Article Text

Download PDFPDF
Implementing an institution-wide quality improvement policy to ensure appropriate use of continuous cardiac monitoring: a mixed-methods retrospective data analysis and direct observation study
  1. Michael F Rayo1,
  2. Jerry Mansfield2,
  3. Daniel Eiferman3,
  4. Traci Mignery2,4,
  5. Susan White5,
  6. Susan D Moffatt-Bruce3
  1. 1Department of Quality and Safety, The Ohio State University, Columbus, Ohio, USA
  2. 2Department of Nursing, The Ohio State University, Columbus, Ohio, USA
  3. 3Department of Surgery, The Ohio State University College of Medicine, Columbus, Ohio, USA
  4. 4Department of Surgery, The Ohio State University, Columbus, Ohio, USA
  5. 5School of Health Sciences and Rehabilitation, College of Medicine, Ohio State University, Columbus, Ohio, USA
  1. Correspondence to Dr Michael F Rayo, Department of Quality and Safety, The Ohio State University, 37 W. Kenworth Rd, Columbus, OH 43214, USA; mike.rayo{at}cogenisys.com

Abstract

Background Hospitals have been slow to adopt guidelines from the American Heart Association (AHA) limiting the use of continuous cardiac monitoring for fear of missing important patient cardiac events. A new continuous cardiac monitoring policy was implemented at a tertiary-care hospital seeking to monitor only those patients who were clinically indicated and decrease the number of false alarms in order to improve overall alarm response.

Methods Leadership support was secured, a cross-functional alarm management task force was created, and a system-wide policy was developed based on current AHA guidelines. Process measures, including cardiac monitoring rate, monitored transport rate, emergency department (ED) boarding rate and the percentage of false, unnecessary and true alarms, were measured to determine the policy's impact on patient care. Outcome measures, including length of stay and mortality rate, were measured to determine the impact on patient outcomes.

Results Cardiac monitoring rate decreased 53.2% (0.535 to 0.251 per patient day, p<0.001), monitored transport rate decreased 15.5% (0.216 to 0.182 per patient day, p<0.001), ED patient boarding rate decreased 36.6% (5.5% to 3.5% of ED patients, p<0.001) and the percentage of false alarms decreased (18.8% to 9.6%, p<0.001). Neither the length of stay nor mortality changed significantly after the policy was implemented.

Conclusions The observed improvements in process measures coupled with no adverse effects to patient outcomes suggest that the overall system became more resilient to current and emerging demands. This study indicates that when collaboration across a diverse team is coupled with strong leadership support, policies and procedures such as this one can improve clinical practice and patient care.

  • Human factors
  • Implementation science
  • Healthcare quality improvement
  • Governance
  • Leadership

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.