Getting the best out of data in aged care.

Aged care and health settings face several significant challenges. How can they deliver personalised services, maximise capacity levels and keep an emphasis on quality of care, all with a finite budget? And how is it possible to manage the volumes of information they need to process, efficiently and effectively? The more locations the provider runs out of, the more complicated this becomes.

Most human services managers will freely admit they are not using data effectively. For most organisations, it’s not about a lack of access to data, but rather the capability to use it effectively to deliver.

Many tend to manage their information within a series of spreadsheets, between different contacts from each location. This is manual, very prone to error, and labour intensive. Not to mention that it lacks the oversight of important data that could result in more strategic and efficient decision-making.

Trying to track, connect and understand the things that are happening both online (e.g. website visits, form completions) and offline (e.g. walk-ins, phone calls) in a central location is not without its challenges.

The pace of change in the health and aged care sector, combined with processes that are out of alignment with the role and importance of data, threatens a setting’s ability to run efficiently and meet growing demand.

Here we look at how providers can simply and effectively use their data to keep up with demand and impact the overall quality of care provided.

Data in aged care settings.

Many aged care organisations have a wealth of data, but few have access to it in real-time or make it available to the relevant levels.

As a result, business decision-makers tend to have a low level of trust in how they are using tools such as data analytics. This makes it difficult to produce real insights.

In the aged care ecosystem, data can be a critical tool that highlights invaluable efficiencies. These can include:

• A better understanding of customers
• The ability to adapt services to meet customer needs
• Enabling frontline staff to understand what is happening in all settings.

Significant opportunities exist within the aged care sector to better use the available data in organisations to drive innovation, experience, and efficiency within aged care settings. And it isn’t as difficult as it might appear.

What does this mean in practice?

Rather than relying on ‘gut feel’, applying data analytics can provide actionable, data-driven insights to support business decisions.

There are a few steps to ensure aged care providers are using data – through data-collection practices and dashboards – to drive innovation and business development within their organisations. These are:

1. Ensure your data is valuable
2. Reduce the toil around data collection & management
3. Put your data in a format that invites & enables analysis

1. Ensure your data is valuable.

For data to be truly valuable, it should be two things: accurate and relevant.

Accuracy as an important characteristic of data may seem obvious, but it is not always the reality. When data collection relies on manual entry by multiple people, the use of separate/versioned documents, and with no validation on what is being entered where, there is almost certainly a high margin of error. Or, to put it in other terms, if your team is sharing and collating Excel spreadsheets to create reports, the data is probably messy.

And for this I would recommend some relatively simple fixes and practices:

• Start storing data in a single (preferably cloud-based) location that accommodates everyone’s data entry needs – products like Google Sheets are an easy, free solution.
• Create a single point of data entry that validates the data that’s being entered. For example, a Google Form provides a good way of doing this – everyone will be using the same form, meaning the data is entered in a consistent structure. Additionally, form fields can be set up to allow the validation of data, so that dates, phone numbers, email addresses and other types of data are correctly formatted.

Relevance is perhaps a more ambiguous characteristic; what do we include and exclude? Because there’s so much data available these days, and if it’s there wouldn’t we want to make use of it? Don’t we want to include all the metrics, graphs and tables?

My answer: nope. Just because you can track and report on it, doesn’t mean you should. Because too much data is too much. You need to be honest with yourself and consider what’s relevant in the group conversations that lead to decisions. And if you find, over time, that some data points are not being used, then get rid of them. Unused data only serves as visual and cognitive noise.

Here’s a few tips to ensure the data you are collecting and reviewing is relevant:

• Collaboratively create a measurement plan within your team. This will help you initially define, organise and agree on what’s important in terms of reporting. But keep it simple – I’d recommend no more than 15 metrics, if possible. Even then, it is helpful to have a single key metric that is superior to all others.
• On a semi-regular basis (around every 3-6 months) collectively review what you are reporting on. Consider if you are using the data from your current reports, and to what extent. Also look at any new data points that could be incorporated to build out the current set of metrics.

2. Reduce toil around manual data collection & management.

I’ll be the first to admit that data entry is not fun. It is, at best, a drab routine and, at worst, pure drudgery. And it not only increases the potential for human error, but also represents an ongoing and, often, significant cost. It is time that team members spend on repetitive, systematic tasks that they could otherwise be spending on problems that require creativity and skill (which is what those in marketing and sales are paid for).

With this in mind, it is of great benefit to both the individual and the business to reduce the need for the manual handling of data wherever possible. Here are a few things you can do in the interest of achieving this:

• Start by identifying your different data sources and integrating them where possible. For example, in the case of a healthcare provider we worked with, they were comparing digital data from Google Analytics to offline actions (e.g. in-person visits, phone calls, contract signature) that were being recorded. Originally, this was all being manually collated in reports. But we found it was far more reliable and efficient to connect Google Analytics (via the Google Analytics Spreadsheet Add-on) to the spreadsheet being used to collect offline behaviour. In this way, a significant portion of the data being reported on could be automated.
• Don’t collect things you don’t use. This comes back to the previous point on developing a measurement plan. Simply put, if you aren’t using the data and cannot see how you would in the future, it probably isn’t worth the time and effort invested in recording it.

3. Put your data in a format that invites and enables analysis.

Here we get to the matter of how data is represented, and the often-overlooked benefit of a good dashboard. Because when data looks good, people will want to look at it. Design can improve both engagement and comprehension. And by providing our teams with nicely formatted and branded dashboards, we make them look good within their organisation.

But it’s not only the aesthetics of the dashboard that count here; it’s also the functionality and accessibility. Ideally, it will be intuitive enough that anyone in your team can jump in and, without the need for a walkthrough, understand the data in front of them and how it can be manipulated.

To make your dashboard both appealing and usable, here’s what you can do:

• Get a designer involved (or put on your personal design hat). A good dashboard structure starts with a solid wireframe and set of style guidelines. Particularly in multi-dashboard reports, an established template will aid understanding and be a massive time-saver when you’re putting it together.
• Apply good content structure and labeling. Make the important stuff big, front and centre. Use clear and informative titles – the meaning of graphs and tables are not always immediate. A descriptive title like “New contacts by referral source” is helpful to the person viewing the data. Or better yet, frame the data with the question it answers, like “What is the trend for organic traffic & bookings?”. Moreover, you can create different areas in your dashboard where you organise data into logical groups – for instance, you may have a section where you place all your data controls (filters, date-range selector etc.), one where you put all your website performance metrics (sessions, form completions etc.), and another where you place offline behavioural data (phone calls, tours, contract signatures etc.).

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Keeping up with the pace of change, and the role and importance of data is a growing requirement in today’s competitive marketplace. Yet, as you can see, just a bit of thought and a few simple changes can make great use of the volumes of information collected each day and turn the wealth of data into real valuable insights. In turn, this can give everyone a better understanding of customers, allowing the organisation to adapt services to meet their needs, improving the effectiveness, efficiency, and experience with minimal effort.