28 June 2022 | CUSTOMER STORIES

Tackling The Covid-19 Backlog: Data Driving Decisions

Waitemata DHB implemented Qlik with Acumen BI in 2016, with a vision to build a powerful data environment to drive decision making. The DHB recently created a waitlist planning tool to help operations managers and clinicians manage the elective surgery backlog. 

The arrival of Covid-19 and subsequent lockdowns forced New Zealand’s DHBs to reduce planned care delivery. Since the pandemic began, the number of people waiting longer than four months for treatment has more than trebled from just over 8000, in February 2020, to nearly 27,000 in March 2022.

Measuring the impact

Waitematā DHB, like others nationwide, has had a particularly challenging time in the planned care space as a result of Covid-19.

Senior clinical information analyst Monique Greene says the DHB needed to quantify the size of the problem, by accurately measuring the impact at a specialty, subspecialty and patient level.

“We also wanted to identify high risk patient groups from a clinical need perspective as well as an equity perspective,” she says.

Qlik tools and capabilities were already embedded in the organisation, so they decided to build a waitlist planning tool as a Qlik dashboard.

Users can look at a historical date range and understand what the waitlist flows were during that time — how many patients were added to the surgical lists and how many were taken off — as well as scenario test different options to help with the Covid recovery.

“We started from a really strong standpoint: all of the data that we needed for the app was already available to us, so it involved pulling it together and understanding what would be useful for the services,” Greene says.

The tool went live in May 2021 and informed the DHB’s recovery plan, which had to be submitted to the Ministry of Health.

A user review

David Resoli, Waitematā DHB general manager surgical and ambulatory services, says “good data drives good decision making”.

“One of the issues with healthcare data is that you can get multiple data sources and multiple versions of the truth,” he says.

“The beauty of a product like Qlik and this waitlist tool is that it is transparent and it’s use is universal across the specialties. This provides a common language and understanding of the situation, which is a really powerful tool for making decisions and healthcare leadership.”

Waitematā DHB Cutaneous Oncology (skin cancer) Service operates in partnership with primary care partners, with GPs with a special interest in treating skin conditions outside of hospital.

However, during lockdown GPs were delivering services primarily online and targeted face-to-face appointments to those with the highest clinical need, causing wait times to balloon.

The team used the waitlist tool to model what the skin service waitlist would look like four to twelve weeks away and reflect on historic trends in order to develop a response.

“The tool was able to highlight to us the changing shape and nature of that waiting list and whether it was growing,” says Resoli.

“That early intelligence leads to analysis, which leads to decision making. We were able to start asking questions, rather than respond to a crisis that had already occurred,” he says.

Resoli also uses the tool to have conversations with services about their capacity, and what would happen if capacity was added or moved to different areas.

“That enables the senior team to come around the table together and have a much more fruitful conversation about what steps we could take as a whole of system, as we recover from the impact of Covid-19,” he says.

A focus on equity

The four Northern Region DHBs have committed to focus on equity as they tackles waitlists, which involves identifying and prioritising Māori and Pacific patients who have been waiting a long time.

“With the Qlik app, we have access to that information in three clicks of a button in order to have a meaningful conversation with my teams around next steps,” explains Resoli.

The tool allows Waitematā to monitor its Covid recovery and whether, as capacity comes back online, the ethnicity of those on waitlists reflects that of the wider population.

“There are more than 5000 people on the surgical waitlist: it is an unfortunate reality that we have to choose between priorities and where precious resources are deployed,” Resoli says.

“These tools are not static, so the next generation of analysis will be around ‘treatment in turn’, enabling us to identify quickly which patients have been booked for treatment out of turn and whether was that appropriate?”

Making it Qlik

The data and analytics tools and team sit within Waitematā DHB’s Institute for Innovation and Improvement, i3.

Director, Penny Andrew, says the team, culture and data that enabled the creation of the waitlist planning tool has been developed over a number of years.

Key to the success of this programme of work is the close connection between the analytics team and the clinicians and operations managers who use the tools they develop.

“It is different to the traditional model as there is a really close relationship: the data team attend their colleagues’ operations meetings and department meetings and run through the dashboards with them and problem solve with them,” Andrew explains.

Resoli agrees, describing his relationship with Greene and the analytics team as “not transactional, but transformational.”

Over time the DHB has built its own expertise inhouse and now has clinicians and public health staff who can build dashboards themselves. 

Start locally, scale nationally

In May, the government announced a new taskforce that will develop a national strategy for planned care, by September.

Andrew says this new plan must be data driven, in order to understand the problem and track improvement.

“For any business intelligence tool, there are some fundamental principles in what has been built here that we can share, such as standardisation of data definitions,” she says.

“The model is to build in one place, prototype and then scale: that works really well because it makes you really agile, you can do it faster and improve and adapt.”

She would like to see the new taskforce bring together the really good data analysts already working in the DHBs and link them with the operations managers and clinical staff to build tools together that are useful nationwide.

“This is a really good way to build a data environment to help drive improvement and joined up care across the health sector,” Andrew says.

Acumen BI are a leading data, analytics and machine learning solution provider for NZ health organisations.

Acumen BI have worked with the Ministry of Health, Waitemata, Counties Manukau and Capital & Coast DHB’s to deliver data and analytics projects across a variety of use cases.

Waitemata DHB’s ‘waitlist’ analysis builds on the significant amount of work undertaken with Qlik to date in the health sector.

Waitemata DHB won the Organisational Transformation Award at the 2019 Qlik APAC Digital Transformation Awards.

There are over 200,000 Qlik licenses in the health sector across ANZ.

Acumen BI look forward to continuing its work with the health sector to establish scalable and governed patterns for ‘system wide health sector data and analytics’.

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TAGS | Health|Qlik

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