SPONSORED COMMENT
For over forty years we’ve been talking about ‘management information’. It’s an ongoing challenge for providers working to improve the data insights they offer their clients, and for clients trying to assess the meaning of this data and what they think they need.
The issue for most organisations is a lack of access to data, much of which is held by their suppliers. Not only are they dependent on suppliers providing data; suppliers are often not collecting the appropriate data in the first place.
Taking a data led approach means extracting relevant information, integrating siloed data to see the whole picture, and knowing what to do when the facts are presented.
1. What is healthcare data?
We all tend to agree that there is a critical need for robust data, but when we talk about healthcare data, what do we mean?
Frequently, data presented to organisations tends to focus on how often the service is being accessed by employees. This may go some way to demonstrating its value and justifying cost, but the significance of this descriptive data should be questioned. It’s unlikely that such basic data can be used effectively by organisations, providers and consultants to better manage and reduce health risks.
Additional demographic data including age, gender, reason for utilisation, provides a better understanding of who and why, but fails to identify wider trends and underlying causes.
In simple terms, clients want to know:
1. What should I be worried about?
2. How do I manage these problems?
These simple questions cannot be answered without analysis of data that most providers do not have access to, either because they only see a ‘snapshot’, or the data they collect is limited. We should look beyond the quantitative and encourage the use of qualitative data that provides context and clarity to the ‘what’ and insight into the ‘how’.
2. The risk of data in isolation
Businesses with multiple suppliers may receive useful insights into specific areas of health and wellbeing but without data integration it is difficult to understand any correlation. This can lead to businesses missing significant causal factors that, when identified, could help prevent or better manage ill health across the workforce.
Health data is often used to justify the scale of a problem and why a healthcare solution is needed. We’ve all seen media reporting specific data that demonstrates the scale of particular health concerns, but not necessarily with consideration for sample size or other seemingly unrelated data which actually has a significant influence on said issue.
Data from over 120,000 cases managed by HCML, shows a strong correlation between workplace ill health and underlying causation. Mental ill health and musculoskeletal disorders remain the top two reasons for long-term absence; 94 per cent of cases had higher levels of inactivity compared to national averages, and when combined with excess weight in 68 per cent of cases, significantly increased the incidence of both conditions.
Additional factors included 43 per cent of cases getting less than 6 hours sleep per night, and many had negative attitudes, beliefs and fears about their condition, work or life.
Identifying psychosocial factors is crucial to understanding health conditions and recommending the right solution for employees. When we broaden our data analysis, we start to recognise the impact of underlying causes and shift focus on prevention which yields greater workforce productivity and cost efficiencies for businesses.
3. Proactive use of data
Taking a health risk management approach requires going beyond the standard clinical assessment. Based on an advanced version of the biopsychosocial approach, our assessment considers all aspects of an individual’s life which may impact on their health.
This data is used to develop a very different approach to care, addressing ‘in the moment’ health needs as well as understanding what is needed in the longer term. This means using the data to reduce the risk of further ill health or the severity of conditions, and support employees to manage the factors that are likely to affect their health in multiple ways in the future. Regularly measuring outcomes is critical to better health management for the individual and the whole organisation.
Using data, we truly make a difference to people’s lives.