Case studies
The National Integrated Health Services Information (NIHSI) has transitioned to the National Health Data Hub (NHDH).
The case studies below illustrate the types of information and uses of data that are now possible using the NHDH. They demonstrate the value of the NHDH in describing person-centred experiences in the health and aged care system and the contribution this linked information makes in progressing health policy and research, improving service delivery, and thereby delivering a range of public benefits.
About the project
This project used NHDH to investigate patterns of guideline indicated cardiovascular (CVD) medication use among 67,800 people discharged from hospital following a coronary heart disease (CHD) related admission. About half (35,200 or 52%) of these people had acute coronary syndrome (ACS), which includes heart attacks and unstable angina. In addition, the project examined demographic characteristics, clinical factors, and community-based health-care service use that were associated with patterns of medication use in the year following hospitalisation.
This analysis made use of linked hospitalisations, deaths, MBS and PBS datasets held within the NHDH (formerly NIHSI). The linkage of these datasets, at the person level, allowed patient pathways to be examined.
What we learnt from this project using NHDH data
The linked report provides results from the study: Medication use for secondary prevention after coronary heart disease hospitalisations: Patient pathways using linked data
This project identified that there are population subgroups who were less likely to initiate, or continue to access, preventive medications after a hospitalisation for CHD.
Some key findings from the report:
3 in 5 (60%) people with ACS were dispensed 3 or more of the 4 recommended cardiovascular medicines within 40 days of leaving hospital. Women, people aged under 65, and those with less severe CHD subtypes, were less likely to be dispensed the recommended medicines within this timeframe.
Around 3 in 4 (75%) CHD patients were still taking their medicines 1 year after leaving hospital. People in older age groups and those who regularly saw their GP were more likely to be doing so.
People who had been dispensed the CVD medicines in the year before going to hospital were significantly more likely to be dispensed medicines after being discharged from hospital and to be still taking them 1 year later.
1 in 5 (20%) CHD patients had an emergency CVD-related readmission and 1 in 15 (6.7%) died within 2 years after the hospital admission.
Why is this useful?
The results of this project help inform strategies to improve medication use, for the purpose of secondary prevention, for patients with CHD. This work builds on existing literature and improves understanding of how people use and interact with the health system.
Why is this not possible without the NHDH?
This project would not have been possible without the person level integration of medications information from the PBS, health service use data from the MBS, admitted patient care datasets, and national deaths data.
About the project
This project, using the NHDH, is the first ever comprehensive examination of health services used by Australians in the final 12 months of life, and the cost of those services to the health system.
What we learnt from this project using NHDH data
Findings from the analysis were presented in the following reports:
- Overall population: Last year of life: patterns in health service use and expenditure released on 21 July 2022
- This analyses was also released in an AH22 data insights article on 7 July 2022 (Chapter 6): Australia’s health 2022: data insights
- People who died by suicide: Health service use in the last year of life, released on 4 November 2022.
The results in the first two reports showed that spending on key health services is 14 times higher for Australians in their last year of life than for other Australians. On average, people who died used more health services in their last year of life than the rest of the population used over a 12-month period. Costs for health services were also higher for people in their last year of life than for people who were not, ranging from 4.8 times as high for MBS services to 39 times as high for hospital admissions. Total health service costs were highest among people who died from cancer (in particular, colorectal, breast and prostate cancer).
The second report used the NHDH to examine the patterns of health service use in the last year of life for people who died by suicide. The research found that people who died by suicide accessed fewer health services in their last year of life than those who died from other causes. Almost half of those aged 15-64 years who died by suicide did not have any contact with the hospital in the year prior to death, and 9% of females and 6% of males who died by suicide had a mental health related emergency department presentation in their last year of life.
Why is this useful?
The results of this project will help policy advisors to the Department of Health and Aged Care and health practitioners (including people working in palliative care settings) understand how people interact with the Australian health system in the period leading up to death. It provides, for the first time, detailed information on the patterns and cost of health service use in the last year of life for the overall population as well those who died from specific causes including suicide. The findings will be useful for assessing and evaluating health service planning and policy and estimating future health service use costs.
The size of the NHDH, and significant population coverage, are unique in Australia and, as a result, this work allows a better understanding of how people use and interact with the health system in the last year of their lives.
Bringing together different sources of data provides an opportunity to address gaps in our understanding of the impacts of population growth, ageing, increased longevity, a growing economy and increased spending on health.
Why is this not possible without the NHDH?
This project would not have been possible without the integration of national cause of death data with a range of health services data such as MBS, PBS, Aged Care and hospital admittance and emergency department data.
About the project
Over the past few months, the Health Economics and Modelling Branch at the Australian Government Department of Health and Aged Care (the Department) has been developing the Health Outcomes Modelling and Evaluation (HOME) Model.
What we learnt from this project using the NHDH data
Aimed at modelling the patient journey from birth to death, this project will enable unpacking interactions across the health and aged care sectors using the integrated data available in the NHDH.
Why is this useful?
Developing this tool is critical for the Department to be able to facilitate evidence-based policy making that balances the costs and benefits of health and aged care interventions for government with long term patient wellbeing. Such modelling will impact policy development and service delivery and will deliver significant community benefits.
Why is this not possible without the NHDH?
The NHDH plays a crucial role in the development of the HOME Project as it enables analysis of linked person-centred granular data detailing patient health service use to identify the factors influencing patient outcomes and patterns of health and aged care service usage.
About the project
The lack of primary healthcare data containing dementia diagnosis information is a key data gap for monitoring dementia in Australia. The NHDH has partly filled this gap through the linkage of GP and other medical specialist data through services provided under the Medicare Benefits Schedule (MBS) with other datasets that have dementia diagnostic information (i.e. hospitals, aged care, mortality and prescription medication data). The NHDH allows for greater insights on people living with dementia, and their interactions with Australia’s health and aged care systems.
What we learnt from this project using NHDH data
There have been multiple dementia focused reports using NHDH data.
The Dementia in Australia report revealed that:
- Half of all MBS services used by people with dementia were for GP consultations, with an average of 20 GP consultations in a single year.
- There was substantially more geriatrician referred plans and chronic disease plans on average for people with dementia compared with people without dementia,
- On average a person with dementia had 5 specialist services in a single year.
The report, Younger onset dementia: new insights using linked data, explored health and aged care service factors associated with entry to residential aged care for people with younger onset dementia. The study found more than half of people with younger onset dementia in the study eventually required permanent residential aged care, with one quarter aged under 65 at entry. Respite residential care was used by one-third of people with younger onset dementia who went on to enter permanent residential aged care. Polypharmacy and the dispensing of antipsychotic drugs increased in the 6 months after entry to permanent residential aged care, from what was already a high base in the community.
Analysis of linked data in the NHDH has also assisted in developing new analytical approaches to determining prevalence of disease. Generally, people with more progressed dementia are captured in administrative datasets as they come into contact with more parts of the health system. Machine learning techniques applied to the NIHSI data were used to explore whether early dementia (i.e. recently diagnosed or pre-diagnosis) could be predicted from primary and secondary care service utilisation, as recorded in Medicare claims data. Details are in Predicting early dementia using Medicare claims: a feasibility study using the NIHSI. This study is also significant because it demonstrated the utility of Medicare claims data for health monitoring, despite them containing no diagnosis information.
Why is this useful?
The use of the NHDH has been integral to the success of the new National Centre for Monitoring Dementia and its work program. Dementia is often poorly and inconsistently captured in individual health data sources. However, because the NIHSI contains diagnosis data from a range of sources over time, the construction of cohorts can draw on multiple data sets and episodes of care. This has greatly improved the accuracy of identifying people living with dementia in Australia and has expanded the scope of reporting on this condition.
Why is this not possible without the NHDH?
The NHDH brings together multiple sources of dementia diagnosis and health system information into a person-centred, longitudinal data source that provides not only better coverage for monitoring dementia, but also provides insight into the interactions that people with dementia have throughout the disease's progression.
About the project
This project used NHDH to examine the number of people hospitalised for Family and Domestic Violence (FDV) in Australia from 2010 to 2019. The project explored the demographic profile of people with an FDV related hospital stay, as well as the characteristics of their hospital experiences, including visits to the emergency department, and any subsequent deaths. To improve interpretability of the results, a comparison group was constructed using a stratified random sample of the hospital data.
What we learnt from this project using the NHDH
The results from the report, Examination of hospital stays due to family and domestic violence 2010-11 to 2018-19 found:
- Around 1 in 8 (3,600 or 12%) people who had an FDV hospital stay had at least one additional hospital stay for FDV, with almost 2 in 3 (62%) of these occurring within one year.
- Around 1 in 5 (21%) people who had a FDV stay had multiple assault hospital stays (including both FDV and other assault).
- Partners were responsible for most FDV hospital stays, and most repeat hospital stays.
In addition, people who had an FDV hospital stay had a higher rate of death and different causes of death than a comparison group with similar characteristics. The FDV group were 10 times more likely to die due to assault, 3 times more likely to die due to accidental poisoning or liver disease, and 2 times more likely to die due to suicide, than the comparison group.
Why is this useful?
This project aimed to explore how enduring linked data on a national scale could be used to improve the understanding of repeat hospital stays for FDV over time, as well as patterns of broader hospital service use and death for people hospitalised for FDV. This was able to be achieved due to the ability to determine person level data, rather than episode level data.
The study identified certain groups in the community more vulnerable to FDV related hospitalisation. About 1 in 10 hospital stays among the FDV group were for Pregnancy, childbirth and puerperium, highlighting the risks to mothers of this type of violence. Also, hospitalisation for Mental and behavioural conditions was relatively more common among the FDV group (11% of all hospital stays) than the comparison group (4%), also highlighting the important connections between FDV and poor mental health.
Of the FDV group, 5.7% had a death recorded from 2010 to 2019, compared with 4.4% of the comparison group. The cause of death for these groups also varied. The leading causes of death among the FDV group (where a cause of death was listed) were coronary heart disease, accidental poisoning, suicide and liver disease. The leading causes of death for the comparison group were coronary heart disease, lung cancer and cerebrovascular disease.
When examining the rate ratios, the FDV group were 10 times as likely to die due to assault, 3 times as likely to die due to accidental poisoning or liver disease, and 2 times as likely to die due to suicide, as the comparison group.
These findings provide enhanced understanding of the nature, and possible downstream impacts on well-being of those experiencing FDV. Timely interventions can potentially reduce avoidable deaths and other health-related complications among the community.
Why is this not possible without the NHDH?
The health system plays an important role in responding to family and domestic violence (FDV). Hospitals are one important intervention point in cases where FDV results in injuries requiring admitted hospital treatment and care. The findings from this project would not have been possible without the use of linked health service data readily available in the NHDH due to the data being available at a person level, and across various datasets.
What can we learn from integrating cohort study data with the NHDH?
Generation Victoria (GenV) is Australia’s largest-ever birth and parent cohort study. Open to every child born Oct 2021-Oct 2023 and living in Victoria, it has recruited more than 90,000 babies, mothers, and fathers since its inception. GenV includes families from all ethnic backgrounds, all lifestyles, and all levels of health and ability. The study is collecting information from children and parents, biospecimens, and consent for record linkage. GenV includes existing integrated Victorian data on service delivery across all sectors including health, education and social care, and the environments children are growing up in. It has achieved high recruitment and retention rates, rich phenomic and genomic datasets, and many embedded collaborative studies and trials.
Linking GenV data with the NHDH data will present a more holistic view of the issues that might impact the health and wellbeing of children and their parents and allow for more fulsome and robust insights about their health. In particular, NHDH data can generate evidence that will help identify and remove inequity in key areas such as mental health and wellbeing, obesity and diabetes, allergy and immunity, infection, healthy pregnancy, development, and climate and environment. For example, it could be used to identify unmet health service needs and to develop new preventative and treatment programs that go beyond medical interventions, such as improving recreation opportunities in areas of high obesity.
Why is this useful?
Integration of GenV data with the NHDH would enhance the value of the self-reported and local data and enable the generation of new and timely insights to drive evidence-based policy implementation. It would accelerate discoveries that might improve access to and delivery of services, diagnosis, prevention and treatments that will ultimately improve the health outcomes and wellbeing of future populations.
Furthermore, the inclusion of GenV data in the NHDH would meet each of the goals of the National Health Reform Agreement, specifically to:
- Deliver safe, high-quality care in the right place at the right time.
- Prioritise prevention, and help people manage their health across their lifetime.
- Drive best-practice and performance using data and research, and
- Improve efficiency and ensure financial sustainability.
Why is this not possible without NHDH?
Although GenV already includes large-scale and significant data, integration with the NIHSI would provide a more comprehensive representation of childhood and family health and health service use in Australia. The NHDH is the only mechanism to capture interstate health care use by people who live near state borders, and to bring together hospital care, pharmaceutical use and government funded health service use in the same data space. With expedited access to contemporary data, the integrated data will support researchers and stakeholders to work together to generate timely solutions.