procurement effectiveness as summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(Procurement Planning Scatter Plot for linearity test)\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(Supplier Selection and Evaluation Scatter Plot for linearity test)\u003c/b\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(Contract Management Scatter Plot for linearity test).\u003c/b\u003e Normality of residuals was satisfied, as both the Kolmogorov\u0026ndash;Smirnov (p\u0026thinsp;=\u0026thinsp;0.200) and Shapiro\u0026ndash;Wilk (p\u0026thinsp;=\u0026thinsp;0.052) tests indicated no significant deviations, confirming that residuals were approximately normally distributed. Homoscedasticity was verified using the Breusch\u0026ndash;Pagan test (p\u0026thinsp;=\u0026thinsp;0.145), indicating constant variance of residuals across predicted values. Independence of errors was confirmed with a Durbin\u0026ndash;Watson statistic of 1.953, showing no autocorrelation among residuals. Multicollinearity was not a concern, as Variance Inflation Factor (VIF) values ranged between 1.373 and 1.964 and Tolerance values exceeded 0.1, confirming that independent variables contributed uniquely to the model. Finally, outlier analysis using Cook\u0026rsquo;s Distance revealed a low average influence (0.029), with only one case slightly exceeding the threshold, indicating that the regression results were not substantially distorted. Collectively, these tests confirmed that the data met all necessary assumptions for multiple regression analysis, supporting the robustness and reliability of the findings.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eModel Summary\u003c/p\u003e \u003cp\u003eMultiple regression analysis, summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e showed a very strong positive relationship between the combined predictors\u0026mdash;procurement planning, supplier selection and evaluation, and contract management\u0026mdash;and medicine procurement effectiveness (R\u0026thinsp;=\u0026thinsp;0.971). The model explained 94.2% of the variation in procurement effectiveness (R\u0026sup2; = 0.942; Adjusted R\u0026sup2; = 0.940), with a low standard error (0.116), indicating accur\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eMedical Stores Department (MSD) P.O. Box 9081 Dar es Salaam, Tanzania\u003c/em\u003e\u003c/p\u003e \u003cp\u003eate and consistent predictions. These results demonstrate that the model fits the data well and that the three factors collectively have a strong and significant influence on medicine procurement effectiveness in regional hospitals.\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\u003eRegression Model Summary\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=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted R Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.971\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ea. Predictors: (Constant), Contract Management, Procurement planning, Supplier Selection\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eb. Dependent Variable: Medical Procurement Effectiveness\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eANOVA\u003c/h3\u003e\n\u003cp\u003eANOVA results confirmed that the regression model predicting medicine procurement effectiveness was statistically significant (F\u0026thinsp;=\u0026thinsp;414.618, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. This indicates that procurement planning, supplier selection and evaluation, and contract management jointly and individually have a significant impact on procurement effectiveness. Overall, the model provides a good fit, supporting the conclusion that effective planning, supplier management, and contract oversight enhance medicine procurement performance in regional hospitals.\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\u003eANOVA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of Squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e414.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003ea. Dependent Variable: Medical Procurement Effectiveness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eb. Predictors: (Constant), Contract Management, Procurement planning, Supplier Selection\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCoefficients Statistics\u003c/p\u003e \u003cp\u003eThe coefficients analysis shows that procurement planning (B\u0026thinsp;=\u0026thinsp;0.298, β\u0026thinsp;=\u0026thinsp;0.302), supplier selection and evaluation (B\u0026thinsp;=\u0026thinsp;0.185, β\u0026thinsp;=\u0026thinsp;0.173), and contract management (B\u0026thinsp;=\u0026thinsp;0.433, β\u0026thinsp;=\u0026thinsp;0.654), as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, have a positive and significant effect on medicine procurement effectiveness (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This indicates that improvements in planning, supplier management, and contract management each contribute significantly to enhancing procurement performance in regional hospitals\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\u003eCoefficients Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandardized Coefficients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcurement planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupplier Selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContract Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ea. Dependent Variable: Medical Procurement Effectiveness\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study demonstrates that procurement planning, supplier selection and evaluation, and contract management all significantly influence the effectiveness of medicine procurement in regional hospitals. Procurement planning was positively associated with procurement effectiveness (B\u0026thinsp;=\u0026thinsp;0.298, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that structured activities such as needs assessment, budgeting, and adherence to procurement schedules enhance medicine availability, reduce costs, and improve operational efficiency. These findings align with Agency Theory, which emphasizes monitoring and accountability to ensure alignment between agents (procurement officers) and principals (hospital management) ((\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Prior studies in Tanzania, Kenya, and South Africa similarly report that effective procurement planning reduces stock-outs, ensures timeliness, and improves cost control ((\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e); (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e); (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)). Hospitals should strengthen forecasting, budgeting alignment, and training in data-driven procurement to enhance efficiency and accountability.\u003c/p\u003e \u003cp\u003eSupplier selection and evaluation also positively influenced procurement effectiveness (B\u0026thinsp;=\u0026thinsp;0.185, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Transparent prequalification, regular performance assessment, and compliance monitoring improve medicine quality, timely supply, and cost efficiency. These results support Agency Theory by demonstrating that supplier evaluation acts as a control mechanism to reduce opportunistic behavior and align supplier actions with hospital objectives ((\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e); (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e); (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)). Hospitals should implement standardized evaluation frameworks and supplier relationship management systems to maintain consistent supply quality and build trust in procurement operations.\u003c/p\u003e \u003cp\u003eContract management emerged as the strongest predictor of procurement effectiveness (B\u0026thinsp;=\u0026thinsp;0.433, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Effective contract oversight, timely supplier payments, and strategic risk management enhance medicine availability and reliability. These findings corroborate prior evidence showing that well-managed contracts improve procurement predictability and operational efficiency while limiting information asymmetry between principals and agents ((\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e); (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) ). Hospitals should establish dedicated contract monitoring teams, enforce timely payments, and integrate supplier performance scorecards to strengthen accountability and operational efficiency in medicine procurement.\u003c/p\u003e \u003cp\u003eOverall, the study confirms that structured procurement planning, rigorous supplier evaluation, and effective contract management collectively enhance the reliability, efficiency, and quality of medicine procurement in resource-limited settings. These findings reinforce Agency Theory principles and provide evidence-based recommendations for improving public sector procurement practices in Tanzanian hospitals.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitation\u003c/h2\u003e \u003cp\u003eThis study focused on three regional referral hospitals in the Dar es Salaam region, highlighting procurement practices within this specific context. Future research could explore hospitals in other regions to provide a broader understanding of medicine procurement across Tanzania. Furthermore, this study used a purely quantitative approach, whereas incorporating qualitative perspectives could offer deeper insights into the experiences and opinions of procurement officers, suppliers, and other stakeholders.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e The study concludes that procurement planning, supplier selection and evaluation, and contract management are critical drivers of medicine procurement effectiveness in regional hospitals. To sustain and enhance these outcomes, hospitals should strengthen planning processes through systematic forecasting, budgeting, and scheduling aligned with organizational priorities. Supplier evaluation mechanisms should be standardized and regularly monitored to ensure accountability, reliability, and quality in the supply chain. Furthermore, effective contract management, including timely payments, compliance monitoring, and risk mitigation, should be institutionalized to minimize disruptions and improve operational efficiency. Policymakers and regulatory authorities, such as the Public Procurement Regulatory Authority (PPRA), are encouraged to provide supportive frameworks, digital tools, and training programs to reinforce these practices, thereby promoting consistent medicine availability and overall healthcare quality.\u003c/p\u003e\n\u003ch3\u003eQuestionaire\u003c/h3\u003e\n\u003cp\u003eThe questionnaire used in this study was developed by the research team for the purposes of this project. The full English-language version of the instrument is provided in the Supplementary File named \u003cem\u003eQuestionnaire for procurement effectiveness in regional hospitals\u003c/em\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eController and Auditor General\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPSP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCertified Procurement and Supplies Professional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMedical Stores Department\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAOT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Audit Office of Tanzania\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePublic Procurement Regulatory Authority\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSPTB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProcurement and Supplies Professionals and Technicians Board\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not require formal review or approval by an institutional ethics committee according to national regulations, as it involved minimal-risk and anonymized survey data. Permission to conduct the study and collect data from participating institutions was granted by the \u003cstrong\u003e\u003cem\u003eProcurement and Supplies Professionals and Technicians Board (PSPTB) (Ref. No. CD.294/574/01A/264).\u003c/em\u003e\u003c/strong\u003e Additional administrative permissions were obtained from Amana, Mwananyamala, and Temeke Regional Referral Hospitals.\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the ethical standards of the Declaration of Helsinki and international guidelines for research involving human participants.\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent before taking part in the study. Participants were informed about the study’s purpose, procedures, potential risks and benefits, their right to withdraw at any time without penalty, and the measures taken to ensure privacy and confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This research received no external funding\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eJFN, BM, NC, and KM contributed to the study concept and participated in the study design, planning, data interpretation, and reporting. JFN acted as Principal Investigator, supervised data collection, and contributed to reporting. BM contributed to the training and management of data collection, while NC and KM participated in proposal writing and co-supervised data collection. KM and JFN managed data entry and analysis, and together prepared the first draft of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors sincerely acknowledge the cooperation and support of Amana, Mwananyamala, and Temeke hospitals during this study. We also extend our gratitude to the entire research team and all individuals who actively participated in and contributed to the successful completion of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003evan der Kate Bahn, Jennifer Cohen Y. MR. A feminist perspective on COVID-19 and the value of care work globally. 2020;(2020). 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Intelligent Energy Management for Distributed Power Plants and Battery Storage. 2023;2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedroso CB, Beaulieu M. Best practices for procurement contract management Best practices for procurement contract management Carolina Belotti Pedroso *. 2024;(May).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuchoi J, Student M. ISSN 2411\u0026ndash;7323 \u0026copy; SAGE www.sagepublishers.com GLOBAL PUBLISHERS. 2024;8(4):874\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"medicine procurement, health supply chain, medicine stock-out, procurement planning, contract management, supplier evaluation","lastPublishedDoi":"10.21203/rs.3.rs-8141502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8141502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEfficient procurement practices are essential to ensuring the availability, affordability, and quality of medicines in public healthcare systems. Despite various reforms in regulatory frameworks and public procurement systems, Tanzanian regional hospitals continue to face frequent stock-outs and procurement inefficiencies, leading to treatment delay and increased financial burden on patients. This study examined the effect of procurement practices, specifically procurement planning, supplier selection and evaluation, and contract management, on the effectiveness of medicine procurement in regional referral hospitals in Dar es Salaam.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e A descriptive cross-sectional quantitative design was used, involving 80 respondents from Amana, Temeke, and Mwananyamala regional referral hospitals. Primary data were collected using structured questionnaires and analyzed using SPSS version 31. Correlation and multiple regression analyses tested the relationships between procurement practices and the effectiveness of medicine procurement. Reliability was assessed using Cronbach\u0026rsquo;s alpha, with all variables exceeding 0.70.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAll three procurement practices positively and significantly influenced medicine procurement effectiveness. Procurement planning had B\u0026thinsp;=\u0026thinsp;0.298, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, showing that improved planning enhances timely and cost-effective medicine availability. Supplier selection and evaluation had B\u0026thinsp;=\u0026thinsp;0.185, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that effective supplier management improves medicine reliability and quality. Contract management had the strongest effect with B\u0026thinsp;=\u0026thinsp;0.433, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, demonstrating that proper contract oversight, timely payments, and risk management ensure consistent high-quality supply. Together, these practices explained 94.2% of the variation in procurement effectiveness (Adjusted R\u0026sup2; = 0.940), highlighting their combined impact on improving hospital medicine procurement if implemented effectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eEffective and joint implementation of procurement planning, supplier evaluation, and contract management can improve medicine procurement and reduce stock-outs in regional hospitals. Strengthening accountability, compliance monitoring, and supplier management is key to sustaining improvements in public medicine supply systems.\u003c/p\u003e","manuscriptTitle":"Effect of Procurement Practices on Medicine Procurement Effectiveness in Tanzania’s Regional Referral Hospitals: Evidence from Mwananyamala, Amana, and Temeke Hospitals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 14:18:12","doi":"10.21203/rs.3.rs-8141502/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-16T07:34:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-13T13:28:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-08T14:47:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134748780111180567885121965893944928299","date":"2026-03-05T09:02:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228470764674229650745067459807397155381","date":"2026-03-03T16:30:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3970235836388901862284314454086028497","date":"2026-03-03T12:23:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25420069114068963651980449802695342410","date":"2026-03-03T12:11:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7572605704498351667523100251794439564","date":"2026-02-27T07:37:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229707209963793751728967719358143124349","date":"2026-02-27T06:54:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102963888154216581065929402866864558623","date":"2026-02-26T22:19:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T19:30:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244538136735901320208549388096286407263","date":"2026-02-26T16:20:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T13:49:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84047919286706394389526625828809393814","date":"2026-02-26T12:55:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318240770069161597506023239625973113966","date":"2026-02-26T12:27:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-11T03:58:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-04T05:40:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-03T18:05:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-12-03T17:58:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60c92c78-f01f-4744-9aa2-1079d95a9e74","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T08:09:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 14:18:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8141502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8141502","identity":"rs-8141502","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}