OBJECTIVE -Understanding how individuals weigh the quality of life associated with complications and treatments is important in assessing the economic value of diabetes care and may provide insight into treatment adherence. We quantify patients' utilities (a measure of preference) for the full array of diabetes-related complications and treatments.RESEARCH DESIGN AND METHODS -We conducted interviews with a multiethnic sample of 701 adult patients living with diabetes who were attending Chicago area clinics. We elicited utilities (ratings on a 0 -1 scale, where 0 represents death and 1 represents perfect health) for hypothetical health states by using time-tradeoff questions. We evaluated 9 complication states (e.g., diabetic retinopathy and blindness) and 10 treatment states (e.g., intensive glucose control vs. conventional glucose control and comprehensive diabetes care [i.e., intensive control of multiple risk factors]). CONCLUSIONS -End-stage complications have the greatest perceived burden on quality of life; however, comprehensive diabetes treatments also have significant negative quality-of-life effects. Acknowledging these effects of diabetes care will be important for future economic evaluations of novel drug combination therapies and innovations in drug delivery. RESULTS Diabetes Care 30:2478-2483, 2007D iabetes significantly increases an individual's risk of developing multiple microvascular and cardiovascular complications, and the risk of these complications can be significantly reduced with intensive and comprehensive diabetes care (1). Current recommendations for the ideal risk factor targets (e.g., A1C Ͻ7%) and specific therapies (e.g., prophylactic aspirin) for diabetes care reflect the findings of multiple clinical trials (2-4).Although intensive and comprehensive diabetes care may generate significant health benefits, the current level of adoption of comprehensive diabetes care is incomplete. Quality-of-care studies indicate that there has been a steady rise in the proportion of patients taking beneficial medications such as aspirin and that there have been reductions in the proportion of patients with poor risk factor control (5). At the same time, large proportions of patients continue to have poor glycemic (20%), blood pressure (33%), and cholesterol control (40%) (5). These ongoing deficiencies have led to a large public investment in diabetes quality improvement programs (6).The success of these quality improvement efforts depends, in part, on whether or not patients are willing to take the multiple medications that comprise comprehensive diabetes care. Patients' willingness to adopt this care is likely to be determined, in part, by their perceptions of the relative quality-of-life effects of complications and treatments (7,8). These perceptions are also critical for economic evaluations of quality improvement efforts and treatment innovations. The development of combination drugs such as the polypill, a proposed treatment combining an aspirin, a diuretic, an ACE inhibitor, a ␤-blocker, fo...

During the first 4 years of the HDC, multiple improvements in diabetes care were observed. If these improvements are maintained or enhanced over the lifetime of patients, the HDC program will be cost-effective for society based on traditionally accepted thresholds.

Approximately 2% and 4% of ICU patients discharged to the ward are readmitted within 48 and 120 hours, within a median time of 3 days. Medical patients in academic hospitals are more likely to be readmitted than patients in community hospitals without residents. ICU readmission rates could be useful for policy makers and investigations into their causes and consequences.

Background Strains on the capacities of intensive care units (ICUs) may influence the quality of ICU-to-floor transitions. Objective To determine how 3 metrics of ICU capacity strain (ICU census, new admissions, and average acuity) measured on days of patient discharges influence ICU length of stay (LOS) and post–ICU discharge outcomes. Design Retrospective cohort study from 2001 to 2008. Setting 155 ICUs in the United States. Patients 200 730 adults discharged from ICUs to hospital floors. Measurements Associations between ICU capacity strain metrics and discharged patient ICU LOS, 72-hour ICU readmissions, subsequent in-hospital death, post–ICU discharge LOS, and hospital discharge destination. Results Increases in the 3 strain variables on the days of ICU discharge were associated with shorter preceding ICU LOS (all P < 0.001) and increased odds of ICU readmissions (all P< 0.050). Going from the 5th to 95th percentiles of strain was associated with a 6.3-hour reduction in ICU LOS (95% CI, 5.3 to 7.3 hours) and a 1.0% increase in the odds of ICU readmission (CI, 0.6% to 1.5%). No strain variable was associated with increased odds of subsequent death, reduced odds of being discharged home from the hospital, or longer total hospital LOS. Limitation Long-term outcomes could not be measured. Conclusion When ICUs are strained, triage decisions seem to be affected such that patients are discharged from the ICU more quickly and, perhaps consequentially, have slightly greater odds of being readmitted to the ICU. However, short-term patient outcomes are unaffected. These results suggest that bed availability pressures may encourage physicians to discharge patients from the ICU more efficiently and that ICU readmissions are unlikely to be causally related to patient outcomes. Primary Funding Source Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Society of Critical Care Medicine.

Background ICU readmission rates are commonly viewed as indicators of ICU quality. However, definitions of ICU readmissions vary, and it is unknown which, if any, readmissions are associated with ICU quality. Objective Empirically derive the optimal interval between ICU discharge and readmission for purposes of considering ICU readmission as an ICU quality indicator. Research Design Retrospective cohort study Subjects 214,692 patients discharged from 157 U.S. ICUs participating in the Project IMPACT database, 2001–2008. Measures We graphically examined how patient characteristics and ICU discharge circumstances (e.g., ICU census) were related to the odds of ICU readmissions as the allowable interval between ICU discharge and readmission was lengthened. We defined the optimal interval by identifying inflection points where these relationships changed significantly and permanently. Results 2,242 patients (1.0%) were readmitted to the ICU within 24 hours; 9062 (4.2%) within 7 days. Patient characteristics exhibited stronger associations with readmissions after intervals greater than 48–60 hours. By contrast, ICU discharge circumstances and ICU interventions (e.g. mechanical ventilation) exhibited weaker relationships as intervals lengthened, with inflection points at 30 to 48 hours. Due to the predominance of afternoon readmissions regardless of time of discharge, using intervals defined by full calendar days rather than fixed numbers of hours produced more valid results. Discussion It remains uncertain whether ICU readmission is a valid quality indicator. However, having established two full calendar days (not 48 hours) following ICU discharge as the optimal interval for measuring ICU readmissions, this study will facilitate future research designed to determine its validity.