Understanding Health Care as a Complex System

Abstract

As the United States Embarks on health care reform, policy makers speak of using a variety of levers to control the health care system and its accelerating costs. These levers include a variety of regulations that are enforced through surveys, certifications, payments, and penalties. However, these mechanical approaches often lead to unintended consequences. This is due to the enormous complexity of the health care system—both in lay terms by its complicated design and in scientific terms by its nonlinear, dynamic, and unpredictable nature. To help guide future policies and avoid the unanticipated consequences of regulation, policy makers and physicians need to understand health care as a complex system and apply the principles of complexity science to achieve its goals. In contrast to mechanical systems in which component parts interact linearly to produce a predictable output, the components of complex systems interact nonlinearly over multiple scales and produce unexpected results. The output of a mechanical system can be controlled by manipulating each of its parts, while the output of a complex system is dynamic, behaving differently according to its initial conditions and feedback. For example, the health care system comprises networks of components (hospitals, clinics, nursing homes, rehabilitation units, patient homes, families, and patients) that interact nonlinearly on different scales (the patient, family, medical center, and government), and often produce unintended consequences (adverse drug reactions, nosocomial infections, rehospitalizations, and functional decline). As more regulations are created to control the behavior of a complex system, the more the system may deviate from a desired outcome.1 Commenting on the complexity of the Australian health care system, Sturmberg et al2 wrote that the prevailing trends to use disease protocols, financial levers, and siloed programs to manage the health care system are fatally flawed and will lead to unintended consequences. For example, pay-for-performance and value-based payment models that aim to improve hospital care at lower cost may encourage overly aggressive treatment without concern for life expectancy or adverse effects. Contrary to expectation, these models have had no effect on mortality3 or Medicare spending.4 Similarly, clinical practice guidelines intended to improve quality of care and reduce health care variations have not reduced socioeconomic disparities in the treatment of diabetes5 and could increase the medication costs of patients with multiple chronic conditions.6 If health care is viewed as a complex rather than a mechanical system, several of its intrinsic properties can be exploited to influence its dynamic behavior and guide it in a more favorable direction. These properties include nonlinear interactions of component parts, emergent, self-organized behavior, and the dependence on simple rules.