Addressing Issues

Professional Training: Preparing Providers for Systems Change

Important Concepts for Health Care Providers

The following is a review of concepts that will help health care professionals effectively contribute to the process of systems change.

Understanding Systems

Clinical systems improve when changes are made in the performance of the system, rather than in the performance of individual physicians or other professionals. A system is defined as "a set of interdependent elements interacting to achieve a common aim." This definition emphasizes the importance of interdependence and interaction. For example, elements in the system that work to obtain a patient's A1C value usually include:

• People - doctors, nurses, laboratory technicians, phlebotomists, and receptionists
• Technology - automated analyzers, computerized reports, patient records, etc.

The elements alone do not constitute the system - rather the elements plus their interactions constitute the system.

The patient safety arena has taught health care teams a great deal about looking for root causes of problems in the system rather than blaming individual professionals when things go wrong. Greater improvement is leveraged by changing the patterns of interaction among the elements of the system and in redesigning the overall flow of work rather than trying to improve the individual elements. For example, using a registry and call-back system will increase health care professionals' implementation of standards of care more than their participation in continuing education about the importance of standards of care. The registry provides information to manage a population of people with diabetes in addition to critical information at the time of a patient's visit.

Continuing education for health care professionals is traditionally a passive activity that provides updated information on best practices. Unless these best practices are integrated into the system of care, the process of care is rarely improved. By understanding the systems involved in delivering care, health care professionals can gain insight into existing opportunities for improvement. System change tools such as flowcharts, cause-and effect diagrams, and registry data are used to achieve clinical improvements.

Efficacy vs. Effectiveness

Clinical efficacy is the desirable outcome that is associated with an intervention under ideal circumstances such as in clinical trials. For example, the Diabetes Control and Complications Trial demonstrated that:

• intensive management compared with standard care resulted in significant lowering of A1C.
• improved control resulted in a 35 percent decrease in microvascular complications for each one percent reduction in A1C.

Clinical effectiveness associates the desirable outcomes with an intervention in the real world. For example, Health Partners of Minnesota provides valid and reliable information for physician/provider groups to use in their efforts toward continuous improvement of patient care and outcomes. As a result, optimal diabetes care results (A1C <8.0 + LDL <130 + BP < 130/85 + No Tobacco + Daily Aspirin) tripled between 1999 and 2005.  Between 1994 and 2005, eye complications decreased by 20 percent, amputations by 55 percent, and heart attacks by 29 percent. For further information visit www.healthpartners.com/files/28455.pdf.

The difference between the efficacy and effectiveness of an intervention defines the performance "gap" described in the How section. Implementation of systems of care can successfully bridge the gap and result in improved clinical outcomes. These systems are developed and implemented through multiple small-scale improvements in the components of the health care delivery system.

Individual Competency vs. System Capability

Individual competency requires individual health care professionals to attain, demonstrate and maintain competency within their discipline. For example, physicians attend an accredited medical school, train in an accredited residency, become board certified, and complete ongoing CME and recertification requirements. The premise is that if the individuals competently practice their discipline, then the standards of care will always be met. This fails to occur, however, for three reasons.

• The complexity of clinical needs for numerous chronic diseases makes it difficult for individual health care professionals to function effectively without some form of technological assistance.
• Even the most competent health care professionals will fail to perform their best if they are not supported by appropriate systems.

• Definition System capability refers to coordination of the components of clinical care to ensure achieving the desired outcomes.

  Competency will preserve the core of practice but it is not able to stimulate the progress and actions that are needed to continually improve care.

System capability refers to coordination of the components of clinical care to ensure achieving the desired outcomes, such as use of registries and recall systems to remind patients of the need for annual influenza vaccinations. System support of health care professionals results in improved process and clinical outcomes. Continuous striving to improve the systems of care stimulates progress to better care.

Clinical Research vs. Quality Improvement

Clinical research involves trials conducted to test if a single variable (medication, procedure, counseling) in a stable setting will result in a difference between the control and study groups. All other variables are controlled in an attempt to minimize variation. When applied in the clinical practice environment, however, control over confounding variables is lost and the results may differ from those demonstrated in the trial.

Quality Improvement is used in systems that are not tightly controlled. Multiple small changes are made and evaluated to determine how best to achieve optimal outcomes. For more information, click here.

Enumerative vs. Analytic Statistics

Enumerative statistics are used in clinical research to evaluate the outcome of testing a hypothesis. The analysis assumes a stable system - one in which all variables are held constant except the one under study. The goal is to estimate whether the outcomes between the control and study group are different. The statistics ascribe a degree of confidence to the accuracy of the estimate.

Analytic statistics are used to evaluate clinical improvement such as Plan-Do-Study-Act (PDSA) cycles. The goal of the analysis is to determine the stability

of the process producing the data. For example, will the patient recall system that increased the rate of eye exams from 36 percent to 70 percent consistently result in the higher percentage of patients having annual exams? In this example, the accuracy of the measure is not the issue - was the improvement in the rate of eye exams 70 percent or 68 percent or 72 percent? Rather, if the process is statistically stable, one can assess its current performance and take action either to predict future performance or to measure the effects of an improvement intervention. For example, now that eye exam rates have improved to 70 percent, how can we further improve the system to increase the rate to >90 percent?

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