1. Improving Care and Promoting Health in Populations: Standards of Medical Care in Diabetes—2020

Developers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials. To review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit. We updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information. We included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes. Teams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes. One hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001). Many CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.

Developed more than a decade ago, the Chronic Care Model (CCM) is a widely adopted approach to improving ambulatory care that has guided clinical quality initiatives in the United States and around the world. We examine the evidence of the CCM's effectiveness by reviewing articles published since 2000 that used one of five key CCM papers as a reference. Accumulated evidence appears to support the CCM as an integrated framework to guide practice redesign. Although work remains to be done in areas such as cost-effectiveness, these studies suggest that redesigning care using the CCM leads to improved patient care and better health outcomes.

The effectiveness of quality improvement (QI) strategies on diabetes care remains unclear. We aimed to assess the effects of QI strategies on glycated haemoglobin (HbA(1c)), vascular risk management, microvascular complication monitoring, and smoking cessation in patients with diabetes. We identified studies through Medline, the Cochrane Effective Practice and Organisation of Care database (from inception to July 2010), and references of included randomised clinical trials. We included trials assessing 11 predefined QI strategies or financial incentives targeting health systems, health-care professionals, or patients to improve management of adult outpatients with diabetes. Two reviewers independently abstracted data and appraised risk of bias. We reviewed 48 cluster randomised controlled trials, including 2538 clusters and 84,865 patients, and 94 patient randomised controlled trials, including 38,664 patients. In random effects meta-analysis, the QI strategies reduced HbA(1c) by a mean difference of 0·37% (95% CI 0·28-0·45; 120 trials), LDL cholesterol by 0·10 mmol/L (0·05-0.14; 47 trials), systolic blood pressure by 3·13 mm Hg (2·19-4·06, 65 trials), and diastolic blood pressure by 1·55 mm Hg (0·95-2·15, 61 trials) versus usual care. We noted larger effects when baseline concentrations were greater than 8·0% for HbA(1c), 2·59 mmol/L for LDL cholesterol, and 80 mm Hg for diastolic and 140 mm Hg for systolic blood pressure. The effectiveness of QI strategies varied depending on baseline HbA(1c) control. QI strategies increased the likelihood that patients received aspirin (11 trials; relative risk [RR] 1·33, 95% CI 1·21-1·45), antihypertensive drugs (ten trials; RR 1·17, 1·01-1·37), and screening for retinopathy (23 trials; RR 1·22, 1·13-1·32), renal function (14 trials; RR 128, 1·13-1·44), and foot abnormalities (22 trials; RR 1·27, 1·16-1·39). However, statin use (ten trials; RR 1·12, 0·99-1·28), hypertension control (18 trials; RR 1·01, 0·96-1·07), and smoking cessation (13 trials; RR 1·13, 0·99-1·29) were not significantly increased. Many trials of QI strategies showed improvements in diabetes care. Interventions targeting the system of chronic disease management along with patient-mediated QI strategies should be an important component of interventions aimed at improving diabetes management. Interventions solely targeting health-care professionals seem to be beneficial only if baseline HbA(1c) control is poor. Ontario Ministry of Health and Long-term Care and the Alberta Heritage Foundation for Medical Research (now Alberta Innovates--Health Solutions). Copyright © 2012 Elsevier Ltd. All rights reserved.