Analytical tools play a vital role in accumulating the knowledge needed to make decisions in many areas that directly affect our lives and health, including diagnostics, risk assessment and prediction, decision making in the healthcare and pharmaceutical industries.

How business intelligence helps fight COVID-19

Hospitals, research centers, academic institutions, pharmaceutical companies and consulting agencies around the world are joining forces to fight COVID-19. Here is how big data analytics, accumulated by many countries during the pandemic, supports them in this complex task:

Source: Applications of Big Data Analytics to Control COVID-19 Pandemic

Predictive analytics is not only about analyzing statistical data on cases and morbidity specifics, but also building forecasts of epidemic development in a particular country, region, or locality. Thus, healthcare enterprises are able to determine in advance the required resources, including medical staff, hospital beds, ventilators, personal protective equipment, such as masks, gloves, gowns, and eye protection.

Data types and sources

Health data come from various sources. In addition to patient data obtained directly from hospitals, European and US organizations use data collected through portable/mobile device sensors or medical devices (activity, geolocation, psychological condition), online questionnaires, websites or mobile applications (e.g., flight and rail travel data), data from local and international healthcare systems (capacity of medical facilities, available staff), as well as records from open databases, websites and social networks (including mining of news, viral posts and other publications using AI).

Smart Analytics solutions used in Europe and USA to fight COVID

Since 2008, Smart Analytics experts have been implementing analytical systems for healthcare enterprises in Germany, Spain, Belgium, Italy, Canada and Saudi Arabia.

Of course, clinics have always collected data on their patients, but some 15 years ago, they were mostly processed and stored through Excel tables. Our team has been developing and continuously enhances our information and analytical solutions that handle big volumes of health data and offer effective and visual decision-making tools for analyzing hospital performance, managing costs, planning and predicting risks.

Smart Analytics health tools enable users to:

• consolidate data on hospital activities from various sources
• compare the performance of hospital with the average for the region/country as a whole
• monitor the dynamics of key indicators of the quality of medical/nursing care
• analyze the reasons for changing the values of key indicators of medical/nursing care quality

At the very beginning of COVID-19 pandemic, we quickly finalized COVID analytics modules that help clinics upload patient data on a daily and even hourly basis and receive aggregated data from other market participants.

The system contains information on the date of treatment and the date of discharge of each patient, on the patient location before treatment (at home, abroad), whether there were any complications and of what kind, diagnosis, medical manipulations, prescribed medications, and so on.

Portal is designed to:

1. Track the impact of COVID on hospital occupancy (comparing the number of visits with the pre-COVID base year). In particular, a temporary ban on surgical operations during the outbreak of coronavirus may affect the hospital reporting so that the load on surgery unit would be reduced and, accordingly, cause a decrease in funding for the next year. Analytics allows you to take into account pent-up demand, general trends, and compare indicators with data from other hospitals.
2. Assess the impact of COVID on therapeutic and surgical interventions. Analysis of the cost of health services provided by various medical fields, comparison of data from a particular hospital with the entire hospital group allows planning future workload, and determining services with the highest pent-up demand.
3. Assess bed occupancy and forecast future load depending on the statistics of the entire group, and daily monitoring. For example, if there were no patients on mechanical ventilation in a particular hospital during the analyzed period, but analytics show that they are in the group, it is possible to predict the future load and be prepared for it in advance.
4. Ongoing analysis of patients with coronavirus disease enables you to create a profile of a typical patient (gender, age and other demographic characteristics) and, determine which specialists are needed to treat such patients.