T-Analytica Data Analysis

NHP HIS Dashboard

The Nagaland Health Project Hospital Information System Dashboard (NHPHIS Dashboard) is a web- based platform that provides real-time data and insights on the performance of health facilities (District hospitals) in Nagaland. It is part of the Nagaland Health Project (NHP), a World Bank- supported initiative to improve the management and delivery of health services in the state.

The NHPHIS Dashboard provides a variety of data and reports on key health indicators, such as:

  • Daily patient visits and demographics
  • Lab test indicators
  • Drug dispensing indicators
  • IPD management indicators
  • Billing indicators

The dashboard is designed to be used by a variety of stakeholders, including health facility managers,district and state health officials, and policymakers. It can be used to identify areas where improvement is needed, track progress over time, and make informed decisions about resource allocation and service delivery.

Here are some specific details about the NHPHIS Dashboard:

  • Dashboard structure: The dashboard is organized into a series of modules, each of which focuses on a specific aspect of health facility performance. For example, there are modules for patient demographics, service utilization, disease surveillance, drug and supply chain management, human resources, financial performance, and quality of care.
  • Data sources: The dashboard integrates data from all the health facility (district Hospitals) Hospital Management Information System (Bahmni).
  • Data visualization:The dashboard uses a variety of data visualization tools, such as charts, graphs, and maps, to present data in a clear and concise way.
  • Reporting functionality: The dashboard allows users to generate custom reports on a variety of health indicators.

The NHPHIS Dashboard is a valuable tool for improving the efficiency and effectiveness of health services in Nagaland. By providing real-time data and insights on health facility performance, the dashboard can help stakeholders to identify and address areas of need, track progress over time, and make informed decisions about resource allocation and service delivery.

NHP BMW Dashboard

The NHP-BMW (Bio-Medical Waste Management System) dashboard is a web-based tool that provides real-time data and insights on the performance of biomedical waste management application is being used in Nagaland. It is designed to help decision-makers at all levels of the health system to identify and address areas for improvement.

The dashboard includes a variety of features and functionality, including:

  • Key performance indicators (KPIs): The dashboard displays a range of KPIs for biomedical waste management, such as the amount of waste generated, the percentage of waste that is segregated properly, and treatment and dispose of waste.
  • Trend analysis: The dashboard allows users to track KPIs over time to identify trends and patterns. This can help to identify areas where progress is being made, as well as areas where additional support is needed.

The NHP-BMW Dashboard is a valuable tool for improving the efficiency and effectiveness of biomedical waste management in Nagaland. It is used by a wide range of stakeholders, including health facility managers, district health officers, state health officials, and policymakers.

Here are some specific examples of how the NHP-BMW Dashboard is being used to improve biomedical waste management in Nagaland:

  • District health officers: District health officers use the dashboard to track the performance of all health facilities in their district. This information helps them to identify health facilities that are struggling and to provide them with additional support.
  • State health officials:State health officials use the dashboard to track the performance of the entire biomedical waste management system in Nagaland. This information helps them to identify areas where additional resources are needed and to develop policies and programs to improve biomedical waste management.
  • Policymakers:Policymakers use the dashboard to inform their decision-making about biomedical waste management policy and resource allocation. For example, the dashboard could be used to identify the districts with the highest rates of non-compliance with biomedical waste management regulations, so that policymakers can target these districts with interventions to improve compliance.

Mantra Dashboard

Mantra Application Dashboard is a Shiny based analytics platform that provides near real-time insights on a wide range of maternal and newborn health indicators across the health facilities in Uttar Pradesh. The dashboard is appended to Mantra Application which digitally captures labour room register details of a pregnancy case in the facility to improve the monitoring and service quality in antenatal and postnatal care.

The dashboard provides insights on over 150 MNCH indicators under the following categories:

  • Maternal health status and other related indicators before and after delivery
  • Newborn health status and other related indicators
  • Referral details of mothers and newborns

The dashboard leverages on state-of-the-art technologies including R, Python and Arrow file system for fast computation and scalability. The major features of the dashboard include:

  • Interactive visualization of key indicators using Leaflet GIS and High chart libraries.
  • Bivariate Analysis of mutually related indicators
  • Custom reports as per user requirements

The system currently captures and processes over 3.5 million deliveries and related indicators over the entire state of Uttar Pradesh. It is utilized by users at different levels ranging from Subcentres, PHCs, CHCs, District hospitals, Medical Colleges, Health Ministry and UNICEF for a variety of tasks including monitoring, performance evaluation and report generation.

BRLPS Dashboard

Community-Based Organizations (CBOs) dedicated to driving positive change and empowerment. The Bihar Rural Livelihoods Promotion Society (BRLPS) understands the need for a data-driven system. To further monitor and support these organizations, we are thrilled to work with BRLPS to develop our newly Comprehensive Centralized CBO Dashboard, a powerful tool that offers invaluable insights into the cbo health, membership, financial activities, farming activities, and much more of CBOs. This dynamic reporting tool offers insights at the state, district, block, panchayat, and village levels, aiding in the evaluation and enhancement of various programs and initiatives. We have analyzed key components of the BRLPS Applications Dashboard and the Comprehensive HR Indicators integrated into the system, highlighting how they facilitate informed decisions and workforce management. Here we are dealing with more than 25 million data and helping 38 Districts and 534 blocks in their decision-making.

We assess the financial well-being of Self-Help Groups (SHGs) by examining their savings and loan accounts, including different loan types, amount repayment, amount outstanding, capitalization timelines, and other critical financial data. Our in-depth analysis covers the Bank Sakhi program, focusing on various aspects such as transactions, agent commissions, deposits, withdrawals, and the performance of active and inactive agents. We aim to empower SHGs and Village Organizations (VOs) and integrate them into the agricultural ecosystem to promote knowledge sharing, financial inclusion, and community-driven initiatives. Our collaboration includes agricultural analysis, encompassing both hybrid and local seed varieties, crop assessments specific to the growing season, and the promotion of Zaid crops in addition to traditional ones to optimize agricultural yields and income.

We conduct performance assessments of Cluster Level Federations (CLFs) and provide project-wise grading reports to gauge their effectiveness in enhancing livelihoods. We also meticulously track the distribution of goats and poultry to SHGs on a year and month-wise basis. Our district-wise analysis considers mortality among member beneficiaries and evaluates the insurance coverage for these members. Furthermore, we aim to harness the potential of Neera, a unique beverage, to empower rural communities. We employ various analytical components to gain insights into daily pH value analysis, daily BRIX value analysis, forecasting, collection procedures by tappers, asset acquisitions, and performance evaluations at both the district and block levels.

The BRLPS Dashboard provides a variety of data and reports on key indicators, such as:

  • Financial Activities
  • Community Finance
  • SHGs' Financial Health
  • Cadre Presence
  • Aadhar and Insurance Linkages
  • Bank Sakhi Analysis
  • Agricultural Development
  • Neera Program Evaluation
  • CBOs grading Analysis

Key Features of the Comprehensive Community-Based Organizations (CBO) Dashboard:

Dashboard Structure: The Comprehensive CBO Dashboard is meticulously designed with a user-friendly interface, organized into modular components. It leverages robust technical platforms such as RShiny, Power BI, and Python for efficient data processing and presentation. Each module is thoughtfully structured to focus on specific aspects of CBOs and their operations. These modules encompass vital areas, including CBO formation, membership management, financial transactions, cadre presence, and more, offering a comprehensive and systematic view of CBO performance and community development efforts.

Data Sources: For a truly comprehensive understanding, our dashboard seamlessly integrates data from diverse sources, including Oracle, MS SQL, and others. This integration provides a 360-degree perspective on community engagement and development.

Data Visualization: The Comprehensive CBO Dashboard harnesses the power of data visualization tools, utilizing libraries like HighCharts, Matplotlib, Plotly, and D3.js for complex data representation. Expect to see interactive charts, graphs, maps, and other visual aids that simplify data interpretation. These visualizations can be embedded seamlessly into the Power BI platform, enhancing accessibility and enabling stakeholders to quickly identify trends and areas in need of attention.

Reporting Functionality: Users are empowered with the capability to generate custom reports on a wide array of indicators and metrics. These reports can be exported in various formats, such as PDF or Excel, and may be scheduled using R and Python scripting to ensure timely updates. Whether you're interested in the financial health of Self-Help Groups, the presence of cadre in CBOs, or the progress of flagship programs, you can customize your reports to align with your specific community development initiatives.

This structured, user-centric approach positions the Comprehensive CBO Dashboard as a dynamic platform that leverages the technical prowess of RShiny, Power BI, Python, Oracle, MS SQL, and others. It fosters informed decision-making, strengthens community empowerment, and cultivates sustainable growth by harnessing the full potential of data.

UP Climate Change Authority Dashboard

UP Climate Change Authority Dashboard, a dynamic dashboard offering valuable insights into air quality indicators, is a comprehensive dashboard divided into three main tabs—Air Quality Overview, Air Quality Live, and Air Quality Historical—that provides real-time and historical data visualization, including a GIS-based map, to enhance our understanding of air quality conditions. Powered by R Shiny and utilizing feather data through CPCB-provided APIs, the dashboard covers essential metrics such as the Air Quality Index, station uptime, PM2.5, PM10, NO2, SO2, O3, CO, temperature, relative humidity, and wind speed, all within the last 24 hours.

  • Air Quality Overview: This tab provides a comprehensive view of air quality monitoring stations on a GIS-based map, offering real-time Air Quality Index (AQI) data on an hourly basis. The color-coded AQI range reflects the severity of pollution for quick assessment.
  • Air Quality Live: In this section, multiple charts are dynamically generated from live data obtained through CPCB APIs. These charts include the Average Air Quality Index in the past 24 hours and trends in average pollutant concentrations, both at the city and station level.
  • Air Quality Historical: The Historical tab displays charts derived from historical data, with daily updates. It covers a range of charts, including the Monthly Air Quality Index in past years, the Monthly Pollutant Concentrations in past years, the Wind Speed and Direction Chart, and the Average Air Quality Index over the last year. This historical perspective aids in understanding long-term air quality trends.

This dashboard leverages CPCB authorized APIs to deliver state-specific data for the provided data points and air quality indicators. It supports comprehensive decision-making for policies aimed at combating air pollution and monitoring the situation within Uttar Pradesh state.

  • Station Observation Time: Date Time IST (Based on the last data retrieved in near-real time.)
  • Air Quality Index (AQI): (Based on the past 24 hours)
  • Uptime of the station (based on PM2.5 data): in %
  • PM2.5 (ug/m3) - Near real-time (within the last 24 hours)
  • PM10 (ug/m3) - Near real-time (within the last 24 hours)
  • NO2 (ug/m3) - Near real-time (within the last 24 hours)
  • SO2 (ug/m3) - Near real-time (within the last 24 hours)
  • O3 (ug/m3): Near real time (within the last 24 hours)
  • CO (mg/m3): Near real-time (within the last 24 hours)
  • Temperature (C): Near real time (last 24 hours)
  • Relative Humidity (%): Real-time (last 24 hours)
  • Wind Speed (meters per second) - Near Real Time (the previous 24 hours)

The dashboard's design features modularity, encapsulating each component within separate R Shiny modules for enhanced reusability and maintainability. Dynamic updates driven by reactive expressions cater to user interactions, caching and error handling mechanisms ensures the dashboard's continued functionality even when CPCB APIs are unavailable, The dashboard demonstrates technical depth in the following areas:

  • Data modeling and preparation: The air quality data undergoes thorough cleaning, transformation, and aggregation using R's dplyr and tidyr packages, ensuring data quality and clarity.
  • Data visualization: The dashboard utilizes plotly to create interactive line charts, bar charts, and choropleth maps. These visualizations allow users to explore air quality trends, anomalies, and insights. The choropleth maps are built with the GIS-based Leaflet tool, offering an interactive spatial perspective for users to zoom, pan, and explore regions of interest.
  • Dashboard architecture: The dashboard is designed with modularity and reusability in mind, supported by reactive expressions for dynamic updates based on user interactions, enhancing the user experience.
  • Deployment and performance: The dashboard is securely deployed on Shinyapps.io, employing measures to protect against unauthorized access. To optimize performance and scalability, the dashboard caches data from the CPCB custom APIs, utilizes load balancing to distribute traffic across multiple servers, and follows best practices for resource management.
  • R Shiny packages and tools: The dashboard leverages R Shiny packages like shinydashboardPlus for additional features and plotly for advanced visualizations to provide an enhanced user experience.
  • CPCB custom APIs: HTTP requests to the CPCB custom APIs are made using the httr package, granting timely access to live air quality data. The well-documented APIs simplify their integration into the dashboard, ensuring seamless data retrieval.
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