The Evolution & History of Quality Improvement in Healthcare

Now using AI we can achieve true population health and equity

Presentation Background:

It has been more than 20 years since the epic publications of “The Quality Chasm” and “To Err is Human”.  No longer could quality be assumed in our hospitals and with our providers.  In the ensuing 25 years, we’ve been flooded with hundreds of quality indicators.  Methodologies such as Lean, Six Sigma, PDCA, and others have been developed and implemented.  Accrediting organizations and payors have placed huge demands on the health care system to acquire and submit data.

But despite “pay for performance” and data transparency, have we made progress? The life expectancy and maternal mortality in the USA is declining. Medical errors according to a recent study is the third leading cause of death- behind cancer and heart disease.  Indicators may have improved, but has QUALITY improved? Is the patient better off?

Today, artificial intelligence is expanding exponentially with huge potential to improve health care.  Dr. Berkowitz will discuss national best practices that must be implemented to stay ahead of the curve and truly deliver, in an era of transparency, the quality of care our patients deserve, with the goal of achieving true population health and health equity.

       “Despite these advances, the life expectancy in the USA has declined.”

Presentation Objectives:

  1. Discuss the four stages of quality improvement in health care during the last 20 years.
  2. Review health care outcomes and address the issue of whether we have improved quality outcomes during this time and the necessity to achieve health equity.
  3. Discuss the effect of COVID-19 on achieving quality goals.
  4. Review national best practices from organizations that have materially improved patient outcomes.
  5. Discuss the critical role of artificial intelligence in the future of quality improvement.