Leveraging Data Analytics for Improved Care Outcomes

Introduction to Data Analytics in Social Care:

Data analytics play a major role in today’s social care and can have a transformative effect on care outcomes when used effectively.

With that being said, it’s important to understand what data analytics are and how to use them to achieve the best possible results.

Data analytics is the collection, interpretation, and use of data to inform decisions. In the social care industry, it is important to note that data analytics can be used in both clinical and day-to-day operational settings.

Initially, providers captured and interpreted this data by manually compiling handwritten care records and analysing them one by one. However, this was a very manual and time-consuming process for providers, regardless of how many service users they provided care to.

The rise of digital care management software enabled many providers to shift away from this manual process and embrace a new and digitally streamlined process for collecting and interpreting data.

In the early stages of social care, data analytics were primarily used for compliance and auditing purposes.

At the time, data collected was used reactively and in retrospect of incidents occurring; however, the shift towards person-centred care saw providers move towards using data analytics proactively and not just when an incident occurred.

Combined with the rise of digital care management software, this person-centred approach to data analytics empowered providers to track service users’ patterns, preferences, and outcomes, which can then be easily acted on.

By tracking the individual service users’ details, providers are better able to identify and predict trends in care delivery and how the service user interacts with their care, ultimately leading to better care outcomes.

Key Metrics Tracked in Social Care:

In social care, people should be at the centre of everything, and as such, the most important metrics tracked in care data analytics software are centred on individuals’ care outcomes, such as changes in their emotional wellbeing, levels of independence, and symptom management.

Additionally, data analytics software tracks falls, incidents, and any other safeguarding concerns, allowing providers to identify trends, intervene quickly, and potentially prevent issues from re-occurring.

Providers can also monitor changes in a service user’s physical, cognitive, and behavioural indicators, empowering them to identify signs of deterioration and proactively prevent major incidents from occurring.

This data is vital for evaluating the effectiveness of the individual’s care plan and whether the plan aligns with their current care requirements.

Care data analytics software also allows providers to track the time it takes for staff to respond to alerts, complete care tasks, and fill out documentation, which can then be used to monitor operational efficiency and quickly identify any potential bottlenecks that may be occurring.

By utilising this data, providers are better able to monitor challenges in physical, cognitive, and behavioural indicators, allowing them to easily identify signs of deterioration and proactively prevent any incidents from occurring.

When issues facing service users are rectified quickly and effectively, stakeholders’ satisfaction and trust in the care being delivered significantly increase.

In addition to tracking individual metrics relating to care delivery, care data analytics software empowers providers to monitor metrics like facility occupation, average length of stay, and cost-per care package delivered.

These metrics can then be used to inform future strategic planning and will demonstrate the ROI of the investment into your digital system and staff development.

Integration of Analytics Tools in Care Management Software:

One of the most common analytics tools embedded into modern care data analytics software is Microsoft Power BI, an interactive digital visualisation tool that enables care staff to access interactive dashboards comprised of business-wide metrics, such as occupancy levels, adherence with care plans, and incident trends, directly from within the system.

When analytics tools are embedded into care management systems, they eliminate the requirement for users to jump from system to system to find the metrics they are looking for, and as a result, staff are better able to make data-driven decisions quicker and more effectively.

Additionally, these dashboards can be configured by role, ensuring that only the correct staff have access to the right information.

As these dashboards are highly configurable, they can be easily created for all levels of digital literacy, so whether you’re a tech expert or a complete beginner, you can effectively utilise these dashboards.

The live nature of Power BI dashboards empowers providers to proactively identify potential issues and empowers them to act immediately to rectify the situation before it escalates.

One of the main benefits of utilising care data analytics software is its ability to easily integrate across different care settings, such as in GP offices, residential care facilities, and even in adult day care centres.

This seamless integration significantly improves the continuity of care as service users move between providers, ultimately improving the standard of care they receive.

Additionally, as regulatory bodies such as HIQA and the CQC expect care organisations to provide personalised care for their service users that is backed by extensive data, these systems empower providers to create personalised care plans and easily generate an evidence report with just a few clicks.

Challenges and Solutions in Care Analytics:

One of the main challenges providers face when looking to implement a care data analytics software is data privacy; however, the national data protection laws in the UK and Ireland enforce strict data handling guidelines that all providers must abide by.

Providers who mismanage employee or service user data and disregard data security can face significant fines, loss of stakeholder trust, and other additional legal repercussions.

One of the ways these systems enforce compliance with regulatory best practices is by utilising the built-in permission or role-based access functionality within the system, meaning only the correct staff have access to the correct information.

Another common barrier to adoption that providers experience when trying to implement a new digital care management system is a lack of interoperability between health and social care systems.

Often, this results in an incomplete overview of the service user’s care history, as data is siloed in different health and social care systems.

To rectify this, modern digital care management systems come with open API’s which allow different systems to easily share data across the software ecosystem, allowing them to see a complete overview of the service user’s care history in one system.

Analytics are only as good as the data they use, and as such, it’s crucial that providers have a standardised layout for data entry and effectively communicate expectations with staff.

To help with this, in 2024, the Professional Records Standards Body (PRSB) introduced Minimum Operational Data Standards (MODS) for social care providers to comply with when inputting and displaying service user information.

This reduces data discrepancies in care management systems as everyone is speaking the same language, which has transformative effects on service users’ care outcomes.

When providers have a complete overview of the care an individual is receiving, they are better equipped to make data-driven decisions that will have a positive impact on service user care outcomes.

Best Practices for Implementing Care Analytics:

When researching a new care data analytics software or looking to enhance their data analytics capabilities, providers must have clearly defined goals relevant to their organisation.

Whether it’s improving care task completion rates, reducing the occurrence of incidents, or enhancing organisational efficiency, having clear, well-defined goals reduces the time investment required when researching new systems and allows providers to embed outcome- and data-driven processes with ease.

Another key consideration care organisations have to keep in mind when researching new systems is interoperability with their current tech stack and the ability of the system to scale with the organisation as they grow.

Additionally, it is essential that care organisations involve their care staff as early in the decision-making processes as possible, as they will be the ones using the software on a daily basis.

By doing so, you enable them to identify gaps in functionality and any potential deal-breaking issues that may arise when using the software, ultimately preventing organisations from investing in a software that is not fully suitable for them.

It is also recommended that staff are provided with ongoing, role-specific training to ensure they are utilising the system to its maximum potential and subsequently yield the best possible results for service users.

When adopting a new care data analytics software, providers must implement strict data handling processes and policies that are in line with national data protection regulations (e.g., GDPR in Ireland).

Whilst it may not be a regulatory requirement, it is recommended that organisations involve their Data Protection Officer (DPO) as early in the process as possible.

Once the system has been successfully implemented, providers should schedule regular data reviews to review the quality of the data and the analytical output, empowering them to proactively identify trends occurring and further embed data-driven decision making into the organisation.

Ready to see the power of data analytics in care? Book a demo with OneTouch Health to see how Power BI seamlessly integrates with the OneTouch platform, allowing you to better identify gaps in care delivery and improve care outcomes for your service users.