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Background: High-sensitivity troponin T (hs-TnT) assays promise greater discrimination of evolving myocardial infarction, but the impact of unguided implementation on the effectiveness of care is uncertain.Methods and Results: We evaluated the impact of hs-TnT reporting on care and outcome among chest pain patients presenting to 5 emergency departments within a multicenter randomized trial. Patients were allocated to hs-TnT reporting (hs-report) or standard reporting (std-report; Roche Elecys). The primary end point was death and new or recurrent acute coronary syndrome by 12 months. A total of 1937 patients without ST-segment elevation were enrolled between July 2011 and March 2013. The median age was 61 (interquartile range, 48-74) years, and 46.3% were women. During the index hospitalization, 1466 patients (75.7%) had maximal troponin <30 ng/L within 24 hours. Randomization to hs-report format did not alter the admission rate (hs-report: 57.7% versus std-report: 58.0%; P=0.069). There was no difference in angiography (hs-report: 11.9% versus std-report: 10.9%; P=0.479). The hs-reporting did not reduce 12-month death or new/recurrent acute coronary syndrome in the overall population (hs-report: 9.7% versus std-report: 7.2% [hazard ratio, 0.83 (0.57-1.22); P=0.362]). However, among those with troponin levels <30 ng/L, a modest reduction in the primary end point was observed (hs-report: 2.6% versus std-report: 4.4%, [hazard ratio, 0.58; 95% confidence interval, 0.34-0.1.00; P=0.050).Conclusions: High-sensitivity troponin reporting alone is associated with only modest changes in practice. Clinical effectiveness in the adoption of high-sensitivity troponin may require close coupling with protocols that guide interpretation and care.Clinical Trial Registration: URL: http://www.ANZCTR.org.au. Unique identifier: ACTRN12611000879965. [ABSTRACT FROM AUTHOR]

The article presents a study which concluded that adverse clinical outcomes in acute coronary syndrome (ACS) care decrease with adherence to evidence-based guidelines. Guidance compliance is said to be facilitated and ensured by quality improvement tools and systems, examples of which are a standard protocol for administering timely percutaneous coronary intervention, an electronic discharge checklist and an electronic decision support program that is embedded in the clinical workflow.

Evidence-based guidelines recommend cardiac rehabilitation(CR) for secondary prevention of recurrent myocardial infarction(re-MI) and risk factor management, but poor referral and completion rates persist. Regular audit can measure the effectiveness of services. A 2011 audit of public CR services, by the South Australian Department of Health CR Clinical Network showed a 12% program attendance rate. Following development of standardised minimum data and uniform electronic data capture, 24 CR services have contributed within 3 audits. We aimed to link referral and attendance with administrative data to assess characteristics and outcomes of eligible patients. Methods: The CR patient database for 2013-2015 was linked to patients discharged alive with a primary cardiac-related diagnosis and/or interventional procedure, identified through public hospital administrative data. Outcomes were defined as readmission for cardiovascular causes and death captured through the Births Deaths and Marriages database. Patient categories were not referred, referred/declined and attended CR. Associations with cardiovascular readmission and composites of death, new/re-MI, heart failure, atrial fibrillation and stroke over the 12-month follow-up duration were reported using inverse probability weighted survival methods among those who attended and those referred/declined. Results: Of 49,909 eligible cardiac separations, referral rate was 15,089/49,909 (30.2%) and attendance 4,286/15,089 (28.4%). Those referred/declined were older (median: 67.3 vs 65.3 years, P< 0.001), more likely to be female (32.3% vs 26.5%, P< 0.001) with more heart failure (17.1% vs 10.9%, P< 0.001) and arrhythmia (6.1% v 2.1%, P< 0.001) admissions, ≥2 comorbidities (35.3% v 23.3%, P< 0.001), with higher socio-economic disadvantage (median IRSAD: 950.1 vs 960.4, p<0.001). Attending patients had lower cardiovascular readmission, (attended vs not referred: 27.3% vs 34.5% and attended vs referred/declined ; 27.3% vs 41.4%, P< 0.001). After clinical and social factors adjustment there was no difference in composite clinical outcomes to 12-months, but attendance was associated with reduced cardiovascular readmission (HR:0.68, 95% IQR: 0.58-0.81, P = 0.001). Conclusions: This analysis highlights the complexity of factors that influence referral, non-attendance and attendance to CR. Conducting clinical audit and reporting to services is vital for measuring program effectiveness and can be a mechanism for service improvement. [ABSTRACT FROM AUTHOR]

BACKGROUND- An evidence-practice gap in acute coronary syndromes (ACS) is commonly recognized. System, provider, and patient factors can influence guideline adherence. Through using guideline facilitators in the clinical setting, the uptake of evidence-based recommendations may be increased. We hypothesized that facilitators of guideline recommendations (systems, tools, and workforce) in acute cardiac care were associated with increased guideline adherence and decreased adverse outcome. METHODS AND RESULTS- A cross-sectional evaluation of guideline facilitators was conducted in Australian hospitals. The population was derived from the Acute Coronary Syndrome Prospective Audit (ACACIA) and assessed performance, death, and recurrent myocardial infarction (death/re-MI) at 30 days and 12 months. Thirty-five hospitals and 2392 patients participated. Significant associations with decreased death/re-MI were observed with hospital strategies to facilitate primary percutaneous coronary intervention for ST-elevation MI patients (38/428 [8.9%] versus 30/154 [19.5%], P<0.001) and after adjustment (odds ratio [OR], 0.47 [95% confidence interval (CI), 0.24 to 0.90], P<0.023), electronic discharge checklists (none: 233/1956 [11.9%], integrated; 43/251[17.1%], P=0.069, electronic; 6/124 [4.8%], P<0.001) and after adjustment (integrated versus none: OR, 1.66 [95% CI, 0.98 to 2.80], P=0.057 and electronic versus none: OR, 0.49 [95% CI, 0.35 to 0.68], P<0.001), and intensive cardiac care unit (ICCU) staff-to-patient ratios (neither: 200/1257 (15.9%), CCU: 135/1051 (12.8%), ICCU: 8/84 (9.5%), P=0.049 and after adjustment (CCU versus neither: OR, 0.74 [95% CI, 0.47 to 1.14], P=0.172 and ICCU versus neither: OR, 0.55; [95% CI, 0.38 to 0.81] P=0.003). CONCLUSIONS- Facilitating uptake of evidence in clinical practice may need to consider quality improvement systems, tools and workforce to achieve optimal ACS outcomes.