Once perceived as a taboo topic, mental health has been in the limelight lately. Many surveys have found that workers in Asia Pacific (Apac) are struggling with mental health issues due to the uncertainties and changes brought about by the pandemic.
This impacts businesses too, as the World Health Organization estimates that depression and anxiety will cost the global economy US$1 trillion ($1.3 trillion) per year in lost productivity. “[Recognising this,] 91% of Apac companies have at least one well-being initiative in place. However, most employees are reluctant to seek help as they fear being stigmatised,” says Antonio De Castro, senior industry consultant for the Global Health and Life Sciences Practice at SAS, an analytics solutions provider.
He adds that although direct surveys can provide information on an employee’s well-being, those surveys are time-consuming and offer limited insights. “Traditional ways, such as direct surveys, tend to look into isolated aspects of health, which creates a risk to neglect [other] important elements that impact the concerned individual.”
This is why organisations are looking for indirect ways of capturing information to complement traditional methods. “For example, they can provide websites for their employees and observe their digital behaviour. [They can therefore know] which links/sections get the most traffic, which profiles are prominently visiting particular sections, and what type of content is resonating with their workforce,” says De Castro.
Thereafter, organisations should use advanced analytics to gain insights that can empower them to deliver “whole-person care”, which De Castro says is a more holistic approach to looking at employees’ well-being.
A data platform is key to delivering whole-person care
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Taking a whole-person care approach requires a data platform that enables data integration and interoperability. This is because organisations need to consolidate and analyse a multitude of datasets from different sources and systems, such as electronic health records, health claims, mental health questionnaires, and social determinants data.
“With a robust data platform (which also checks security and privacy qualifications) integrating the variety of relevant data, we can analyse those data and operationalise the results,” says De Castro.
For instance, The Black Dog Institute — a non-profit medical research institute in Australia — partnered with SAS to support healthcare workers’ mental wellness during the pandemic. They created a digital platform to connect frontline healthcare workers to a network of support services, giving them convenient and confidential access to mental health resources. By analysing the site traffic, the institute can continuously learn about the types of messages that are most effective on the different profiles of healthcare workers.
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De Castro notes that insights gained from the data analysed by a robust data platform can also be used effectively by mental health organisations for whole-person care by:
- Raising awareness about people in need, which can combat stigma and discrimination.
- Enabling research, evaluation and quality improvement. The generation of insights will lead to continuous improvement of quality, strengthening the service delivery in mental health organisations.
- Advocating for system and policy change. Using information from mental health projects, they can engage public stakeholders more effectively to improve current systems and policies. Informing stakeholders and policymakers about findings can help disseminate information across sectors and influence further change.
Since there is still a stigma around mental health, organisations need to keep data on their employees’ mental health safe. De Castro advises them to ensure data security and privacy by establishing adequate data access according to different roles within an organisation.
Data should always be looked at as an aggregate too. “When we analyse the data, it should be anonymised, and personal information should not be part of the analysis. What we need to look for are collective behavioural patterns that can indicate different mental states.”
Photo: Sydney Sims/Unsplash
