Many factors influence patients' decisions to seek medical care when they experience symptoms of illness. Different factors influence the ability of patients to enter the health care system once they decide they wish to. Yet a different set of considerations affect the provision of timely and effective care. For a number of surgical conditions, delays in providing definitive care are especially likely to increase the frequency of serious adverse outcomes, including death, immediate complications, and long-term disability. For these delay-sensitive conditions, we currently understand very little about the relationship between time to treatment and outcomes, which components of this total time are the most important determinants of outcome, and which components may be modifiable. Past work has focused on conditions such as myocardial infarction and trauma and has emphasized particular segments of time (e.g., time from injury to hospital; time from onset of chest pain to emergency room door). None has articulated a conceptual framework that encompasses the full range of factors that might influence delays. These include patient factors (knowledge, beliefs, and coping strategies), physician factors (knowledge, diagnostic acumen), hospital factors (availability of diagnostic tests and operating rooms), and health system factors (health insurance, utilization management, gatekeeping). We propose to study three delay-sensitive conditions: appendicitis, ectopic pregnancy, and intestinal obstruction. In phase 1, we will review medical records retrospectively to establish the relationship between overall time to treatment and health outcomes and to examine variability in different components of this time. Multivariate analysis will permit us to examine the effect of time to treatment after adjustment for age and comorbid conditions. In phase 2, we will gather data concurrently from patients and their physicians, as well as from medical records, to assess the full range of patient, physician, and health system factors contributing to variability in time to treatment. These analyses will substantially improve our understanding of the relationship between time to treatment and health outcomes. Studying three conditions will permit some initial observations about how unique or generalizable these relationships are in different clinical settings. These data may also lead to hypotheses about which factors associated with delays might be modifiable, leading to the design of specific interventions to reduce delays and improve outcomes.
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