information required to understand how and why things go wrong and how they can best be improved can rarely be found in large national datasets. Studies of malpractice claims provide the greatest series, but much of this type of work is based on point of care research. Observational field studies, focused interviews, and other qualitative research techniques can provide critical information. However, quantitative assessments are also important; de Leval used statistical modeling to document the relationship between intraoperative errors and postoperative outcomes. Other techniques such as statistical process control charts can help to document the results of an intervention and distinguish them from chance. Human factors engineering, cognitive psychology, and organizational behavior are just a few examples of the disciplines that can provide critical tools for research in this area (Table 7.2).

Optimizing the Health Care Delivery System

Overview

In the context of our conceptual model, we consider the health care delivery system to represent the external factors that influence and act upon the various micro-systems of care. Aspects of the delivery system – the “macro environment” – include the workforce, payment, and the social context. Each of these elements is influenced by health policy and regulatory changes. To practicing clinicians, this environment is almost invisible. Nonetheless, it directly shapes how we function in various micro-systems and how we make choices about treating patients. As a result, the delivery system has far-reaching effects in health care. Despite the important influence of these external forces, health policy evaluation is rarely the focus of surgical scientists. We will consider two areas of scientific inquiry related to the delivery system: policy evaluation and assessing the surgical workforce

(Table 7.1).