News

Congress and the President struggle to “repeal and replace” the Affordable Care Act (“Obamacare”). What Americans need for their health and healthcare, as well as those who provide and pay for it, seem lost in rhetoric. This is not a political debate but vague unscientific dialogue centered on words like “access” rather than what that means to patients seeking health care.  It is painfully clear that there are too many pressures for all the wrong reasons to achieve the legislative solutions so urgently needed.  Fundamental to our dilemma is the failure to understand and acknowledge the problems, without which there will be no successful solutions.

While the central issue is whether quality health care is a right or a privilege, the underlying considerations are simply financial.  A basic tenet of business to achieve a solution is to identify the problem, the need of the market.  One of the reasons that health care and health are such enigmas to identify the solution is that the problem is multifactorial and complex with competing constituencies.  Unraveling the ACA is difficult because it addresses this complexity and the linkages in its provisions.  ACA provisions do not merely focus on insurance coverage and finance; remarkably they had begun to solve the costs, quality and outcomes of care.

Quture embeds HFACS in QualOptima as an integral classification and causation nanocodes system.  QualOptima is available to healthcare providers to integrate quality management, risk management and credentialing on its unified database with analytics technology as Quture’s innovative and transformative Value Data Center.  QualOptima is an extraordinary experiential learning platform, designed for organizational, clinician and patient learning to achieve optimal outcomes.

One use of QualOptima is to reduce medical errors and transform patient safety processes.  Quture offers medical malpractice insurers and healthcare organization self-insured trusts the capability to:

• learn from errors based on aggregated data;
• embed proven intervention strategies into optimal clinical processes;
• calculate, track and report accurate adverse events data;
• coordinate risk management and insurer claims management processes;
• devise and implement healthcare provider disclosures with patients;
• report (transparent) errors as regulators’ requirements evolve;
• manage claims and defense settlements and trials, and
• achieve better measurement and data-driven decisions for granting clinical practitioner privileges based on current clinical competence, exceeding FPPE-OPPE standards.

Martin Makary, in his recent article[1] “Medical error—the third leading cause of death in the US.”  He begins with his observations: “The science of safety has matured to describe how communication breakdowns, diagnostic errors, poor judgment, and inadequate skill can directly result in patient harm and death.”

Dr. Makary’s perspectives of human factors in medical errors mirrors the positions of learning from errors and scientific approach of Quture.  He observes: “Human error is inevitable. Although we cannot eliminate human error, we can better measure the problem to design safer systems mitigating its frequency, visibility, and consequences.”

Quture advocates the strategy for hospitals to carry out a rapid and efficient independent investigation into deaths to determine the potential contribution of error, the very same words as Dr. Makary. He proposes a root cause analysis approach medico-legal protections to maintain anonymity would enable local earning while using. QualOptima HFCAS introduces a standardized data collection and reporting processes; such a standardized and common database is essential to an accurate national picture of the problem, its causes and solutions.

Healthcare Science

Optimal outcomes, clinical, operational and financial, depend upon creating a culture of learning from mistakes.   The Institute of Medicine’s goal of creating learning health systems depends upon advancing the science of safety.  Dr. Makary concludes his article stating: “To achieve more reliable health care systems, the science of improving safety should benefit from sharing data nationally and internationally, in the same way as clinicians share research and innovation about coronary artery disease, melanoma, and influenza. Sound scientific methods, beginning with an assessment of the problem, are critical to approaching any health threat to patients. The problem of medical error should not be exempt from this scientific approach. More appropriate recognition of the role of medical error in patient death could heighten awareness and guide both collaborations and capital investments in research and prevention.”

HFACS provides new methods to restructure design of analysis of adverse events, accidents, human and system errors.  In real-time settings, like hospitals and intake of medical malpractice claims, this is retrospective but with a prospective component. In real-time, methods involve the following seven (7) steps:

• Identification and reporting of events in single incidents (cases), whether near misses or adverse event;
• Triage of single incidents AND those single cases in the context of aggregated data for prioritization of further actions;
• Investigation of single incidents in the context of identifying opportunities to improve:

International Classification Systems

The preceding Section HFACS in Health Care Internationally discusses the work of Bill Runciman, M.D., in Australia and the international human factors classification systems in the patient safety endeavors of the World Health Organization (WHO) and the World Alliance for Patient Safety.  In the United States, others groups have developed their own human factors classification systems based on the initial James Reason concepts, but without the expertise from the extensive meta-analysis for development of HFACS by Drs. Shappell and Wiegmann.

While Dr. Shappell was a Commander in the United States Navy, reporting to the Admiral of the Atlantic Fleet, he was tasked to reduce an alarming rate of aviation accidents.  Working with his associate, Doug Wiegmann, Ph.D., who was then at the Pensacola Air Station, they conducted a meta-analysis of over 16,000 accidents involving U.S. Navy/Marine Corps (1990-98), U.S. Air Force (1991-97), U.S. Army (1992-98).  Their collaborative human factors meta-analysis led to what is now the Human Factors Analysis & Classification System (HFACS).  Dr. Shappell continues to conduct studies of both civil and military accidents as part of an ongoing project with NASA and the U.S. Navy/Marine Corps.  Previously, he served as Chief, Human Factors Branch US Naval Safety Center, then Head, Aeromedical Department US Naval Safety Center Reserve Unit (1999-2004).

Healthcare organizations, without human factors expertise, have developed a variety of unsuccessful systems characterized as patient safety human factors classification systems

and taxonomies.  methods have been used to analyze medical malpractice claims data.  Despite excellent endeavors to date, these methods have not significantly impacted preventable medical errors and reduced patient harm from those efforts.  The most obvious include:

• Joint Commission Patient Safety Event Taxonomy (PSET);
• CRICO (Risk Management Foundation affiliated with Harvard); and
• MedStar Health, National Center for Human Factors in Healthcare.

There is a significant experience internationally with human factors classification and taxonomy systems in healthcare organizations and liability insurance claims.  These systems and processes date back to the 1990’s, so the evidence is that these have had little or no impact on the rate of preventable medical errors in the United States and most other countries globally.

The study from Dr. Makary of Johns Hopkins University Medical School estimated that medical error is the third biggest cause of death in the US and therefore requires greater attention. “Medical error leading to patient death is under-recognized in many other countries, including the UK[i] and Canada[ii].”  The study recognizes the inherent problem in existing systems, similar to Quture’s experiences, that the International Classification of Diseases (ICD) codes established for billing limit effectiveness of human factors analysis and classification.