Driving better outcomes for Aotearoa New Zealand
“Insights and intelligence data about the people we serve are crucial to keep people and whānau at the centre of service design, delivery and performance. Along with mātauranga Māori and quantitative data, this creates a whole and detailed picture of health service performance and whether people’s needs are being met”
Te Pae Tata Interim Health Plan 2022
Every action a patient, provider or administrator takes in the health system creates new data.
Nearly one third of the world’s data are now created by the healthcare industry, but collecting data is not the same as understanding it.
Data analytics involves extracting insights from data and identifying patterns, to enable informed decisions.
This presents exciting opportunities for health systems to harness the power of data analytics to improve outcomes, enhance operational performance and create a better patient experience.
Aotearoa New Zealand’s health system has numerous data sets – both electronic and paper
-based – and Te Pae Tata, Interim New Zealand Health Plan, commits to strengthening the use of health insights and intelligence to ensure equity of access and outcomes from all health services across Aotearoa.
“Our priority is to integrate our information sources to generate insights across the health system, and to understand the voices and feedback from consumers and whānau.”
“These data will inform plans to meet service needs as our population grows, ages and becomes increasingly diverse.” – Te Pae Tata.
This report recognises and celebrates the successful use of data analytics to drive better outcomes for the health of all New Zealanders.
Visualising population health and closing equity gaps
“I want to ensure that we have a strong Pacific voice in the analytics that we do.”
Namoe Tuipulotu, Head of Pacific Intelligence & Insights, Te Whatu Ora
Data played a critical role in informing the pandemic response in Aotearoa New Zealand.
Data analytics was used to monitor the spread of the Covid-19 virus, identify hotspots, and make decisions about public health interventions.
In the Northern region of the country, analytics was also used to target people most at-risk for complications from the virus.
Māori and Pacific regional coordination hubs had direct access to a Covid-19 dashboard, displaying clinical risk scores for local people who had tested positive.
Namoe Tuipulotu – Head of Pacific Intelligence & Insights, Te Whatu Ora, was working in the Pacific Hub at the time and says it is important to have Pacific people developing these types of dashboards if they are meant to reflect and show what’s happening for Pacific communities.
“By doing that, you get a true understanding of what the system is delivering as a whole, but also
get a better understanding of where Pacific people fit in that space,” she says.
Te Pae Tata Interim Health Plan 2022 says the interpretation and use of intelligence about communities will be led and interpreted by those communities, including Pacific people and Tāngata whaikaha – disabled people.
Tuipulotu says there is an intention to build an intelligence function within Te Whatu Ora Pacific Health Directorate.
“I want to ensure that we have a strong Pacific voice in the analytics that we do,” she says.
“It is about building relationships and partnerships across the system, but also making sure that we have key people in roles to provide the translation between what is happening in the business and how we present information to the communities that need it.”
Northern Region Health Coordination Centre (NRHCC)
As the Covid-19 pandemic spread around the world in early 2020, health districts in the Northern region of New Zealand worked rapidly to develop a regional view of hospital capacity and occupancy.
The Covid-19 Dashboard was used to support Covid-19 testing, vaccination, managed isolation and community care and is being expanded to other areas such as planned care, pulling from national datasets.
Developing a regional view
In March 2020 the Northern region was planning for an inundation of Covid-19 cases and for the hospitals to be overwhelmed, says former Head of Analytics at Waitematā, Delwyn Armstrong.
This meant the regional analytics teams, which includes Auckland, Counties Manukau,Waitematā and Northland Districts, were initially focused on getting a regional view of hospital capacity and occupancy.
Within three weeks, the team had developed a regional data store and soon after they had visibility of real time hospital capacity and occupancy across the region: something never achieved before. Due to the success of New Zealand’s lockdown, the hospital view was not as urgent as predicted, but as testing ramped up the dashboard was used to display a regional view of Covid-19 test results.
Armstrong, who is now Director Health Analytics and Insights, TeWhatu Ora – Health New Zealand, says after vaccinations began the dashboard displayed immunisation data and was also used to monitor people in quarantine or managed isolation.
When the Delta wave hit, it started to be used in relation to patient care, helping to direct ambulances carrying Covid-19 patients by identifying sites with ‘Covid-ready’ beds to care for them, she says.
As the level of infection increased, the majority of Covid patients were now in the community, and the focus turned to predicting who might need high-level care.
Visualising a clinical risk score
As the number of Covid-19 cases quickly grew, the regional dashboard was populated with more and more data.
This enabled the regional team, led by health informatics fellow at the i3 Institute for Innovation and Improvement, Cheng Kai (CK) Jin, to create a machine learning algorithm to predict the risk of hospitalisation.
Data around demographics, vaccination status, long term conditions, medications, and test results was used to create the clinical risk score, which was then automatically calculated and displayed in the operational dashboard.
This helped clinicians decide who needed to be seen and whether they met criteria for anti-viral drugs and pulse oximeters for monitoring in the community.
“The dashboard enabled data driven allocation of health services,” says Armstrong.
Data was shared with primary health organisations twice a day, so general practitioners could see all of their patients who had recently tested positive and what their risk scores were.
The Māori and the Pacific Regional Coordination Hubs had direct access to the dashboard.
Namoe Tuipulotu, Pacific
Data enabling an equity focus
Namoe Tuipulotu – Head of Pacific Intelligence & Insights, Te Whatu Ora, was working in the Pacific Regional Coordination Hub when she got involved in developing the dashboard.
“It is really important that we have Pacific people developing these types of dashboards if they are meant to reflect and show what’s happening for Pacific communities,” she explains.
Tuipulotu says the clinical risk score was particularly useful for identifying high risk patients and visualising who had been contacted or assessed within 24 and 48 hours. This information could be filtered by ethnicity and age group.
“It enabled us to see whether we were serving our Pacific people appropriately,” she says.
For example, a user could extract a list of high-risk Pacific patients who had tested positive in the last 24 hours.
“In my experience if you can’t tell the clinicians who a particular patient is they may lose trust in the data, but we were able to get down to NHI (National Health Index) level data, allowing clinical teams at the hub to sense check whether or not the data was accurate, which really helped with data quality,” Tuipulotu explains.
“It highlighted to the director of Pacific Health, who could feed up to the Executive Leadership Team, what was being done by these Pacific hubs and providers. It was really helpful to be able to drill down in different ways, because the data my manager might want would not necessarily be the same as what the doctor on call that day would want to see.
“Data is power so having this information readily available was extremely important during the pandemic,” says Tuipulotu.
“Having the right data also makes your processes so much more efficient.”
Delwyn Armstrong, Director
A scalable platform for the future
The NRHCC regional data store was originally hosted on-premise, but was shifted to the cloud as the amount of data coming in started to multiply, ultimately holding around four million Covid-19 test results.
Armstrong says this was “a real step change”.
“It was hard, but it really changed things for us in terms of scalability,” she explains.
The Covid-19 Dashboard now has around 60 different pages and Armstrong describes it as “like a big web site, providing windows to multiple different data sets in a completely integrated way”.
Data is key to the health system’s planning to enable it to ‘catch-up’ on services and care that was unable to be delivered during lockdown.
Armstrong says a range of initiatives are now underway, such as bringing together all planned care data, in order to nationally tackle wait lists.
“We’re looking to use various data sources to target the people who’ve been waiting the longest and who have the greatest need,” she says.
“Having these analytics tools means that decision makers can put in different scenarios to look at how we can shape our services.”
Tuipulotu strongly believes that “if you’ve got the right information readily available, you can make better decisions.
“Analytics is about shifting from counting widgets to starting to understand outcomes and how we can know we are truly making a difference for our patients,” she says.
Answering new questions and delivering greater value
“When you are implementing software systems, you need to make sure that people understand and use the data, because that’s where the real benefit comes from. Key to that is data literacy.”
Stuart McCaw, Programme Manager at Te Whatu Ora – Health New Zealand Capital, Coast, Hutt Valley
While vast amounts of healthcare data are available, the challenge is making this data usable and actionable.
Decision makers need to understand the different levers that drive patient outcomes, the level of performance at a healthcare facility, and the impact of policies that are designed or delivered across a health program, and at all levels of care.
In a data driven organisation, questions are encouraged. It is not simply about producing reports detailing what was done in the past, but questioning why and how it could be improved for the future?
Successful organisations have a culture in which all staff – from nursing and allied health professionals on the frontline, right up to executive level – are empowered to ask questions of data.
Data literacy is the ability to read, work with, analyse and communicate with data. Data literate staff understand what questions to ask and how to get true benefit from available data. This becomes a virtuous cycle, as data driven organisations produce data literate employees, who then contribute more to their roles.
Access to the right analytics tools drives adoption of data-driven decision making and increased data literacy amongst health staff. The ability to deliver self-serve analytics also frees up resource to focus on providing greater value back to an organisation.
This was the case for Te Whatu Ora Capital, Coast, Hutt Valley and Wairarapa, where the introduction of automation and self-service analytics means many queries do not come to the analytics team anymore and the time needed to produce reports is significantly reduced, allowing them to focus on providing greater value back to their customers.
Te Whatu Ora, Capital, Coast, Hutt Valley and Wairarapa
Te Whatu Ora, Capital, Coast, Hutt Valley and Wairarapa Mental Health, Addiction and Intellectual Disability Service (MHAIDS) provides services across Wellington, Porirua, Kāpiti, the Hutt Valley and the Wairarapa, as well as some central region and national services.
Telling better stories
MHAIDS provides mental health, addiction and intellectual disability services across Capital, Coast, Hutt Valley and Wairarapa districts.
There is a large range of information coming into the combined service – including addiction, forensic, and intellectual disability data – which is being recorded in multiple systems across multiple locations.
Data flows from source systems into a data warehouse, with the visualisation and analytics tool over the top, enabling MHAIDS to have one application that sources information from many disparate systems, creating a single source of data.
The MHAIDS dashboard went live in early 2022, pulling together a range of measures spanning quality, reportable event and client data that are of interest to the service.
Hope McCrohon, MHAIDS Senior Analyst, says the tool allows her team to “tell better stories”.
“We have the ability to look at multiple measures on one screen, which is especially important in mental health as you need to see at least three measures to get a good idea of what you are looking at,” she says.
“We also have HR and finance measures from across MHAIDS to back up our client data and it is all in one place, which is really nice place to be.”
Steve McGinnity, Analyst in the MHAIDS Business Systems Team, says users can also filter information by things like ethnicity or team.
“We can see what impact any given project is having on a service by just looking at the data,” he explains.
“We are seeing a significant uptake of the dashboard being used in clinical governance meetings, as it allows them to see trends over time.”
Users’ ability to see what happens to the information they input and have access to it has had a huge impact on data quality.
“These tools have really helped to improve people’s understanding of what we do with the data and how the information that they contribute influences a whole range of measures,” McCrohon says.
Hope McCrohon, MHAIDS
Team leaders have always been interested in how they can use data to make improvements and address certain issues, but information siloes made it difficult to work with.
“Having everything in one place means the users can go and interact with the data and because the interface is very user friendly, people are able to find information easily, which gains and maintains their interest,” McCrohon says.
The analytics solution also enables questions to be raised and answered in real time.
McCrohon points to a local project on improving the district’s access and intake processes. At a progress meeting, analysts were able to answer questions on workflow and call numbers immediately.
“Historically, this would have involved someone writing down a request, sending it to my team, formulating the data, and sending it back. It could have been the next meeting or the following meeting that they would have got the answers to the questions,” she says.
“That ability to answer questions in real time is one of the key benefits at the service level as it frees up our capacity for other work.” A shift away from manual reporting has allowed the data analytics team to focus on quality improvement.
“This could mean focusing on improved data quality, or digging into the data and understanding the story,” McCrohon says.
After working in the district for 13 years, she says the data analytics space today “feels like a different world”.
“Previously there was a disconnect between the information reports we were sending out and people’s experience on the ground. Now teams have confidence in the data, reports are automated, and people are taking ownership of their information,” she says.
“We have consistent measures and consistent understanding of what those measures mean.” McGinnity agrees saying, “with automation and self-service analytics there are a lot of queries that do not come to us anymore and the amount of manual work to produce reports is significantly reduced.
“It provides greater efficiency and allows me to focus on providing greater value back to our customers.”
Stuart McCaw, Programme
Improving data literacy
Stuart McCaw’s focus is on getting benefit out of the analytics investment.
“When you are implementing software systems, you need to make sure that people understand and use the data, because that’s where the real benefit comes from. Key to that is data literacy,” he says.
McCaw adopted and adapted a competency-based data literacy programme developed in Australia (Databilities ™ model from Data to the People) and the first tranche of training was in MHAIDS.
He assesses which of a range of competencies a staff member needs to have and at what level.
Before the Covid-19 pandemic hit, McCaw was training staff in-person in groups. During lockdowns, he started virtual training one-on-one and found this hugely beneficial in terms of attendance and being able to train staff using their own data.
“It’s important that we train and work on the information that people have to use in their working lives,” says McCaw.
“I’m teaching them to understand trends over time: to identify a potential problem on a graph and then comment on what processes they are putting in place to address it.”
A survey of MHAIDS trainees shows an average 70 percent increase in confidence in using analytics and their understanding of their data, which has led to increased use of the analytics tools.
The highest interest in training sessions is from team leaders who are keen to understand information around staffing needs, such as Full Time Equivalent calculations and vacancies.
“The data that supports the recruitment process is really important to them, so getting the data right is really important to them and we have an application that exposes them to what our payroll system shows about their staffing,” he says.
Training highlighted a need to improve the service’s management of position data, which led to McCaw co-designing and piloting a new process and information flow, with early indications that it is having a positive impact.
“This was a data quality improvement process, but it is also fundamentally helping to manage our understanding of our staff mix within our teams, ensuring that is accurate and therefore vacancies are accurately reflected,” he says.
“This has a significant impact on recruiting and speeding up that process.”
“It really reduces the noise in the system and allows staff to focus on what’s important and answer their questions quickly,” McCaw says.
Streamlining patient pathways
“The dashboards provide live information that informs decision making at an operational level. Like an airplane, we’re not flying blind.”
John Cartwright, General Manager Emergency Department and Middlemore Central
By analysing large amounts of data to identify patterns, trends, and potential areas for improvement in the patient journey, users can manage and improve hospital efficiency and patient flow.
Data analytics can also be used to predict patient demand, allowing hospitals to better plan for staffing needs and resource allocation and prevent overcrowding and long wait times.
Middlemore Hospital is the largest in Aotearoa New Zealand and its Command Centre is
using a variety of live dashboards to manage patient flow.
An AI tool that forecasts surgical and medical admissions and discharges over the next seven days, helps staff to prepare and allocate resources.
Rosie Whittington, Te Whatu Ora Counties Manukau, Health Intelligence Manager, says “this supports users in their decision making, using real-time dashboards to plan for the future.”
Te Whatu Ora – Health New Zealand, Counties Manukau
Middlemore is the largest hospital operated by Te Whatu Ora – Health New Zealand. It offers secondary-level care and a selected range of community and domiciliary services for the population of Counties Manukau and niche specialist tertiary services for regional and national consumers in orthopaedic and plastic surgery, burns, spinal injury rehabilitation, renal dialysis, and neonatal intensive care.
At Middlemore Central Command Centre, various dashboards light up the screens.
The dashboards are key to the command centre’s role of managing patient flow in the busy hospital and are well used on wards, as well as displayed in the executive suite and incident management meeting room.
Users can see at a glance the overall hospital occupancy and a simple traffic light system provides an overview of performance.
Using this real time data, the Command Centre can coordinate and overcome obstacles to good patient flow, such as ensuring staff are where they need to be.
John Cartwright, General Manager Emergency Department and Middlemore Central, compares the Command Centre to the cockpit of an airplane.
“The dashboards provide live information that informs decision making at an operational level. Like an airplane, we’re not flying blind,” he says.
“We can see at a glance what is going on in the hospital rather than having to call all wards one by one. It is a game changer and allows us to function more efficiently.”
Kirstine Kent, Te Whatu
Forecasting data enables planning
When a patient is admitted to the hospital, they need a bed in the correct location, attached to the relevant specialty, consultants and nurses, in order to get the specialised care necessary for recovery and discharge.
Live dashboards set the scene in the morning bed meetings, showing how many patients need a bed in what area and how many are expected to be discharged.
Rosie Whittington, Te Whatu Ora Counties Manukau Health Intelligence Manager, says that with finite resources it is better to understand what is coming through the front door. This enables clinical teams to prepare.
“We wanted to visualise the numbers of people coming in over the next week so that we can learn accordingly and predict impact on non-scheduled care,” she says.
“Data was available for long term planning, but we needed data in the short term for hourly and daily forecasting.”
They embarked on a project to forecast surgical and medical admissions and discharges over the next seven days, using AI platform Data Robot.
An algorithm was trained on historical hospital data, to find patterns in what has happened on certain days and weeks, and even hours of the day, in order to forecast the future.
It now pulls occupancy data in real time from the Patient Administration System and uses this to forecast admissions and discharges.
Dashboards visualise this data so managers can see actual demand, historical demand and predicted demand.
“This supports users in their decision making, using real time dashboards to plan for the future,”Whittington says.
“The algorithm is always learning because of the process we have built around it to retrain when it drifts, and we are always checking how the model performed compared to what actually happened.”
Rosie Whittington, Te Whatu
Informing the future
Forecasting data allows the Command Centre to be more responsive to staffing and resource needs on the ground.
Cartwright sends morning emails, highlighting key priorities and what they are anticipating through the doors.
This allows staff to take preliminary action, such as review their rosters, use satellite hospital capacity or consider the virtual care option, Hospital in the Home.
“It allows services to plan and move things around if needed,” explains Cartwright.
“For example if we are expecting lots of vascular surgery patients they will need ICU capacity and a certain number of minutes of acute theatre time, but they can’t start surgery until an ICU bed is available,” he explains.
“It makes a real impact as sometimes the algorithm has forecast a bad day, but we did some escalation that encouraged more discharges and were able to cope with the demand.
“We wouldn’t be able to do that without really easy access to good information and the staff trusting the data,” he says.
Joan Lau, Te Whatu Ora
Empowering and adding value
Joan Lau,TeWhatu Ora Counties Manukau Advanced Analytics Manager, says everyone in the organisation sees the same information, from a nurse working on the floor up to a general manager.
She describes how in the past, “analytics was something we had to do for reporting”.
“It wasn’t adding value, but we realised it’s really about empowerment and the arrival of Covid-19 really showed how powerful that can be,” she says.
Use of data during the pandemic response elevated awareness and understanding of the power of data, from the coalface all the way up to executive levels of the health system.
Kirstine Kent, Service Manager at Te Whatu Ora Counties Manukau, describes how the hospital has spent a lot of time developing its dashboards, which are “tailor made for us and how we work and how we think”.
“Without these dashboards, we would have to send people out to do manual counts. Instead, we have this repository in the middle of the hospital with all the information we need about all specialties in real time and at the same time,” Kent says.
“I can see how many patients are in all our seven location sites; I know how busy the birthing units and our mental health facilities are, and I even know how the hospital is feeling in terms of the staff on the wards,” she says.
“This information just wasn’t available in the past, and now it’s all right here on our screens and at our fingertips.”
John Cartwright, General
Te Whatu Ora – New Zealand Health Partnerships
Te Whata Ora – New Zealand NZ Health Partnerships, is part of Te Whatu Ora – Health New Zealand and delivers the Health Finance, Procurement and Information Management System (FPIM).
FPIM supports the New Zealand health system’s day-to-day finance, procurement and supply chain operations, managing how goods and services are sourced, ordered, delivered, stored, used and paid for.
As part of this work, the organisation has developed a Health System Catalogue. This delivers a single national procurement catalogue, national data standards, a central data repository of actual spend on medical devices, known as the Spend Data Repository (SDR), and a framework for procurement compliance.
Moving from Data Analytics to Insights
When Te Whatu Ora Health New Zealand was created in July 2022, NZ Health Partnerships was tasked with taking a national view of health spend data. This information was held in nine different Enterprise Resource Planning (ERP) systems used across the country’s 20 hospital districts.
At the time, half of these districts used the national FPIM solution, while the rest used a range of ERPs to manage their day-to-day operations.
Erik Salzmann, Te Whatu Ora – NZ Health Partnerships Solutions Architect, explains that the organisation needed to pull that data together to provide a national view.
It went live in 2021 with an analytics tool and a data platform and rapidly stood up the data pipelines to all ERP systems. The challenge then becomes harmonising and standardising the data.
“The hard part is pulling all of that together and making sense out of it, and that is where we are using visualisation tools to assist us,” Salzmann says.
The analytics tool is used to do data validation and verification, as well as the visualisation, analytics and forecasting for the Spend Data Repository.
Procurement teams within districts have access to the data relevant to their districts to view what is happening locally and whether staff are buying catalogued items off national contracts. If not, they can have the conversation about ‘why not’?
Jakkie van Wyk, Head, FPIM Implementation and Data, says the organisation created a four year business plan for 2021-2024, which focused on moving from data to analytics to insights.
“We thought it would take us four years to get there, but we have been able to move much faster than expected and are already doing a lot of work on insights,” she says.
Jakkie van Wyk, NZ
Agile and Flexible Financial Forecasting
The SDR was originally created to collate spend reporting for District Health Boards (DHBs). In July 2022, the DHBs were disestablished and the new national organisation, TeWhatu Ora – Health New Zealand, was created.
vanWyk says NZ Health Partnerships’ ability to access spend data at a national level meant it was asked to produce regular national reports.
The organisation developed the Financial Forecasting and Reporting solution for Te Whatu Ora consolidating the budgets of all former DHBs.
vanWyk describes that as a minimum viable product that Te Whatu Ora – NZ Health Partnerships is now looking to productionise.
“We are very proud that our application was used to help Te Whatu Ora do the budget and we have seen the real value in that application,” she says.
The analytics tool means that if finance and reporting hierarchies change, they can build the new hierarchy and remap the existing cost centres, without touching the ERP system themselves, which would be a hugely costly and lengthy process.
“It means we can be really agile and flexible and respond quickly to requests, without touching the integrity of our data sitting underneath,” vanWyk explains.
There are huge efficiency gains to be made by being able to see data at a national level, such as replenishing from central warehouses and viewing where stock is sitting and where demand is.
“Analytics helps us draw the data out and consolidate those views because they need that high level data at a national level,” she says.
TeWhatu Ora – NZ Health Partnerships has completed a sharing exercise with HealthSource, the organisation which does procurement for the four Northern Region Districts.
HealthSource uses the visualisation tool and the same data solution, so once data sharing agreement were legally in place, the technical sharing of data was done “in the blink of an eye”, Salzmann says.
“By linking data sources together, HealthSource have been able to retain a single source of truth by keeping data in the area where it is recorded, rather than duplicating it into another database.
“We just shared accounts and suddenly they had access to run reports across our data and we have access to run reports across their data.”
NZ Health Partnerships can look at spend for the Northern region over a period of time, without copying any information into their own environment. The organisation wants to enable this for all the districts to do their reporting.
“They can continue to run their business and we can continue to do our work without duplicating any of that effort, by linking databases together,” vanWyk explains.
“We want to be contributors into the sector by ensuring the data is accurate and reliable, so other people can draw on and get benefits from it,” she says.
A custodian approach means if a user wanted to overlay financial inventory information with patient information or ward occupancy, in order to do comparisons or planning, they could be given self-service access to this data without having to build major pipelines between systems.
Salzmann says, “the potential is vast as the data is out there, but currently it’s sitting in isolated silos.We aim to pull it together to give people access so they can run their own reports.”
Erik Salzmann, NZ
Enabling the Future
The Spend Data Repository is initially focused on medical devices, of which there an estimated 250,000 in the sector.
vanWyk says this build provides the foundation to expand the scope to other areas, and they are already inputting all spend data from the districts.
Work has moved so rapidly that NZHP is already looking to assess what additional categories will be added to the Health System Catalogue.
“The ability to share data without having to build data pipelines makes the solution really beneficial as we aim to become a ‘one stop shop’ for any financial procurement or inventory information to the sector.”
Enabling Self Service
TeWhatu Ora – New Zealand Health Partnerships sees itself as the custodians of health data related to finance procurement, inventory and supply chain.
Salzmann says by providing secure and reliable data, the organisation can enable users to innovate across the sector.
The organisation is also embarking on a proof of concept around machine learning.
One of the challenges facing the sector is demand forecasting for medical devices or medical equipment on the hospital wards, which currently requires physical counting of what is on the shelves.
The proof of concept will use key pieces of information – such as ward occupancy, patient turnaround or staffing levels – to determine what inventory levels are needed.
Salzmann says this could potentially apply to around half of all devices and equipment.
“You can predict the requirements of a ward based on historical data based on machine learning,” he says.
“This means you no longer have to cycle count every day, but may just once a month, which releases resource to do other work.
“And that’s just the beginning as from that point onwards, the world’s your oyster in terms of what you can do with the data.
vanWyk says, “it is incremental wins and gains that actually make a huge difference.
“Whatever we do, we always aim to make life easier for users and to help improve patient experiences – enabling better decision making through data insights.”
*case study completed in 2022 when NZHP was an ‘entity’ of Te Whatu Ora, it has since become part of the national organisation.