Process control charts in infection prevention: Make it simple to make it happen - 18/04/17

Doi : 10.1016/j.ajic.2016.09.021

Timothy L. Wiemken, PhD, MPH, FAPIC, CIC ^a,^* , Stephen P. Furmanek, MPH ^a, Ruth M. Carrico, PhD, RN, FNP-C, FSHEA, CIC ^a, William A. Mattingly, PhD ^a, Annuradha K. Persaud, MPH ^a, Brian E. Guinn, MPH ^a, Robert R. Kelley, PhD ^b, Julio A. Ramirez, MD ^a
^a Division of Infectious Diseases, University of Louisville, Louisville, KY
^b Department of Math and Computer Science, St Mary's College of Maryland, St Mary's City, MD

^*Address correspondence to Timothy L Wiemken, PhD, MPH, FAPIC, CIC, Director Healthcare Epidemiology and Patient Safety Program, Division of Infectious Diseases University of Louisville, 501 E Broadway Suite 120b Louisville, KY 40202. (T.L. Wiemken).Director Healthcare Epidemiology and Patient Safety ProgramDivision of Infectious Diseases University of Louisville501 E Broadway Suite 120bLouisvilleKY40202

Highlights

•	Utilization of Statistical Process Control (SPC) in infection prevention is critical to clearly understand trends and issues in any particular facility.
•	Use of SPC in infection prevention is limited partially due to the cost associated with software that provides a simple user interface with automated evaluation of the data.
•	Using free, open-source software, we created an application to create process control charts using infection prevention data.
•	This manuscript outlines our selection of software, creation of the application, evaluation using simulated infection prevention data, and offers all programs for free download.

Le texte complet de cet article est disponible en PDF.

Abstract

Background

Quality improvement is central to Infection Prevention and Control (IPC) programs. Challenges may occur when applying quality improvement methodologies like process control charts, often due to the limited exposure of typical IPs. Because of this, our team created an open-source database with a process control chart generator for IPC programs. The objectives of this report are to outline the development of the application and demonstrate application using simulated data.

Methods

We used Research Electronic Data Capture (REDCap Consortium, Vanderbilt University, Nashville, TN), R (R Foundation for Statistical Computing, Vienna, Austria), and R Studio Shiny (R Foundation for Statistical Computing) to create an open source data collection system with automated process control chart generation. We used simulated data to test and visualize both in-control and out-of-control processes for commonly used metrics in IPC programs.

Results

The R code for implementing the control charts and Shiny application can be found on our Web site (spcapp). Screen captures of the workflow and simulated data indicating both common cause and special cause variation are provided.

Conclusions

Process control charts can be easily developed based on individual facility needs using freely available software. Through providing our work free to all interested parties, we hope that others will be able to harness the power and ease of use of the application for improving the quality of care and patient safety in their facilities.

Le texte complet de cet article est disponible en PDF.

Key Words : Quality improvement, Health care-associated infection, Surveillance

Plan

	Conflict of interest: None to report.
	TLW, SPF, RMC, and JAR contributed to the design of the protocol. TLW, SPF, AKP, BEG, WAM, RRK, BEG, and KAB contributed to computer programming. TLW, SPF, WAM, RMC, KAB, and JAR had primary writing responsibilities. TLW and KAB were responsible for video recording and editing. All authors provided a critical review of the manuscript and approved the final version.