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PURPOSE We wanted to assess the impact of an electronic health record-based diabetes clinical decision support system on control of hemoglobin A 1c (glycated hemoglobin), blood pressure, and low-density lipoprotein (LDL) cholesterol levels in adults with diabetes. METHODSWe conducted a clinic-randomized trial conducted from October 2006 to May 2007 in Minnesota. Included were 11 clinics with 41 consenting primary care physicians and the physicians' 2,556 patients with diabetes. Patients were randomized either to receive or not to receive an electronic health record (EHR)-based clinical decision support system designed to improve care for those patients whose hemoglobin A 1c , blood pressure, or LDL cholesterol levels were higher than goal at any offi ce visit. Analysis used general and generalized linear mixed models with repeated time measurements to accommodate the nested data structure. RESULTSThe intervention group physicians used the EHR-based decision support system at 62.6% of all offi ce visits made by adults with diabetes. The intervention group diabetes patients had signifi cantly better hemoglobin A 1c (intervention effect -0.26%; 95% confi dence interval, -0.06% to -0.47%; P = .01), and better maintenance of systolic blood pressure control (80.2% vs 75.1%, P = .03) and borderline better maintenance of diastolic blood pressure control (85.6% vs 81.7%, P = .07), but not improved low-density lipoprotein cholesterol levels (P = .62) than patients of physicians randomized to the control arm of the study. Among intervention group physicians, 94% were satisfi ed or very satisfi ed with the intervention, and moderate use of the support system persisted for more than 1 year after feedback and incentives to encourage its use were discontinued.CONCLUSIONS EHR-based diabetes clinical decision support signifi cantly improved glucose control and some aspects of blood pressure control in adults with type 2 diabetes. INTRODUCTIOND espite recent improvement trends in the United States, in 2008 less than 20% of patients with diabetes concurrently reach evidence-based goals for hemoglobin A 1c (glycated hemoglobin), systolic and diastolic blood pressure, and low-density lipoprotein (LDL) cholesterol levels.1,2 Care is unsatisfactory in both subspecialty and primary care settings, but because more than 80% of diabetes care is delivered by primary care physicians, effective strategies to improve diabetes care in primary care settings are urgently needed.Among the major barriers to better diabetes care is lack of timely intensifi cation of pharmacotherapy in patients who have not achieved recommended clinical goals. Many factors contribute to this problem, including competing demands at the time of the visit 3 and medication In theory, treatment intensifi cation and control of hemoglobin A 1c , blood pressure, and lipid levels in patients with diabetes mellitus could be improved by providing patient-specifi c and drug-specifi c clinical decision support at the time of a clinical encounter. Electronic health recor...

PURPOSEThe Chronic Care Model (CCM) provides a conceptual framework for transforming health care for patients with chronic conditions; however, little is known about how to best design and implement its specifi cs. One large health care organization that tried to implement the CCM in primary care provided an opportunity to study these issues. METHODSWe conducted a qualitative, comparative case study of 5 of 18 group clinics 18 to 23 months after the implementation began. Built on knowledge of the clinics from a previous study of advanced access implementation, data included in-depth interviews with organizational leaders and varied clinic personnel, observation of clinic care processes, and review of written materials.RESULTS Relatively small and highly variable care process changes were made during the study period. The change process underwent several marked shifts in strategy when initial efforts failed to achieve much and bore little resemblance to the change process used in the previously successful large-scale implementation of advanced access scheduling. Many barriers were identifi ed, including too many competing priorities, a lack of specifi city and agreement about the care process changes desired, and little engagement of physicians.CONCLUSION These fi ndings highlight specifi c organizational challenges with health care transformation in the absence of a blueprint more specifi c than the CCM. Effective models of organizational change and detailed examples of proven, feasible care changes still need to be demonstrated if we are to transform care as called for by the Institute of Medicine.

clinicaltrials.gov Identifier: NCT00652509.

Orthostatic hypotension (OH) is associated with hypertension and diabetes mellitus. However, in populations with both hypertension and diabetes, its prevalence, the effect of intensive versus standard systolic blood pressure (BP) targets on incident OH, and its prognostic significance are unclear. In 4266 participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) BP trial, seated BP was measured 3 times, followed by readings every minute for 3 minutes after standing. Orthostatic BP change, calculated as the minimum standing minus the mean seated systolic BP and diastolic BP, was assessed at baseline,12, and 48 months. The relationship between OH and clinical outcomes (total and cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, heart failure hospitalization or death and the primary composite outcome of non-fatal myocardial infarction, non-fatal stroke and cardiovascular death) was assessed using proportional hazards analysis. Consensus OH, defined by orthostatic decline in systolic BP ≥20 mm Hg and/or diastolic BP ≥10 mm Hg, occurred at ≥1 time point in 20% of participants. Neither age nor systolic BP treatment target (intensive, <120 mm Hg versus standard, <140 mm Hg) was related to OH incidence. Over a median follow-up of 46.9 months, OH was associated with increased risk of total death (HR=1.61, 95% CI 1.11–2.36) and heart failure death/hospitalization (HR=1.85, 95% CI 1.17–2.93), but not with the primary outcome or other prespecified outcomes. In patients with type 2 diabetes and hypertension, OH was common, not associated with intensive versus standard BP treatment goals, and predicted increased mortality and heart failure events.

Clinical inertia is defined as lack of treatment intensification in a patient not at evidence-based goals for care. Clinical inertia is a major factor that contributes to inadequate chronic disease care in patients with diabetes mellitus, hypertension, dyslipidemias, depression, coronary heart disease, and other conditions. Recent work suggests that clinical inertia related to the management of diabetes, hypertension, and lipid disorders may contribute to up to 80 percent of heart attacks and strokes. Clinical inertia is, therefore, a leading cause of potentially preventable adverse events, disability, death, and excess medical care costs. This paper addresses three specific objectives: (1) to present a conceptual model of clinical inertia that takes into account recent developments in human factors research, cognitive science, and organizational behavior; (2) to operationally define clinical inertia and propose simple clinical protocols that can be used to identify and map its incidence across populations of patients and physicians; and (3) to propose future research to reduce clinical inertia by specifically targeting the root causes of the problem. Ultimately, a better understanding of clinical inertia and the development of specific interventions to reduce it may be a productive strategy to reduce passive errors that contribute to hundreds of thousands of adverse events and tens of thousands of premature deaths annually in the United States.

Key Points Question How long does blood pressure remain lower compared with usual care after a 12-month intensive intervention (home telemonitoring and pharmacist management)? Findings In this follow-up of a cluster randomized trial of 326 patients with uncontrolled hypertension, research clinic measurements showed that home blood pressure telemonitoring with pharmacist management lowered blood pressure more than usual care in the first 18 months, but this was not sustained through 54 months. The results from routine clinical measurements suggested significantly lower blood pressure in the intervention group for up to 24 months. Meaning Long-term maintenance strategies may be needed to sustain blood pressure intervention effects over several years.

The objective of this study was to demonstrate a method to accurately identify patients with specific conditions from claims data for care improvement or performance measurement. In an iterative process of trial case definitions followed by review of repeated random samples of 10 to 20 cases for diabetes, heart disease, or newly treated depression, a final identification algorithm was created from claims files of health plan members. A final sample was used to calculate the positive predictive value (PPV). Each condition had unacceptably low PPVs (0.20, 0.60, and 0.65) when cases were identified on the basis of only 1 International Classification of Diseases, ninth revision, code per year. Requiring 2 outpatient codes or 1 inpatient code within 12 months (plus consideration of medication data for diabetes and extra criteria for depression) resulted in PPVs of 0.97, 0.95, and 0.95. This approach is feasible and necessary for those wanting to use administrative data for case identification for performance measurement or quality improvement.