Understanding Forecasting and Quantification of Paracetamol and Iron tablets in Nepal’s Public Health System

Understanding Forecasting and Quantification of Paracetamol and Iron tablets in Nepal’s Public Health System | 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 Understanding Forecasting and Quantification of Paracetamol and Iron tablets in Nepal’s Public Health System Heem Sunder Shakya, Gurpreet Kaur, Karan Shakya, Roshan Man Bajracharya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9256359/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background Ensuring regular and uninterrupted availability of essential drugs is a cornerstone of an effective public health system. Despite their importance, the public health supply chain continues to face challenges, particularly relating to consistent supply of essential drugs, including accurate forecasting and efficient procurement processes. The study focused on sub-national levels health institutions with an objective to understand how existing forecasting practices impact the efficiency and reliability of supply chains in public health logistics. Method The research employed a mixed-methods approach, using quantitative surveys and qualitative interviews to gather data from various public health institutions. A sample size of 325 health institutions were selected across geographical settings. Data analysis involved both quantitative statistical and qualitative thematic analysis. Result There were no clear pattern of using data like LMIS, HMIS, and Population data. 50% of the health institution thought the method they were using was not effective. 58% of the health staff received no formal training. 97% of the health institution did not have automated software for quantification. 56% of the health institutions did not have printed guideline in their office premises and almost none of the health facilities were using computer based program for forecasting. Conclusions There is a significant gap on the process of quantification and forecasting of health products. Interventions are needed to institutionalize the standard forecasting/quantification process, efficient use of information, use of modern technology-automated system, and strengthening capacities of health staff should be implemented to make positive impact on Nepal’s public health supply chain system. Forecasting LMIS Procurement Quantification Supply Chain System Figures Figure 1 INTRODUCTION Operational and effective supply chains provide critical medicines, vaccines, and essential medicines to support communicable disease prevention, control, and response activities. 11 Essential medicines which includes paracetamol and iron tablets are those medicines that cater to the primary health care needs of the people. 9 Government of Nepal has a special programme to supplement Iron tablets for pregnant women. 10 To improve the child survival and development outcomes intake of 180 iron tablets during the pregnancies. 6 Efficient supply chain management require trained and competent staff to execute operations. The skills needed to manage a supply chain include quantification/forecasting, inventory management and analysis, and procurement management. 11 Supply chain (forecasting, procurement) gaps result in frequent drugs and medicines stock-outs or overstocks leading to expiration of health products. 10 We aim to address these gaps through this research to analyze existing quantification and forecasting processes and identify systemic gaps and propose practical, evidence-based solutions to improve quantification/forecasting efficiency to ensure timely procurement and availability of these two essential medicines. METHODS We employed a mixed-methods approach, combining quantitative surveys with qualitative interviews. We collected data from a wide range of Nepal’s health institutions at sub-national levels, including district health offices, municipalities, hospitals, primary healthcare centers, and health posts. The duration of data collection was from January to November 2025. Ethical approval from the NHRC was taken for the research and client consent was taken before filling up the questionnaire. We selected a sample size of 325 health institutions across all 7 provinces, covering diverse geographical settings. We used the formula n = Z 2 x p x (1 - p) / E 2 and adjusted using n adjusted = n/1 + n − 1/N. To ensure representative sampling, we applied stratification by dividing the total population into seven provincial subgroups. We then applied random sampling from each province. The data were tabulated in Excel sheet and available statistical software were used for the data analysis. Inclusion criteria like demographic characteristics, geographical locations, time frame, experience, and willingness to participate in the research were taken. On the part of exclusion criteria unwillingness and inability to participate were considered. Three hundred and twenty five (325) samples were collected from 7 provinces and 44 districts (Fig. 1 .) These health institutions includes 4 from Academic Institution (AI), 20 from Basic Healthcare Center (BHCC), 4 from City/Urban Healthcare Center (CHCC), 8 from District Health Office (DHO), 70 from Gaun Palika (Rural Municipality) (GP), 41 from Hospital at all levels, 110 from Health Post (HP), 51 from Nagar Palika (Urban Municipality) (NP), and 17 from Primary Healthcare Center (PHCC). Key informant interviews were carried out with 51 public health officials across provinces and health institutions. RESULTS 1. Practice of Quantification/Forecasting : On the question, “Do you do quantification and forecasting exercise before procurement?”, 87% of health institutions indicated conducting exercise on forecasting/quantification of paracetamol and iron tablets before the procurement ( Graph 1. ). A chi-square test of independence was carried out to determine the association between health facility type and binary outcome (Yes/No). The analysis showed a significant association between the two variables, X 2 (8) = 20.50, p = 0.009, showing that distribution of the outcome differs among the type of health facilities. 2. Use of information in quantification/forecasting : Regarding the question, “What data do you consider or refer during the quantification/forecasting exercise? (multiple answers)”, 71% of health institutions used the LMIS data followed by HMIS data, population data, experts opinion, and none ( Graph 2. ). To assess the association between health facility and information used for quantification and forecasting the Pearson’s Chi-Square ( X 2 ) test of independence was conducted. Statistically significant association was observed between health facilities an use of LMIS data, X 2 = 21.64, df = 8, p = 0.006, showing that reliance of LMIS data varied significantly over the types of health facilities. However, no statistically significant association were found between types of health facilities and other data information HMIS (X 2 = 11.75, df = 8, p = 0.163) Population ( X 2 = 12.09, df = 8, p = 0.147) Expert ( X 2 = 9.70, df = 8, p = 0.287) None ( X 2 = 9.62, df = 8, p = 0.293) 3. Effectiveness of the quantification/forecasting process : When asked, “On a scale of 1 (low) to 5 (high), how effective do you find the current forecasting methods you use?”, 50% (scale 1 to 3) of the staff thought the methods they applied for forecasting/quantification was not sufficiently effective, while the remaining respondents considered their methods as effective ( Graph 3. ). A chi-square test of independence showed that there was no association between health facility types and perceived reliability of the process, X 2 (32) = 39.16, p = 0.179. The strength of association is small (Cramer’s V = 0.17), indicating minimal practical differences on reliability of the process across the health facilities studied 4. Training on quantification and forecasting : Regarding the inquiry, “Are you formally trained on how to do quantification/forecasting of health product?”, 42% of the staff had received formal training on forecasting and quantification of health products, whereas 58% of staff received no training ( Graph 4. ). The chi-square test showed a statistically significant association between types of health facility and training status ( X 2 = 34.75, df = 8, p < 0.001). The test indicated that the proportion of health facilities reporting training status differed significantly across the health facilities. 5. Use of computer-based program for quantification and forecasting of health products : On the query, “Do you have computer Program/Software to do Quantification/Forecasting?”, only 3% of the health institutions used computer-based forecasting and quantification tools. On further examination of the 3% users, most of the health facilities were using the MS- Excel spreadsheet which was not automated. 6. Availability of quantification/forecasting guidelines : When asked, “Do you have guidelines on “How to do Quantification/Forecasting of Health products ?”, 56% of the health institution did not have forecasting and quantification guidelines in their health facilities ( Graph 5. ). The chi-square test of independence showed that the availability of guidelines in the health facilities was not dependent on the health institution type. However, it was not evenly distributed among the health institutions. The chi-square statistics was large enough to reject independence. DISCUSSION The study showed that the majority of health institutions were involved in quantification and forecasting process before the procurement, the methods they were following were found not effective and efficient. The information or data used to determine the forecast was inconsistent, many of the health institutions used LMIS followed by the HMIS and population data. Apart from use of LMIS data, utilization of other sources of data did not differ significantly across the health facilities. Accurate forecasting of pharmaceutical needs is contingent upon high-quality data from routine health information systems and such data are vital for both macro-level planning and micro-level implementation within health institutions, yet they often remain underfunded and underutilized; this lack of effective data utilization can lead to stock-outs of essential health products and directly impacts health service delivery. 26 There is a poor coordination between 3-tiers of government, delay budget release, maldistribution of staff, procurement/forecasting issues, and quality of data reporting. 27 More than half of the health institutions staff did not have a formal training 13 on how to do quantification and forecasting of health products and among two health institutions one did not have the quantification and forecasting guideline in their office premises. There were almost none of the health facilities were found to be using automated computer based quantification and forecasting tools. The supply chain management problem is exacerbated due to absence of training and guidelines to minimize the wastage due to effective quantification, forecasting, and inventory management; health facilities should place a mechanism to exchange medicines from overstocked facilities to under stocked ones; health institutions has to improve store management capacity by employing trained and competent health staff, equipping the store with necessary technology and software programs. 15 In this research several limitations may have arise that could affect the validity and applicability of the findings. These limitations are categorized into methodological constraints, contextual factors, data availability, and stakeholder engagement issues. CONCLUSIONS The reliability and effectiveness of the existing quantification and forecasting methods of health products is in question. Unavailability of forecasting guidelines and staff not trained in the methods of quantification affects on the quality of process health institutions are doing and their end product. In the present time of advanced information technological progress the lack of automated computer based tools for forecasting and quantification is very serious and alarming. Concerned government authorities - the three-tiers of local, provincial, and federal government including the development partners should make a concerted effort to take adequate and coordinated steps 12 to address the short comings found above to strengthen the forecasting and quantification process of health products including essential drugs. The recommended interventions are institutionalization of standardized forecasting and quantification process, efficient use of information (LMIS, HMIS, and Population), evidence based strategy 18 , ethical training 14 and standards 21 , strict inspection for quality of drugs 22 , compliance to public procurement regulatory 24 , use of modern technology-automated system 20 , and strengthening capacities of health staff must be implemented to make positive impact on Nepal’s public health supply chain system to reduce wastage 16 and in making year-round availability of health products in the health institutions. Declarations We declare that this manuscript represents valid work and that neither this manuscript nor one with substantially similar content under the present authorship has been published or is being considered for publication elsewhere and the authorship of this article will not be contested by anyone whose names are not listed here, and that the order of authorship as placed in the manuscript is final and accepted by the co-authors. These declarations also represent the authorship which is signed by all the authors in the order in which they are mentioned in the original manuscript. We certify that all the data collected during the study is presented in this manuscript and no data from the study has been or will be published separately. We attest that, if requested by the editors, we will provide the data/information or will cooperate fully in obtaining and providing the data/information on which the manuscript is based, for examination by the editors or their assignees. We also certify that we have taken all necessary permissions from our institution and/or department for conducting and publishing the present work. There is no ethical problem or conflict of interest. We hereby transfer, assign all copyright ownership, including any and all rights incidental thereto, exclusively to Discover Public Health (DPH), in the event that such work is published by the DPH. The DPH shall own the work, including 1) copyright; 2) the right to grant permission to republish the article in whole or in part, with or without fee; 3) the right to produce preprints or reprints and translate into languages other than English for sale or free distribution; and 4) the right to republish the work in a collection of articles in any other mechanical or electronic format. We give the rights to the corresponding author to make necessary changes as per the request of the journal, do the rest of the correspondence on our behalf and he/she will act as the guarantor for the manuscript on our behalf. Ethical Approval and accordance: We confirm that in the research there were no involvement of human or live vertebrates. The ethical approval of the research is obtained from Ethical Committee of Nepal Health Research Council (NHRC), Government of Nepal and a consent letter is received from Management Division, Department of Health Services, Ministry of Health and Population Nepal . (attached). Author Contribution Contribution Details:Nature of work 1 A 2 A 3 A 4 AConcepts √ √ √ √Design √ √ √ √Definition of intellectual content √ √ N/A N/ALiterature search √ N/A N/A N/AClinical studies N/A N/A N/A N/AExperimental studies N/A N/A N/A N/AData acquisition √ N/A N/A N/AData analysis √ N/A √ √Statistical analysis √ N/A √ √Manuscript preparation √ N/A N/A N/AManuscript editing √ √ √ √Manuscript review √ √ √ √Guarantor √ N/A N/A N/AA = Author (1=Corresponding Author)N.B. Except Original article use not applicable (N/A) wherever necessary. Acknowledgement I would like to thank Nepal Health Research Council and Management Division, Department of Health Services, Ministry of Health and Population for providing ethical approval for the research and letter of support for the data collection from the public health institutions. Appreciate the support and guidance from my co-authors - Dr. Gurpreet Kaur, Dr. Karan S. Shakya, and Dr. Roshan Man Bajracharya. And I would like to thank my data collection team which comprises of - Ms. Smita Khadka, Mr. Laxmi Prasad Dahal, Mr. Gyanendra Shrestha, Mr. Madhav Khanal, Ms. Astha Sharma, Mr. Shikhar Gautam, Mr. Sudip Paudel, Ms. Swostika Budathoki, Mr. Ram Bahadur Gharti, Mr. Subash Dawadi, Ms. Prakriti Bhandari, Mr. Karn Dhoj Chand, Mr. Rabindra Karki, Mr. Samman Japrel, Mr. Prayash Lamsal, Mr. Ram Narayan Pandit, Mr. Aashish Shrestha, Mr. Manoj Kumar Sah, and Ram Prasad Koirala. Data Availability Statement: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Due to ethical and privacy considerations, some data may be restricted. All relevant data supporting the findings of this study are included within the article and its supplementary information files where applicable (the section is added in the manuscript). Consent to participate: Authors declare that the study was conducted in accordance with ethical standards. Written informed consent was obtained from all participants prior to engagement in the research. Objectives and scope of research was clarified in the beginning. References Acharya M, Dahal A. Free essential Medicines through Public Health Facilities in Nepal: A Qualitative study University of Arkansas for Medical Sciences. Little Rock, AR, USA: The University of Toledo, OH, USA; 2016. Thapa AB, Shakya R, Al PT. (2025), WHO prequalification of medicines in low- and middle-income countries: Situational analysis of Nepali manufacturers and recommendations, Volume 21, Issue. Adhikari B, Ranabhat K, Khanal P, Poudel M, Marahatta SB, Khanal S et al. (2024). Procurement process and shortages of essential medicines in public health facilities: A qualitative study from Nepal. PLOS Glob Public Health 4(5). Ahmad K, Singh J, Singh RA. Public Health Supply Chain for Iron Folic Acid supplementation in India. PLoS ONE; 2023. Almalki S. (2024). Transforming healthcare through effective health administration practices: a systematic review. J Ecohumanism, 3(7). Anil K, Basel P, Singh S. Low birth weight and its associated risk factors: health institution-based case-control study. Plos One; 2020. Bilal A. Effective supply chain strategies in addressing demand and supply uncertainty: a case study of Ethiopian pharmaceutical supply services. Pharmacy. 2024;12(5):132. Demessie M, Workneh B, Mohammed S, Hailu A. ;availability of tracer drugs and implementation of their logistic management information system in public health institutions of Dessie, north-east Ethiopia. Volume 9. Integrated Pharmacy Research and Practice; 2020. Dhakal N, Gyanwali P, Humagain B, Jha BCR, Sah N, Pradhan P, Dhimal A. M., and, Jha A. (2023). Assessment of quality of essential medicines in public health care facilities of Nepal: Findings of nationwide study. https://doi.org/10.1371/journal.pgph.0001841 Report DHSA. (2022, 2024). Ministry of Health and Population. Donato. S., Roth. S., Parry. J., (2016). Strong Supply Chains Transform Public Health By ensuring the efficient and effective delivery of medicines and commodities, supply chains support healthy populations and regional health security. ISBN 978-92-9257-654-7 (e-ISBN). Erismann S, Pesantes M, Beran D, Leuenberger A, Farnham A, White M, Prytherch H. How to bring research evidence into policy? Synthesizing strategies of five research projects in low-and middle-income countries. Health Research Policy and Systems; 2021. Feyisa D, Jemal A, Aferu T, Ejeta F, Endeshaw A. Evaluation of cold chain management performance for temperature-sensitive pharmaceuticals at public health institutions supplied by the Jimma pharmaceuticals supply agency hub, southwest Ethiopia: pharmaceuticals logistic management perspective using a multi-centered, mixed-method approach. Advances in Pharmacological and Pharmaceutical Sciences; 2021. Gaidhane A. (2023). Ethical considerations in public health practice: addressing challenges and embracing opportunities. Gebremariam ET, Gebregeorgise DT, Fenta TG. Factors contributing to medicines wastage in public health facilities of South West Shoa Zone, Oromia Regional State, Ethiopia: A qualitative study. Journal of Pharmaceutical Policy and Practice; 2019. GFA Consulting Group GmBH. Essential Drug Procurement and Management in Nepal - Current Challenges and How to Address Them. Kathmandu Nepal; 2009. Ghimire A. Sub-standard medicines in Nepal: a crisis of access, equity, and a call for action. Public Health: Front; 2025. K K. A comprehensive review on prevention and management of hospital-acquired infections: current strategies and best practices. International Journal of Biological and Pharmaceutical Sciences Archive; 2023. Karim A, Burri C, Kila JSN, Bambwelo N, Bakukulu JT, de Savigny D. (2024). Systems Thinking for Supply Chains: Identifying Bottlenecks Using Process Mapping of a Child Health Intervention in the Democratic Republic of the Congo (DRC). Systems. Lam LD, Le Luong BP, Mai Linh HT, Hung PM. (2023). Application of Machine Learning in Predicting the Amount of Pharmaceutical Drugs Ordered for the Manufacturer. 1st International Conference on Health Science and Technology. Aung MK, Bhaumik A, Midhun Chakkaravarthy. Analyzing ethic and procurement performance of humanitarian organizations in Myanmar. International Journal for Multidisciplinary Research; 2023. Neupane A, Tamang MB, S., Giri B. (2021). Incidences of poor-quality pharmaceutical products in Nepal. Roshan Man Bajracharya. (2025). Basic Research Methods and Statistical Data Analysis. BP International. DOI: https://doi.org/10.9734/bpi/mono/978-81-990309-3-0 . Sarawa D, Masud A. Strategic public procurement regulatory compliance model with mediating effect of ethical behavior. Heliyon; 2020. Tucker S, McNett M, Melnyk B, Hanrahan K, Hunter S, Kim B, Kitson A. Implementation science: application of evidence-based practice models to improve healthcare quality. Worldviews on Evidence-Based Nursing; 2021. Wagenaar, B., Gimbel, S., Hoek, R., Pfeiffer, J., Michel, C., Manuel, J., … Sherr,K. (2014). Stock-outs of essential health products in mozambique – longitudinal analyses from 2011 to 2013. Tropical Medicine & International Health, 19(7), 791–801. https://doi.org/10.1111/tmi.12314 Wasti et al. Health Research Policy and Systems (2023). Additional Declarations No competing interests reported. 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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-9256359","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638152230,"identity":"f21752a8-5177-4b2a-9422-bc2f7403d0fb","order_by":0,"name":"Heem Sunder Shakya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACAxDB2ACimQ8AmRIypGhhSwBp4SFFCw+YTViLOXvz0Y0/d9gZGxw/8/nVjRoLHgb2w0c34NNi2XMs7TbvmWQzgzO526xzjgEdxpOWdgOvw27kmN1mbGO2MTiQu804hw2oRYLHDL+W+++/3fzZVm9jcP7NM+Ocf8RoucHDdoO37bAZ0Drmx7ltxGg5k2Z2m7ftuLHkjWdmzLl9EjxsBP1y/PAzoMOqDfvOJz/+nPOtTo6f/fAxvFrgQOEAA5sEiMFGlHIQkG9gYP5AtOpRMApGwSgYUQAAH1NOSoxKKRkAAAAASUVORK5CYII=","orcid":"","institution":"Noida International University, UP/New Delhi, INDIA","correspondingAuthor":true,"prefix":"","firstName":"Heem","middleName":"Sunder","lastName":"Shakya","suffix":""},{"id":638152231,"identity":"fc222434-c2f0-4d2e-bfd7-87394a6059d7","order_by":1,"name":"Gurpreet Kaur","email":"","orcid":"","institution":"Noida International University, UP/New Delhi, INDIA","correspondingAuthor":false,"prefix":"","firstName":"Gurpreet","middleName":"","lastName":"Kaur","suffix":""},{"id":638152232,"identity":"4adaf952-af36-4cd4-aa89-e8f849a21cfb","order_by":2,"name":"Karan Shakya","email":"","orcid":"","institution":"Kenyon College","correspondingAuthor":false,"prefix":"","firstName":"Karan","middleName":"","lastName":"Shakya","suffix":""},{"id":638152233,"identity":"0e896753-b98a-4401-99fd-5292fcb4fe31","order_by":3,"name":"Roshan Man Bajracharya","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Roshan","middleName":"Man","lastName":"Bajracharya","suffix":""}],"badges":[],"createdAt":"2026-03-29 04:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9256359/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9256359/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109094657,"identity":"fccac4bf-5333-4045-b064-e3de04a9c5ea","added_by":"auto","created_at":"2026-05-12 13:53:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":820477,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of Nepal showing geographical distribution of data collection sites:\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig1Maprevised.png","url":"https://assets-eu.researchsquare.com/files/rs-9256359/v1/1a12eda3227ccc82f58c4ae1.png"},{"id":109096123,"identity":"9ae5c80e-5c8f-4410-bda7-9e954ee0f0e8","added_by":"auto","created_at":"2026-05-12 14:01:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":948709,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9256359/v1/83c48581-0a58-4ef8-b04c-e5bb3841e6cb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding Forecasting and Quantification of Paracetamol and Iron tablets in Nepal’s Public Health System","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eOperational and effective supply chains provide critical medicines, vaccines, and essential medicines to support communicable disease prevention, control, and response activities.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Essential medicines which includes paracetamol and iron tablets are those medicines that cater to the primary health care needs of the people.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Government of Nepal has a special programme to supplement Iron tablets for pregnant women.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e To improve the child survival and development outcomes intake of 180 iron tablets during the pregnancies.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Efficient supply chain management require trained and competent staff to execute operations. The skills needed to manage a supply chain include quantification/forecasting, inventory management and analysis, and procurement management.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Supply chain (forecasting, procurement) gaps result in frequent drugs and medicines stock-outs or overstocks leading to expiration of health products.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe aim to address these gaps through this research to analyze existing quantification and forecasting processes and identify systemic gaps and propose practical, evidence-based solutions to improve quantification/forecasting efficiency to ensure timely procurement and availability of these two essential medicines.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eWe employed a mixed-methods approach, combining quantitative surveys with qualitative interviews. We collected data from a wide range of Nepal\u0026rsquo;s health institutions at sub-national levels, including district health offices, municipalities, hospitals, primary healthcare centers, and health posts. The duration of data collection was from January to November 2025. Ethical approval from the NHRC was taken for the research and client consent was taken before filling up the questionnaire. We selected a sample size of 325 health institutions across all 7 provinces, covering diverse geographical settings. We used the formula n\u0026thinsp;=\u0026thinsp;Z\u003csup\u003e2\u003c/sup\u003e x p x (1 - p) / E\u003csup\u003e2\u003c/sup\u003e and adjusted using n\u003csub\u003eadjusted\u003c/sub\u003e = n/1\u0026thinsp;+\u0026thinsp;n\u0026thinsp;\u0026minus;\u0026thinsp;1/N. To ensure representative sampling, we applied stratification by dividing the total population into seven provincial subgroups. We then applied random sampling from each province. The data were tabulated in Excel sheet and available statistical software were used for the data analysis. Inclusion criteria like demographic characteristics, geographical locations, time frame, experience, and willingness to participate in the research were taken. On the part of exclusion criteria unwillingness and inability to participate were considered.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThree hundred and twenty five (325) samples were collected from 7 provinces and 44 districts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.) These health institutions includes 4 from Academic Institution (AI), 20 from Basic Healthcare Center (BHCC), 4 from City/Urban Healthcare Center (CHCC), 8 from District Health Office (DHO), 70 from Gaun Palika (Rural Municipality) (GP), 41 from Hospital at all levels, 110 from Health Post (HP), 51 from Nagar Palika (Urban Municipality) (NP), and 17 from Primary Healthcare Center (PHCC). Key informant interviews were carried out with 51 public health officials across provinces and health institutions.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cb\u003e1. Practice of Quantification/Forecasting\u003c/b\u003e: On the question, \u0026ldquo;Do you do quantification and forecasting exercise before procurement?\u0026rdquo;, 87% of health institutions indicated conducting exercise on forecasting/quantification of paracetamol and iron tablets before the procurement (\u003cb\u003eGraph 1.\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eA chi-square test of independence was carried out to determine the association between health facility type and binary outcome (Yes/No). The analysis showed a significant association between the two variables, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e (8)\u0026thinsp;=\u0026thinsp;20.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009, showing that distribution of the outcome differs among the type of health facilities.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Use of information in quantification/forecasting\u003c/b\u003e: Regarding the question, \u0026ldquo;What data do you consider or refer during the quantification/forecasting exercise? (multiple answers)\u0026rdquo;, 71% of health institutions used the LMIS data followed by HMIS data, population data, experts opinion, and none (\u003cb\u003eGraph 2.\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eTo assess the association between health facility and information used for quantification and forecasting the Pearson\u0026rsquo;s Chi-Square (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) test of independence was conducted. Statistically significant association was observed between health facilities an use of LMIS data, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;21.64, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006, showing that reliance of LMIS data varied significantly over the types of health facilities.\u003c/p\u003e \u003cp\u003eHowever, no statistically significant association were found between types of health facilities and other data information\u003c/p\u003e \u003cp\u003eHMIS \u003cem\u003e(X\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;11.75, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.163) Population (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;12.09, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.147)\u003c/p\u003e \u003cp\u003eExpert (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.70, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.287) None (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.62, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.293)\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Effectiveness of the quantification/forecasting process\u003c/b\u003e: When asked, \u0026ldquo;On a scale of 1 (low) to 5 (high), how effective do you find the current forecasting methods you use?\u0026rdquo;, 50% (scale 1 to 3) of the staff thought the methods they applied for forecasting/quantification was not sufficiently effective, while the remaining respondents considered their methods as effective (\u003cb\u003eGraph 3.\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eA chi-square test of independence showed that there was no association between health facility types and perceived reliability of the process, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e (32)\u0026thinsp;=\u0026thinsp;39.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.179. The strength of association is small (Cramer\u0026rsquo;s \u003cem\u003eV\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.17), indicating minimal practical differences on reliability of the process across the health facilities studied\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. Training on quantification and forecasting\u003c/b\u003e: Regarding the inquiry, \u0026ldquo;Are you formally trained on how to do quantification/forecasting of health product?\u0026rdquo;, 42% of the staff had received formal training on forecasting and quantification of health products, whereas 58% of staff received no training (\u003cb\u003eGraph 4.\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eThe chi-square test showed a statistically significant association between types of health facility and training status (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;34.75, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8, \u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001). The test indicated that the proportion of health facilities reporting training status differed significantly across the health facilities.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. Use of computer-based program for quantification and forecasting of health products\u003c/b\u003e: On the query, \u0026ldquo;Do you have computer Program/Software to do Quantification/Forecasting?\u0026rdquo;, only 3% of the health institutions used computer-based forecasting and quantification tools.\u003c/p\u003e \u003cp\u003eOn further examination of the 3% users, most of the health facilities were using the MS- Excel spreadsheet which was not automated.\u003c/p\u003e \u003cp\u003e \u003cb\u003e6. Availability of quantification/forecasting guidelines\u003c/b\u003e: When asked, \u0026ldquo;Do you have guidelines on \u0026ldquo;How to do Quantification/Forecasting of Health products ?\u0026rdquo;, 56% of the health institution did not have forecasting and quantification guidelines in their health facilities (\u003cb\u003eGraph 5.\u003c/b\u003e). The chi-square test of independence showed that the availability of guidelines in the health facilities was not dependent on the health institution type. However, it was not evenly distributed among the health institutions. The chi-square statistics was large enough to reject independence.\u003c/p\u003e "},{"header":"DISCUSSION","content":"\u003cp\u003eThe study showed that the majority of health institutions were involved in quantification and forecasting process before the procurement, the methods they were following were found not effective and efficient. The information or data used to determine the forecast was inconsistent, many of the health institutions used LMIS followed by the HMIS and population data. Apart from use of LMIS data, utilization of other sources of data did not differ significantly across the health facilities. Accurate forecasting of pharmaceutical needs is contingent upon high-quality data from routine health information systems and such data are vital for both macro-level planning and micro-level implementation within health institutions, yet they often remain underfunded and underutilized; this lack of effective data utilization can lead to stock-outs of essential health products and directly impacts health service delivery.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThere is a poor coordination between 3-tiers of government, delay budget release, maldistribution of staff, procurement/forecasting issues, and quality of data reporting.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMore than half of the health institutions staff did not have a formal training\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e on how to do quantification and forecasting of health products and among two health institutions one did not have the quantification and forecasting guideline in their office premises. There were almost none of the health facilities were found to be using automated computer based quantification and forecasting tools. The supply chain management problem is exacerbated due to absence of training and guidelines to minimize the wastage due to effective quantification, forecasting, and inventory management; health facilities should place a mechanism to exchange medicines from overstocked facilities to under stocked ones; health institutions has to improve store management capacity by employing trained and competent health staff, equipping the store with necessary technology and software programs.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this research several limitations may have arise that could affect the validity and applicability of the findings. These limitations are categorized into methodological constraints, contextual factors, data availability, and stakeholder engagement issues.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThe reliability and effectiveness of the existing quantification and forecasting methods of health products is in question. Unavailability of forecasting guidelines and staff not trained in the methods of quantification affects on the quality of process health institutions are doing and their end product. In the present time of advanced information technological progress the lack of automated computer based tools for forecasting and quantification is very serious and alarming. Concerned government authorities - the three-tiers of local, provincial, and federal government including the development partners should make a concerted effort to take adequate and coordinated steps\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e to address the short comings found above to strengthen the forecasting and quantification process of health products including essential drugs.\u003c/p\u003e \u003cp\u003eThe recommended interventions are institutionalization of standardized forecasting and quantification process, efficient use of information (LMIS, HMIS, and Population), evidence based strategy\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, ethical training\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and standards\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, strict inspection for quality of drugs\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, compliance to public procurement regulatory\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, use of modern technology-automated system\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, and strengthening capacities of health staff must be implemented to make positive impact on Nepal\u0026rsquo;s public health supply chain system to reduce wastage\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and in making year-round availability of health products in the health institutions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eWe declare that this manuscript represents valid work and that neither this manuscript nor one with substantially similar content under the present authorship has been published or is being considered for publication elsewhere and the authorship of this article will not be contested by anyone whose names are not listed here, and that the order of authorship as placed in the manuscript is final and accepted by the co-authors. These declarations also represent the authorship which is signed by all the authors in the order in which they are mentioned in the original manuscript.\u003c/p\u003e \u003cp\u003eWe certify that all the data collected during the study is presented in this manuscript and no data from the study has been or will be published separately. We attest that, if requested by the editors, we will provide the data/information or will cooperate fully in obtaining and providing the data/information on which the manuscript is based, for examination by the editors or their assignees. We also certify that we have taken all necessary permissions from our institution and/or department for conducting and publishing the present work. There is no ethical problem or conflict of interest.\u003c/p\u003e \u003cp\u003eWe hereby transfer, assign all copyright ownership, including any and all rights incidental thereto, exclusively to Discover Public Health (DPH), in the event that such work is published by the DPH. The DPH shall own the work, including 1) copyright; 2) the right to grant permission to republish the article in whole or in part, with or without fee; 3) the right to produce preprints or reprints and translate into languages other than English for sale or free distribution; and 4) the right to republish the work in a collection of articles in any other mechanical or electronic format. We give the rights to the corresponding author to make necessary changes as per the request of the journal, do the rest of the correspondence on our behalf and he/she will act as the guarantor for the manuscript on our behalf.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eEthical Approval and accordance:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe confirm that in the research there were no involvement of human or live vertebrates. The ethical approval of the research is obtained from Ethical Committee of Nepal Health Research Council (NHRC), Government of Nepal and\u0026nbsp;a consent letter is received from Management Division, Department of Health Services, Ministry of Health and Population Nepal\u0026nbsp;. (attached).\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eContribution Details:Nature of work 1 A 2 A 3 A 4 AConcepts \u0026radic; \u0026radic; \u0026radic; \u0026radic;Design \u0026radic; \u0026radic; \u0026radic; \u0026radic;Definition of intellectual content \u0026radic; \u0026radic; N/A N/ALiterature search \u0026radic; N/A N/A N/AClinical studies N/A N/A N/A N/AExperimental studies N/A N/A N/A N/AData acquisition \u0026radic; N/A N/A N/AData analysis \u0026radic; N/A \u0026radic; \u0026radic;Statistical analysis \u0026radic; N/A \u0026radic; \u0026radic;Manuscript preparation \u0026radic; N/A N/A N/AManuscript editing \u0026radic; \u0026radic; \u0026radic; \u0026radic;Manuscript review \u0026radic; \u0026radic; \u0026radic; \u0026radic;Guarantor \u0026radic; N/A N/A N/AA = Author (1=Corresponding Author)N.B. Except Original article use not applicable (N/A) wherever necessary.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eI would like to thank Nepal Health Research Council and Management Division, Department of Health Services, Ministry of Health and Population for providing ethical approval for the research and letter of support for the data collection from the public health institutions. Appreciate the support and guidance from my co-authors - Dr. Gurpreet Kaur, Dr. Karan S. Shakya, and Dr. Roshan Man Bajracharya. And I would like to thank my data collection team which comprises of - Ms. Smita Khadka, Mr. Laxmi Prasad Dahal, Mr. Gyanendra Shrestha, Mr. Madhav Khanal, Ms. Astha Sharma, Mr. Shikhar Gautam, Mr. Sudip Paudel, Ms. Swostika Budathoki, Mr. Ram Bahadur Gharti, Mr. Subash Dawadi, Ms. Prakriti Bhandari, Mr. Karn Dhoj Chand, Mr. Rabindra Karki, Mr. Samman Japrel, Mr. Prayash Lamsal, Mr. Ram Narayan Pandit, Mr. Aashish Shrestha, Mr. Manoj Kumar Sah, and Ram Prasad Koirala.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Availability Statement: \u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Due to ethical and privacy considerations, some data may be restricted. All relevant data supporting the findings of this study are included within the article and its supplementary information files where applicable (the section is added in the manuscript).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026nbsp;declare\u0026nbsp;that the study was conducted in accordance with ethical standards. Written informed consent was obtained from all participants prior to engagement in the research. Objectives and scope of research was clarified in the beginning.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcharya M, Dahal A. Free essential Medicines through Public Health Facilities in Nepal: A Qualitative study University of Arkansas for Medical Sciences. Little Rock, AR, USA: The University of Toledo, OH, USA; 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThapa AB, Shakya R, Al PT. (2025), WHO prequalification of medicines in low- and middle-income countries: Situational analysis of Nepali manufacturers and recommendations, Volume 21, Issue.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdhikari B, Ranabhat K, Khanal P, Poudel M, Marahatta SB, Khanal S et al. (2024). Procurement process and shortages of essential medicines in public health facilities: A qualitative study from Nepal. PLOS Glob Public Health 4(5).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmad K, Singh J, Singh RA. Public Health Supply Chain for Iron Folic Acid supplementation in India. PLoS ONE; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlmalki S. (2024). Transforming healthcare through effective health administration practices: a systematic review. J Ecohumanism, 3(7).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnil K, Basel P, Singh S. Low birth weight and its associated risk factors: health institution-based case-control study. Plos One; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBilal A. Effective supply chain strategies in addressing demand and supply uncertainty: a case study of Ethiopian pharmaceutical supply services. Pharmacy. 2024;12(5):132.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemessie M, Workneh B, Mohammed S, Hailu A. ;availability of tracer drugs and implementation of their logistic management information system in public health institutions of Dessie, north-east Ethiopia. Volume 9. Integrated Pharmacy Research and Practice; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhakal N, Gyanwali P, Humagain B, Jha BCR, Sah N, Pradhan P, Dhimal A. M., and, Jha A. (2023). Assessment of quality of essential medicines in public health care facilities of Nepal: Findings of nationwide study. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pgph.0001841\u003c/span\u003e\u003cspan address=\"10.1371/journal.pgph.0001841\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReport DHSA. (2022, 2024). Ministry of Health and Population.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonato. S., Roth. S., Parry. J., (2016). Strong Supply Chains Transform Public Health By ensuring the efficient and effective delivery of medicines and commodities, supply chains support healthy populations and regional health security. ISBN 978-92-9257-654-7 (e-ISBN).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErismann S, Pesantes M, Beran D, Leuenberger A, Farnham A, White M, Prytherch H. How to bring research evidence into policy? Synthesizing strategies of five research projects in low-and middle-income countries. Health Research Policy and Systems; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeyisa D, Jemal A, Aferu T, Ejeta F, Endeshaw A. Evaluation of cold chain management performance for temperature-sensitive pharmaceuticals at public health institutions supplied by the Jimma pharmaceuticals supply agency hub, southwest Ethiopia: pharmaceuticals logistic management perspective using a multi-centered, mixed-method approach. Advances in Pharmacological and Pharmaceutical Sciences; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaidhane A. (2023). Ethical considerations in public health practice: addressing challenges and embracing opportunities.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGebremariam ET, Gebregeorgise DT, Fenta TG. Factors contributing to medicines wastage in public health facilities of South West Shoa Zone, Oromia Regional State, Ethiopia: A qualitative study. Journal of Pharmaceutical Policy and Practice; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGFA Consulting Group GmBH. Essential Drug Procurement and Management in Nepal - Current Challenges and How to Address Them. Kathmandu Nepal; 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhimire A. Sub-standard medicines in Nepal: a crisis of access, equity, and a call for action. Public Health: Front; 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK K. A comprehensive review on prevention and management of hospital-acquired infections: current strategies and best practices. International Journal of Biological and Pharmaceutical Sciences Archive; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarim A, Burri C, Kila JSN, Bambwelo N, Bakukulu JT, de Savigny D. (2024). Systems Thinking for Supply Chains: Identifying Bottlenecks Using Process Mapping of a Child Health Intervention in the Democratic Republic of the Congo (DRC). Systems.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLam LD, Le Luong BP, Mai Linh HT, Hung PM. (2023). Application of Machine Learning in Predicting the Amount of Pharmaceutical Drugs Ordered for the Manufacturer. 1st International Conference on Health Science and Technology.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAung MK, Bhaumik A, Midhun Chakkaravarthy. Analyzing ethic and procurement performance of humanitarian organizations in Myanmar. International Journal for Multidisciplinary Research; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeupane A, Tamang MB, S., Giri B. (2021). Incidences of poor-quality pharmaceutical products in Nepal.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoshan Man Bajracharya. (2025). Basic Research Methods and Statistical Data Analysis. BP International. DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.9734/bpi/mono/978-81-990309-3-0\u003c/span\u003e\u003cspan address=\"10.9734/bpi/mono/978-81-990309-3-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSarawa D, Masud A. Strategic public procurement regulatory compliance model with mediating effect of ethical behavior. Heliyon; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTucker S, McNett M, Melnyk B, Hanrahan K, Hunter S, Kim B, Kitson A. Implementation science: application of evidence-based practice models to improve healthcare quality. Worldviews on Evidence-Based Nursing; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWagenaar, B., Gimbel, S., Hoek, R., Pfeiffer, J., Michel, C., Manuel, J., \u0026hellip; Sherr,K. (2014). Stock-outs of essential health products in mozambique \u0026ndash; longitudinal analyses from 2011 to 2013. Tropical Medicine \u0026amp; International Health, 19(7), 791\u0026ndash;801. https://doi.org/10.1111/tmi.12314\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWasti et al. Health Research Policy and Systems (2023).\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":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Forecasting, LMIS, Procurement, Quantification, Supply Chain System","lastPublishedDoi":"10.21203/rs.3.rs-9256359/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9256359/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEnsuring regular and uninterrupted availability of essential drugs is a cornerstone of an effective public health system. Despite their importance, the public health supply chain continues to face challenges, particularly relating to consistent supply of essential drugs, including accurate forecasting and efficient procurement processes. The study focused on sub-national levels health institutions with an objective to understand how existing forecasting practices impact the efficiency and reliability of supply chains in public health logistics.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eThe research employed a mixed-methods approach, using quantitative surveys and qualitative interviews to gather data from various public health institutions. A sample size of 325 health institutions were selected across geographical settings. Data analysis involved both quantitative statistical and qualitative thematic analysis.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThere were no clear pattern of using data like LMIS, HMIS, and Population data. 50% of the health institution thought the method they were using was not effective. 58% of the health staff received no formal training. 97% of the health institution did not have automated software for quantification. 56% of the health institutions did not have printed guideline in their office premises and almost none of the health facilities were using computer based program for forecasting.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThere is a significant gap on the process of quantification and forecasting of health products. Interventions are needed to institutionalize the standard forecasting/quantification process, efficient use of information, use of modern technology-automated system, and strengthening capacities of health staff should be implemented to make positive impact on Nepal\u0026rsquo;s public health supply chain system.\u003c/p\u003e","manuscriptTitle":"Understanding Forecasting and Quantification of Paracetamol and Iron tablets in Nepal’s Public Health System","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 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