Article

Evaluation of a diabetes management program in China demonstrated association of improved continuity of care with clinical outcomes.

Nuffield Centre for International Health and Development, University of Leeds, 71-75 Clarendon Road, Leeds, West Yorks, UK.
Journal of Clinical Epidemiology (impact factor: 4.27). 07/2008; 61(9):932-9. DOI:10.1016/j.jclinepi.2007.12.013 pp.932-9
Source: PubMed

ABSTRACT The aim of the study was to evaluate a community-based diabetes management program in Shanghai, China and to examine the association between continuity of care and clinical outcomes.
The diabetes management program was implemented in downtown Shanghai. One hundred fifty-six patients participated in the intervention group and 182 patients were in the control group. Participants were elders without severe diabetic complications. Patient weight, body mass index, blood pressures, and fasting blood glucose were collected from outpatient records at baseline and the end of the study in both groups. Fructosamine level was measured to monitor glycemic control for patients in the intervention group. Continuity of care was measured based on our broad definition.
Improved patient health outcomes were observed in the diabetes management program: patients in the intervention group significantly reduced their weight, systolic blood pressure, and fasting blood glucose compared with those in the control group (P<0.05). In hierarchical regression models, continuity of care scales had a significant association with weight loss and fasting blood glucose reduction.
This study suggested that continuity based on broad terms can act as an important management tool to improve the quality of primary care in similar urban settings.

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    Article: Is there a survival benefit within a German primary care-based disease management program?
    Antje Miksch, Gunter Laux, Dominik Ose, Stefanie Joos, Stephen Campbell, Burgi Riens, Joachim Szecsenyi
    [show abstract] [hide abstract]
    ABSTRACT: To compare the mortality rate of patients with type 2 diabetes who were enrolled in the German diabetes disease management program (DMP) with the mortality rate of those who were not enrolled. This observational study was part of the ELSID study (Evaluation of a Large Scale Implementation of disease management programs) in Germany. Participants had type 2 diabetes and were either enrolled or not enrolled in the DMP. The DMP provides systems-based, multifaceted, and patient-centered interventions. To reduce imbalances between the groups, a matched sample was created using sex, age, retirement status, federal state, pharmacy-based cost groups, and diagnostic-cost groups as matching criteria. Cox proportional hazards regression model and the Kaplan-Meier method were used to assess overall mortality. The observation period was 3 years beginning on January 1, 2006. A total of 11,079 patients were included in the analysis. As of January 1, 2006, 2300 patients were enrolled in the DMP and 8779 were receiving routine care. There were 1927 matched pairs of patients in the DMP group and the non-DMP group. The overall mortality rate was 11.3% in the DMP and 14.4% in the non-DMP group (log-rank test P <.01). We found an association between participation in the German diabetes DMP and reduced mortality. This reduced mortality cannot be attributed directly to the DMP. However, further research should evaluate whether a primary care-based DMP contributes to increased life expectancy in patients with diabetes.
    The American journal of managed care 01/2010; 16(1):49-54. · 2.46 Impact Factor
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Keywords

blood pressures
 
care scales
 
community-based diabetes management program
 
control group
 
diabetes management program
 
downtown Shanghai
 
fasting blood glucose
 
fasting blood glucose reduction
 
hierarchical regression models
 
hundred fifty-six patients
 
Improved patient health outcomes
 
intervention group
 
management tool
 
outpatient records
 
Patient weight
 
patients
 
severe diabetic complications
 
significant association
 
similar urban settings
 
systolic blood pressure
 

Xiaolin Wei