The cornerstone of diabetes care is management of risk factors for vascular complications, particularly control of blood pressure, cholesterol, and blood glucose. Most treatment guidelines call for lowering hemoglobin A1c below 7 percent, blood pressure below 130/80, and low-density lipoprotein (LDL)-cholesterol below 100 mg/dL (2.59 mmol/L) (Grundy et al. 2004; American Diabetes Association 2008;). Despite demonstrating substantial health benefits, trials that have compared tight control strategies to conventional approaches have also consistently shown that a large proportion of patients fail to reach targets for A1c (Abraira et al. 1995; UKPDS Study Group 1998a; Patel et al. 2008;) and blood pressure (Hansson et al. 1998; UKPDS Study Group 1998b;) even after a battery of treatments. In one of the largest trials of blood glucose control, the United Kingdom Prospective Diabetes Study (UKPDS) (UKPDS Study Group 1998a), for example, the median A1c in the intensive treatment group over the course of the study was 7.5 percent, meaning that most patients were unable to achieve or maintain the 7 percent target, even though these patients were early in the course of diabetes. In the Hypertension Optimal Treatment (HOT) trial (Hansson et al. 1998), over half of subjects randomized to the lowest diastolic blood pressure (DBP) target failed to reach it. Successful control of diabetes risk factors depends on a number of factors, including a patient's baseline value of the risk factor, the efficacy of treatment, pathophysiological factors, treatment contraindications and side effects, and each patient's willingness to accept multiple and potentially burdensome treatments. Guidelines often emphasize the benefits of treating to targets without consideration of their costs and side effects, and often without reference to the potential diminishing effects of adding a third, fourth, or fifth medication. Discontinuation rates from A1c-lowering therapies in the UKPDS ranged from 10 to 25 percent over a 3-year period (UKPDS Study Group 1995), suggesting that the side effects or inconvenience of these treatments are significant even among clinical trial volunteers. Little quantifiable information exists on the necessary resources and potential harms associated with a strategy of treating to target levels of risk factors. For patients having multiple uncontrolled risk factors, the overall treatment burden could be substantial. Although trials of intensive risk factor control often report improved health outcomes on average, these trials often fail to provide information that is critical for guiding decision making and policy making in the real world (Hayward, Hofer, and Vijan 2006). First, these studies rarely report the incremental efficacy of each successive treatment in the intensification regimen, and without these data, the benefits of repeatedly adding or titrating medications cannot meaningfully be weighed against their harms. Second, because trial patients tend to be healthier, more adherent, and more likely to be screened for nonresponse and intolerance to treatment (Nallamothu, Hayward, and Bates 2008), the rate at which targets are reached in real-world settings is likely to be significantly lower than that observed in the clinical literature, and the polypharmacy requirements could be much higher. We therefore developed a simulation model that integrates three of the key determinants of attaining targets—efficacy of treatment, individual variation in treatment response, and treatment tolerance—to estimate the impact of a treat-to-target strategy for a nationally representative diabetic population. We assess the attainability of targets across three risk factors and the level of polypharmacy required. We conclude with a discussion of the implications of our findings for patient care and quality measurement.