Patient, clinician, and health system factors may all contribute to suboptimal management of dyslipidemia. Drawing from the Health Belief model,24
the Landon et al. health care organization model,25
and the Jaen et al. competing demands model,26
we have developed a conceptual model () for how these factors interact. A theoretical model should have face validity, provide measurable variables, and enhance understanding beyond what would be expected from consideration of individual factors affecting preventive service delivery. In our conceptual model, we have incorporated the concept of patient perception of risk and subsequent behavior from the Health Belief model; the association between detailed structural characteristics of health systems and physician behavior from Landon's model; and the role of physician characteristics and the idea of competing interests from the Jaen et al. model.
Conceptual model of patient, clinician, and health system factors affecting management of cholesterol in high-risk patients.
The Health Belief model argues that health behaviors are related to personal beliefs about susceptibility to disease, seriousness of disease, benefit of intervention, and risk of intervention. In this model, individuals who do not believe they are at high risk of disease are unlikely to pursue preventive health behavior even if the benefits of the behavior are high and the risks are low, and individuals who believe they are at high risk of disease may pursue preventive health behavior even if the benefits are low and the risks are high.24
This model has proven useful in understanding and predicting many preventive health behaviors, including diet and exercise. However, the model is not as useful in examining the barriers to acting on such beliefs, i.e., barriers related to the structural organization of the health care system and barriers related to specific aspects of the health care visit, such as limited time. In the Health Belief model, the barriers are limited primarily to the patient's perceived barriers to behavior change.
In contrast, the Landon et al. model of health care organization focuses on characteristics of the health care system that can influence health care delivery.25
In the Landon et al. model, disease processes and outcomes can be influenced by financial incentives, management strategies such as utilization review, structure of care such as the location of the practice site and staffing patterns, and finally normative influences such as the culture of the organization. The strengths of this model are that it details health plan and provider group characteristics that are probably influential but have not been the focus of extensive research. Such a model is extremely useful in conceptualizing changes to health care organizations in order to improve care, but does not necessarily address the patient's and provider's perceptions of risk or barriers nor their interaction with the health system.
Finally, the Jaen et al. health care model is posited on a theory of competing interests.26
In the Jaen et al. model, the patient, the physician, and the practice environment are separate domains that interact during the health care visit. The model emphasizes the physician's role in delivering preventive services, specifically, physician's skills and attitudes. It also puts forth the idea of competing or alternative demands for the physician's time as a physician barrier. This model is extremely useful for illustrating the physician's perceptions of barriers to provision of health services and is also valuable in that it empathizes with the clinician and pinpoints a potentially reversible barrier rather than placing blame on the individual clinician's character. As a result of research showing that physician-level variation is small compared with patient and health system variation, we believe that the physician's behavior is more heavily influenced by the environment of the health system, e.g., variable such as “lack of time” may be more of a health system characteristic than a physician-level characteristic, and that women's agendas for screening play a more important role.
Our model postulates that perceptions of the risks and barriers to screening and treatment of CVD risk factors will affect the clinician's behavior and the patient's behavior during the health care visit. We further hypothesize that these perceptions can be partially predicted from patient characteristics such as gender. In addition, the health system structure affects screening and treatment of CVD risk factors by affecting clinician behavior and patient behavior. We use this model in framing the following review of patient, clinician, and health system variables that may contribute to gender differences in management and will refer back to it throughout the paper. Although conceptualized for CVD risk factor management, this model may easily be applied to understand gender differences in the management of other diseases as well.