Butterfly Children Charitable Foundation (AW BI: BI Platform)

2023: Implementation of AW BI BI system for Butterfly Children Charitable Foundation

Since 2011, the Butterfly Children Charitable Foundation has been helping children suffering from gene dermatoses, which affect the skin with hereditary diseases. One of the main tasks of the fund is to establish an effective system of providing medical care to patients. To do this, the fund has introduced the system "Register of Genetic and Other Rare Diseases," which supports the database for the wards of the fund: personal data, medical indications, information on the assistance provided, etc. - more than a thousand characteristics.

AW BI is used to improve forecasts for the amount of assistance required by trust funds.

Applied analytical tasks solved by non-profit organizations, in particular the foundation, have a number of features. Let's list some of the information panels, the need for which arose in the first place:

• Formation of epidemiological and medical analytics;
• Monitoring of fundraising;
• Forecasting the development of the condition of the wards;
• Forecasting the amount of assistance needed.

Based on the requirements, special attention was paid to predictive analytics, which was successfully implemented by the BI-system AW BI. The main purpose of this analytical solution is to manage processes and support the activities of a non-profit organization.

The fund's data sources are a fairly extensive system:

• First of all, this is the Register of Genetic and Other Rare Diseases, collected in. database PostgreSQL Here data is stored about the wards of the foundation, medical staff and employees of the foundation;
• DRM is a system for accounting for relationships with donors. This receives financial information from CloudPayments, 1C: Accounting, MixPlat;
• Excel files where the archive and historical data of the fund are stored.

A number of dashboards were created in four main areas:

• Epidemiology;
• Medicine;
• Social information;
• Fundraising.

As an example, consider the information panel "Epidemiology." Data collected here:

• By gender and age structure with automatic recalculation of data over time. Special attention is paid to the survival of patients to a certain age. These statistics are important, among other things, to ensure data transparency to justify the fund's performance;
• Distribution of wards by diagnoses, the list of which is constantly expanding. Drill-down is implemented and data filtering relative to each other.

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Фото: AW BI

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Фото: AW BI

Already, the analytics, including the predictive one provided by the AW BI system, help calculate the amount of treatment and funding required for each patient, which allows to extend the term and significantly improve the quality of life of the fund's wards.

In the near future, for the needs of the fund, it is planned to implement machine learning (ML), which will expand the existing predictive analytics of the solution and open up the following possibilities:

• Predicting the development of the disease in the ward;
• Forecasting the amount of assistance required by the ward;
• What-if analysis taking into account the forecast model.