VIEWPOINT

Vol. 137 No. 1599 |

DOI: 10.26635/6965.6572

ANZACS-QI Heart Failure Registry: a new approach using age-stratified sampling of hospital discharges to guide quality improvement (ANZACS-QI 79)

Heart failure affects approximately 1.6% of adults in New Zealand and is associated with significant morbidity, mortality and healthcare costs.

Full article available to subscribers

Heart failure affects approximately 1.6% of adults in New Zealand1 and is associated with significant morbidity, mortality and healthcare costs. Although heart failure incidence rates were declining up to the 2000s, incidence rates have plateaued since 2013.2 Despite advances in heart failure management, 1- and 5-year survival after first-ever heart failure hospitalisation in New Zealand remain poor at 69% and 37% respectively.3 Significant ethnic disparities exist in heart failure outcomes in New Zealand, with Māori and Pacific peoples experiencing higher incidence rates4 and mortality.5

There are effective evidence-based treatments for patients with heart failure.6,7 Management is guided by heart failure phenotype, which is based upon left ventricular ejection fraction (LVEF): heart failure with reduced ejection fraction (HFrEF, LVEF ≤40%), heart failure with mildly reduced ejection fraction (HFmrEF, LVEF 41–49%) and heart failure with preserved ejection fraction (HFpEF, LVEF ≥50%).6,7 A range of pharmacotherapy and devices have been shown to improve outcomes in patients with HFrEF, including angiotensin-converting enzyme inhibitors (ACEi),8 angiotensin receptor blockers (ARB),9 angiotensin receptor-neprilysin inhibitors (ARNI),10 beta-blockers,11 mineralocorticoid receptor antagonists (MRA),12 sodium-glucose cotransporter-2 (SGLT2) inhibitors,13 implantable cardiac defibrillators (ICD)14 and cardiac resynchronisation therapy (CRT).15 In contrast, these treatments have not been shown to reduce mortality and morbidity in patients with HFmrEF or HFpEF, with the recent exception of SGLT2 inhibitors.16,17

Despite strong clinical evidence and guideline recommendations, sub-optimal initiation and maintenance of guideline-directed medical therapy (GDMT) have been documented in heart failure.18–20 It is important to have systems to identify these evidence–practice gaps in order to inform strategies to improve and achieve equitable outcomes for patients with cardiovascular disease in New Zealand.21 One such system is the ANZACS-QI (Aotearoa New Zealand All Cardiology Services—Quality Improvement, formerly All New Zealand Acute Coronary Syndrome—Quality Improvement) programme,22 which utilises a web-based system to create a clinical registry of patients with cardiac conditions.

In this paper, we describe the initial experience with the Acute Decompensated Heart Failure (ADHF) Registry and its limitations; and describe the implementation of the revised ANZACS-QI Heart Failure Registry, which has the primary aim to support evidence-based management of and quality improvement measures for patients who are hospitalised with heart failure in New Zealand.

Acute Decompensated Heart Failure (ADHF) Registry

In December 2015, the ADHF Registry module20 was created within the ANZACS-QI platform. This was a traditional registry that included patients hospitalised with decompensated heart failure who have had contact with local heart failure services. Site participation and patient inclusion have been voluntary.

As of August 2023, 5,739 heart failure hospitalisations from 18 district health boards have been included in the ADHF Registry. The clinical characteristics of heart failure hospitalisations included in the ADHF Registry are shown in Table 1. The mean age was 70.4 years (standard deviation [SD] 15.5 years), 3,455 (60.2%) were male, 1,450 (25.3%) were Māori and 814 (14.2%) were Pacific people. Over 75% received investigation with a NTproBNP (N-terminal pro-brain natriuretic peptide) or echocardiogram during hospitalisation. The number of registry completions decreased significantly following the COVID-19 pandemic, from an average of 1,062 per year between 2016 and 2020 to an average of 144 per year between 2021 and 2023. The patients included in the registry following the COVID-19 pandemic were older and less likely to be Māori or Pacific peoples (Table S1).

Of the 2,568 (44.7%) patients with HFrEF, 1,801 (70.1%) were discharged on an ACEi/ARB, 2,182 (85.0%) were discharged on a beta-blocker and only 979 (38.1%) were discharged on an MRA. The lower proportion of patients discharged on an ACEi/ARB may be partly explained by the introduction of subsidised sacubitril/valsartan in late 2018 and the registry form not being updated to include this new medication.

View Table 1–2, Figure 1.

Challenges and limitations of ADHF Registry

Data collection for heart failure quality improvement poses unique challenges compared to other cardiovascular diseases that require specific attention.3

The key limitation of the ADHF Registry is that it was unlikely to have captured a representative cohort of hospitalised heart failure patients in New Zealand. Identification of hospitalised patients with heart failure is challenging as they are managed under a variety of settings and services, unlike patients with acute coronary syndromes, which can be reliably identified from coronary care units and cardiac catheterisation laboratories. Furthermore, there is insufficient clinician resource to include all hospitalised patients with heart failure in a registry. The patients entered into the ADHF Registry were likely a selected cohort who were engaged with heart failure services, and candidates for more intensive GDMT up-titration as suggested by the higher proportion of patients with HFrEF. Furthermore, the number of patient entries into the registry and number of participating hospital sites varied significantly over time. The lack of a representative cohort in the ADHF Registry poses limitations on interpretation of its data. It is difficult to draw any comparisons over time and between healthcare regions in order to guide quality improvement.

Secondly, the ADHF Registry long-form captured a comprehensive dataset with a relatively large number of data fields (99 variables). This may have adversely impacted the completeness and sustainability of data collection given the time constraints on clinicians for registry data entry. Several important data fields were incomplete/unknown; for example, 34% had no documented heart failure ejection fraction phenotype, 55% had unknown heart failure aetiology and 70% had unknown New York Heart Association (NYHA) symptom class (Table 1). Several key data fields, such as LVEF, are not obtainable from national datasets, and hence there is a reliance on manual data entry by clinicians.

Consequently, there has been limited reporting of data outputs and performance indicators to users and district health boards, and therefore the ADHF Registry has been unable to impact heart failure care in New Zealand.

ANZACS-QI Heart Failure Registry

The ADHF Registry has demonstrated an evidence–practice gap, with findings suggesting prescribing of ACEi/ARB and MRA on discharge could be improved for those with HFrEF, and that ethnic inequities likely exist with Māori and Pacific people being over-represented in the registry cohort. Ongoing data collection via a heart failure registry is needed to support evidence-based management and guide quality improvement measures in New Zealand.

Taking the learnings from the ADHF Registry, we propose a revised ANZACS-QI Heart Failure Registry that is based upon stratified sampling of hospital discharge coding, utilises the existing ANZACS-QI infrastructure, receives governance from the Heart Failure Working Group and focusses on established quality improvement indicators for heart failure management.23,24 An overview of the registry workflow is shown in Figure 1.

Case identification and age-stratified sampling

As it is not practical to include all heart failure hospitalisations, a representative sample will be identified from the National Minimum Dataset (NMDS)25 for each hospital district to include in the registry. The NMDS is a national collection of hospital discharge information, coded utilising the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM). ICD-10-AM codes I50.x, I11.0, I13.0 and I13.2 in both primary and secondary diagnostic positions will be used for case identification—these codes have been shown to have high accuracy (sensitivity 90%, positive predictive value 92%) in identifying heart failure hospitalisations in the New Zealand setting.26,27 The sampling method must i) ensure adequate representation of patient sub-groups and hospital districts, and ii) identify a large enough sample to confidently estimate the performance indicators. This needs to be balanced with resource constraints on user time for registry data entry.

The minimum sample size calculated to estimate the performance indicator of LVEF assessment is 61 for metropolitan districts (~2,500 heart failure hospitalisations/year) and 48 for non-metropolitan (around 200 heart failure hospitalisations/year) with a confidence interval of 95% and a margin of error of 10%. This calculation is based upon the assumption that 80% of heart failure hospitalisations will have a LVEF assessment within 2 years. We anticipate that this sample size will be sufficient to estimate performance indicators for those with HFrEF both nationally and by individual district level, assuming that 40% of heart failure hospitalisations have HFrEF. However, the sample size will be under-powered at an individual district level to assess performance indicators by key demographic sub-groups.

Hence, we propose that each district enter a sample of 60–80 heart failure hospitalisations per year into the registry. The seven metropolitan districts (Waitematā, Te Toka Tumai Auckland, Counties Manukau, Capital Coast and Hutt Valley, Waitaha Canterbury and Southern) will contribute 80 per year, and the remaining districts 60 per year to reflect their population size and healthcare resource. The sample size has been increased to account for the small proportion of hospital discharges that are coded incorrectly for heart failure. A total of 1,340 heart failure hospitalisations would be entered into the registry annually if all districts participated, which accounts for approximately 5% of total heart failure hospitalisations nationally.

Age stratification will be applied to the sampling method to ensure that there is adequate representation of demographic sub-groups—such as younger patients and Māori and Pacific people—without increasing the sample size. Forty percent of the sample will be randomly selected from those 18–59-year-olds, 40% from 60–79-year-olds and 20% from ≥80-year-olds. We applied this stratified sampling method to a national annual cohort of heart failure admissions in 2018 (Table S2) and found that the proportion of Māori was significantly increased in the stratified sample (18.6% vs 26.0%, p<0.001), whereas the proportion of Pacific people was similar (7.7% vs 7.5%, p=0.98)

Case identification and age-stratified sampling will be done centrally by Health Intelligence, Health New Zealand – Te Whatu Ora, Counties Manukau on a quarterly basis. Heart failure hospitalisations in those aged <18 years, recurrent hospitalisations within the same 3-month period and patients admitted to a hospital outside of their domicile of residence (to allow assessment of outpatient follow-up) will be excluded from the sample. The identified sample with corresponding patient National Health Index (NHI) numbers and hospital admission and discharge dates will be made available to local users for entry into registry.

Data entry

The ANZACS-QI Heart Failure Registry will require manual data entry by clinicians as several key fields required for heart failure quality improvement, such as LVEF and presence of a left bundle branch block, are not available from routinely collected national datasets. We aimed to minimise the number of data fields to encourage accurate, complete and sustainable data entry, while obtaining sufficient information to assess key quality performance indicator measures,23,24 with an emphasis on class IA guideline recommendations.6,7 To minimise the burden of data entry, the registry will be supplemented by linkage to other national datasets using established methodology.22 For example, the specific formulation and doses of GDMT dispensed at discharge and during outpatient follow-up are obtainable from the pharmaceutical data warehouse. The potential advantages of this approach were considered against time delays to data-linkage, which restricts timely feedback into quality improvement processes.

The revised Heart Failure Registry form (Table 2) has a total of 33 mandatory data fields for user completion, of which nine are pre-populated demographic variables. The data fields include demographic characteristics, relevant comorbidities, in-hospital investigations and classes of medications on discharge. There are an additional five variables that capture outpatient care within the 6-months post-discharge. These are only mandatory for a new diagnosis of HFrEF. The data dictionary containing full definitions of variables is available on the ANZACS-QI web platform and on request.

Local users will complete registry forms for the identified sample on a quarterly basis. This will be done retrospectively 6 months after heart failure hospitalisation, as coded hospitalisation data are usually available no earlier than 6 weeks post-discharge, and to allow for data on index hospitalisation and outpatient follow-up to be entered at the same time point. We anticipate that the local users will be healthcare teams who participate in the care of heart failure patients in their district, but who may not have been involved in the care of the patients entered in the registry.

Hospitalisations coded incorrectly as having decompensated heart failure and patients discharged from services other than cardiology or other medical specialities (e.g., surgery) will be excluded. These variables are included in the registry form and allow the form to be completed without entry of data.

Reporting

Data outputs will be analysed every 6 months using the rolling average of the previous 12 months of data. Summary reports will be generated and distributed back to local users to support quality improvement measures. The reports will contain indicator data nationally, by hospital district and for key demographic variables of age group, gender and ethnicity.

The below proposed performance indicators are adapted from established quality and performance measures for heart failure management.6,7,23,24 The proportion of the identified sample with completed registry forms will be reported to ensure ongoing quality of the registry outputs. Inpatient care indicators will include the proportion of patients having LVEF assessment either during index hospitalisation or within the past 2 years and the proportion of patients with HFrEF who were prescribed GDMT on discharge. Outpatient performance indicators will be reported for the subset of patients with a new diagnosis of HFrEF. This will include the proportion of patients who have been seen in an outpatient clinic, who have had a repeat LVEF assessment and who have been prescribed target doses of GMDT. Data from the ANZACS-QI registry can be supplemented by the Pharmaceutical Collection data warehouse to allow identification of the proportion of patients who are dispensed doses of GDMT ≥50% of target doses and who are adherent to GDMT with a proportion of days covered (PDC) of ≥0.8 at 6 months post-discharge. The pilot and initial phases of the registry will be used to inform and refine potential performance indicators with guidance and agreement from the Heart Failure Working Group of the New Zealand branch of the Cardiac Society of Australia and New Zealand (CSANZ), ANZACS-QI and the National Cardiac Clinical Network.

As the ANZACS-QI Heart Failure Registry only includes a sample of total hospitalisations, data will also be reported from the total heart failure hospitalisation cohort derived from NMDS. The crude number of heart failure hospitalisations and rate per 100,000 population per year will be reported for comparison. Outcome indicators will be reported via linkage to the Mortality Collection and will include all-cause mortality, cardiovascular-specific mortality and re-hospitalisation with heart failure at 30 days and 1 year post-discharge.

There will be scope for more exploratory analyses of the ANZACS-QI registry in a research setting. Data access proposals can be made via the existing ANZACS-QI infrastructure.

Ethics considerations and approval

ANZACS-QI has national ethics approval as part of the Vascular Risk Equity for Aotearoa New Zealand (VAREANZ) programme based at The University of Auckland. VAREANZ (previously known as “Predict”, then Vascular Informatics using Epidemiology and the Web [VIEW]) was originally approved by the Northern Region Ethics Committee in 2003 (AKY/03/12/314), with subsequent approval by the National Multi-region Ethics Committee in 2007 (MEC07/19/EXP) and with annual re-approval since as part of a vascular research programme (2023 EXP 18564). Governance of the ANZACS-QI registry data is by the ANZACS-QI governance group on behalf of the New Zealand branch of the CSANZ, as described previously.22 The Heart Failure Working Group co-chair is a member of both the CSANZ New Zealand Regional Committee and the ANZACS-QI governance group.

Under the previous ethics approvals, there is no requirement for individual patient consent to enter their data into the ANZACS-QI registry. This is on the basis that any identifiable data are used for quality improvement and that only de-identified data are linked with national datasets for quality improvement and research purposes under VAREANZ governance. Data were entered prospectively by clinician teams involved in patient care, and patient posters and information sheets are displayed in cardiology ward locations where patients are entered into the ANZACS-QI registry.

However, the ANZACS-QI Heart Failure Registry will require retrospective data entry for patients who were admitted in multiple different ward locations. It will therefore not be practical to inform patients in any meaningful way via these posters. Apart from the sampling method of identifying patients for the registry, all processes are identical to those already approved under the existing ethics approvals. An amendment to current VAREANZ ethics approval has been granted for the pilot phase of this proposed registry (2023 AM 13442).

Implementation

ANZACS-QI is a Ministry of Health-funded and National Cardiac Network-supported quality improvement programme. The implementation of the ANZACS-QI Heart Failure Registry will be overseen by a working group formed by members of the Heart Failure Working Group of the New Zealand branch of CSANZ. Processes, including those for reporting, will be aligned with ANZACS-QI governance. The Heart Failure Registry has been introduced as a pilot to the Northern Region in November 2023. Locality approval from individual sites has been obtained for pilot implementation of the registry.

Feedback will be sought from users, and identified issues with the registry will be reviewed and addressed by the governance group. Findings from the pilot study will be made available and published. Our goal will be to implement the registry nationally, with all public hospitals contributing to data collection, and outputs linked to agreed-upon key performance indicators.

Anticipated strengths and limitations

Our proposed heart failure registry will identify a representative sample of total heart failure hospitalisations in New Zealand. This will allow for benchmarking between districts and allow comparisons over time to assess effectiveness of quality improvement strategies. The shortened registry form, focussing on key guideline recommendations, will hopefully facilitate complete and sustainable data collection. The registry utilises the existing ANZACS-QI infrastructure, and data collected will be enriched by linkage to other healthcare datasets. Scheduled reporting of evidence-based indicators will provide regular feedback to users, support clinicians in providing evidence-based heart failure management and provide data to assist with implementation of quality improvement strategies.

There are some limitations to acknowledge with this registry. Firstly, there is the clinician/user time required to complete data entry, and we have minimised the data fields in the registry form and sample size to address this. Feedback from users will be sought from the pilot process, particularly from smaller hospital districts that may have less staff resource to enter a relatively larger sample. Secondly, as the registry form also captures 6 months of post-discharge care, there will be a delay in the reporting of evidence-based indicators. Linkage analyses, particularly for medication dosages, will be further delayed and how this will integrate into quality improvement processes will need to be determined in the pilot phase. Lastly, as the registry is designed to capture a representative sample of all heart failure hospitalisations, assessment of heart failure performance indicators may be inadvertently influenced by inclusion of those with end-stage heart failure or life-limiting comorbidity. Strategies to address these limitations will be developed during the pilot process.

Conclusions

The primary aim of the revised ANZACS-QI Heart Failure Registry is to support evidence-based management of and quality improvement measures for patients who are hospitalised with heart failure in New Zealand. It differs from other ANZACS-QI registries, as a representative age-stratified sample will be identified and entered into the registry retrospectively from coded heart failure hospitalisations. This registry has been implemented as a pilot to the Northern Region.

View Appendix.

Heart failure is a major healthcare problem in New Zealand. The Acute Decompensated Heart Failure (ADHF) Registry was introduced in 2015, and has identified the need for quality improvement strategies to improve care of patients hospitalised with heart failure. In this paper, we describe the implementation of the revised ANZACS-QI Heart Failure Registry, which has a primary aim to support evidence-based management of and quality improvement measures for patients who are hospitalised with heart failure in New Zealand. Taking the learnings from the initial experience with the ADHF Registry, the revised ANZACS-QI Heart Failure Registry i) utilises age-stratified sampling of hospital discharge coding to identify a representative heart failure cohort, ii) utilises existing ANZACS-QI infrastructure for data-linkage to reduce the burden of manual data entry, iii) receives governance from the Heart Failure Working Group, and iv) focusses on established quality improvement indicators for heart failure management.

Authors

Daniel ZL Chan: Department of Cardiology, Health New Zealand – Te Whatu Ora Te Tai Tokerau, Whangārei, New Zealand.

Robert N Doughty: Department of Medicine, The University of Auckland, Auckland, New Zealand; Greenlane Cardiovascular Service, Health New Zealand – Te Whatu Ora Te Toka Tumai Auckland, Auckland, New Zealand.

Mayanna Lund: Department of Cardiology, Health New Zealand – Te Whatu Ora Counties Manukau, Auckland, New Zealand.

Aleisha Easton: Department of Cardiology, Health New Zealand – Te Whatu Ora Counties Manukau, Auckland, New Zealand.

Katrina K Poppe: Department of Medicine, The University of Auckland, Auckland, New Zealand.

Daman Kaur: Department of Cardiology, Health New Zealand – Te Whatu Ora Te Matau a Māui Hawkes Bay, Hastings, New Zealand.

Lia Sinclair: Cardiology Service, Health New Zealand – Te Whatu Ora Te Pae Hauora o Ruahine o Tararua MidCentral, Palmerston North, New Zealand.

Julie Chirnside: Cardio-respiratory Integrated Services, Health New Zealand – Te Whatu Ora Waitaha Canterbury, Christchurch, New Zealand.

Catherine Malone: Cardio-respiratory Integrated Services, Health New Zealand – Te Whatu Ora Waitaha Canterbury, Christchurch, New Zealand.

Helen McGrinder: Greenlane Cardiovascular Service, Health New Zealand – Te Whatu Ora Te Toka Tumai Auckland, Auckland, New Zealand.

Andy McLachlan: Department of Cardiology, Health New Zealand – Te Whatu Ora Counties Manukau, Auckland, New Zealand.

Jo Scott: Cardio-respiratory Integrated Services, Health New Zealand – Te Whatu Ora Waitaha Canterbury, Christchurch, New Zealand.

Jennifer Roberts: Cardiology Outpatients, Health New Zealand – Te Whatu Ora Capital, Coast and Hutt Valley, Wellington, New Zealand; Te Kura Tapuhi Hauora, Te Herenga Waka – Victoria University of Wellington, Wellington, New Zealand.

Cara Wasywich: Greenlane Cardiovascular Service, Health New Zealand – Te Whatu Ora Te Toka Tumai Auckland, Auckland, New Zealand.

Gerry Devlin: Gisborne Hospital, Health New Zealand – Te Whatu Ora Tairāwhiti, Gisborne, New Zealand.

Matire Harwood: Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.

Sue Wells: Department of General Practice and Primary Healthcare, The University of Auckland, Auckland, New Zealand.

Wil Harrison: Department of Cardiology, Health New Zealand – Te Whatu Ora Counties Manukau, Auckland, New Zealand.

Andrew J Kerr: Department of Medicine, The University of Auckland, Auckland, New Zealand; Department of Cardiology, Health New Zealand – Te Whatu Ora Counties Manukau, Auckland, New Zealand.

Acknowledgements

Programme implementation is coordinated by the National Institute for Health Innovation at The University of Auckland. Access to the New Zealand National Administrative Health datasets is overseen by The University of Auckland Vascular Risk Equity for Aotearoa New Zealand programme. We acknowledge all New Zealand cardiologists, physicians, nursing staff and radiographers who have supported and contributed to ANZACS-QI and the ADHF Registry. We also acknowledge the ANZACS-QI governance group and the Cardiac Society of Australia and New Zealand’s New Zealand Regional Committee for their ongoing support for a heart failure registry. We thank Mildred Ai Wei Lee, Rosie Whittington and Robert Ross for their assistance with data access and analysis.

Correspondence

Daniel ZL Chan: Department of Cardiology, Private Bag 9742, Whangārei 0148, New Zealand. Ph: +64-09-430-4100.

Correspondence email

Daniel.Chan@northlanddhb.org.nz

Competing interests

DZC is supported by the A H Couch Trust. RND is the holder of the Heart Foundation Chair of Heart Health. KKP is supported in part by a Heart Foundation Heart Health Research Trust fellowship. MH is supported by the New Zealand Heart Foundation and Healthier Lives (National Science Challenge).

1)       Ministry of Health – Manatū Hauora. Annual Data Explorer 2019/20: New Zealand Health Survey [Internet.] 2020 [cited 2020 Nov].

2)       Chan DZL, Kerr A, Grey C, et al. Contrasting trends in heart failure incidence in younger and older New Zealanders, 2006-2018. Heart. 2022;108:300-306. https://doi.org/10.1136/heartjnl-2021-319853.

3)       Selak V, Poppe K, Chan D, et al. Identification of clinically relevant cohorts of people with heart failure from electronic health data in Aotearoa: potential, pitfalls and a plan. N Z Med J. 2022;135(1563):96-104.

4)       Chan DZL, Grey C, Doughty RN, et al. Widening ethnic inequities in heart failure incidence in New Zealand. Heart. 2024;110:281-289. https://doi.org/10.1136/heartjnl-2023-322795.

5)       Carr J, Robson B, Reid P, et al. Heart failure: ethnic disparities in morbidity and mortality in New Zealand. N Z Med J. 2002;115(1146):15-7.

6)       Atherton JJ, Sindone A, De Pasquale CG, et al. National Heart Foundation of Australia and Cardiac Society of Australia and New Zealand: Guidelines for the Prevention, Detection, and Management of Heart Failure in Australia 2018. Heart Lung Circ. 2018;27(10):1123-208. doi: 10.1016/j.hlc.2018.06.1042.

7)       McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42(36):3599-726. doi: 10.1093/eurheartj/ehab368.

8)       Yusuf S, Pitt B, Davis CE, et al. Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med. 1991;325(5):293-302. doi: 10.1056/NEJM199108013250501. 

9)       Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced left-ventricular systolic function intolerant to angiotensin-converting-enzyme inhibitors: the CHARM-Alternative trial. Lancet. 2003;362(9386):772-6. doi: 10.1016/S0140-6736(03)14284-5.

10)    McMurray JJ, Packer M, Desai AS, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med. 2014;371(11):993-1004. doi: 10.1056/NEJMoa1409077.

11)    MERIT-HF Study Group. Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet. 1999;353(9169):2001-7.

12)    Pitt B, Zannad F, Remme WJ, et al. The effect of spironolactone on morbidity and mortality in patients with severe heart failure. Randomized Aldactone Evaluation Study Investigators. N Engl J Med. 1999;341(10):709-17. doi: 10.1056/NEJM199909023411001.

13)    Packer M, Anker SD, Butler J, et al. Cardiovascular and Renal Outcomes with Empagliflozin in Heart Failure. N Engl J Med. 2020;383(15):1413-24. doi: 10.1056/NEJMoa2022190. 

14)    Bardy GH, Lee KL, Mark DB, et al. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med. 2005;352(3):225-37. doi: 10.1056/NEJMoa043399. 

15)    Cleland JG, Daubert JC, Erdmann E, et al. The effect of cardiac resynchronization on morbidity and mortality in heart failure. N Engl J Med. 2005;352(15):1539-49. doi: 10.1056/NEJMoa050496.

16)    Anker SD, Butler J, Filippatos G, et al. Empagliflozin in Heart Failure with a Preserved Ejection Fraction. N Engl J Med. 2021;385(16):1451-61. doi: 10.1056/NEJMoa2107038.

17)    Kittleson MM, Panjrath GS, Amancherla K, et al. 2023 ACC Expert Consensus Decision Pathway on Management of Heart Failure With Preserved Ejection Fraction: A Report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2023;81(18):1835-78. doi: 10.1016/j.jacc.2023.03.393. 

18)    Tromp J, Ouwerkerk W, Teng TK, et al. Global disparities in prescription of guideline-recommended drugs for heart failure with reduced ejection fraction. Eur Heart J. 2022;43(23):2224-2234. doi: 10.1093/eurheartj/ehac103.

19)    Chan D, Doughty RN, Lund M, et al. Target Doses of Secondary Prevention Medications Are Not Being Achieved in Patients with Reduced LV Systolic Function After Acute Coronary Syndrome in New Zealand: An ANZACS-QI Study. Heart Lung Circ. 2020;29(9):P1386-1396. https://doi.org/10.1016/j.hlc.2020.03.013.

20)    Lund M, McGrinder H, van Arragon M, Kerr A. Acute Decompensated Heart Failure: Identifying Gaps to Bridge. Heart Lung Circ. 2017;26(S1):S7-S8. https://doi.org/10.1016/j.hlc.2017.05.020.

21)    Selak V, Poppe K, Grey C, et al. Ethnic differences in cardiovascular risk profiles among 475,241 adults in primary care in Aotearoa, New Zealand. N Z Med J. 2020;133(1521):14-27.

22)    Kerr A, Williams MJ, White H, et al. The All New Zealand Acute Coronary Syndrome Quality Improvement Programme: Implementation, Methodology and Cohorts (ANZACS-QI 9). N Z Med J. 2016;129(1439):23-36.

23)    Heidenreich PA, Fonarow GC, Breathett K, et al. 2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. Circ Cardiovasc Qual Outcomes. 2020;13(11):e000099. https://doi.org/10.1161/HCQ.0000000000000099.

24)    Aktaa S, Polovina M, Rosano G, et al. European Society of Cardiology quality indicators for the care and outcomes of adults with heart failure. Developed by the Working Group for Heart Failure Quality Indicators in collaboration with the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail. 2022;24(1):132-42. doi: 10.1002/ejhf.2371.

25)    Ministry of Health – Manatū Hauora. National Minimum Dataset (Hospital Events) Data Dictionary. Version 7.9.2. [Internet]. Wellington, New Zealand: Ministry of Health; 2020 [cited 2020 Nov]. Available from: https://www.tewhatuora.govt.nz/assets/Our-health-system/Data-and-statistics/NZ-health-stats/Data-references/Data-dictionaries/National-Minimum-Dataset-Hospital-Events-data-dictionary/nmds_data_dictionary_v7.9.2_1.pdf

26)    Chan D, Poppe K, Lund M, et al. Validation of Heart Failure Discharge Coding Utilising the PEOPLE Study and ADHF Registry. Heart Lung Circ. 2021;30(s2):S75. https://doi.org/10.1016/j.hlc.2021.05.041.

27)   Chan DZL, Kerr AJ, Tavleeva T, et al. Validation Study of Cardiovascular International Statistical Classification of Diseases and Related Health Problems, Tenth Edition, Australian Modification (ICD-10-AM) Codes in Administrative Healthcare Databases (ANZACS-QI 77). Heart Lung Circ. 2024; pre-print. https://doi.org/10.1016/j.hlc.2024.03.015.