Data-driven public healthcare resources management done right

It has been a long way already and the future hides a lot of uncertainty – while the heroic struggle of governments with the pandemic is plain to see, yet this war was for the most part waged in an uncharted territory dotted with unknowns, so it’s worth looking at the trials and failures, weak and strong sides. How did governments deal with digital tools in their battles against the epidemic?

What were the problems and challenges of the public sector in this area? Did any country fare significantly better than others, and why are all eyes turning to Germany?

The public sector vs the pandemic

Whereas businesses mainly had to maintain their continuity and secure their economic results or, sometimes, seize new opportunities presented by the pandemic, the challenge for public sector could be summarized in one sentence:

To stop the epidemic from developing in order to protect human life and health, and be prepared for problems emerging in the course of doing so.

But in order to assess the activities of the public sector and look at the problems encountered, it is necessary to zoom in to a more detailed level.

Preliminarily speaking, the most important tasks that fell on the shoulders of public authorities during the pandemic have been:

• Reducing the number of new infections
• Providing the resources needed to treat as many patients as possible
• Minimizing the negative social and economic effects of epidemic restrictions
• Convincing as many people as possible to get vaccinated and organize an effective vaccination process

What do all the above have in common?

Numbers.

All of the above tasks can be described with numbers. And it is the numbers, and getting them right, that have become some of the major challenges for the public sector in fighting the epidemic.

The tasks of the public sector related to the management of the epidemic crisis were carried out on the basis of poor quality data.

What does it mean? In short: there were no common definitions of basic terms, no common methodologies to gather the data, no transparent procedures.

In terms of data, what went wrong with the tasks carried out by the public sector?

•  In reducing the number of new infections

Statistics of infections have been severely tainted with comparability issues since the pandemic started. In some countries, they are based on screening tests. Other countries test only those who report COVID-19 symptoms.

It is impossible to draw any rational conclusions from comparing the statistics in both cases. Based on these two different policies, it is impossible to find which country is developing the epidemic faster or which one is more effective in preventing it.

When you add different efficiency of the tests and their types (antibodies and PCR), a rather disturbing conclusion arises: regarding the pace of the epidemic, the contagiousness of the virus and how it penetrates populations, we are still in the dark.

•  In providing the resources needed to treat as many patients as possible

To follow the development of the epidemic, we describe it with statistics. We observe the number of infections, the number of recoveries and, of course, the death rate.
And here comes the next data-related problem – different states have adopted different definitions of death after contracting COVID-19! For example, if someone had had a coronary heart disease, and died of a heart attack while infected with the coronavirus, in one country they would be classified as a COVID-19 victim, and in another – as a victim of a heart attack.
This means that today’s staggering 3,5 million deaths from COVID-19 worldwide shown on worldometers.info is really just a really rough approximation.

• In minimizing the negative social and economic effects of epidemic restrictions

There is an ongoing debate as to whether lockdown costs outweigh the health benefits. The rise in unemployment due to the closure of many companies, and limited access to health care, have been taking their toll for over a year now and researchers from Harvard Medical University, John Hopkins University, and Duke University have proved this can be measured. According to their calculations, unemployment caused by lockdowns will result in more than 0.8 million additional deaths over the next 15 years in the United States only. Are governments measuring the social and economic costs of epidemic restrictions? In most countries, cyclical lockdowns have been the only way to contain the virus for over a year… 

• In convincing as many people as possible to get vaccinated and coordinating an effective vaccination process

Vaccinations against COVID-19 are progressing at varying rates. Countries are struggling with the supply of vaccines, have organizational difficulties. 

According to global research conducted by Gallup over 1 billion people expressed reluctance to vaccinate – such a staggering number must be partly due to a lack of trust in governments. 

Germany – a success story on the pandemic battlefield?

In the long run of the pandemic, Germany has made several important decisions and developed relatively successful procedures to manage the pandemic. 

• Cooperation of key health and science institutions. Both local and national public health institutions, as well as partners from the scientific community, developed analyses and collected data on an ongoing basis. Already at the beginning of the pandemic, national crisis management was also mobilized to understand the epidemiology of the coronavirus. 
• The government also mobilized state-run and private laboratories to rapidly increase the volume of tests. One of the first tests was carried out in a hospital in Berlin. Subsequently, Germany became a leader in RT-PCR testing, which is now the standard method for diagnosing COVID-19. 
• Germany implemented additional security measures to minimize transmission in long-term care facilities. This and other measures significantly reduced the infection rate among Germans who reached the age of 70.

All this translates into an overall reduced fatality rate, and a relaxation of restrictions which did not result in significant recurrences of the epidemic. As of May 2020, the death rate amounted to 4.6 percent, compared with 13.1 percent and 12 percent in Italy and Spain, respectively. South Korea is portrayed as an equivalent example to Germany in terms of managing to secure the over-70 population from infections (11 percent of all cases). Such data demonstrates significant success in isolating the most at high-risk groups.

In April 2020, Robert Koch Institute, together with SAS, announced the creation  of an information and forecasting platform for intensive care beds with ventilators that provides an overview of existing capacity as well as demand.The platform is an example of how analytical software can help solve one of the greatest challenges during a pandemic like SARS-CoV-2: coordinating intensive care based on forecasting, so that personnel and resources are available exactly where and — most importantly — when they are needed.

As C&F, we took part in the project, covering the platform’s maintenance and performing its quite sophisticated security audit. SAS’s solution enables the management of resources that are instrumental in treating COVID-19 patients – and therefore helps avoid scenarios known from the first wave of the pandemic, when one of the main causes of the high mortality rate was limited access to resources (e.g. oxygen, ventilators), formation of local “bottlenecks”, and lack of  central information support systems for the operational management. 

The system that is now used in Germany is in fact a real-time data acquisition and analysis environment for intensive care bed (ICU) capacities and aggregated case numbers.
It covers 1298 hospitals and provides real-time information on available COVID-19 resources on all organizational levels.

We are still far from announcing the end of the crisis, the epidemic is still ongoing, although we can hope that it is slowly coming to an end. Certainly, however, we can already draw conclusions for the future. Scientists say that there is a risk of further pandemics. We have to be better prepared. Certainly, a great deal can be done in the area of data use which, as the Germans have proved, can be of great help.

Getting rid of factors that negatively impact data quality is particularly important in the capacity of the health system (ICU and HCP capacity), number of total and new deaths, normalization of the number of infections and geographical variances.

Authorities should make sure the collection of critical data is implemented on solid foundations of simple but up-to-date databases, a rigorous data collection process and efficient data reporting and democratization.

This approach, enhanced by regionally or globally standardized data collection, reporting and analysis. will lead to the public sector obtaining a true picture of the situation and the ability to make rational decisions. Data-driven decisions. 

Following article was prepared with close cooperation with Maciej Kornacki. His knowledge and experience constitute a strong contribution to this article and the entire project.