Transforming Population Health for Australia’s Primary Health Networks


The healthcare sector has always been awash with data. From primary to tertiary care, patient data is collected at practically every step of the healthcare journey. But despite its prevalence and massive influence, healthcare data is rarely holistic.

Most data is siloed into different systems throughout the various stages of the healthcare continuum. Disparate systems and privacy considerations make the playing field even more complicated, and these are only projected to get more involved over time. Even if we work within these constraints, there will still be a disconnect between meaningful research and the predictors that determine patient outcomes.

Disconnected healthcare data means a limited understanding of a patient’s end-to-end journey.

Data disconnection breeds discontent. It also means that our data is not harnessed to its full potential. Worse, without a contiguous system in place, we can't use data to properly understand a person’s journey through the system or how to support better care in the future.

I've found that healthcare information systems are great at collecting data, but they provide few if any insights that analyse the process or monitor their data throughput. Managers are forced to function in the dark and react to events rather than plan in advance, which impacts their jobs and patient outcomes in a number of ways.

At Outcome Health, changing this approach is our primary mission.

Making an Impact on Population Health

Outcome Health is a healthcare technology not-for-profit based in Blackburn, Australia. We manage different verticals in the healthcare space: We have clinicians on the ground providing mental health and chronic disease management, and also provide healthcare insights using our data population tool. Outcome Health has a 21-year history of providing innovation to the primary healthcare sector. This history has been built on championing innovation and disrupting markets to the benefit of the primary health sector. Outcome Health continues to expand its technical and clinical teams and is excited about what new opportunities will be presented to the healthcare sector and how it will continue to help its customers make a difference.

Population health is our pedigree. It's our job to help people understand their populations better and then use data-driven insights to make decisions about fund allocations and new objectives. While our customers are Primary Health Networks (PHNs), the primary users of our reports are General Practices, which are public-facing companies at the front line of the primary health system.

Public-facing healthcare organisations such as PHNs are funded to provide health services for their communities that make a difference by delivering positive health outcomes. The trouble is the vast majority of these organisations are swimming in data, often siloed and therefore face a significant challenge to deliver data-driven insights about what's working, what's not, and what funding may deliver positive outcomes for their communities.

But by leveraging the power of data, Outcome Health can identify at-risk populations, current healthcare trends, and pressing needs within specific locations or patient cohorts. This allows us to direct public-facing organisations towards impactful plans of care and encourage the establishment of services within specific areas.

I've worked with health-related data sets for nearly 20 years and joined Outcome Health in 2014 as a Data Manager. I currently serve as the Chief Information Officer and work across the technical team to support the best possible outcomes for clients. It's been an honour to watch Outcome Health grow over the years, and I find myself continuously impressed with the data-driven outcomes we deliver to 1,500+ GP clinics.

And over my years of service, the face of our business intelligence strategy has changed by leaps and bounds.

Levelling Up the BI Playing Field

Data has always been an incredible way to impact healthcare, but as I mentioned earlier, gathering it into a cohesive stream hasn’t always been easy. In fact, Outcome Health struggled to rectify siloed data sets for many of our earliest years.

Our initial data journey started with building data warehouses; a useful if relatively ineffective method of collection. A colleague of mine encouraged us to build a warehouse of General Practice data, hoping to provide huge benefits to the health sector if the “sleeping giant of the data world” could be unlocked and used for analysis, population health planning, and future research.

Our first data warehouse was a tentative success. However, we were unable to make our data easily accessible. Even though we had compiled each set of data into the same stack, we had no way of making it easily readable by stakeholders and less technically inclined users. We knew we couldn't scale to answer everyone's questions in the organisation, and we also knew that our existing technology was a bit too limited.

For real-world impact, data needs to be in the hands of end users—not just analysts.

The manual writing of database scripts, the tedious programming of Microsoft Excel, and our aging SQL Server Reporting Services stack were all limiting factors. Our existing system was horribly clunky. We had to write custom scripts for everything, which drained time out of our day for other things. Queries were taking a day or longer to come up with some very basic insights. Worse, using our basic analysis tools just felt wrong.

I remember how unbelievably frustrating it was to manage everything at such a micro level. I knew right away that we needed easier access, self-service, and process navigation. After all, how could we deliver accurate insights to our clients without a fast and easy system?

Thus began our BI platform journey.

The Analytics Lightbulb Moment

I'd never even heard of Qlik before starting our software investigation.

We were looking for months to find the right service, and thinking through every possible consideration to find the perfect fit. Then, out of nowhere, Qlik appeared. I was contacted by a reseller with an interesting proposition: I take 30 minutes out of my day on a Friday afternoon, and get a full demo of the Qlik product without paying a dime. What did I have to lose?

The meeting was scheduled for 3 p.m. and our 30-minute meeting ran until 5:30 p.m. I was blown away. I had my first dashboard up and running within two hours of setting up. It was so simple, and yet so powerful—enough to do everything we needed and then some. Plus, we could get an enormous amount of work done in almost no time at all. What would've taken weeks to complete with our old setup took half an hour or less in Qlik, which allowed us to come up with high-quality data insights without grinding out painstaking queries or writing up custom code.

It's hard to believe that was 12 years ago now. A 30-minute chance appointment late one Friday afternoon was the lightbulb moment I needed to forever change my understanding and use of business intelligence software.

Leveraging Qlik for the POLAR platform

Outcome Health now uses Qlik to support our POLAR reporting platform, which provides data and analytics to over 5,000 users across 1,500 general practices throughout Australia. 

The platform is primarily used by PHNs, and we use Qlik to transform and present the data to support better patient health outcomes, quality improvement exercises, and get people excited about what they see. Working with partner Notitia has been helpful to manage licenses, log support tickets, and understand the architecture surrounding Qlik's newest functions.

I've found Qlik to be ideally suited to the primary care environment. Not only is it easy to use and extremely intuitive, but it effortlessly bridges the computer literacy gap between users and their systems.

Today, our POLAR dashboards fit into two models:

  1. Data discovery: This is where we present all the data to the end user in a manageable template design. I use the analogy of a wedding cake to explain its function. Starting at the bottom, you apply filters to scopes of data (layers) to reduce your cohort until presented with patients that matter to your analysis. Every filter reduces the patient cohort and makes the layers of your cake smaller and smaller.
  2. Guided analytics: We guide the user through a series of steps to get to the cohort they need. This approach works well for our suite of reports focusing on chronic disease, and follows through four steps: selecting the population cohort in question; reviewing and explaining why the patient falls into that cohort; managing the cohort and ensuring adequate healthcare services; and monitoring the data quality slant.

Although this process may seem complicated, Qlik is ideally suited to this guided self-service approach. It's been extremely impactful on client outcomes.

In fact, we used Qlik's easy process to innovate a COVID monitoring dashboard. Our Director of BI, Jamie Supple, was the driver of this report. The initial goal was to provide data for early warning and detection to the Department of Health in Victoria. But with Qlik, the capabilities quickly scaled to vaccine rollouts, outcome monitoring, and patient management.

Our COVID dashboard has been through 26 iterations so far, and it’s been the lifeblood for a lot of clinics during the pandemic. Our team can better respond to government regulations and state requirements, serving our customers with even better data. It’s been one of our most used reports and has driven more engagement for our POLAR platform.

Our work on POLAR was recognised at the Qlik ANZ Health & Public Sector Digital Transformation Awards 2022, where we won the award for Excellence in Providing Better Community Outcomes with Data.

Not only has Qlik's partnership brought us where we are today, but it's been used for dozens of different use cases around our organisation. When I first started using Qlik, I thought of it as purely a BI presentation tool. However, the more I explored Qlik's data processing capabilities, the more I started to understand how efficiently it can transform and prepare data for reporting and analysis, which was historically where we relied on SQL Server. Knowing that Qlik can be an end-to-end analysis and reporting solution is the first step in understanding that it is more than just a BI presentation tool.

Linking the Future of Healthcare Data

We've built an incredible foundation on the back of Qlik. We've grown as an organisation over the past decade, and are leaving a larger impact as the years go on. So when it comes to the future of our data and population health, I can only surmise that a more holistic approach is on the horizon.

The holy grail for health data analysis is monitoring health outcomes from the cradle to the grave. We want to know where a person starts, where they end, and how their care was applied throughout the years. We need to know what went wrong so we can make things right and reduce any friction for future patient care.

It starts by asking questions. What exactly happens to a person throughout their life, and more importantly, what are the health data points in between? Is analysing health-related data points an exercise in 'joining the dots,' or is it an exercise in looking at the lines between the dots to see patterns that could predict a person’s health outcomes? Are we an end-to-end journey on the timeline, or a network of different relationships that, in the end, lead somewhere great?

By leaning on a responsible model of security and lasting protection, we can move into the realm of fully visualised and fully connected healthcare journeys.

Here in Australia, linkage projects with data kept at different government organisations are becoming increasingly valid. The next stage in our technical evolution is to engage our information within data communities while protecting personally identifiable information.  By leaning on a responsible model of security and lasting protection, we can move into the realm of fully visualised and fully connected healthcare journeys.

Having seen POLAR's benefits to the primary care sector, I look forward to pointing our powerfully cohesive data at the entire healthcare journey to learn more about what it means to receive great treatment. With the foundation we’ve built, it might not take as long as we think.