Healthcare analytics and quality improvement teams must collaborate

Frequent and open dialogue between quality improvement and analytics teams is a path to better healthcare outcomes.

This Content Component encountered an error

I am a very strong advocate of enabling frequent and open interaction -- and where possible, integration -- between healthcare analytics and quality improvement specialists when I form teams to undertake healthcare improvement initiatives.

Trevor StromeTrevor Strome

Traditionally, analytics is seen as a backroom, IT-driven activity to process data requests and build reports and dashboards. Quality improvement (QI) activities, on the other hand, work best when they're undertaken on (or near) the front lines of healthcare where patient care occurs.

Quality cannot be improved if QI experts are unfamiliar with whom to ask for analytics-derived information and insight, what to ask for, or even what information is possible or available. When such requests do get made, the healthcare analytics teams that are working in isolation are often unable to put these vague requests into context, and may provide information that is unsuitable, untimely or worse, simply inaccurate for the intended purpose.

When QI and analytics experts are integrated on QI projects, they can collaborate to identify what information is essential for the success of a project. This includes knowing about and selecting the right sources of data, applying the appropriate analysis, and delivering the information in a helpful format (whether a report, mobile application, dashboard or other analytic application).

This integration does not happen by itself -- it takes a concerted effort by the healthcare organization to bring these two groups of professionals together. The following tips are designed to enable healthcare organizations to maximize their potential for quality improvement.

  • Identify common goals and objectives. Although they come from different domains within a healthcare organization, analytics and QI professionals need to understand that their common ground is to generate and utilize insights into the operations of a healthcare organization, and identify and rectify quality and performance issues.
  • Provide basic cross-training. QI experts should have some basic training on key analytics topics ranging from what data is available and what kinds of analysis are possible or necessary for current quality issues, to ways in which that information can be communicated to those who need it. Likewise, analytics professionals should have some basic QI training, including the basics of various QI methodologies (Lean, Six Sigma, etc.) used within a healthcare organization, and how analytics enhances those methodologies.
  • Ensure executive support. Tight integration of the analytics resources on QI teams may not be the usual way of doing things within an organization, and it may encounter resistance from the managers of analytics resources, perhaps even the QI and analytics experts themselves. As is common with most changes within an organization, support at the management and executive levels is necessary to ensure that any barriers to this high level of integration on QI projects are overcome, and to help sustain the integration over the long term.
  • Share in the success. Be sure to recognize the important role that analytics experts have had in achieving goals when celebrating successful outcomes of QI initiatives. This will help demonstrate the value of analytics and QI collaboration, and will provide the healthcare analytics professionals the satisfaction of knowing they have directly contributed to improving healthcare.

Healthcare organizations must innovate to achieve their quality and performance improvement goals. In my experience, one strategy that has worked is to engage analytics professionals on front-line QI initiatives. Not only will this liberate them from the confines of the back office, but it also will enable them to see firsthand how the information and insight they help generate is used to enable safe, effective and efficient patient care.

About the author:
Trevor Strome, MSc, PMP, is an informatics/process improvement lead for the Emergency Program at the Winnipeg Regional Health Authority, and an assistant professor in the Faculty of Medicine's Department of Emergency Medicine at the University of Manitoba and Seven Oaks General Hospital. Trevor is the author of Healthcare Analytics for Quality and Performance Improvement; read more about the book here. Let us know what you think about the story; email editor@searchhealthit.com or contact @SearchHealthIT on Twitter.

Example of analytics in healthcare

This was first published in October 2013

Dig deeper on Clinical data analytics software and systems

Pro+

Features

Enjoy the benefits of Pro+ membership, learn more and join.

-ADS BY GOOGLE

SearchCompliance

SearchCIO

SearchCloudComputing

SearchMobileComputing

SearchSecurity

SearchStorage

Close