Skip to main content

Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction.

Publication ,  Journal Article
Fry, C; Engel, J; Granger, B; Komada, M; Lovins, J
Published in: Computers, informatics, nursing : CIN
May 2023

Clinical decision support in the EHR is an innovation that can support guideline adherence in acute myocardial infarction. Cardiac rehabilitation referral and left ventricular systolic function assessment are part of evidence-based clinical practice guidelines associated with reduced morbidity and mortality following acute myocardial infarction. Effective clinical decision support is sustained by evidence-based principles for design and implementation. This quality improvement project evaluated the impact of practice advisories designed using principles of effective clinical decision support design to improve performance of left ventricular systolic function assessment and ambulatory referral to cardiac rehabilitation for patients hospitalized with acute myocardial infarction. Performance in cardiac rehabilitation referral and left ventricular systolic function assessment was measured for a 3-month interval pre- and post-intervention. Pre-implementation, cardiac rehabilitation referral or valid documented reason for non-referral was 80.3%. Rehabilitation referral or documented valid reason for non-referral increased to 98.4% post-implementation ( P < .001). Left ventricular systolic function assessment increased from 94.2% to 100% following clinical decision support implementation ( P = .120). This quality improvement project supports the positive impact of effective clinical decision support design and implementation to improve outcomes for patients hospitalized with acute myocardial infarction.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Computers, informatics, nursing : CIN

DOI

EISSN

1538-9774

ISSN

1538-2931

Publication Date

May 2023

Volume

41

Issue

5

Start / End Page

323 / 329

Related Subject Headings

  • Ventricular Function, Left
  • Nursing
  • Myocardial Infarction
  • Humans
  • Evidence-Based Practice
  • Decision Support Systems, Clinical
  • 4205 Nursing
  • 4203 Health services and systems
  • 3904 Specialist studies in education
  • 1110 Nursing
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Fry, C., Engel, J., Granger, B., Komada, M., & Lovins, J. (2023). Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction. Computers, Informatics, Nursing : CIN, 41(5), 323–329. https://doi.org/10.1097/cin.0000000000000959
Fry, Corey, Jill Engel, Bradi Granger, Michael Komada, and Jon Lovins. “Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction.Computers, Informatics, Nursing : CIN 41, no. 5 (May 2023): 323–29. https://doi.org/10.1097/cin.0000000000000959.
Fry C, Engel J, Granger B, Komada M, Lovins J. Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction. Computers, informatics, nursing : CIN. 2023 May;41(5):323–9.
Fry, Corey, et al. “Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction.Computers, Informatics, Nursing : CIN, vol. 41, no. 5, May 2023, pp. 323–29. Epmc, doi:10.1097/cin.0000000000000959.
Fry C, Engel J, Granger B, Komada M, Lovins J. Evidence-Based Clinical Decision Support to Improve Care for Patients Hospitalized With Acute Myocardial Infarction. Computers, informatics, nursing : CIN. 2023 May;41(5):323–329.

Published In

Computers, informatics, nursing : CIN

DOI

EISSN

1538-9774

ISSN

1538-2931

Publication Date

May 2023

Volume

41

Issue

5

Start / End Page

323 / 329

Related Subject Headings

  • Ventricular Function, Left
  • Nursing
  • Myocardial Infarction
  • Humans
  • Evidence-Based Practice
  • Decision Support Systems, Clinical
  • 4205 Nursing
  • 4203 Health services and systems
  • 3904 Specialist studies in education
  • 1110 Nursing