Why variance management is key to improving healthcare.
By John Feldman, Founder and Chairman of Applied Pathways
How do you know you are successful if you don’t set goals? In healthcare — and everywhere else, for that matter — quality is defined as achieving your desired outcomes.
But just what is “variance,” and how does it impact quality?
In statistics, variance calculates how data is distributed about the mean or expected value. In other words, variance measures quality by letting you know how close you are to meeting the goals you intended to achieve. Higher variance means lower quality.
In manufacturing, quality is determined by how closely the final product matches the desired specifications.
To understand just how variance management can impact healthcare, let’s first take a look at how quality control experts in other industries elucidate the relationship between quality and variance.
That’s nice, but can you do it again?
Engineer and statistician W. Edwards Deming, credited with helping Japan improve the quality of its manufacturing industry after World War II, defined quality as “predictability,” and called variance “the enemy of quality.” To achieve an intended outcome, Deming thought it was important to plan for common-cause variation, which can be predicted, and special-cause variation, which cannot.
Harold F. Dodge, one of the principal architects of the science of statistical quality control, said, “You cannot inspect quality into a product.” In other words, once the inspection takes place, it’s too late. Rather, data from the quality inspection needs to be utilized to continually improve the process.
Management consultant Joseph Juran, who focused on management training and the human element of quality control for a variety of businesses, stated that quality is “a fitness for use.” Juran said that resistance to change often causes a reduction in quality, and insisted that high-performance quality management systems must contain planning, control and improvement (known as the “Juran Trilogy”).
Businessman Philip B. Crosby, who developed the concept of Zero Defects while working as senior quality engineer at aircraft manufacturer The Martin Company, defined quality as “a conformance to requirements.” He warned against the high cost of nonconformance, and said that the desired performance standard of zero defects could only be achieved through the proper management system.
Historically, healthcare has been a late adopter of established practices shown to work in other industries. But what if healthcare managed quality and variance in the same way other industries do?
Making a list, checking it twice
The National Academies’ Health and Medicine Division (HMD), formerly The Institute of Medicine (IOM), defines quality as, “The degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge.”
Author and expert on the challenges of modern medicine Atul Gawande makes the case that something as simple as a checklist can substantially improve healthcare outcomes (“The Checklist Manifesto: How to Get Things Right”).
To that end, the HMD outlines six specific aims that a healthcare system must fulfill to deliver quality care:
Safe: Care should be as safe for patients in healthcare facilities as in their homes;
Effective: The science and evidence behind health care should be applied and serve as the standard in the delivery of care;
Efficient: Care and service should be cost effective, and waste should be removed from the system;
Timely: Patients should experience no waits or delays in receiving care and service;
Patient centered: The system of care should revolve around the patient, respect patient preferences, and put the patient in control;
Equitable: Unequal treatment should be a fact of the past; disparities in care should be eradicated.
Knowledge is power
The knowledge underpinning evidence-based medicine (EBM), which optimizes decision making by emphasizing the use of evidence, is evolving so rapidly that clinicians cannot keep pace. As sophisticated analytics, deep learning, machine learning and big data accelerate learning, the challenge for healthcare organizations will be to determine how to close the ignorance gap — the delta between evidence and awareness. A knowledge management ecosystem will bridge the gap between knowledge and ignorance, enabling healthcare organizations to reproducibly achieve their intended outcomes by keeping variance low.
The objective of EBM is to apply best practices to achieve intended outcomes. The purpose of knowledge management is to deliver wisdom to those who need to apply it. As medical knowledge advances, so should the care delivered to patients.
What do you think? Are you working to reduce variance in your organization? If so, let us know what steps you are taking and we’ll write about the responses we get.