The Role of Data Governance During A Pandemic

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Data governance - who's counting?

858 212. About the population of Reunion**, and the gap between the WHO’s and John Hopkins’ total confirmed cases of COVID-19 worldwide**. On the 29th of October 2020, the WHO reported 44,002,003 confirmed cases. Worldometer which John Hopkins base their figures on, reported 44,860,215 cases. 858,212 is a big number – a whole island.

The role of data governance

This large gap between reported figures raises tough questions on the reliability of COVID-19 tracking data. In dealing with situations like pandemic data, how important are aspects of data governance such as standardised definitions? How do governments and international institutions prepare for the unpreparable while managing data successfully? Indeed, real-time data is crucial and is the only key to understand the current crisis and its effects. However, real-time reporting must be supported by an effective data governance that sets out the rules that control, influence and regulate the proper and effective management of data.

The trade-off between timely and accurate data

As the epidemic evolved into a pandemic, governments were caught short and so scrambled to get any data they could. As a result, concerns of data governance and data quality were ignored. The direct consequence of bad quality data is misinformed decision making based on inaccurate information; the quality of the solutions is driven by the quality of the data. Although COVID-19 tracking data is highly complex and is subject to many data quality issues, it is still better to release good-enough data to inform decision making, rather than to take the risk of losing more lives without using any data. This ongoing trade-off between reporting timely and accurate information strains the reliability of the data. In a time of uncertainty, it also pressures decision-making bodies even more into making the right decision.

COVID-19 exposes shortcomings in data management

Getting consistency is also a daunting challenge in the face of a tsunami of data. This wave of information raises a number of challenges related to data collection and management as organisations struggle to coordinate on a global scale how to collect, transform, store and access COVID-19 data in a consistent manner. Having a data-driven approach creates much sought after competitive advantage. However, it requires durable investment, effort and time to establish strong data foundations. Something most countries and organisations don’t have in place, as the pandemic has proved. More specifically, we have seen how the condition of COVID-19 data is impacted, not only by the quality of the data recorded itself, but the robustness of the information management systems that enable it.

Establishing a data governance framework

A huge part of data governance is to ensure data is fit for purpose. In the case of the pandemic, the purpose of COVID-19 data is to inform and support better decisions. WHO has set out the rationale behind the collection of COVID-19 data – ‘Obtaining timely, accurate and complete weekly mortality statistics will help show the impact of COVID-19 on overall mortality across countries. […] Additionally, this will help monitor the impact of interventions.’ To ensure data collection consistency of member states, WHO has set international COVID-19 reporting norms and standards. These clarify how to certify COVID-19 as a cause of death, where it should be recorded, what terminology to use, how to code COVID-19 for mortality, and what variables and metadata are to be submitted to WHO. To get consistent and reliable data, this is the kind of standardisation we need.

Differences in the data collection and data management policies of each country affect the quality of aggregated data

Despite WHO’s guidance, it is still up to member states to set their own data collection and management policies. The difference in policies across countries naturally creates discrepancies in the quality of the aggregated data. Several countries have seen surges in reported deaths, not because more people died, but because they changed what they counted. For example, they started counting care home deaths too. Indeed, the WHO technical guidance note that specifies exactly what data to report and how was published only beginning of June. It is not surprising that these changes in the way of collecting data happened and resulted in gaps between COVID-19 tracking data. This makes the point about preparedness even more important and raises the question of who gets to decide what and to what extent.

Breaking down the siloes

In any situation, the urge to report good numbers in a timely manner will always clash with the need for good quality data to support effective decision making. The inconsistencies between data collection and reporting between countries can only be solved with a stronger resilience in the alignment between governments and public health organisations. If we want to bring the gap down, a refinement of guidelines and a more proactive approach is required when designing data-driven solutions. Countries must remain interconnected and speak the same language. Hopefully, this global crisis has taught us all to be better data consumers when dealing with data condition. 

* Based on numbers updated at 11AM GMT on 29 October, 2020.

** Population information source: UN Demographics Statistics Database.

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