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OBJECTIVE—The Diabetes Care Protocol combines task delegation (a practice nurse), computerized decision support, and feedback every 3 months. We studied the effect of the Diabetes Care Protocol on A1C and cardiovascular risk factors in type 2 diabetic patients in primary care.
RESEARCH DESIGN AND METHODS—In a cluster randomized trial, mean changes in cardiovascular risk factors between the intervention and control groups after 1 year were calculated by generalized linear models.
RESULTS—Throughout the Netherlands, 26 intervention practices included 1,699 patients and 29 control practices 1,692 patients. The difference in A1C change was not significant, whereas total cholesterol, LDL cholesterol, and blood pressure improved significantly more in the intervention group. The 10-year coronary heart disease risk estimate of the UK Prospective Diabetes Study improved 1.4% more in the intervention group.
CONCLUSIONS—Delegation of routine diabetes care to a practice nurse combined with computerized decision support and feedback did not improve A1C but reduced cardiovascular risk in type 2 diabetes patients.
Improving patients’ outcomes, in order to reduce cardiovascular risk, remains one of the most important goals in diabetes care. Structured and regular review of patients has been shown to improve the process of care (1), and team changes and case management have been shown to improve glycemic control (2). Computerized decision support systems (CDSSs) have been shown to improve practitioners’ performance (3), and feedback on performance given to primary care physicians (PCPs) has been demonstrated by Ziemer et al. (4) to lower patients’ A1C levels and improve practitioners’ behavior.
Against this background, the Diabetes Care Protocol (DCP) was developed, which reduced patients’ cardiovascular risk in a before-after study (5). The current randomized clinical trial aims to investigate the effects of the DCP on A1C and cardiovascular risk in type 2 diabetic patients in primary care.
Primary care practices throughout the Netherlands that were not involved in other diabetes care improvement programs were block randomized to intervention (26 practices) or the control group (29 practices). The number of PCPs working in each practice and the presence of a practice nurse before intervention were taken into account before randomization. The intervention, also described elsewhere (5), consisted of 1) diabetes consultation hour run by a practice nurse, 2) a CDSS that contained a diagnostic and treatment algorithm based on the Dutch type 2 diabetes guidelines (6) and provided patient-specific treatment advice, 3) a recall system, and 4) feedback every 3 months regarding the percentage of patients meeting the treatment targets (cessation of smoking, A1C <7%, systolic blood pressure <140 mmHg, total cholesterol <4.5 mmol/l, LDL cholesterol <2.5 mmol/l, and BMI <27 kg/m2) on both the practice and the patient levels (6). The PCPs were advised that they should prescribe new medication and refer patients if necessary. The control group continued with the same diabetes care that they had received before entering the study, which means that diabetes care was provided by the PCP or by a practice nurse under PCP responsibility. The University Medical Center Utrecht ethics committee approved the study, and patients provided written consent.
From the 171,821 registered patients, all type 2 diabetic patients were identified. Patients who had a short life expectancy, were unable to visit the primary care practice, or were receiving diabetes treatment from a medical specialist were excluded. Initially, 3,979 patients were eligible (2,136 in the control group and 1,843 in the intervention group), but 548 subjects refused to participate (409 control and 139 intervention subjects), and an additional 40 (35 control and 5 intervention subjects) failed to participate for unknown reasons (for both groups, P < 0.05). The final, mainly Caucasian, study population consisted of 3,391 patients (1,692 control and 1,699 intervention). After 1 year, 2,841 patients (1,389 control and 1,452 intervention) completed a follow-up examination; 187 patients (115 control and 72 intervention) refused to participate in the final measurements, and 13 others (12 control and 1 intervention) failed to show for unknown reasons (for both groups, P < 0.05). The groups did not differ with regard to the number of patients who died, moved, became terminally ill, or were referred to a specialist.
Between March 2005 and August 2007, patients were each seen twice for annual diabetes checkups. Patients who did not show received one reminder. In the CDSS, age, sex, ethnicity, duration of diabetes, and smoking habits were registered. A1C, total cholesterol, and HDL cholesterol were measured in local laboratories. LDL cholesterol was calculated. Blood pressure was measured according to a standard operating procedure.
The 10-year coronary heart disease (CHD) risk estimate, as established by the UK Prospective Diabetes Study (UKPDS) (7), was calculated using the above-mentioned variables, excluding LDL cholesterol.
The primary outcome was the 1-year difference in A1C. Secondary outcomes were the 1-year difference in the 10-year UKPDS CHD risk estimate and the percentage of patients that reached A1C ≤7%, systolic blood pressure ≤140 mmHg, total cholesterol ≤4.5 mmol/l, and LDL cholesterol ≤2.5 mmol/l (6).
We performed intention-to-treat analyses with baseline values carried forward in the case of missing values. To correct for clustering at the practice level, generalized linear models were used, and after clustering had been taken into account, a 0.3% difference in A1C and a 2% difference in UKPDS CHD risk could be detected with 90% power (α = 0.05), with at least 1,080 patients in each treatment arm.
There were more solo practices (58 vs. 50%) and fewer duo practices (24 vs. 30%) compared with national data (8). The mean ± SD age (46.8 ± 7.4 years) of the participating PCPs was comparable with the mean Dutch PCP age (8). Baseline characteristics of the intervention and control groups were comparable, except for smoking status, history of cardiovascular disease, and HDL cholesterol levels (Table 1).
The difference in A1C change between the two groups was not significant. Systolic and diastolic blood pressure and total and LDL cholesterol improved significantly more in the intervention group. As a result, the calculated 10-year UKPDS CHD risk decreased 1.4% more in the intervention group. After 1 year, significantly more patients in the intervention group reached the treatment targets, with 18.9% of the patients meting all treatment targets (Table 1).
The DCP is the first pragmatic diabetes care intervention using a CDSS that improves patient outcome. As recommended by the National Institute of Clinical Excellence, we calculated the 10-year UKPDS CHD risk estimate for all subjects and used this measurement as a determinant of clinical care. Recently, the Action in Diabetes and Vascular Disease (ADVANCE) study showed that A1C reduction does not prevent CHD (9). This result indicates that we should focus on the patient's total cardiovascular risk profile. Our study showed no difference in A1C change between the two treatment arms, but the DCP led to improved diabetes care, which is shown by a 1.4% higher reduction in 10-year CHD risk estimate in the intervention group.
The DCP combines several interventions. The CDSS structures diabetes care, which may lead to improvements in the process of care (1). In addition, the DCP added a practice nurse who acted as a case manager and provided periodic feedback. Both interventions can improve blood glucose control (2,4).
Practices were self-selected, which may suggest a special interest of the PCP in improving diabetes care. This could be the reason why baseline values of A1C, blood pressure, and cholesterol were lower than those of most other Dutch primary care diabetes studies (10). Because mean A1C at baseline was almost at the treatment target, there was little room for improvement. Changes in blood pressure and cholesterol, however, were significant.
The percentage of patients who reached all treatment targets remained strikingly low: 18.9%. This could be explained by overly strict targets (11), physicians inert in prescribing more medications (4), or noncompliant patients (12). Whether the effects of the DCP will sustain has to be determined by longer-term follow-up data.
For this study, we received an unrestricted grant from Pfizer B.V.
We thank the practices and patients who participated in this study and Diagnosis4Health for making the research data available.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.