Volume 48, Issue 12, December 2019

Clinic factors associated with better delivery of secondary prophylaxis in acute rheumatic fever management

Emma Quinn    Seham Girgis    Joseph Van Buskirk    Veronica Matthews    Jeanette E Ward   
doi: 10.31128/AJGP-07-19-4987   |    Download article
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Background and objectives
Acute rheumatic fever (ARF) is a complication of infection with group A streptococcus. ARF is treated with a long-term regimen of antibiotic secondary prophylaxis. Recent data have shown that only 36% of clients receive >80% of their regimen. The aim of this study was to determine clinic-level factors independently associated with the performance of primary healthcare clinics in delivering secondary prophylaxis to patients with ARF.
Cross-sectional de-identified data from clinics agreeing to data retention through the Audit and Best Practice for Chronic Disease National Research Partnership were accessed to calculate secondary prophylaxis performance scores and clinic-level factors associated with secondary prophylaxis performance using regression analysis.
Thirty-six clinics and 496 client records met eligibility criteria for analysis. Clinic secondary prophylaxis performance was significantly associated with ‘systematic processes of follow-up’. Every one unit increase in ‘systematic approach to follow-up’ increased the median level of secondary prophylaxis performance by 30% (95% confidence interval: 2, 66). Clinic accreditation status, location or workforce were not associated with secondary prophylaxis performance.
General practitioners as clinical leaders are well placed to support managers to critically review follow-up and electronic reminder systems for secondary prophylaxis delivery at clinic level.

Acute rheumatic fever (ARF) is an immune-mediated complication of infection from the highly contagious group A streptococcus (GAS).1 Prior infection with GAS generally manifests as either pharyngitis or impetigo.2,3 While age-standardised ARF incidence rates vary globally,4 Aboriginal and Torres Strait Islander people in Australia have some of the highest rates (85 per 100,000 population).5 Recurrent episodes of ARF can result in permanent damage known as rheumatic heart disease (RHD).6 Both ARF and RHD are viewed as diseases arising from conditions of colonisation, marginalisation and poverty.7

After an initial episode of ARF, an individualised clinical management plan is required, including a long-term regimen of antibiotic secondary prophylaxis commonly using benzathine penicillin G (BPG) to reduce the risk of recurrent ARF in the context of continuing GAS exposure.6 Because serum penicillin levels wane immediately following administration, both dosage and timing of an individual’s secondary prophylaxis injections are critical.8 Four-weekly BPG (every 28 days) is currently the regimen of choice.6 These national guidelines also state, however, that, ‘Some health services prefer to administer BPG on the same day every month, rather than every 4 weeks’. A calendar month rather than a four-weekly regimen of BPG is considered ‘an acceptable alternative’.6 Decisions about the appropriate regimen rest with the responsible specialist clinician to whom the patient has been referred by the primary healthcare team, usually a paediatrician or paediatric cardiologist who can refer to national guidelines.6 Delivery of the nominated secondary prophylaxis regimen then rests with the multidisciplinary primary healthcare (PHC) team including general practitioners (GPs) serving the community in which the patient resides.

With the establishment of Australia’s Rheumatic Fever Strategy (RFS) in 2009, efforts to improve secondary prophylaxis through registers in Northern Territory, Western Australia, Queensland and South Australia have received unprecedented attention. Each state and territory participating in the RFS National Partnership Agreement must report the percentage of patients registered in their jurisdiction receiving >80% of their secondary prophylaxis regimen.9 Secondary prophylaxis performance remains highly variable.10,11 From 2008 to 2014, the proportion of patients receiving >80% of their scheduled secondary prophylaxis regimen did not improve.12 Two recent interventional studies using well-designed continuous quality improvement (CQI) methods did not show improvements in primary outcomes of secondary prophylaxis provision.13,14

There has been little standardisation in measuring individual secondary prophylaxis adherence.15 Even less attention has been given to the development of a measure of secondary prophylaxis performance at the clinic level. Measuring and improving clinic performance would provide GPs and their PHC colleagues with useful insights about the care provided from their service to the population. In response, these researchers obtained access to a national PHC database to develop a measure of secondary prophylaxis performance and, importantly, identify factors at an organisational level that were associated with better secondary prophylaxis performance.


Data sources

As described elsewhere,16 the Audit and Best Practice for Chronic Disease (ABCD) project began in 2002 to investigate and improve PHC, initially for clinic management of Aboriginal and Torres Strait Islander people with chronic disease. Later topics for CQI modules included ARF/RHD. PHC clinics chose their own CQI focus and could elect to participate only once or repeatedly in the same or different CQI modules. From 2005 until 2014, PHC sites participating in this CQI project were also asked to agree to share their de-identified CQI data with the ABCD National Research Partnership (NRP).16 Approximately two-thirds of participating PHCs did so. When participating in their elected modules, each PHC submitted a community profile, known as the Health Care and Community Survey (HCCS). Clinic staff also used standardised audit tools to submit de-identified clinical information about the clinical topic retrieved from at least 30 randomly selected clinical records (for smaller communities, PHCs were asked to audit all available records). A participatory Systems Assessment Tool (SAT) was also completed to identify strengths and weaknesses onsite. As resources produced through this CQI program referred to people attending PHC services as ‘clients’ rather than ‘patients’, this term is used throughout this article. The term ‘clinic’ encompasses all PHC types.

In 2018, these researchers received ABCD NRP clinic and client data from 2008 to 2014 for clinics completing at least one ARF/RHD CQI module. Clinics were excluded if they had not concurrently completed their HCCS and SAT in the same year as the clinical ARF/RHD audit. If a clinic had completed more than one ARF/RHD audit cycle, their most recent cycle was used. With respect to client audit data, clinics had been instructed to complete the clinical audit for clients who had a history of a recorded diagnosis of definite or suspected ARF/RHD and resident in the community for ≥6 months in the past 12 months. This study only included clients prescribed BPG intramuscular injections for ARF/RHD at least monthly for ≥12 months prior to the audit for analysis. For each client, receipt of their prescribed regimen was calculated as a percentage.

Clinic secondary prophylaxis performance measure and potential explanatory variables

Until very recently,17 there had been little evidence quantifying the accrued benefit in risk reduction of ARF recurrence for individuals prescribed secondary prophylaxis from increasing percentiles of regimen adherence. de Dassel et al showed that patients receiving <40% of their scheduled secondary prophylaxis regimen gained no protection against ARF recurrence.17 Receiving >80% of prescribed secondary prophylaxis was clearly superior, while the risk reduction for patients receiving between 40% and 80% of their secondary prophylaxis regimen exhibited a linear dose–response relationship.17 These finding were used in the current study to weight and allocate points to calculate a salient measure of each clinic’s secondary prophylaxis performance. Accordingly, the points system assigned no points to any secondary prophylaxis provision by the clinic for a client receiving less than 40% of their scheduled secondary prophylaxis. After assigning points on the basis of each client’s receipt of scheduled secondary prophylaxis regimen (Table 1), clinic performance was further weighted to reward secondary prophylaxis ≥80% to derive a value for the clinic’s secondary prophylaxis performance from 0 to 60. To confirm the conceptualisation of the approach, two GPs, a clinical pharmacist, a public health nurse with RHD policy experience and a public health physician were provided with a copy of the seminal article17 and the proposed points allocation system for feedback. For analyses, the researchers selected the median point score from the total number of points per clinic as the continuous secondary prophylaxis performance outcome measure.

Table 1. Assignment of points to produce a clinic-level secondary prophylaxis performance measure
Client adherence to secondary prophylaxis (%) Points allocation at clinic level
<40 0
40–49 5
50–59 10
60–69 15
70–79 20
80–99 40
100 60

The dataset contained a profile of the community that the clinic served (ie HCCS); this included data on the jurisdiction, governance of the clinic (community controlled or government managed), location (major city/regional versus remote/other), accreditation status and estimated Aboriginal community size served by the clinic (<500, 500–1000, >1000 people). The researchers also received 20 SAT scores assigned by clinical teams as continuous variables using a scale of values ranging from 0–11: ‘limited or no support’ (0–2), ‘basic support’ (3–5), ‘good support’ (6–8) and ‘fully developed support’ (9–11; Appendix 1, available online only). These were used as study variables given the range of barriers and enablers to optimal secondary prophylaxis performance sourced from expert opinion.12

Statistical analyses

Univariate analyses were first conducted to assess the median level of clinic-level points (continuous variable) across categorical clinic variables using either the Wilcoxon test or Kruskal–Wallis test as appropriate. For continuous explanatory variables, univariate linear regression analyses were performed to assess the association between the 20 SAT items scores and clinic-level points. Any univariate associations significant at the P ≤0.25 level were entered into a multiple regression base model and refined using backwards elimination. This statistical approach enabled determination of independent factors associated with secondary prophylaxis performance at the clinic level (accounting for all other potential covariates). In building the base multiple regression model, a P value cut-off of 0.25 was set to minimise the risk of missing an influential explanatory variable. In the final multivariate regression model, a 0.05 alpha level was adopted for statistical significance. As the weighting procedure for calculating the clinic-level points outcome variable was a non-linear transformation, a natural logarithmic transformation was applied to this outcome when modelling the clinic-level points variable. This allowed for valid modelling of a linear relationship between clinic-level points and all covariates. Analyses were undertaken using SAS Enterprise Guide version 7.1 and R version 3.5.1.

Ethical approval

Ethics approval was obtained for use of NRP data for secondary analyses.16


The final sample comprised data from 36 clinics (Table 2), representing more than half of all clinics participating in this CQI initiative, completing the ARF/RHD clinical audit module and consenting to NRP data retention (n = 60).12 There was a median of 11 ARF/RHD clients per clinic (range 1–42). Table 3 shows key demographics of clients whose data met eligibility criteria. As also shown in Table 3, the proportion of clients on four-weekly regimens receiving >80% of their prescribed secondary prophylaxis was identical to that of clients on monthly regimens (both 27%).

Table 2. Characteristics of clinics included in the study (n = 36)
Characteristic n (%)
State or territory
Northern Territory 13 (36)
Queensland 21 (58)
South Australia and Western Australia 2 (6)
Community controlled or other* 6 (17)
State/territory managed 30 (83)
Major city/regional 3 (8)
Remote community/other 33 (92)
Accredited (AGPAL or QIC) 22 (61)
Not accredited/other 14 (39)
Estimated Aboriginal service population§
<500 8 (22)
500–1000 14 (39)
>1000 14 (39)
*‘Other’ for the governance variable includes clinics funded from government and community controlled sources.
‘Other’ for the location variable includes clinics reported as primary health clinic.
‘Other’ for the accreditation variable includes those clinics classified as other in the audit module, or reported as accreditation status in progress for the next 12 months.
§As provided by the clinic in audit documentation
AGPAL, Australian General Practice Accreditation Limited; QIC, The QIC Health and Community Services Standards
Table 3. Characteristics of clients whose de-identified data were contained in the dataset after applying eligibility criteria (n = 496)
Characteristic n (%)* Number (%) receiving ≥80% of their regimen
Female 174 (35) 44 (25)
Male 322 (65) 90 (28)
Age group (years)
<18 249 (50) 46 (18)
18–35 63 (13) 19 (30)
36–50 165 (33) 60 (36)
>50 19 (4) 9 (47)
Indigenous status
Aboriginal or Torres Strait Islander 477 (96) 131(27)
Non-Indigenous/not stated 19 (3) 3 (16)
ARF/RHD classification
Priority severe RHD 118 (24) 41 (35)
Priority moderate RHD 97 (20) 26 (27)
Priority ARF/mild RHD 221 (45) 55 (25)
Unable to determine 1 (<1) 0 (0)
Not recorded 59 (12) 12 (20)
Documented management plan in place
Yes 414 (83) 114 (28)
No 82 (17) 20 (24)
Prescribed benzathine penicillin G injection regimen
Monthly 266 (54) 72 (27)
Four-weekly 229 (46) 62 (27)
Other 1 (<1) 0 (0)
*Because of rounding to one decimal place, the percentages in the table above may not add up exactly to 100.
Recorded diagnosis as per national guidelines6 in the clinical record system
ARF, acute rheumatic fever; RHD, rheumatic heart disease

Using the weighted measure – clinic-level points – it was determined that there was a median value of 15 clinic-level points across all 36 clinics (interquartile range: 10.00–23.75 points). Two (5%) clinics obtained the maximum possible 60 points. No categorical clinic variables were associated with secondary prophylaxis performance at the P ≤0.05 level (Table 4). Univariate analyses of the continuous SAT items and the log-transformed clinic-level outcome variable initially found two covariates significantly associated at ≤0.05 level (Table 5). After controlling for ‘systematic approach to follow-up’, no additional covariates were significantly associated with the outcome in a multivariable model. The calculation of the continuous secondary prophylaxis performance variable was transformed via the natural logarithm, and so beta coefficients reported in Table 5 must first be back-transformed to be readily interpretable. Specifically, beta coefficients are exponentiated (with base e) in order to obtain a percentage change in clinic-level points with a one-unit increase in the covariate. Recalling that scores for each of the SAT variables ranged from one to 11, a one-unit increase in score in ‘systematic approach to follow-up’ was associated with a 30% relative increase in the median clinic-level points (95% confidence interval [CI]: 2, 66).

Table 4. Characteristics of clinics and their association with performance of delivering secondary prophylaxis for their eligible clients
Clinic characteristic Clinic level points
State or territory Median (interquartile range) P value
Northern Territory 15.0 (10.0–20.0) 0.26*
Queensland 10.0 (7.5–17.5)
South and Western Australia 27.5 (15.0–40.0)
Community controlled or other 10.0 (10.0–15.0) 0.62
State/territory managed 15.0 (10.0–30.0)
Major city/regional 10.0 (5.0–40.0) 0.71
Remote community/other§ 15.0 (10.0–20.0)
Accredited (AGPAL or QIC) 10.0 (10.0–40.0) 1.0
Not accredited/otherǁ 15.0 (10.0–20.0)
Estimated service population#
<500 10.0 (10.0–15.0) 0.47*
500–1000 17.5 (10.0–35.0)
>1000 15.0 (10.0–20.0)
*Two-sided Kruskal–Wallis test
†‘Other’ for the governance variable includes clinics funded from government and community controlled sources.
‡Two-sided Wilcoxon rank sum test
§‘Other’ for the location variable includes clinics reported as primary health clinic.
ǁ‘Other’ for the accreditation variable includes those clinics classified as other in the audit module, or reported as accreditation status in progress for the next 12 months.
#As provided by the clinic in audit documentation
AGPAL, Australian General Practice Accreditation Limited; QIC, The QIC Health and Community Services Standards
Table 5. Univariate linear associations between clinic Systems Assessment Tool item scores and performance of secondary prophylaxis at clinic level
Systems Assessment Tool (SAT) item Median SAT (IQR) Clinic level points
B-coefficient (95% CI) P value
Team structure and function 6.50 (5.00–8.00) 0.293
(0.013, 0.572)
Clinical leadership 7.00 (5.00–8.50) 0.162
(–0.167, 0.490)
Appointments and scheduling 6.50 (5.00–8.00) 0.204
(–0.057, 0.465)
Care planning 7.00 (6.00–9.00) 0.101
(–0.218, 0.421)
Systematic approach to follow‑up 8.00 (6.00–9.00) 0.265
(0.022, 0.508)
Continuity of care 6.00 (5.00–8.00) 0.208
(–0.059, 0.476)
Client access and cultural competence 9.00 (6.00–9.00) 0.074
(–0.175, 0.323)
Physical infrastructure, supplies and equipment 7.00 (5.00–8.00) 0.207
(–0.060, 0.474)
Electronic client list 8.00 (6.00–9.00) 0.142
(–0.125, 0.408)
Evidence-based guidelines 8.00 (7.00–9.00) 0.222
(–0.129, 0.572)
Specialist–generalist collaborations 6.50 (4.50–8.00) 0.115
(–0.106, 0.336)
Assessment and documentation 7.00 (5.00–8.50) 0.051
(–0.205, 0.307)
Self-management education and support 6.50 (5.00–7.50) 0.104
(–0.165, 0.372)
Communication and cooperation with governance and operations 6.00 (3.50–7.00) 0.161
(–0.072, 0.394)
Linking with other health services 6.00 (4.00–8.00) 0.172
(–0.064, 0.408)
Working out in the community 6.00 (4.00–8.00) 0.192
(–0.026, 0.410)
Communication and cooperation on regional health planning 4.00 (1.50–7.00) 0.044
(–0.165, 0.252)
Organisational commitment 5.50 (4.00–7.00) 0.108
(–0.160, 0.376)
Quality improvement strategies 8.00 (6.00–9.00) 0.067
(–0.181, 0.314)
Integration and health system components 6.00 (4.50–8.00) 0.044
(–0.196, 0.285)
*Significant at P <0.25
Significant at P <0.05
CI, confidence interval; IQR, interquartile range


This unique study first conceptualised a contemporary quantitative measure of clinic performance in the provision of secondary prophylaxis to Aboriginal people with ARF under their care for whom the consequence of inadequate secondary prophylaxis is early death from RHD. This clinic-based secondary prophylaxis performance measure was weighted to reflect objective benefits that accrue for individual clients17 but aggregated at the clinic-level to provide a system-level performance measure useful for managers and quality improvement activity. Despite the modest sample (n = 36 centres), it was sufficient in size to provide relevant insights about the importance of clinic-based systems to achieve higher rates of clinic secondary prophylaxis performance. Specifically, high functionality in the clinic’s ‘systematic processes of follow-up’ was associated significantly with the clinic’s objective secondary prophylaxis performance. Every one-unit increase in ‘systematic approach to follow-up’ increased the median value of clinic secondary prophylaxis performance by 30% (95% CI: 2, 66). System-level change, while complex18 and sometimes hard to measure,19 has been shown to be effective at improving the quality of some aspects of PHC for Aboriginal and Torres Strait Islander people.20,21 GPs can provide the clinical leadership to support clinic managers to improve local reminder systems.

Nonetheless, it was disappointing to find no difference in the proportion of clients receiving ≥80% secondary prophylaxis whether they were assigned 28-day versus calendar month regimens. Given the imminent revision of the national guidelines6 and meta-analyses of pharmacokinetic studies,22 recommendations for GPs about the timing of the secondary prophylaxis regimen needs urgent reconsideration. Suggesting that clinics consider a regimen of 12 rather than 13 injections per year as a way to increase secondary prophylaxis adherence, while well-intended, appears to have little objective basis. As the majority (73%) of clients did not receive levels of secondary prophylaxis known to offer best protection from ARF recurrence (ie ≥80%), GPs are well placed to act on these findings by providing supportive clinical leadership to focus on system-level changes within primary healthcare.


Clinic managers are encouraged to critically review and improve their follow-up and electronic reminder systems, as these are strongly associated with benefits for their clients that require secondary prophylaxis for ARF from the clinic and are within their control as health leaders to improve.

Appendix 1. Systems Assessment Tool items
  1. Team structure and function
  2. Clinical leadership
  3. Appointments and scheduling
  4. Care planning
  5. Systematic approach to follow-up
  6. Continuity of care
  7. Client access and cultural competence
  8. Physical infrastructure, supplies and equipment
  9. Maintenance and use of electronic client list
  10. Evidence-based guidelines
  11. Specialist–generalist collaborations
  12. Assessment and documentation
  13. Self-management education and support, behavour risk reduction and support
  14. Communication and cooperation on governance and operation of the health centre and other community-based organisations and programs 
  15. Linking health centre clients with other health services
  16. Working out in the community
  17. Communication and cooperation on regional health planning and development of health resources
  18. Organisational commitment
  19. Quality improvement strategies
  20. Integration of health system components
Competing interests: EQ initiated this work on voluntary placement in 2018 as visiting epidemiologist with the Kimberley Population Health Unit. This work was completed while JB was employed as a trainee in the NSW Biostatistics Training Program funded by the NSW Ministry of Health. He undertook this work while based at the Public Health Observatory, Sydney Local Health District.
Provenance and peer review: Not commissioned, externally peer reviewed.
Funding: The ABCD National Research Partnership Project was supported by funding from the National Health and Medical Research Council (#545267), the Lowitja Institute and in-kind and financial support from a range of community controlled and government agencies.
All authors acknowledge Aboriginal Elders past and present, and emerging Aboriginal leaders, future descendants and the continuing relationship of Aboriginal people to the country and its waters. We acknowledge that their lands were never ceded to Europeans through formal negotiations or treaties. EQ, JB and SG work on Eora country. VM is a Quandamooka woman working on Bundjalung country. JW works on Yawuru country. We thank those who provided feedback on our methodological approach.
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  1. Parnaby MG, Carapetis JR. Rheumatic fever in Indigenous Australian children. J Paediatr Child Health 2010;46(9):527–33. doi: 10.1111/j.1440-1754.2010.01841.x. Search PubMed
  2. McDonald M, Currie BJ, Carapetis JR. Acute rheumatic fever: A chink in the chain that links the heart to the throat? Lancet Infect Dis 2004;4(4):240–45. doi: 10.1016/S1473-3099(04)00975-2. Search PubMed
  3. McDonald MI, Towers RJ, Andrews RM, Benger N, Currie BJ, Carapetis JR. Low rates of streptococcal pharyngitis and high rates of pyoderma in Australian Aboriginal communities where acute rheumatic fever is hyperendemic. Clin Infect Dis 2006;43(6):683–89. doi: 10.1086/506938. Search PubMed
  4. Rothenbühler M, O’Sullivan CJ, Stortecky S, et al. Active surveillance for rheumatic heart disease in endemic regions: A systematic review and meta-analysis of prevalence among children and adolescents. Lancet Glob Health 2014;2(12):e717–26. doi: 10.1016/S2214-109X(14)70310-9. Search PubMed
  5. Australian Institute of Health and Welfare. Acute rheumatic fever and rheumatic heart disease in Australia. Cat. no. CVD 86. Canberra: AIHW, 2019. Available at [Accessed 8 November 2019]. Search PubMed
  6. ARF/RHD writing group. The Australian guideline for prevention, diagnosis and management of acute rheumatic fever and rheumatic heart disease (2nd edn). Casuarina, NT: RHD Australia, 2012. Search PubMed
  7. Brown A, McDonald MI, Calma T. Rheumatic fever and social justice. Med J Aust 2007;186(11):557–58. doi: 10.5694/j.1326-5377.2007.tb01052.x. Search PubMed
  8. Currie BJ, Burt T, Kaplan EL. Penicillin concentrations after increased doses of benzathine penicillin G for prevention of secondary rheumatic fever. Antimicrob Agents Chemother 1994;38(5):1203–04. doi: 10.1128/aac.38.5.1203. Search PubMed
  9. Council on Federal Financial Relations. Schedule E: Rheumatic Fever Strategy: National partnership agreement on Specified projects. Parkes, ACT: The Treasury, 2018. Search PubMed
  10. Australian Institute of Health and Welfare. Better cardiac care measures for Aboriginal and Torres Strait Islander people: Third national report 2017. Cat. no. IHW 197. Canberra: AIHW, 2018. Search PubMed
  11. Health Policy Analysis. Evaluation of the Commonwealth Rheumatic Fever Strategy: Final report. Canberra: Primary Healthcare Branch, DoH, 2017. Search PubMed
  12. Bailie J, Matthews V, Laycock A, Bailie R. Priority evidence-practice gaps in Aboriginal and Torres Strait Islander health care: Acute rheumatic fever and rhuematic heart disease care (with supporting data 2008–2014), phase 2 report. Darwin: Menzies School of Health Research, 2016. Search PubMed
  13. Ralph AP, Fittock M, Schultz R, et al. Improvement in rheumatic fever and rheumatic heart disease management and prevention using a health centre-based continuous quality improvement approach. BMC Health Serv Res 2013;13:525. doi: 10.1186/1472-6963-13-525. Search PubMed
  14. Ralph AP, de Dassel JL, Kirby A, et al. Improving delivery of secondary prophylaxis for rheumatic heart disease in a high-burden setting: Outcome of a stepped-wedge, community, randomized trial. J Am Heart Assoc 2018;7(14):e009308. doi: 10.1161/JAHA.118.009308. Search PubMed
  15. Kevat PM, Reeves BM, Ruben AR, Gunnarsson R. Adherence to secondary prophylaxis for acute rheumatic fever and rheumatic heart disease: A systematic review. Curr Cardiol Rev 2017;13(2):155–66. doi: 10.2174/1573403X13666170116120828. Search PubMed
  16. Bailie R, Si D, Shannon C, et al. Study protocol: National research partnership to improve primary health care performance and outcomes for Indigenous peoples. BMC Health Serv Res 2010;10:129. doi: 10.1186/1472-6963-10-129. Search PubMed
  17. de Dassel JL, de Klerk N, Carapetis JR, Ralph AP. How many doses make a difference? An analysis of secondary prevention of rheumatic fever and rheumatic heart disease. J Am Heart Assoc 2018;7(24):e010223. doi: 10.1161/JAHA.118.010223. Search PubMed
  18. Bailie J, Laycock A, Matthews V, Bailie R. System-level action required for wide-scale improvement in quality of primary health care: Synthesis of feedback from an interactive process to promote dissemination and use of aggregated quality of care data. Front Public Health 2016;4:86. doi: 10.3389/fpubh.2016.00086. Search PubMed
  19. Larkins S, Woods CE, Matthews V, et al. Responses of Aboriginal and Torres Strait Islander primary health-care services to continuous quality improvement initiatives. Front Public Health 2016;3:288. doi: 10.3389/fpubh.2015.00288. Search PubMed
  20. Gibson-Helm ME, Rumbold AR, Teede HJ, Ranasinha S, Bailie RS, Boyle JA. Improving the provision of pregnancy care for Aboriginal and Torres Strait Islander women: A continuous quality improvement initiative. BMC Pregnancy Childbirth 2016;16:118. doi: 10.1186/s12884-016-0892-1. Search PubMed
  21. Si D, Bailie R, Connors C, et al. Assessing health centre systems for guiding improvement in diabetes care. BMC Health Serv Res 2005;5:56. doi: 10.1186/1472-6963-5-56. Search PubMed
  22. Broderick MP, Hansen CJ, Faix DJ. Factors associated with loss of penicillin G concentrations in serum after intramuscular benzathine penicillin G injection: A meta-analysis. Pediatr Infect Dis J 2012;31(7):722–25. doi: 10.1097/INF.0b013e31825051d4. Search PubMed

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