Health resource variability in the achievement of optimal performance and clinical outcome

Carolyn M. Astley, Colin J. MacDougall, Patricia M. Davidson, Derek P. Chew

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

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.

LanguageEnglish
Pages512-520
Number of pages9
JournalCirculation: Cardiovascular Quality and Outcomes
Volume4
Issue number5
DOIs
Publication statusPublished - Sep 2011

Keywords

  • Acute cardiac care
  • Acute coronary syndromes
  • Guideline adherence
  • Knowledge translation
  • Quality improvement

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Medicine(all)

Cite this

@article{ca1d9f2d566a40ffb7443ecff7bb5bf2,
title = "Health resource variability in the achievement of optimal performance and clinical outcome",
abstract = "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.",
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Health resource variability in the achievement of optimal performance and clinical outcome. / Astley, Carolyn M.; MacDougall, Colin J.; Davidson, Patricia M.; Chew, Derek P.

In: Circulation: Cardiovascular Quality and Outcomes, Vol. 4, No. 5, 09.2011, p. 512-520.

Research output: Contribution to journalArticle

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AU - Astley, Carolyn M.

AU - MacDougall, Colin J.

AU - Davidson, Patricia M.

AU - Chew, Derek P.

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N2 - 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.

AB - 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.

KW - Acute cardiac care

KW - Acute coronary syndromes

KW - Guideline adherence

KW - Knowledge translation

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