A new rolling forecasting framework using Microsoft Power BI for data visualization: A case study in a pharmaceutical industry.

CONTEXT AND OBJECTIVES: Demand forecasting is a vital step for production planning and consequently, for supply chain efficiency, especially for the pharmaceutical (pharma) supply chain due to its unique characteristics. Numerous models and techniques that are proposed in the literature but little in concrete and generic framework to forecasting process, mainly for pharmaceutical supply chain. Unlike studies in the literature, this study not only perfectly predict the sales of a pharma manufacturer, but also visualize the results via a developed dashboard using modern information technology and business intelligence. MATERIAL AND METHODS: In this research, a rolling forecasting framework comprising of different steps and specialized tools is proposed that can assist supply chain managers to perform an accurate sales forecasting and consequently a better performance and specifically patient satisfaction. The proposed generic framework combines the use of Visual studio C++ software to extract optimal forecasting and the Power BI software to monitor the accuracy of the obtained sales forecasts. Three exponential smoothing methods are integrated in the proposed framework, which is open to adding more new forecasting methods. RESULTS: The proposed framework is tested for many data sets from a pharmaceutical manufacturer company, and the results obtained show superior performance, especially a clear decline in both forecast errors, which can reach 75% and a drop of stock level to 50%. Therefore, the company is currently using it and a future integration with their ERP is being carried out. CONCLUSION: The proposed rolling forecasting framework contributes to insightful decision-making through the visualization of accurate future sales and turnover, and consequently, an efficient stock management and effective production planning.

Constructing an Automated Quality Control Indicator Dashboard by Linking Cloud-Based Forms with POWER BI.

This paper examines the use of quality control indicator audits in healthcare services to identify potential risk issues and improve the quality of medical care. A multi-stage approach was adopted to establish audit tools. This involved creating a cloud-based assessment form using Microsoft Form, developing Power BI dashboards connected to databases, and creating a mobile application for on-the-go auditing and result retrieval. Mobile application has replaced the need to search for and print audit forms, reducing paper usage. Automated audit results are linked to Power BI dashboards, significantly reducing the time spent on manual documentation and chart analysis, saving an average of 40 minutes per audit indicator. The paper proposes that the dashboard's real-time and automated features assist managers in promptly identifying potential issues and taking necessary intervention and guidance measures. These findings emphasise the significance of quality control indicator audits in enhancing the quality and safety of healthcare services.

Constructing a User-Centric Visual Real-Time Surgical Dashboard.

The existing surgery timetable is very simple, not user-friendly, and has very limited information. This article outlines the creation of a surgical dynamic dashboard for users, using Microsoft Power BI. The dashboard was developed based on in-depth interviews with the surgical team members to determine their requirements. The outcome of dashboard was evaluated by 5-likert scale questionnaire to measure satisfaction of all surgical team members. All team members were very satisfied with the dashboard compared to the existing surgery timetable. In addition, with the function of auto-generated analytic reports through data criteria selection on the dashboard saved time on manually generating reports. This study supports to replace the existing surgery timetable by the user-centric and real time surgical dashboard.

Sonication results in variable quality and enhanced sensory attributes of Adajamir (Citrus assamensis) juice: A study on an underutilized fruit.

Citrus assamensis, commonly known as Adajamir, is an underutilized fruit with distinctive sensory and nutritional properties. The limited amount of research on this particular citrus type was recognized as one of the research gaps for this study. The objective of this study was to evaluate and compare the impacts of sonication, pasteurization, and thermosonication techniques on the quality and sensory attributes of Adajamir juice. A randomized experimental design was used in the study, wherein the juice underwent three different treatments. The results indicate that there were no significant changes in pH or titratable acidity following all treatments. Yet, notable differences in juice color were observed. The use of sonication and thermosonication resulted in an increase in ß-carotenoid levels. Additionally, total phenolic content and antioxidant activities were observed to increase. All three treatments led to a reduction in ascorbic acid levels relative to the control. However, the complete elimination of microbial growth was observed during the thermal treatment. Compared to other approaches, sonication has been shown to be notably more efficacious in enhancing both the flavor and aroma. Sonication has been observed to improve the perceived bitterness to a certain degree. These findings support the potential of sonication as an alternative preservation method for Adajamir juice, offering enhanced quality and sensory acceptance.

Development and validation of a standardized blood culture contamination definition and metric dashboard for a large health care system.

OBJECTIVES: Blood culture contamination is a major problem in health care, with significant impacts on both patient safety and cost. Initiatives to reduce blood culture contamination require a reliable, consistent metric to track the success of interventions. The objective of our project was to establish a standardized definition of blood culture contamination suitable for use in a Veterans Health Administration (VHA) national data query, then to validate this definition and query. A secondary objective was to construct a national VHA data dashboard to display the data from this query that could be used in VHA quality improvement projects aimed at reducing blood culture contamination. METHODS: A VHA microbiology expert work group was formed to generate a standardized definition and oversee the validation studies. The standardized definition was used to generate data for calendar year 2021 using a Structured Query Language data query. Twelve VHA hospital microbiology laboratories compared the data from the query against their own locally derived contamination data and recorded those data in a data collection worksheet that all sites used. Data were collated and presented to the work group. RESULTS: More than 50,000 blood culture accessions were in the validation data set, with more than 1,200 contamination events. The overall blood culture contamination rate for the 12 facilities participating was 2.56% with local definitions and data and 2.43% with the standardized definitions and data query. The main differences noted between the 2 data sets were deemed to be issues in local definitions. The query and definition were then converted into a national data dashboard that all VHA facilities can now access. CONCLUSIONS: A standardized definition for blood culture contamination and a national data query were validated for enterprise-wide VHA use. To our knowledge, this represents the first reported standardized, validated, and automated approach for calculating and tracking blood culture contamination. This tool will be key in quality initiatives aimed at reducing contamination events in VHA.

An overview of the gaming industry across nations: using analytics with power BI to forecast and identify key influencers.

Esports has seen a phenomenal explosion in popularity in recent years, gaining increasing interest from the media, sports, and technology industries. The purpose of this study is to show an overview of the recent evolution of the gaming market in representative countries in Eastern Asia, Western Europe, and North America during 2017-2019, and the corresponding growth projections for the next five years. For this purpose, descriptive, correlational, and forecasting analyses were used to assess the relationships among key variables associated with the growth of the gaming industry and to show different possibilities to address the data using data analytics. The games market revenues, total number of players, Google trends data, GDP per capita and online population were studied as possible key influencers to explain the industry's growth. Predictive analytics with MS Power BI revealed a positive correlation between GDP per capita and market revenues and players in European and North American countries, while in Asia was just the opposite. Also, a positive relationship between Google trends in esports and the games market revenues is noted. Forecasts showed significant growth for each region. Practical implications and future research directions are discussed.

Erratum: Real-time monitoring of a circulating vaccine-derived poliovirus outbreak immunization campaign using digital health technologies in South Sudan doi: 10.11604/pamj.2021.40.200.31525.

[This corrects the article DOI: 10.11604/pamj.2021.40.200.31525.].

Real-time monitoring of a circulating vaccine-derived poliovirus outbreak immunization campaign using digital health technologies in South Sudan.

INTRODUCTION: the use of digital health technologies and geographical information systems (GIS) in the conduct of immunization campaigns had proven to be a success story, and is gaining acceptance towards improving supervision, accountability, and real-time access to quality information. The demand for real-time information by policymakers and stakeholders in the polio eradication programme is increasing towards ensuring a world free from all polioviruses. This study aims to develop a tool that monitor and evaluate the circulating vaccine-derived poliovirus (cVDPV) campaign processes in real-time using open data kits (ODK) to collect data, analyze and visualize using an interactive dashboard in Power BI, towards improving timeliness and completeness of data reporting and providing real-time quality information to stakeholders. METHODS: electronic checklists were developed using open data kits (ODK) and uploaded onto android-based smartphones for data collection during a round of cVDPV outbreak response immunization. Supervisors were deployed to the field and the checklists were utilized at both stages of the campaign activities. A Power BI data visualization tool was used for reporting, analysis, and monitoring the activities of the campaign. RESULTS: an interactive dashboard was developed, providing real-time information that supports stakeholders during the campaign processes with improved timeliness and completeness of data reporting. The usage of the tool during the campaign enhanced close supervision, and increased transparency in data availability and accessibility by all partners. CONCLUSION: the study had shown that real-time information has significantly improved the smooth conduct of the immunization campaign processes through identifying gaps, and challenges in the field and can be utilized in similar resource settings including complex and humanitarian. It has demonstrated the capability of mobile phones using ODK for data collection and linked to a Power BI dashboard for enhanced supervision and transparency, and we encourage further studies to assess the effects of the tools on the campaign results.

Application of the DruGeVar Database in Cancer Genomics and Pharmacogenomics.

In the post-genomic era, there is an increasing and urgent need for managing and visualizing big data. Data complexity and size will turn information growth into knowledge growth only if presented in a comprehensive and user-friendly way. In such a context, the information technology community collaborates in a multidisciplinary manner with other scientific fields searching for and/or developing tools and services for data management and visualization. We have previously developed DruGeVar, a comprehensive database that triangulates drugs with genes and pharmacogenomic biomarkers to serve clinical pharmacogenomics. To empower its functionality, we explored and implemented new visualization tools, such as POWER-BI (Microsoft), which allows for interactive visualization. Herein, we describe the synergy of POWER-BI and DruGeVar, focusing on cancer genomics data in light of translational pharmacogenomics.