The Baader-Meinhof Phenomenon, also known as the frequency illusion, recency bias, or red car syndrome. Is where something you recently learned or heard or thought about starts to seemingly appear everywhere. Your awareness of it increases, and you start to detect it everywhere. Lately, this has been happening to me in regards to the power of data and data systems. The simple act of collecting and reporting and analysing data can provide huge insight and promote behavioural change – for good and for bad.
Reporting Data
Data can be collected and reported to make a positive change to the well-being of people. For example, Mind the Gap is New Zealand’s first pay gap registry. It is a database of New Zealand businesses that shows who is publishing their pay gaps for gender, Maori and Pacific Peoples, and what those pay gaps are. Evidence shows that simply reporting pay gap data can have an influence on reducing those gaps. For example, by applying what the impact of pay gap reporting has been in other countries to New Zealand, a woman earning the current median wage ($26.37) could receive $12.80 - $35.77 a week more (that’s up to $1788 extra a year). To date, no country has introduced ethnic pay gap reporting. Therefore the impact of mandatory reporting on the wages of Māori and Pacific men and other ethnic workers, and particularly Māori and Pacific women could be life-changing.
See Mind the Gap website or policy brief for more information.
Exploiting Data
Social media platforms are fruitful repositories of data. Unfortunately, data from social media users can be exploited by businesses to make a profit. Exploitative marketing can target vulnerable people that may be feeling susceptible to the advertising messages. For example, 51% of parents and pregnant women surveyed for a new WHO/UNICEF report say they have been targeted with marketing from formula milk companies, much of which is in breach of international standards on infant feeding practices. In the WHO report ‘How marketing of formula milk influences our decisions on infant feeding’, it uncovers systematic and unethical marketing strategies used by the formula milk industry and highlights the impact on families' decisions about how to feed their infants and young children. Just one example of how data can be misused to individually target vulnerable mothers, but what if social media algorithms were used for good? To find the vulnerable mothers online and actually direct them towards help.
Data deficiencies
New analyses by the World Health Organisation (WHO) revealed that the full death toll of COVID-19 (between 1 January 2020 and 31 December 202) was approximately 14.9 million (range 13.3 million to 16.6 million). Drastically higher than previously reported death tolls of around 5-6 million. The disparity is largely due to many countries lacking adequate data systems. Measurement of excess mortality is an essential component to understand the impact of the pandemic but data deficiencies make it difficult to assess the true scope of a crisis.
The SCORE for Health Data Report and Technical Package was developed by WHO and partners to assist country data systems to monitor progress toward health-related goals. The SCORE global report included 133 countries, but New Zealand was not one of them. While some countries have achieved a sustainable capacity in key areas, no country has a fully mature health information system capable of meeting its evolving needs.
In Aotearoa New Zealand, we should take a critical look at our data systems to determine if we are able to properly monitor health priorities and identify critical gaps in a timely manner.
