Impacting key performance indicators in an academic MR imaging department through process improvement

J Am Coll Radiol. 2013 Mar;10(3):202-6. doi: 10.1016/j.jacr.2012.08.008. Epub 2012 Dec 12.

Abstract

Purpose: The aim of this study was to evaluate all aspects of workflow in a large academic MRI department to determine whether process improvement (PI) efforts could improve key performance indicators (KPIs).

Methods: KPI metrics in the investigators' MR imaging department include daily inpatient backlogs, on-time performance for outpatient examinations, examination volumes, appointment backlogs for pediatric anesthesia cases, and scan duration relative to time allotted for an examination. Over a 3-week period in April 2011, key members of the MR imaging department (including technologists, nurses, schedulers, physicians, and administrators) tracked all aspects of patient flow through the department, from scheduling to examination interpretation. Data were analyzed by the group to determine where PI could improve KPIs. Changes to MRI workflow were subsequently implemented, and KPIs were compared before (January 1, 2011, to April 30, 2011) and after (August 1, 2011, to December 31, 2011) using Mann-Whitney and Fisher's exact tests.

Results: The data analysis done during this PI led to multiple changes in the daily workflow of the MR department. In addition, a new sense of teamwork and empowerment was established within the MR staff. All of the measured KPIs showed statistically significant changes after the reengineering project.

Conclusions: Intradepartmental PI efforts can significantly affect KPI metrics within an MR imaging department, making the process more patient centered. In addition, the process allowed significant growth without the need for additional equipment or personnel.

MeSH terms

  • Academic Medical Centers
  • Efficiency, Organizational
  • Humans
  • Magnetic Resonance Imaging / statistics & numerical data*
  • Process Assessment, Health Care*
  • Quality Indicators, Health Care*
  • Radiology Department, Hospital / organization & administration*
  • Statistics, Nonparametric
  • Workflow*