Drug Stock Research Articles

Emergency stock in a resource-constrained acute care unit: analysis of the medication management process

Introduction: The research is based on the evaluation and analysis of drug stock management in the Emergency Department of Peltier University Hospital Center in Djibouti. Methods: An observational, longitudinal and descriptive study was conducted from December 1, 2023 to April 30, 2024. The aim was to describe the diseases with the highest incidence in the emergency department and to organize a stock of medicines. Results: the health problems that contributed the greatest number of patients were cerebrovascular diseases and renal failure with a length of stay of 27 and 66 hours respectively. In relation to the stages of drug acquisition management, it was possible to analyze that, although there are most of the drugs in the institution, their use and consumption is deficient since there is no physical or documented existence of a stock of drugs in the emergency department, which is expressed in the prolongation of the stay in the service. A medication guide was developed to improve the emergency stock and better patient management. Conclusions: The lack of a stock of medicines in the emergency department affected the stage (use - consumption), which is the most important for the adequate management of the patient, thus prolonging the stay in the service

Analysis of Drug Inventory Control Using ABC Method (Always Better Control), EOQ (Economic Order Quantity), And ROP (Reorder Point) At Untada General Hospital, Palu

The procurement of pharmaceutical supplies, including drugs, is the part that uses the largest budget in the hospital. The use of this large budget requires the hospitals to control drug stocks to prevent the possibility of emptiness or over stocks that can cause losses. The uncertainty in planning of drug necessity, encourages the application of a method in controlling drug inventory. The aim of this study was to determine the amount and investment value of drugs included in groups A, B, C and to determine the EOQ and ROP values of the drugs. This study was a quantitative study with a retrospective approach using secondary data in the form of drug procurement during January-December 2022 owned by Undata Hospital Palu. The results of the analysis using the ABC method obtained that group A had 64 items (11%) with investment value IDR 11,048,130,440 (75%), group B had 142 items (25%) with investment value IDR 2,976,402,576 (20%), and group C had 364 items (64%) with investment value IDR 737,979,346 (5%). The optimum amount of medicine ordered based on the EOQ method was around 1-100 items at most. The minimum amount of medicine stock to be reordered based on the ROP method is around 1-100 items at most

Pengembangan Aplikasi Manajemen Apotek Berbasis Aplikasi Visual Studio 2022

The development of information technology has encouraged digitalization in various sectors, including the pharmaceutical industry. This research aims to develop a Visual Studio 2022-based pharmacy management application that can increase the efficiency and accuracy of pharmacy data management, including drug data, sales transactions and stock. The research methodology uses a software engineering approach which includes requirements analysis, design, implementation, testing and maintenance stages. This application is designed with an intuitive and responsive user interface using the C++ programming language and a SQL Server database for data management. Application test results show optimal performance in supporting pharmacy business processes, such as stock management, transaction recording and automatic reporting. The conclusion of this research is that the application developed is able to provide an effective and efficient solution to overcome challenges in managing traditional pharmacies. Further development is needed to integrate the application with electronic payment systems and telemedicine features to improve overall pharmacy services.

Stock Prediction Of Single-Use Medicine Using Autoregressive Integrated Moving Average

Stock Prediction of Single-Use Medicine Using Autoregressive Integrated Moving Average the(3, 1, 3) model, derived from the (p,q,d) model where p is the AR level, d is the process level that makes the data stationary, and q is the MA level. The (3, 1, 3) model used provides quite good results the ARIMA (3, 1, 3) model can be a good tool to predict the need for consumable drug stocks show that the ARIMA (3, 1, 3) model gives good results,log likelihood values and information criteria indicating that the model is reliable. Predictions for the demand for consumable drugs in 2025 show a downward trend, Requires further attention to understand the causes. health centres can plan drug procurement more precisely and efficiently meet patient needs without experiencing overstocks or shortages.

Perancaangan Sistem Informasi Apotik Berbasis Web: Optimalisasi Layanan Pelanggan

This research discusses the development and implementation of a "Web-Based Pharmacy Information System" which aims to improve the efficiency of customer service and drug inventory management. By using web technology, PHP programming language, and MySQL database, this system allows pharmacies to monitor drug stocks in real-time, manage patient information, and provide integrated services. The use of PHP and MySQL in developing this application allows the automation of administrative tasks, including drug stock tracking, orders, and patient data management. This system also facilitates customer service with easy access to drug information and online drug ordering services. The research results show that the implementation of the Web-Based Pharmacy Information System has succeeded in increasing pharmacy efficiency, reducing drug stock shortages, and improving customer service. This system supports integrated drug management by integrating patient data, drug stock and customer service in one platform. Overall, this system illustrates how the use of web, PHP, and MySQL technologies can optimize customer service and medication inventory management in the pharmacy context, providing major benefits to pharmacies and patients.

Challenges and Implementation of Drug Inventory Control in Hospitals: Literature Review

One of the most important hospital management functions is the management of pharmaceutical drug logistics. Drug planning is the process of selecting the type and quantity of drugs required for procurement. Various managerial theories can be used to analyze drug control in pharmaceutical installations, and three research journals on pharmaceutical drug logistics control in hospitals are used for this literature review. The results of the analysis show that there are four methods in drug control: EOQ (economic purchase amount), ABC (better control at all times), ROP (point of repurchase), and VEN (vital, essential, and non-essential). One way to help pharmaceutical logistics stock inventory be more efficient, efficient, and responsive to patient needs and service dynamics is to apply one or a combination of these four methods. Good drug stock management can ensure optimal inventory control, improve service quality, reduce costs, and better manage risks.

Evaluation of the Implementation of the Elderly Posyandu in the Petumbukan Health Center Work Area Deli Serdang District in 2024

Posyandu was formed to facilitate the elderly in obtaining health services, coaching and developing potential abilities in order to realize an independent person. Monitoring and evaluation of the implementation of Posyandu Petumbukan is important to do by providing education and socialization of the interests of the elderly, facilitating transportation of Posyandu for the elderly that are difficult to reach, taking a personal and empathetic approach by inviting participation, including home visits, providing additional services such as specialist health checks, social activities, and welfare programs. This qualitative study aims to evaluate the implementation of Posyandu in the Petumbukan Health Center Work Area. The informants were 15 people by conducting in-depth interviews equipped with a voice recorder. The research variables were communication, human resources, attitudes, and SOPs. The results of the study were that there was a need for communication training for cadres and health workers to improve the delivery of clearer and more detailed health information, cadres and health workers need to manage queues well, a friendly attitude needs to be maintained and improved with better training, increasing the number of cadres and health workers with special training for elderly health, the health center also needs to ensure the availability of drug and vitamin stocks periodically through better inventory management,

Analysis of Drug Sales Patterns in the Belawan Naval Hospital Pharmacy Using Apriori Algorithm

Hospital pharmacy plays an important role in ensuring drug availability and effective stock management. With the increasing number of drug redemptions, manual data management becomes inefficient and can lead to understocking or overstocking. Therefore, a method is needed that is able to automatically analyze drug sales patterns to improve stock management efficiency. One approach that can be used is the Apriori algorithm, an effective data mining technique for finding patterns in drug redemptions. This study aims to analyze drug redemption patterns at the Belawan Navy Hospital Pharmacy using the Apriori algorithm. The data used is drug redemption data. The Apriori algorithm is applied to find relationships between drug items that are often purchased together, so that it can provide useful insights in drug stock management. The results of the study showed that the Apriori algorithm successfully identified several significant drug redemption patterns. These patterns can be used to improve the efficiency of drug stock management and ensure timely drug availability, as well as reduce the risk of understocking or overstocking. The results of the study used logistic regression to predict discrete (binary) values from a column based on values from other columns and the accuracy obtained was 1.0 or 100%. This study concludes that the application of data mining with the Apriori algorithm can provide significant benefits in optimizing the management of drug stock redemption in hospital pharmacies.

Improvement of Drug Stock Management Using ABC-VED Analysis in a University Hospital

Objective: Hospitals allocate approximately 35% of their budgets to pharmaceutical and material stocks in order to provide uninterrupted health services. For this reason, hospital managers spend a lot of time and effort in order to keep a minimum level of stock so as not to disrupt health service production and thus to better manage the limited resources of the enterprise. The aim of this study is to group the drugs according to their financial value and vital importance. In this way, it is aimed to perform stock management in the least costly, errorfree and effective way. Method: In the study, data corresponding to one-year (2021) consumption of a total of 1327 items of drugs were analyzed. The total cost is approximately 83 million ₺. In this study, an ABC-VED cross-analysis was performed on the one-year drug consumption data of a university hospital with 853 beds in order to provide an example of a more controlled inventory structure. Results: According to the results, it is seen that the ratio of drugs in the first category, that is, drugs that are both high cost and vital for the patient, to the total drug item is 38%. The cost of these drugs constitutes 87% of the total cost. Conclusion: Taking into account the classifications put forward in the study, strict monitoring of a small number of drugs and regular weekly counts will make drug stock management much easier for managers.

Optimization of K-Means Clustering Method for Drug Grouping at Mertoyudan I Health Center, Magelang

Health centers as health service providers have an important role in ensuring adequate drug availability for the community. However, drug management in health centers often faces obstacles, including the use of manual methods in stock monitoring, which can lead to unavailability or accumulation of unused drugs. This study aims to improve the efficiency of drug management in health centers through the application of the K-Means Clustering method. This method is used to group drug stocks into three main clusters: heavy drugs, moderate drugs, and light drugs. With this grouping, it is expected that pharmacists can more easily determine the type of drug, monitor drug availability in a timely manner, and manage drug procurement according to patient needs. Research methods include literature studies, data collection and analysis, system modeling design, and system testing and evaluation. The results of this study are expected to improve the efficiency of drug management in health centers, so that health services to the community can be more optimal. The results of testing using the Silhouette Coefficient (SC) method produced an average SC of 0.97 which means strong structure, so it can be concluded that it has a strong structure.

A Rare Case of Occupational Aniline Poisoning: Management in a Limited-Facility Setting

Introduction Cyanosis along with altered mental should bring all the possible ethiologies into her mind in a minimum of time, based on the trauma, medical, environmental, and occupational history of the patient. Poisoning with methemoglobinemia inducing agents is one of the most important differentials especially when a history of occupational exposure to these agents is present. Case Report The patient, a 41-year-old healthy woman and engineer, experienced symptoms after exposure to aniline leading to dizziness and weakness, prompting a visit to the emergency department with cyanosis and low oxygen saturation. Initial vital signs showed decreased oxygen levels and elevated respiratory rate with normal ABG values despite ongoing cyanosis. Patient required intubation, mechanical ventilation, and was diagnosed with ARDS based on chest X-ray findings. Management included IV diuretics, 100% oxygen, and antioxidant treatment in the ICU. Despite treatment, oxygen saturation remained at 88% on the first day. Conclusion This case is a reminder of the importance of taking occupational history and management of aniline toxicity in a setting where methylene blue, the drug of choice for aniline toxicity, is not available in the drug stock.

PENGGUNAAN K-MEANS DAN HIERARCHICAL CLUSTERING SINGLE LINKAGE DALAM PENGELOMPOKKAN STOK OBAT

Adequate and efficient availability of medicines is necessary to ensure patients receive optimal care. However, inefficient drug stock management can result in various problems, such as waste of resources, lack of necessary drugs, or even excessive stock. This study aims to improve the efficiency of the drug stock management process by using KMeans Clustering and Hierarchical Clustering methods on drug stock data. The data used includes information on initial stock, purchase, incoming distribution, service, outgoing distribution, outgoing adjustment, and final stock. Clustering analysis was performed to identify patterns in the drug stock data, which was then validated using Silhouette Score. The results showed that Hierarchical Clustering was able to achieve a Silhouette Score of 0.976, while KMeans achieved a Silhouette Score of 0.954

Inventory System Design Using the First In First Out Method

The use of computers is growing rapidly in all fields according to the progress of the times, resulting in many changes in human life in dealing with every problem that occurs and is related to the development process as a whole. One of the developments in the business sector is the Inventory System. Businesses operating in the field of drug sales still use the method of stocking goods, where when one of the stocks of a drug runs low, it will be immediately stocked. The information system that will be created for drug supplies uses the First In First Out (FIFO) method. The FIFO method means that the company will first use old/first-in stock for sales. It is hoped that this research will help leaders and employees manage drug stock transaction data efficiently.

Comparison of Chen's Fuzzy Time Series and Triple Exponential Smoothing in Forecasting Medicine Stocks at the Blang Cut Kuala Community Health Center

Forecasting is estimating future conditions by examining conditions in the past. In social life, everything is uncertain and difficult to predict precisely, so forecasting is needed. Efforts are always made to make forecasts in order to minimize the influence of this uncertainty on a problem. In other words, forecasting aims to obtain forecasts that can minimize forecast errors, which are usually measured by the mean absolute percentage error. This method is usually used for time series-based forecasting and uses data or information from the past as a reference when predicting current data. This research will compare the application of the Fuzzy Time Series Chen method and the Triple Exponential Smoothing method in forecasting drug stock determination at the Kuala Community Health Center, Blang Mangat District, Lhokseumawe City Regency, Aceh. The research results showed that the Triple Exponential Smoothing method was better in forecasting drug stock inventories compared to Chen's Fuzzy Time Series method. Chen's Fuzzy Time Series method produces a MAPE value of 17.67%, which means it has an accuracy of 82.33%, while the Triple Exponential Smoothing method produces a MAPE value of 9.842%, which means it has an accuracy of 90.158%

Peningkatan Efisiensi dan Manajemen Informasi dalam Pelayanan Unit Kesehatan Sekolah (UKS) Berbasis Website

The School Health Unit is an important component in the education system to promote the health and well-being of students. UKS aims to provide comprehensive health services to students, including disease prevention, health monitoring, health counseling, and basic medicine. But there are several obstacles that are often faced in managing data in the UKS, including limited technology infrastructure, lack of training and skills in data management, time constraints, data privacy and security issues and several other obstacles that might occur. For this reason, a website-based information system is needed that can be used easily by all people but still with useful features such as drug stock lists and student visits so as to be more efficient in inputting data. The School Health Unit Information System (SI-UKS) is a technology platform used to manage and organize student health information and support the administrative and operational activities of the School Health Unit. The School Health Unit Information System (SI-UKS) plays an important role in improving the efficiency and management of information in school health services. Through efficient management of student data, good data reporting and analysis, and integrated communication, SI-UKS helps improve the quality of health services and overall student well-being. In designing this website-based Information System using the waterfall method.

Kinetic and Thermodynamic Interplay of Polymer-Mediated Liquid-Liquid Phase Separation for Poorly Water-Soluble Drugs.

Understanding the interplay between kinetics and thermodynamics of polymer-mediated liquid-liquid phase separation is crucial for designing and implementing an amorphous solid dispersion formulation strategy for poorly water-soluble drugs. This work investigates the phase behaviors of a poorly water-soluble model drug, celecoxib (CXB), in a supersaturated aqueous solution with and without polymeric additives (PVP, PVPVA, HPMCAS, and HPMCP). Drug-polymer-water ternary phase diagrams were also constructed to estimate the thermodynamic behaviors of the mixtures at room temperature. The liquid-liquid phase separation onset point for CXB was detected using an inline UV/vis spectrometer equipped with a fiber optic probe. Varying CXB concentrations were achieved using an accurate syringe pump throughout this study. The appearance of the transient nanodroplets was verified by cryo-EM and total internal reflection fluoresence microscopic techniques. The impacts of various factors, such as polymer composition, drug stock solution pumping rates, and the types of drug-polymer interactions, are tested against the onset points of the CXB liquid-liquid phase separation (LLPS). It was found that the types of drug-polymer interactions, i.e., hydrogen bonding and hydrophobic interactions, are vital to the position and shapes of LLPS in the supersaturation drug solution. A relation between the behaviors of LLPS and its location in the CXB-polymer-water ternary phase diagram was drawn from the findings.

Health System-Related Factors that Influence Retention in Care among HIV Infected Pregnant Women in Narok County, Kenya

Purpose: The aim of the study was to establish the health system-related factors that influence retention in care among HIV infected pregnant women in Narok County, Kenya. Methodology: The study adopted a cross-sectional mixed method design. Purposive sampling method was used to sample the required sample size of 117 HIV infected pregnant women, the participants of the Focus Group Discussions (FGD) and Key Informant Interviews (KII). The study was carried out at Narok County Referral and all the sub-county hospitals in Narok County. A structured questionnaire was used to collect quantitative data. Focus group discussion and KII guides were used to collect qualitative data. Quantitative and qualitative data was analyzed using SPSS version 21 and Nvivo version 14 respectively. Chi square test and logistic regression analysis were used to determine the health system-related factors that influence retention in HIV care. Thematic content analysis was done for qualitative data. The mean age of participants was 30 years (SD=6.48). The study results generated were presented in bar graphs and tables for quantitative data. Results were presented as narrations and triangulated with qualitative data. Findings: This study established that health system-related factors (waiting time, health care workers services and ARV availability) influenced retention in care among HIV infected pregnant women. However, only ARV availability had a significant association with retention in care (P<0.001, OR=0.19). The multiple logistic regression was used to predict the influence of grouped variables. Overall, the model was a significant predictor of retention in care. Health system related factors was found to increase the likelihood of being retained in care (OR=5.14), though not significant predictors of retention in care (P<0.34). Unique Contribution to Theory, Practice and Policy: Health system-related factors particularly ARV drug stocks, healthcare workers staffing and timely access of services should be strengthened in order to avert stock outs, minimize waiting time and follow up patients who miss clinic appointments to increase retention among pregnant women in HIV care. Advocate for policy reforms aimed at addressing structural barriers to retention in care, including increased investment in healthcare infrastructure, workforce capacity building, and integration of HIV services within maternal and child health programs. By aligning policy initiatives with the unique needs of HIV-infected pregnant women, policymakers can foster an enabling environment for retention in care, ultimately contributing to the achievement of national and global HIV/AIDS targets.

Classification of Drug Data Usage Using the K-Means Deep Algorithm to Minimize Drug Stock Shortages (Case Study: South Cikarang Community Health Center)

Efficient utilization of medicines is essential for effective health service delivery, especially in community health centers. This research explores the application of the K-Means clustering algorithm to categorize drug usage data and minimize stock shortages. This research, conducted at the South Cikarang Community Health Center, analyzed drug use patterns to identify drugs with high and low demand. Through data collection, cleaning, and pre-processing, medication use data is converted into a format suitable for clustering analysis. The clustering method approach can be applied to analyze the level of drug use produced by utilizing data sets to record the process of drug data results. The K-Means algorithm model applied has results that show new insights, namely grouping usage levels based on 2 clusters; cluster 1 (C0) is a high potential category consisting of 3.4 data from the tested dataset, and cluster 2 (C1) is Low Potential. Consists of 7.2 tested data, right? Collaborative testing can also produce collaborative testing results that show an average figure of 0.545.

SISTEM INFORMASI PENDATAAN OBAT MASUK PADA APOTEK HERBANA CILEGON BERBASIS WEB DENGAN MENGGUNAKAN PEMROGRAMAN CODEIGNITER

Herbana Cilegon Pharmacy is one of the places that functions as a public health service. Seen from its function, this pharmacy functions to provide medicines that the community needs to achieve good and optimal health. Herbana Pharmacy is still done manually, employees have to record drug data in a ledger, so it takes a lot of time. The data collection process at the Cilegon Herbana Pharmacy still uses manual methods and experiences many obstacles in data processing such as data collection, calculations and making drug stock reports. Because errors in drug data collection often occur, causing inconsistencies in the amount of drug stock data recorded in the drug supply book. To overcome this problem, the author designed a system that can help in collecting data easily and can simplify the drug data collection process. To build a sales system at the Cilegon Herbana Pharmacy, the author uses use cases, class diagrams, activity diagrams, sequence diagrams, normalization and hypo, while the implementation uses PHP and MySql. The result of this research is that a web-based drug inventory information system for drug data collection is used to simplify the drug data collection process

Gambaran Penjualan dan Investasi Obat Generik Apotek “X” Kelurahan Karang Anyar Kota Tarakan Menggunakan Analisis ABC Tahun 2022

Pharmacies have a role in providing health services and as a business that follows the principle of profitability. If drug management is inefficient, it can result in excessive drug stocks and/or running out of stock of several types of drugs. This research aims to find out how big the percentage of drugs is in the number of sales transactions and the investment value in planning drug needs using the ABC analysis method at Pharmacy "X". This research is a retrospective study using quantitative descriptive methods. The object studied is data on the number of sales transactions for generic medicines at Pharmacy "X" for the period January-December 2022. The sample used in this study was 168 items of medicine sold throughout 2022 using a total sampling technique. The results of ABC analysis based on investment value show that group A consists of 34 medicinal items with an investment value of IDR 103,417,500 (69.43%), group B consists of 42 medicinal items with an investment value of IDR 30,276,000 (20 .33%) and group C consists of 92 items of medicine with an investment value of IDR 15,258,300 (10.24%). Group A drug items have the highest sales and investment levels, so it is important to ensure stock availability to reduce the risk of decreasing service quality and pharmacy losses.