Priorities for improved management of acute rheumatic fever and rheumatic heart disease: analysis of cross-sectional continuous quality improvement data in Aboriginal primary healthcare centres in Australia

Rheumatic heart disease (RHD) manifests as permanent damage to heart valves resulting from repeated episodes of acute rheumatic fever (ARF), an autoimmune reaction to a Group A streptococcus (StrepA) infection.¹ The incidence of ARF in some Aboriginal communities is among the highest documented globally.^2,3 RHD can lead to heart failure, may require open-heart surgery for valve repair or replacement and often results in premature mortality. Therefore, guideline-adherent prevention and management are critically important.

There has been increased availability of ARF and RHD guidelines for Australian healthcare providers, including quick reference⁴ and comprehensive online versions (https://www.rhdaustralia.org.au/arf-rhd-guideline, accessed 3 October 2019). Other guideline-related resources associated with rural practice,⁵ antibiotic prescription⁶ and rheumatology⁷ all align with these ARF and RHD guidelines. However, knowledge about, and where to seek information on, ARF and RHD remains low among healthcare providers. Consequently, adherence to guidelines may be suboptimal, with patients missing out on much-needed care.⁸ In particular, inadequate delivery of secondary prophylaxis with regular penicillin injections (long-acting benzathine benzylpenicillin G (BPG) once every 28 days) to prevent recurrences of ARF on re-exposure to StrepA infections, can mean that ARF recurrences occur, often progressing to RHD.

Continuous quality improvement (CQI) is a proven strategy to improve guideline adherence, using audit cycles and proactive engagement of primary healthcare (PHC) end users with their own data. For example, where a predetermined target proportion of prescribed penicillin injections is not met, the PHC service can introduce activities to improve the delivery of injections. Although this is challenging in remote Aboriginal community settings,⁹ partly due to high staff turnover¹⁰ and other factors, such as inadequate community engagement,¹¹ some successes with CQI have been seen in ARF and RHD care,¹² as well as in other chronic conditions.^13,14

Australian PHC services are subsidised through Australia’s universal health insurance scheme, Medicare. Aboriginal Medical Services receive additional resources for supplementary services for Aboriginal people to address additional cultural and logistical needs. Some of these more-comprehensive services are run by community-elected boards (community controlled¹⁵), whereas others are part of government services.

The Audit and Best Practice for Chronic Disease (ABCD) project uses participatory action research methods to develop CQI audit tools and processes for use in Aboriginal PHC services to strengthen local delivery systems and improve health outcomes.¹⁶ The CQI tools are based on internationally accepted PHC models and locally developed clinical guidelines for the prevention and management of a range of conditions. Health centre participation in ABCD CQI activities is voluntary and based on local service priorities. Most health centres using ABCD CQI tools volunteered their deidentified data for analysis to the ABCD National Research Partnership (NRP) Project. An ABCD clinical audit tool was developed for capturing quality of care (QOC) indicators for ARF and RHD from participating PHC sites.¹⁷ The availability of such CQI data provides the opportunity to obtain a rare snapshot of how well ARF and RHD are managed in PHC.

This study investigated the delivery of services scheduled in current guidelines for the management of ARF and RHD in Australian PHC centres that participated in the ABCD NRP. Specific objectives were to describe the demographic and clinical profile of ARF and RHD patients whose clinic records were audited, determine the variation in quality of ARF and RHD care across age groups according to key indicators and identify health centre and individual patient factors that affect the quality of ARF and RHD care in participating centres.

The present cross-sectional observational study used ARF and RHD clinical audit data from 63 PHC centres in the Northern Territory (NT), Queensland (Qld), South Australia (SA) and Western Australia (WA) participating in the ABCD NRP Project.

The ABCD ARF/RHD audit tool¹⁷ was developed in consultation with disease experts and Aboriginal and Torres Strait Islander PHC centres with the aim of evaluating the quality of PHC services for RHD.¹⁷ The tool allows assessment of actual practice against best practice standards based on treatment guidelines.⁴

ABCD clinical audits were undertaken between 2009 and 2014 by health centre staff trained in the audit tools and supported by quality improvement facilitators. Between one and six audits (mean 3.3) were completed per health centre.

All patients living in the community for at least 6 of the previous 12 months with a suspected or definite diagnosis of ARF or a diagnosis of RHD were eligible for inclusion. Inactive patients (history of ARF, no RHD and secondary prophylaxis ceased) were excluded. Where the eligible service population was ≤30, all records were included. If the eligible population was >30, a randomly selected sample of patient records was audited, following guidance from the ABCD protocol.¹⁶

The most recent audit of ARF/RHD clinical service delivery conducted by each of the 63 PHC centres between 2009 and 2014 was analysed. Demographic variables collected included age, sex and ethnicity. Variables audited included: diagnoses (ARF, RHD, both), severity classification (Priority 1–4, corresponding to different levels of risk for RHD complications including death), the presence of a current and complete ARF or RHD management plan, penicillin prescription (or not), adherence to dosing regimen if prescribed penicillin, whether the patient received regular doctor and specialist review, alcohol and tobacco use, whether provision of education about ARF and RHD was documented and whether brief interventions regarding cardiovascular risk factors, including smoking, high-level alcohol intake, nutrition and physical activity, were documented.

The main outcome measure was an overall quality of ARF and RHD care composite indicator consisting of up to nine best-practice service items within the audit tool. Not all patients required all nine items (e.g. 50-year-old patients with RHD may no longer require penicillin). The composite indicator comprised documentation of disease classification within the health summary, a current and complete ARF or RHD management plan, planned frequency of penicillin injections, ≥80% of planned penicillin injections received, active recall (if <80% of injections were received), guideline-compliant timing and nature of medical reviews, echocardiogram and client and/or family education on ARF. A service was recorded as delivered if there was a clear record of delivery within the recommended time frames.

Profiles of patients, types of services and QOC indicators were analysed using means, medians and proportions. Scores for the nine QOC indicators were calculated from the most recent audit occasion, representing the percentage of individuals receiving the respective service item. These scores were summarised by age group (<15, 15–24, 25–50, >50 years) and exact 95% binomial confidence intervals (CIs) reported. The overall QOC index was derived for each individual by dividing the number of service targets met by the number of targets for which the individual was eligible. Generalised linear mixed-effects logistic regression was used to analyse the determinants for each QOC indicator considering the following covariates: sex, age group, ARF and RHD status, remoteness of the clinic, number of years CQI cycles had been done and number of cycles. In addition to calculating the odds ratios (ORs) for the fixed effects, the model takes into account the clinic random effect due to the clustering of cases within a clinic. Statistical analysis was performed using R software version 3.6.0 (R Foundation for Statistical Computing, Vienna, Austria).

Ethics approval for the study was granted by the human research ethics committees in all jurisdictions with participating health services,¹⁶ including the NT, New South Wales and Qld, the SA Aboriginal Health Research Ethics Committee, Curtin University, University of Western Australia, WA Country Health Services and the WA Aboriginal Health Information and Ethics Committee.

Clinical records of 1081 patients with ARF or RHD aged 2–81 years were audited. Almost all (97%) participating health centres were located in the NT or Qld, and 94% were in regional or remote areas (Table 1). The majority (88%) of the most recent audits were conducted between 2012 and 2014.

Table 1.  Demographic and health characteristics of clients included in the most recent audit cycle
Data are given as the number of people for whom records were audited, using the most recent audit per person (n), with percentages in parentheses. ARF, acute rheumatic fever; RHD, rheumatic heart disease

Aboriginal and Torres Strait Islander people comprised 96% of eligible patients. Patients aged <25 years comprised 48.9% of the cohort, with 40.5% aged 24–49 years. Sixty-one per cent of audited patients were female, with the proportion of females increasing from 51% in the youngest age group to 67% in the oldest age group (Table 1). There were relatively more patients in the 0–14 year age group in regional areas, and relatively more patients in the ≥50 year age group in urban areas. A diagnosis of ARF only was recorded in 8% of patients; 36% had RHD only and 56% had both ARF and RHD. Over two-thirds of patients aged <25 years had both ARF and RHD recorded, with the percentage of RHD-only patients increasing with age.

Severity classification was recorded in 29.9% of patients; 138 patients (12.7%) were recorded as medium (n = 88) or high (n = 50) priority. High-risk status (Priority 1) increased (from 0.9% to 7.0%) and low-risk status (Priority 3) decreased (from 25.0% to 8.8%) with age as a percentage of all patients (Table 1). Among adults (those aged ≥15 years), 42.4% were recorded as smokers. Alcohol use was poorly recorded, although documentation of ‘no alcohol use’ increased with age.

The median time between previous clinic attendance and audit date was 22 days (Table 2). The most common reason for attendance across all age groups was to receive a BPG injection (45%), being highest for those aged 0–14 (68.9%) and 15–24 (58.1%) years.

Table 2.  Profile of clinic attendance and management of acute rheumatic fever (ARF) and rheumatic heart disease (RHD)
Unless indicated otherwise, data are given as n (%). BPG, benzathine penicillin G; ECG, echocardiogram

Most patients (80.4%) had disease management plans recorded. Current prescription for regular BPG injections varied by age group. Approximately 83% of patients aged <50 years (97.8% of those aged <15 years and 26.3% of older patients) were prescribed regular BPG injections. The program target of receiving ≥80% of injections within the appropriate time frame was met in 46.7% of patients, varying from 64.1% in people aged 15–24 years to 13.2% in people >50 years of age. Only 12.7% of those patients failing to meet the target had a documented follow-up action plan.

In terms of scheduled reviews, 48.6% of patients at high or medium risk of RHD complications and 71.4% of low-risk patients had a record of general practitioner consultation within the recommended time frame (6 and 12 months respectively). Approximately 40% of high- and medium-risk patients were seen by a specialist (cardiologist, physician, paediatrician or specialist registrar) or received an echocardiogram within 6 and 12 months respectively. In contrast, 75.1% of low-risk patients received echocardiograms according to guidelines.

In terms of overall delivery, the youngest age group received the highest level of care with an average of 77% delivery for items in the composite indicator (Fig. 1; see Table S1, available as Supplementary Material to this paper).

Fig. 1.  Guideline adherence of healthcare providers on acute rheumatic fever (ARF) and rheumatic heart disease (RHD) quality of care indicators by age group in the most recent Audit and Best Practice for Chronic Disease (ABCD) cycle (2010–14). Data are the percentages ± 95% confidence intervals. ECG, echocardiography.

For all older age groups, overall delivery of care was substantially lower, at 67%, 66% and 65% for those aged 15–24, 25–49 and ≥50 years respectively. The main weaknesses were found in delivering at least 80% of BPG injections in a timely manner and documentation of provision of client education. Without taking these two indicators into account, the overall composite score increased to between 87% (for those aged <15 years) and 79% (for those aged 25–49 and ≥50 years) across age groups. Moreover, the lower level of service delivery for those aged 15–24 years was less pronounced.

The results of the regression analyses are given in Table 3, with each column representing a separate model undertaken for each QOC indicator.

Table 3.  Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for each of nine acute rheumatic fever (ARF) and rheumatic heart disease (RHD) indicators of quality of care received by ARF and RHD patients in primary care
Each column represents a separate model including an intercept (not reported). The dependent variable is listed in the column header. Statistically significant associations are bolded. BPG, benzathine penicillin G; ECG, echocardiogram

Compared with patients aged <15 years, older age was found to be a significant negative factor for several indicators, in particular the 80% BPG injections target (OR 0.3 and 0.47 for those aged 15–25 and >25–50 years respectively), timely specialist review (ORs 0.27, 0.29 and 0.37 for those aged 15–25, >25–50 and >50 years respectively), timely echocardiogram (OR 0.42, 0.44 and 0.15 for those aged 15–25, >25–50 and >50 years respectively) and client education (OR 0.47, 0.33 and 0.37 for those aged 15–25, >25–50 and >50 years respectively). The effect was particularly strong for the young adult group (15–24 years) for delivering BPG injections and specialist services. As expected, patients with RHD (with and without documented ARF) had a significantly higher odds (ORs 1.79 and 3.05 respectively) of receiving timely specialist visits compared with ARF-only patients.

Health centre-level factors varied substantially across indicators, accounting for between 10% and 74% of the variation in service delivery to patients (Table 3). The centre effects capture the residual clinic-specific variability that is not explained by the fixed effects included in the models in Table 3 (i.e. a large percentage of variance explained by clinic effects means that the included fixed effects were less important in explaining the outcome (QOC measure) than other unmeasured factors). Conversely, a small percentage of variance explained by clinic effects means that the fixed effects explain a large part of the variability in the data. A large percentage of variance explained by clinic effects is not related to the degree of difference in QOC measures between clinics. Health centre factors were particularly pronounced for having patients’ RHD classification recorded (clinic effects = 81.5%) and were weak for access to specialists (clinic effects = 10.6%), echocardiograms (clinic effects = 11.2%) and 80% BPG injections received (clinic effects = 24.1%).

This study provides important insights into patient profiles and management of ARF and RHD across PHC clinics participating in ABCD audits predominantly around remote northern Australia. With over 80% of ARF and RHD patients having a management plan in place and regular BPG prescribed (>90% of those aged <25 years), clinic staff show guideline awareness in managing the disease. However, the relatively low achievement of the 80% benchmark of adherence to BPG and only 12% of poor adherers having action plans indicate that insufficient systems are in place to translate these secondary prevention guidelines into quality care. In addition, only 30% of patients had their priority status recorded, suggesting that this classification was rarely used to guide other management. Some guideline targets were relatively well achieved for Priority 3 patients (>75% having an echocardiogram within the past 2–3 years) compared with much lower guideline concordance in this domain for Priority 1 and 2 patients with moderate and severe RHD. Documentation of provision of health education was low, even among people aged <25 years, in whom secondary prevention has the most potential to improve outcomes.

The relative youth of ARF and RHD patients (approximately half <25 years of age) highlights that this chronic disease has its roots in childhood but can affect survivors into adulthood. Consistent with findings in other populations,¹ females comprised an increasing proportion of cases from early adulthood. Moderate and severe RHD (13% over all ages) peaked in early and mid-adulthood.

Most patients <25 years of age (88.5%) had RHD, with 20% having RHD without a documented history of ARF and a relatively small proportion with a history of ARF only. This suggests that although missed diagnosis of ARF could be due to subclinical symptoms, in many instances ARF is being misdiagnosed by health personnel. The high proportion of patients with RHD also suggests that increased surveillance through opportunistic screening of youth from populations at high risk of RHD could identify undiagnosed RHD, offering opportunities to prevent further progression, although careful consideration of targeting screening to maximise cost-effectiveness is needed.¹⁸

Of major concern is the drop in QOC for young adults 15–24 years compared with children <15 years of age across multiple indicators, including receipt of scheduled BPG injections, management plans, educational sessions and medical and other specialist reviews within guideline-recommended times. This is consistent with other previous reports and highlights the need for transition care that is increasingly being used for chronic paediatric conditions to support children through adolescence and to adulthood.^9,19–21 Engagement of adolescents and young adults urgently needs to be addressed to improve ARF and RHD outcomes.

Many older individuals in this study were found to be prescribed penicillin, in contrast with guidelines, which recommend cessation of penicillin in most people at 35 or 40 years of age, depending on RHD severity.⁴ This problem has recently been explored elsewhere.²² Therefore, the lower penicillin adherence in this age group is less cause for concern. Timely review of penicillin-cessation rules is required, and will be clarified in the upcoming 2020 revision of the existing Australian guidelines.

What might be the priorities needing attention for the PHC management of ARF and RHD? The data suggest that the important areas for improvement include adherence to BPG and provision of patient education. The requirement for culturally appropriate education, provided in vernacular, on many occasions, has been well documented.²³ Many health literacy resources on ARF and RHD have been developed in Aboriginal languages, but greater implementation is needed.²⁴ Surgery delays need attention. System issues and an exerted effort to engage young adults remain overarching challenges. There is increasing recognition that secondary prevention of ARF and RHD comprises not just penicillin and regular follow-up, but also proactive efforts to support primordial²⁵ and primary prevention^26,27 among affected individuals. The present data do not address this, because primordial and primary care indicators were not included in the audits.

Our reliance on appropriate documentation within PHC records may have underestimated service delivery due to a lack of documentation in client records, and crucial RHD severity classification information, on which priority levels and thus service provision are based, were often missing. Further, despite the collection of comprehensive data, we would need additional data points to run the complex models needed to refine the findings. The lack of significance of many analysed factors may be because key factors affecting service delivery are truly hard to quantify and highly variable across individual patients and clinics, requiring a mix of quantitative and qualitative methods to get a more detailed understanding.²⁸ Alternatively, they may be attributable to insufficient high-quality data available for analysis. Although the data are not necessarily representative of all Aboriginal people with ARF or RHD attending PHC clinics in regions where the disease is endemic, comprehensive PHC data focusing on ARF and RHD are rare and registers do not capture all cases or variables accurately.²⁹ Service delivery was highly variable, making it difficult to pinpoint key determinants of weaknesses in QOC. Differences in outcomes seem to be attributable to the characteristics of both the patient population and the health centres. Further research that collects data focusing on the interaction between patients and health workers is required to explore this in depth, as has been done by the ABCD project on CQI in other diseases.^14,28

Currently research is being undertaken as part of a quasi-national RHD study³⁰ to describe the burden of ARF and RHD and to identify primary health system barriers and facilitators to the management of ARF and RHD. Results emerging from these studies, as well as the present ABCD analysis, will feed into the development of policy to address RHD. The End RHD coalition has been formed to drive policy innovation and change to significantly reduce the extremely high rates of the disease in the Indigenous population.²⁷ Given the centrality of PHC to these initiatives, the results reported here provide a good source of baseline data for future monitoring of QOC indicators and PHC practice in our study settings over time.

The authors have no competing interests to declare.