Care models must consider patient factors to ensure safe and effective use of patient-administered anticoagulants

In Australia, atrial fibrillation (AF) affects 1%–2% of the population, placing them at a fivefold increased risk of stroke.1 The prevalence of AF increases sharply with age, with 50% of patients aged 75 years or over.2 Warfarin has been used clinically for more than 70 years and is the mainstay anticoagulant for prophylaxis of stroke as well as for the management of AF. However, in recent years, the novel oral anticoagulants (NOACs) dabigatran, rivaroxaban and apixaban have been developed. These promise more efficacy than warfarin in stroke prevention, while being safer and easier to use.3

A recent review by the Australian Government Department of Health and Ageing provided perspectives on current and future options for improving the use of anticoagulation therapies in managing patients with AF.2 In this article, we focus on strategies to improve anticoagulation management in patients with AF in light of the increasing utility of NOACs.

Warfarin in clinical practice

Despite the availability of oral alternative therapies, warfarin — a vitamin K antagonist — remains efficacious and cost-effective in reducing the incidence of stroke in patients with AF.4 However, warfarin has a narrow therapeutic window, resulting in an unpredictable anticoagulant effect that necessitates frequent monitoring and dosage adjustment.4 Further, warfarin is associated with the clinical trade-off between the risk of ischaemic stroke and an increased risk of bleeding, particularly intracranial haemorrhage. As a consequence, a range of risk factors that can influence warfarin stability have been identified and are well known in clinical practice.5,6 These complexities have resulted in underuse of warfarin, particularly among older people, where the risk of cerebrovascular and cardiovascular events is highest.7

Although warfarin has been used clinically for many decades, there is an ongoing need to improve the monitoring and management of patients who receive it. Optimisation of time in the therapeutic range (TTR) is the key to improving patient outcomes. This requires identification of factors that can influence TTR and the incorporation of management strategies.2 Although multiple comorbidities and concomitant medications are regularly cited as reasons for poor TTR, other relevant patient factors, such as cognitive impairment and inadequate health literacy, should be considered, as these have been shown to influence anticoagulation control.8

Clinical trials of the new anticoagulants

Dabigatran, a thrombin inhibitor, and rivaroxaban and apixaban, both factor Xa inhibitors, are the first oral alternatives to warfarin to be made available for the prevention of stroke and systemic embolism in patients with non-valvular AF. All three NOACs have demonstrated effectiveness in multinational randomised clinical trials although, to date, no studies have directly compared them. Pivotal trials for dabigatran (RE-LY),9 rivaroxaban (ROCKET AF)10,11 and apixaban (ARISTOTLE)12 recruited patients from 40 different countries, with the aim of evaluating their respective efficacy for the prevention of stroke and the risk of haemorrhage compared with warfarin (Box). The results look promising, with all three NOACs demonstrating non-inferiority to warfarin for stroke and systemic embolism prevention.9–12 However, their most consistent clinical benefit is that they are superior to warfarin when it comes to the rate of intracerebral haemorrhage and haemorrhagic stroke.10,12 Further, they have the notable practical advantages of involving fixed dosages and not requiring international normalised ratio monitoring.3

Although these results show clear benefits, there are some significant differences between the trials, including different definitions at end points such as major bleeding, differences in follow-up periods, and different distribution of patients in various countries, making direct comparison difficult.13,14 Most notably, consideration must be given to the quality of warfarin management and stability in the control arms, as this varies markedly and is also at variance with that seen in clinical practice. The mean TTRs for patients taking warfarin in the three NOAC trials9–11 were 64%, 55% and 62%, respectively. These proportions are significantly lower than that found in the Australian population, which has been reported to be about 70% and above.2,15 Across these studies, when TTR was in the higher quartile, patients had an overall better level of health management. This has implications for the generalisability of these findings to an Australian population and, consequently, to the cost-effectiveness in an Australian setting.2

Challenges for chronic AF anticoagulation management in the community

Whatever the choice of anticoagulant, it is imperative that patient-related factors are considered in the selection and management of chronic AF therapies that are primarily self-administered in the community. This is particularly relevant when considering translation from clinical trial settings into the wider clinical practice environment. It is known that clinical use will be different from that within the controlled clinical trial setting. Recently published data on local experience in the use of dabigatran has shown this to be the case.16 Compared with the participants in the RE-LY trial,9 the Australian cohort had older participants, fewer patients with significant renal impairment, and a higher TTR of 70%. These differences will play a role in the real world, outside of the control of the clinical trial arena.

The challenges faced by Australian health care providers are that many patients with AF are older, with multiple comorbidities and on a range of other chronic therapies, and are self-managing their anticoagulation in the community.17 Selection of the appropriate therapy requires not only consideration of specific aspects of the individual drug but, even more importantly, the services and supports for the ongoing management and care after treatment initiation.

In the case of chronic disease management in older patients, approaches to improving anticoagulation must not only focus on medication initiation but also on the patients and the changes that inevitably occur in their ability to self-manage.17,18 A wide range of recommendations from the Department of Health and Ageing review aims to improve health outcomes and remove barriers to the use of warfarin by improving the quality of use.2 We believe that these recommendations should be progressed. A number of them specifically relate to strategies to improve chronic anticoagulation management, including (i) a requirement for national guidelines that are disseminated and implemented; (ii) guidelines for patient management; (iii) availability and coordination of community-based anticoagulation support services for patients for whom therapy is initiated in the community; (iv) optimisation of TTR; and (v) a nationally endorsed shared care model for warfarin monitoring and management.2

We support these recommendations and believe that increased emphasis should be given to improvements in strategies focusing specifically on patient-related factors that influence the management of oral anticoagulation when self-administered in the community. In addition to demographic and clinical risk factors, we identified the following specific patient factors as independent risk factors for instability of anticoagulation and bleeding risk in response to warfarin: cognitive impairment, social isolation, depressed mood, inadequate health literacy, and functional dependence.8 There was a 3.4-fold increased risk of bleeding when multiple psychosocial factors were present.8 Strategies to improve chronic AF anticoagulation management in the community must take patient factors into account, not only at the drug selection and initiation of treatment stage but also through ongoing assessment as the patient’s age increases.19 Cognitive decline has been linked to ageing. Patients with progressive cognitive impairment, and who remain responsible for their own medication management, may have increasing difficulty routinely administering and monitoring any of their medications, not just warfarin. Including patient factors in national guidelines and shared care models is fundamental to improving anticoagulation in AF through regular patient assessment.

Conclusion

Patient factors must be taken into account not only at the point of drug selection but as a routine component of care. These factors include poor cognition, depressed mood, functional dependence, social isolation and inadequate health literacy. Improved models of care are required to monitor and manage patient factors to ensure safe and efficacious anticoagulation, irrespective of the specific drug involved. Translation of clinical trial findings into the broader clinical environment must also include consideration of all the factors that influence patient variability.

Further, improved stroke prevention and AF management are required and include medication innovation as well as innovation in models of patient care. Irrespective of whether warfarin or a NOAC is chosen, the challenges for improving management and monitoring in potentially complex patient cohorts remain.

Despite well developed guidelines for managing acute coronary syndrome (ACS),1-6 local registries in Australia and New Zealand have demonstrated incomplete implementation of evidence-based recommendations,7-10 with variations in care appearing to correlate with differences in clinical outcomes. Geographical challenges, patient characteristics (including cultural diversity), health workforce and the health policy environment are likely factors affecting the optimal translation of this evidence base into timely, effective and risk-appropriate ACS care.11,12

Audits of hospitalisation for ACS in New Zealand have been crucial in defining treatment and resource gaps in practice.9,13 In Australia, registries have included relatively few patients from regional and remote centres.7 However, health service design and workforce provision have been found to be associated with variations in clinical outcomes in Australia.14 Hence, gaining a binational perspective from multiple health services of current ACS management is an essential step in health services redesign. The SNAPSHOT ACS study sought to inform these efforts by documenting care and outcomes among patients with suspected ACS through a comprehensive audit encompassing all hospitals and jurisdictions in Australia and New Zealand.

Methods

Study design and organisation

The SNAPSHOT ACS study was a prospective audit of the care provided to consecutive patients admitted with suspected ACS during a 2-week period in Australia and New Zealand. The study was designed by a binational academic network of clinicians and researchers, and managed by a steering committee with key stakeholder representation. It was developed as a collaborative quality improvement initiative between the Cardiac Society of Australia and New Zealand, the Heart Foundation of Australia, the Australian Commission on Safety and Quality in Health Care, the George Institute for Global Health, and health networks or state governments in New South Wales, Queensland, Victoria, South Australia and Western Australia (Appendix 1). The national organisations provided endorsement, in-kind resources and seed funding for central study management. State governments and health networks provided study coordinators to engage facilities, educate staff and assist with gaining ethics committee approval and data collection. The George Institute built the online database and coordinated data management.

All hospitals (public or private, metropolitan or rural) receiving patients with suspected ACS were identified through public records and health networks and approached about participating. Although sites were given training and support with data entry, each hospital’s participation was discretionary and resourced locally. Written study protocols were provided to all participating sites, and state-based education forums were held to standardise recruitment and data collection. Results were fed back to each site, benchmarked against the relevant state or territory and national aggregate at the end of the audit.

In Australia, ethics approval for opt-out consent was granted in all but two sites in Victoria, where opt-in consent was implemented. In New Zealand, expedited review by the National Multicentre Ethics Committee concluded that this was an audit of health service delivery, and a consent waiver was applied. In Australia, a consent waiver was applied to all inhospital deaths among patients with suspected ACS.

Patient eligibility and classification

Patients were eligible for inclusion if they were admitted for suspected or confirmed ACS between 14 and 27 May 2012 (inclusive). Consecutive first admissions within the audit window were included. Patients were tracked for the duration of the acute care episode, including all transfers between hospitals.

Patients were classified by primary discharge diagnosis into the following groups:

• ST-segment-elevation myocardial infarction/left bundle branch block (STEMI/LBBB): patients with ST-segment elevation or LBBB on an electrocardiogram (ECG) at any time during the admission, with elevation of cardiac biomarkers (except where the patient died before biomarkers were measured).
• Non-STEMI (NSTEMI): patients with evidence of biomarker elevation, with or without ECG changes consistent with ischaemia.
• Unstable angina: recorded separately but combined with “likely ischaemic chest pain” for analysis.
• Likely ischaemic chest pain: patients for whom the diagnosis remained uncertain in the absence of definitive ECG changes and/or biomarker elevation, but who received inhospital coronary revascularisation with either percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).
• Unlikely ischaemic chest pain: extracted from the medical record, reflecting local clinician determination.
• Other diagnosis: patients for whom a clear alternative primary diagnosis emerged, or where evidence of myonecrosis was considered secondary to another disease process (eg, pulmonary embolus).

Patient risk, inhospital care and events

Using a common case-record form with standardised completion note, data collection focused on patients’ presenting characteristics, including clinical variables enabling calculation of the Global Registry of Acute Coronary Events (GRACE) risk score, as well as logistical details of patient presentation and transfers between hospitals.15 Care provided across all institutions involved in acute care was documented, focusing on therapies recommended by published guidelines and inhospital events. Each participating hospital was also asked to complete a survey describing local resources, including cardiac investigation and management capabilities and workforce characteristics.

Inhospital events were defined as shown in Box 1. Reporting of clinical events relied on local documentation using the standardised completion note. Formal adjudication of events was not possible, but monitoring of 2%–5% of all case-record forms for data accuracy and quality was performed during and in the weeks after enrolment by coordinators across all jurisdictions.

Statistical analysis

Patient demographic and clinical characteristics, and rates of interhospital transfer, investigations, invasive procedures, provision of guideline-recommended therapies to patients surviving to hospital discharge, and inhospital events are presented as standard descriptive statistics stratified by discharge diagnosis, Australian Institute of Health and Welfare hospital classification, and health jurisdiction (Australian states or territories and New Zealand).4,5 Due to small sample sizes, the two tiers of medium regional hospital classification were combined, as were the other smaller hospital classifications. Private hospitals were considered as a separate group. These criteria were also applied to New Zealand hospitals. For stratification by jurisdiction, the Australian Capital Territory was combined with NSW, and Tasmania with the Northern Territory.

Dichotomous variables are reported as numbers and percentages and compared using the χ2 test. Continuous variables are reported as medians and interquartile ranges (IQRs) and compared using the Kruskal–Wallis test.

Propensity score-adjusted estimates of the influence of hospital classification and health jurisdiction on provision of angiography, provision of four or five guideline-recommended medications at discharge, referral to cardiac rehabilitation, and major adverse cardiac events (MACE) were generated using logistic regression modelling, stratified by discharge diagnosis. Assessment of angiography and MACE used all patients, while evaluation of rehabilitation referral and discharge medications was confined to patients with a discharge diagnosis of ACS. Propensity scores using age, sex, GRACE score, diagnostic group, heart failure at presentation, renal impairment, diabetes, hypertension, nursing home residence, dementia or cognitive impairment, private insurance, and primary language other than English were constructed for the likelihood of living in each jurisdiction and presenting to a hospital of each classification. Each model included the hospital classifications and jurisdictions as indicator variables, as well as their respective propensity scores, when reporting the jurisdiction or hospital estimates. Interaction terms of each jurisdiction and hospital classification were explored for significance, but no interactions were found. Given the observational and hypothesis-generating nature of these analyses, no adjustment of significance levels was undertaken.

Analyses were performed using Stata 11.2 (StataCorp), and P < 0.05 was considered statistically significant.

Results

Participating hospitals

Of 525 hospitals approached to participate, 478 gained ethics approval, and 435 provided site survey data describing their local resources. Within the 2-week enrolment period, 286 hospitals enrolled 4398 patients with suspected or confirmed ACS. Hospitals not enrolling patients were smaller centres and did not treat patients with suspected ACS during the audit window.

Most patients (65.7%; 2891/4398) presented to principal referral hospitals or hospitals in major cities (7.7%; 337/4398), while 7.3% (319/4398) presented to private hospitals. In terms of cardiac services available at the first presenting hospital, 79.7% of patients (3415/4283) presented where fibrinolysis could be administered, and 59.0% (2528/4283) presented to hospitals capable of providing primary PCI. Only 1.4% of patients (59/4283) presented to hospitals with no reperfusion therapy for STEMI. A quarter of patients (25.9%; 1138/4398) required transfer to at least one other hospital.

The distribution of hospital types by jurisdiction was comparable, except for Victoria, where a selective hospital recruitment strategy operated and there were fewer small regional hospitals (Box 2). Patient characteristics by health jurisdiction and hospital classification are presented in Appendix 2 and Appendix 3, respectively.

Patients with ACS

The risk profile of enrolled patients was high, with a median GRACE risk score of 119 (IQR, 96–144) across the entire population, and 138 (IQR, 114–161) among those with a discharge diagnosis of myocardial infarction (MI), including STEMI and NSTEMI.

Of the 4398 patients, 252 (5.7%) were Indigenous, Pacific Islander or Maori, and 165 (3.8%) were Asian. A primary language other than English was spoken by 294 patients (6.7%). Patient characteristics by discharge diagnosis are shown in Box 3. Among the 837 patients who were discharged with a diagnosis other than ACS, 317 (37.9%) had a troponin level above the local upper reference limit.

Provision of ACS care

Among the 421 patients with a discharge diagnosis of STEMI/LBBB, 106 (25.2%) received fibrinolytic therapy, 163 (38.7%) received primary PCI, and 152 (36.1%) received no reperfusion therapy. Of 1436 patients with STEMI or NSTEMI, coronary angiography was performed in 1019 (71.0%), PCI in 610 (42.5%), and CABG in 116 (8.1%). Reduced provision of invasive management with increasing risk was evident (GRACE score < 100, 90.1% v 101–150, 81.3% v 151–200, 49.4% v > 200, 36.1%; P < 0.001).

Guideline-recommended investigations and therapies were provided less frequently to patients presenting to non-principal referral hospitals, regardless of patient transfers (Box 4). Similar heterogeneity in the provision of care was observed when the results were stratified by jurisdiction (Appendix 4). Variation in the timeliness of care was also evident across jurisdictions; this was most marked in the median time to angiography and, to a lesser extent, in the overall length of stay (Appendix 5).

Inhospital events

Among the patients diagnosed with MI, the inhospital mortality rate was 4.5% (65/1436) and recurrent MI rate was 5.1% (73/1436). Inhospital adverse clinical events were highest among patients with STEMI/LBBB (Box 5). Inhospital mortality and recurrent cardiac failure were frequent among patients discharged with a diagnosis thought not to be ACS. Box 6 shows substantial heterogeneity in clinical events between hospital classifications, in all patients and in those discharged with a diagnosis of ACS.

Adjusted analyses

The propensity-adjusted odds ratios and confidence intervals describing the likelihood of undergoing inpatient angiography, receiving four or five guideline-recommended medications at discharge, receiving referral to rehabilitation, and experiencing inhospital MACE are shown in Box 7. There was a consistently lower likelihood of receiving guideline-recommended medications among patients originally presenting to non-principal referral hospitals. Patients in private hospitals were significantly more likely to undergo angiography, but not necessarily to receive guideline-recommended medications or rehabilitation referral. There was more variation in the occurrence of inhospital MACE at the health jurisdiction level than between hospital types.

Discussion

Optimising patient outcomes after MI through standardisation of care has emerged as a major near-term goal in the health agenda of Australia and New Zealand.17 Through the most representative assessment of ACS health service resources, clinical care provision and outcomes yet conducted in Australasia, this study provides unique insights into the challenges of providing timely and effective ACS care. These include the complexity of patient comorbidities, which brings the logistical challenges of providing timely invasive management to many patients in regional, remote and outer metropolitan centres into sharp focus.11,12

Translating evidence into practice requires a sophisticated understanding of determinants of care provision at the patient, clinical service and health policy level. Variations in clinical decision making, service availability and health policy represent potential targets for improving translation of the ACS evidence base and outcomes. An integrated approach to health service design is paramount to meeting the needs of our culturally diverse and geographically dispersed communities.

The efficient management of patients presenting with suspected ACS remains challenging. More sensitive markers of myonecrosis, such as high-sensitivity troponin assays, have not simplified this.18 This is demonstrated in our study by the substantial proportion of patients with suspected ACS who had elevated troponin levels, but in whom further investigations confirmed a final diagnosis other than ACS.19,20 Nevertheless, our data demonstrate high rates of inhospital events among such patients, as has been observed by others;21,22 yet the current evidence informing their management is very limited.

Similarly, our data demonstrate the substantial burden of clinical complexity among ACS patients, with relatively high prevalences of comorbidities including prior major bleeding events, cerebrovascular disease, cognitive impairment and concurrent malignancy.23 This complexity underscores the everyday challenges in applying the evidence among patients with typical ACS presentations. Reduced application of evidence-based therapies among patients with increased comorbidities has been found in other studies.24,25 Objective risk stratification that balances the benefits of evidence-based therapies against the risks associated with comorbidities may help narrow the evidence–practice gap for ACS patients with comorbidities.26

Our study highlights the potential for variation in care attributable to jurisdictional and geographical differences. The challenge of providing timely access to invasive management, not only in rural areas but also in the growing outer suburbs of cities, is highlighted by the fact that 26% of all ACS patients in our study required transfer. Attempts to improve consistency and quality of care, such as through clinical guidelines and clinical standards,17 need to consider the significant issues of transfer and coordination of care, particularly outside metropolitan areas, if such initiatives are to be effective and cost-effective.

In combination, these observations call for judicious and validated approaches to the development and implementation of clinical standards and performance measures that take these diagnostic and therapeutic complexities into account.

The broad hospital recruitment approach, consecutive patient enrolment, and high inhospital event rates in our study underscore the importance of representative patient inclusion when evaluating practice and outcomes.27 For the effective integration of clinical guidelines, clinical standards and performance measures into everyday care, the real challenge is to develop mechanisms to acquire and feed back such data on a routine and sustainable basis.28 The SNAPSHOT ACS study was the culmination of significant efforts to engage with national agencies and professional bodies, while implementation depended on the jurisdictional health networks. However, the study also required local hospital commitment to data collection and entry, an enormous unresourced effort that is difficult to quantify but attests to the dedication of health care providers to the quality of ACS care and outcomes. Future attempts to understand the lingering evidence–practice gaps will need to consider such resourcing issues carefully. Nevertheless, this study is unique in its ability to gain insights into the provision of care across multiple levels of decision making. Effectively delivering these insights to key decisionmakers at clinical, health service and health policy levels to enable the design and implementation of fully integrated approaches to ACS care remains the “translational” promise of this initiative.

4 Provision of (A) investigations and revascularisation and (B) guideline-recommended therapies, among patients with a discharge diagnosis of acute coronary syndrome, by enrolling hospital classification*

PCI = percutaneous coronary intervention. CABG = coronary artery grafting. * n refers to number of patients.

5 Inhospital clinical events, by principal diagnosis at time of discharge*

MI = myocardial infarction. CHF = congestive heart failure. MACE = major adverse cardiac events. STEMI/LBBB = ST-segment elevation myocardial infarction/left bundle branch block. NSTEMI = non-STEMI. * All comparisons of outcomes between diagnostic categories are significant (P < 0.001). n refers to number of patients.

6 Inhospital clinical events among (A) all patients and (B) patients with a discharge diagnosis of acute coronary syndrome, by enrolling hospital classification

MI = myocardial infarction. CHF = congestive heart failure. MACE = major adverse cardiac events. * n refers to number of patients.

7 Adjusted odds ratios* for likelihood of (A) provision of angiography, (B) provision of four or five guideline-recommended medications at discharge, (C) referral to cardiac rehabilitation, and (D) inhospital major adverse cardiac events, by hospital classification and health jurisdiction

* Principal referral hospitals and State D are the referent categories for hospital classification and health jurisdiction, respectively. Bars indicate 95% confidence intervals, which have been produced using the floating absolute risk method.16