Cardiovascular disease management in Australian adults with type 2 diabetes: insights from the CAPTURE study

BACKGROUND

Type 2 diabetes (T2D) is a well-recognised cardiovascular disease (CVD) risk factor, and recent guidelines for the management of T2D include consideration of CVD risk.

AIM

To assess whether contemporary clinical management of Australians with T2D is in accord with recent national and international guidelines.

METHODS

This Australia-specific analysis of the CAPTURE study, a non-interventional, cross-sectional study included adults diagnosed with T2D ≥180 days prior to providing informed consent and visiting primary or specialist care. Main outcome measures were the use of blood glucose-lowering medications (BGLMs), BGLMs with proven cardiovascular benefits and other CVD medications, stratified by CVD status and care setting.

RESULTS

Of 824 Australian participants in the CAPTURE sample, 332 (40.3%) had CVD. Oral BGLMs were used by 83.9% of all participants, most commonly metformin (76.0%), dipeptidyl peptidase-4 inhibitors (28.8%), sodium-glucose cotransporter-2 inhibitors (SGLT2is; 21.8%) and sulfonylureas (21.7%). Insulin was used by 29.2% of participants. BGLMs with proven CV benefit were used by 22.6%; glucagon-like peptide-1 receptor agonists (GLP-1 RAs) were less commonly used than SGLT2is in all CVD groups, but these drug classes were more often prescribed in specialist than primary care (SGLT2is 25.4 vs 20.7%, GLP-1 RAs 3.2 vs 0.8% respectively). Use of non-BGLMs for CVD risk reduction appeared consistent with guidelines.

CONCLUSIONS

Use of BGLMs with CVD benefits appears low in Australia, irrespective of CVD status. This likely reflects the delay in translation of clinical evidence into contemporary care and prescribing restrictions.

Comparing secondary prevention for patients with coronary heart disease and stroke attending Australian general practices: a cross-sectional study using nationwide electronic database

OBJECTIVES

To compare secondary prevention care for patients with coronary heart disease (CHD) and stroke, exploring particularly the influences due to frequency and regularity of primary care visits.

SETTING

Secondary prevention for patients (≥18 years) in the National Prescription Service administrative electronic health record database collated from 458 Australian general practice sites across all states and territories.

DESIGN

Retrospective cross-sectional and panel study. Patient and care-level characteristics were compared for differing CHD/stroke diagnoses. Associations between the type of cardiovascular diagnosis and medication prescription as well as risk factor assessment were examined using multivariable logistic regression.

PARTICIPANTS

Patients with three or more general practice encounters within 2 years of their latest visit during 2016-2020.

OUTCOME MEASURES

Proportions and odds ratios (ORs) for (1) prescription of antihypertensives, antilipidaemics and antiplatelets and (2) assessment of blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) in patients with stroke only compared against those with CHD only and those with both conditions.

RESULTS

There were 111 892 patients with CHD only, 27 863 with stroke only and 9791 with both conditions. Relative to patients with CHD, patients with stroke were underprescribed antihypertensives (70.8% vs 82.8%), antilipidaemics (63.1% vs 78.7%) and antiplatelets (42.2% vs 45.7%). With sociodemographic factors, comorbidities and level of care considered as covariates, the odds of non-prescription of any recommended secondary prevention medications were higher in patients with stroke only (adjusted OR 1.37; 95% CI (1.31, 1.44)) compared with patients with CHD only. Patients with stroke only were also more likely to have neither BP nor LDL-C monitored (adjusted OR 1.26; 95% CI (1.18, 1.34)). Frequent and regular general practitioner encounters were independently associated with the prescription of secondary prevention medications (p<0.001).

CONCLUSIONS

Secondary prevention management is suboptimal in cardiovascular disease patients and worse post-stroke compared with post-CHD. More frequent and regular primary care encounters were associated with improved secondary prevention.

Learning from the implementation of a quality improvement intervention in Australian general practice: a qualitative analysis of participants views of a CVD preventive care project

Background

Quality improvement collaborative projects aim to reduce gaps in clinical care provided in the healthcare system. This study evaluated the experience of key participants from a Quality Improvement Program (QPulse) that focussed on cardiovascular disease assessment and management. The study goal was to identify critical barriers and factors enabling the implementation of a quality improvement framework in Australian general practice.

Methods

This qualitative study examined in-depth semi-structured interviews with nineteen purposively-selected participants of the QPulse project. Interviewees were from General Practices and the local supporting organisation, a Primary Health Network. Interviews were analysed thematically using the Complex Systems Improvement framework, focusing on five domains: strategy, culture, structure, workforce and technology.

Results

Despite reported engagement with QPulse objectives to improve cardiovascular preventive care, implementation barriers associated with this program were considerable for all interviewees. Adoption of the quality improvement process was reliant on designated leadership, aligned practice culture, organised systems for clear communication, tailored education and utilisation of clinical audit and review processes. Rather than practice size and location, practice culture and governance alignment to quality improvement predicted successful implementation. Financial incentives for both general practice and the Primary Health Network were also identified as prerequisites for systematised quality improvement projects in the future, along with individualised support and education for each general practice. Technology was both an enabler and a barrier, and the Primary Health Network was seen as key to assisting the successful utilisation of the available tools.

Conclusions

Implementation of Quality Improvement programs remains a potential tool for achieving better health outcomes in General Practice. However, enablers such as financial incentives, individualised education and support provided via a supporting organisation, and IT tools and support are crucial if the full potential of Quality Improvement programs are to be realised in the Australian healthcare setting.

Trial registration

ACTRN12615000108516, UTN U1111-1163–7995.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01692-0.

A nationwide study of multimedicine use in people treated with cardiovascular medicines in Australia

STUDY OBJECTIVE

Multimorbidity and multimedicine use are common in people with cardiovascular disease and can lead to harms, such as prescribing errors and drug interactions. We quantified multimedicine use in people treated with cardiovascular medicines in a national sample of Australians.

DESIGN

Cross-sectional study.

DATA SOURCE

Pharmaceutical dispensing claims for a 10% random sample of Australians.

PATIENTS

Australian adults dispensed any cardiovascular medicine between June and August 2019.

INTERVENTION

None.

MEASUREMENTS

We quantified the number and type of cardiovascular and non-cardiovascular medicines dispensed during the study period, and the number of unique prescribers, by age and sex.

MAIN RESULTS

We identified 493,081 people dispensed any cardiovascular medicine (median age = 67 years, 50.2% women). The population prevalence of cardiovascular medicine dispensing increased from 1.7% (n = 10,503) in people 18-34 years to 80.1% (n = 99,271) in people 75-84 years. Cardiovascular medicine dispensing varied by sex; women 18-34 years were more likely to be dispensed any cardiovascular medicine than men (male:female prevalence ratio [PR] = 0.84, 95% confidence interval [CI] = 0.81-0.87), whereas the prevalence of cardiovascular medicine dispensing was higher in men 35-44 years (PR = 1.27, 95% CI 1.24-1.30) and 45-54 years (PR = 1.24, 95% CI 1.22-1.26) and was similar between sexes in people ≥65 years. Overall, both women and men were dispensed a median of 2.0 (interquartile range [IQR] = 1.0-3.0) cardiovascular medicines. Two-thirds of people ≥65 years (73.5%; n = 208,524) were dispensed ≥2 cardiovascular medicines, with 16.6% (n = 6736) of people ≥85 years dispensed five or more. Women and men were dispensed a median of 2.0 (IQR = 1.0-5.0) and 2.0 (IQR = 0.0-4.0) non-cardiovascular medicines, respectively, to treat comorbid conditions, commonly gastroesophageal reflux disease medicines (32.2% of women and 26.6% of men), antibiotics (28.7% of women and 22.4% of men), and antidepressants (26.3% of women and 15.9% of men). One quarter of both sexes had multiple prescribers for their cardiovascular medicines alone, whereas 54.5% (n = 134,939) of women and 49.9% (n = 122,706) of men had multiple prescribers for all medicines.

CONCLUSION

Multimedicine use is common in people treated with cardiovascular medicines and presents a risk for inappropriate prescribing. Understanding the comorbid conditions commonly treated concurrently with cardiovascular disease can help improve co-prescribing guidelines and develop a person-centered approach to multimorbidity treatment.

Prior Cardiovascular Treatments-A Key Characteristic in Determining Medication Adherence After an Acute Myocardial Infarction

Objective: To investigate long-term adherence to guideline-recommended cardioprotective medications following hospitalization for an acute myocardial infarction (AMI), and identify characteristics associated with adherence.

Methods: An Australian population-based cohort study was used to identify participants who had their first AMI between 2006 and 2014 and were alive after 12 months. Linked routinely collected hospital, and prescription medication claims data was used to study adherence over time. Predictors and rates of adherence to both lipid-lowering medication and renin-angiotensin system blockade at 12 months post-AMI was assessed.

Results: 14,200 people (mean age 69.9 years, 38.7% female) were included in our analysis. At 12 months post-AMI, 29.5% (95% CI: 28.8–30.3%) of people were adherent to both classes of medication. Individuals receiving treatment with both lipid-lowering medication and renin-angiotensin system blockade during the 6 months prior to their AMI were over 9 times more likely to be adherent to both medications at 12 months post-AMI (66.2% 95% CI: 64.8–67.5%) compared to those with no prior medication use (treatment naïve) (7.1%, 95% CI: 6.4–7.9%). Prior cardiovascular treatment was the strongest predictor of long-term adherence even after adjusting for age, sex, education and income.

Conclusions: Despite efforts to improve long-term medication adherence in patients who have experienced an acute coronary event, considerable gaps remain. Of particular concern are people who are commencing guideline-recommended cardioprotective medication at the time of their AMI. The relationship between prior cardiovascular treatments and post AMI adherence offers insight into the support needs for the patient. Health care intervention strategies, strengthened by enabling policies, are needed to provide support to patients through the initial months following their AMI.

Findings and lessons learnt implementing a cardiovascular disease quality improvement program in Australian primary care: a mixed method evaluation

Background

There are discrepancies between evidence-based guidelines for screening and management of cardiovascular disease (CVD) and implementation in Australian general practice. Quality-improvement (QI) initiatives aim to reduce these gaps. This study evaluated a QI program (QPulse) that focussed on CVD assessment and management.

Methods

This mixed-methods study explored the implementation of guidelines and adoption of a QI program with a CVD risk-reduction intervention in 34 general practices. CVD screening and management were measured pre- and post-intervention. Qualitative analyses examined participants’ Plan-Do-Study-Act (PDSA) goals and in-depth interviews with practice stakeholders focussed on barriers and enablers to the program and were analysed thematically using Normalisation Process Theory (NPT).

Results

Pre- and post-intervention data were available from 15 practices (n = 19,562 and n = 20,249, respectively) and in-depth interviews from seven practices. At baseline, 45.0% of patients had their BMI measured and 15.6% had their waist circumference recorded in the past 2 years and blood pressure, lipids and smoking status were measured in 72.5, 61.5 and 65.3% of patients, respectively. Most high-risk patients (57.5%) were not prescribed risk-reducing medications. After the intervention there were no changes in the documentation and prevalence of risk factors, attainment of BP and lipid targets or prescription of CVD risk-reducing medications. However, there was variation in performance across practices with some showing isolated improvements, such as recording waist circumference (0.7-32.2% pre-intervention to 18.5-69.8% post-intervention), BMI and smoking assessment. Challenges to the program included: lack of time, need for technical support, a perceived lack of value for quality improvement work, difficulty disseminating knowledge across the practice team, tensions between the team and clinical staff and a part-time workforce.

Conclusion

The barriers associated with this QI program was considerable in Australian GP practices. Findings highlighted they were not able to effectively operationalise the intervention due to numerous factors, ranging from lack of internal capacity and leadership to competing demands and insufficient external support.

Trial registration

Australian New Zealand Clinical Trials Reference Number (ACTRN12615000108516), registered 06/02/2015.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07310-6.

An electronic decision support-based complex intervention to improve management of cardiovascular risk in primary health care: a cluster randomised trial (INTEGRATE)

OBJECTIVES

To determine whether a multifaceted primary health care intervention better controlled cardiovascular disease (CVD) risk factors in patients with high risk of CVD than usual care.

DESIGN, SETTING

Parallel arm, cluster randomised trial in 71 Australian general practices, 5 December 2016 - 13 September 2019.

PARTICIPANTS

General practices that predominantly used an electronic medical record system compatible with the HealthTracker electronic decision support tool, and willing to implement all components of the INTEGRATE intervention.

INTERVENTION

Electronic point-of-care decision support for general practices; combination cardiovascular medications (polypills); and a pharmacy-based medication adherence program.

MAIN OUTCOME MEASURES

Proportion of patients with high CVD risk not on an optimal preventive medication regimen at baseline who had achieved both blood pressure and low-density lipoprotein (LDL) cholesterol goals at study end.

RESULTS

After a median 15 months' follow-up, primary outcome data were available for 4477 of 7165 patients in the primary outcome cohort (62%). The proportion of patients who achieved both treatment targets was similar in the intervention (423 of 2156; 19.6%) and control groups (466 of 2321; 20.1%; relative risk, 1.06; 95% CI, 0.85-1.32). Further, no statistically significant differences were found for a number of secondary outcomes, including risk factor screening, preventive medication prescribing, and risk factor levels. Use of intervention components was low; it was highest for HealthTracker, used at least once for 347 of 3236 undertreated patients with high CVD risk (10.7%).

CONCLUSIONS

Despite evidence for the efficacy of its individual components, the INTEGRATE intervention was not broadly implemented and did not improve CVD risk management in participating Australian general practices.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry, ACTRN12616000233426 (prospective).