IF our health care delivery system is to flourish we need a more robust understanding of the relationship between disease and function as well as the relationship between the socioeconomic and disease status of a population and the needs of its individual members. Pragmatic health plan managers have long known that directing marketing dollars to certain zip codes can sufficiently restrain health care costs to make a real difference in their plans' economic health. Meanwhile social scientists labor to untangle the details that explain this and other, arguably more important, phenomena. The efforts of the VA Center for Health Quality, Outcomes and Economic Research in this supplement represent an important contribution toward this end.

These matters are not just the province of policy scholars. Physicians caring for their individual patients must increasingly navigate rules designed for the population from which their patients have been drawn. They also face normative comparisons of their practice patterns to that of other physicians caring for other patients. And resources are daily being distributed based upon the assumption that valid projections of health care resource needs are derivable from a manageable number of measurable parameters.

What is striking on reading these studies is the detail and complexity of the ecology of people, their socioeconomic context, and their diseases. Mental disorders predict fewer medical clinic visits but more emergency room visits and lower scores on a health plan's preventive indices (Hankin et al., in press). Within diabetes, points along a very broad spectrum of illness and disability can be efficiently and reliably defined using self-report instruments and relatively simple complication indices (Fincke et al., in press; Linzer et al., in press). Moderate alcohol use, nonsmoking, normal body mass index, exercise, and seat belt use predict self-reported health-related quality of life but paradoxically could not be convincingly shown to decrease health care utilization (Borzecki et al., in press). Whether one completes a health status questionnaire at home or in a clinic waiting room materially affects the resulting illness severity score (Miller et al., in press). Counterintuitively, self-report indices of physical and mental comorbidity were found to explain a mere third and quarter, respectively, of ambulatory health care resource consumption (Payne et al., in press). And, surprisingly, the average person who has served in the US Armed Services and chooses to use the Veterans Health Administration health care system carries more than twice the disease burden of otherwise similar nonusers (Rogers et al., in press).

Some of these findings will stimulate the thoughtful clinician to consider taking care of patients in different ways. Since post-traumatic stress disorder is as powerful a predictor of poor health status as depression, the careful clinician should screen for both conditions with equal vigilance.

These findings will also help clinicians, plan managers, and policy makers find the proper niche for some of the newer disease-focused tools like practice guidelines and disease state management methods. Every real health care encounter occurs in the kind of rich and interactive demographic, comorbid, and psychosocial context that these studies strive to describe. Therefore any instrument or construct built with a specific disease focus can reach its full potential only if it fully accounts for and accommodates this messy but inescapable reality.

Like most new knowledge, this work raises new questions. First, what useful actions should be taken based upon the ways in which disease, perceived well-being, function, and health resource need interrelate? If a given population contains 10% diabetics and 5% blind people, does the resource need change if all of the blindness occurs among diabetics? Should a health care system be designed with more walk-in capacity and fewer scheduled appointment openings if 20% of its population suffer post-traumatic stress disorder?

Second, how can these important correlations and interactions be made more accessible and user friendly? Can we expect that busy policy makers and health plan managers will delve into studies like this in order to wisely and equitably distribute resources? Can we expect individual physicians, each with a unique panel of patients, to be sufficiently facile with the truths unearthed in these studies to understand and express why their unique pattern of resource use or their unique success at achieving a given preventive index score is appropriate for their patients, even though they are outliers compared to the mean performance of physicians systemwide or nationwide?

In the past 2 decades, our perspective on health care has broadened to include function as well as physiology and populations as well as patients. The new horizons of this broadened perspective expose great expanses of unknown territory. These careful studies represent another step in the process of mapping the big picture.

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