The Chronic Care Model: Blueprint for Improving Total Diabetes Care

2007 ◽  
pp. 19-33
Author(s):  
Anita C. Murcko ◽  
Jean Donie ◽  
Scott Endsley ◽  
Larry Cooper
2016 ◽  
pp. ckw189 ◽  
Author(s):  
Valentina Barletta ◽  
Francesco Profili ◽  
Rosa Gini ◽  
Leonardo Grilli ◽  
Carla Rampichini ◽  
...  

2010 ◽  
Vol 23 (3) ◽  
pp. 295-305 ◽  
Author(s):  
P. A. O. Strickland ◽  
S. V. Hudson ◽  
A. Piasecki ◽  
K. Hahn ◽  
D. Cohen ◽  
...  

2009 ◽  
Vol 27 (4) ◽  
pp. 153-159 ◽  
Author(s):  
L. Siminerio ◽  
E. H. Wagner ◽  
R. Gabbay ◽  
J. Zgibor

2011 ◽  
Vol 5 (3) ◽  
pp. 501-513 ◽  
Author(s):  
Shihchen Kuo ◽  
Cindy L. Bryce ◽  
Janice C. Zgibor ◽  
Donna L. Wolf ◽  
Mark S. Roberts ◽  
...  

2015 ◽  
Vol 16 (05) ◽  
pp. 481-491 ◽  
Author(s):  
Grace M.V. Ku ◽  
Guy Kegels

AimThe purpose of this study was to investigate the effects of implementing elements of a context-adapted chronic disease-care model (CACCM) in two local government primary healthcare units of a non-highly urbanized city and a rural municipality in the Philippines on Patients’ Assessment of Chronic Illness Care (PACIC) and glycaemic control (HbA1c) of people with diabetes.BackgroundLow-to-middle income countries like the Philippines are beset with rising prevalence of chronic conditions but their healthcare systems are still acute disease oriented. Attention towards improving care for chronic conditions particularly in primary healthcare is imperative and ways by which this can be done amidst resource constraints need to be explored.MethodsA chronic care model was adapted based on the context of the Philippines. Selected elements (community sensitization, decision support, minor re-organization of health services, health service delivery-system re-design, and self-management education and support) were implemented. PACIC and HbA1c were measured before and one year after the start of implementation.FindingsThe improvements in the PACIC (median, from 3.2 to 3.5) as well as in four of the five subsets of the PACIC were statistically significant (P-values: PACIC=0.009; ‘patient activation’=0.026; ‘goal setting’=0.017; ‘problem solving’<0.001; ‘follow-up’<0.001). The decrease in HbA1c (median, from 7.7% to 6.9%) and the level of diabetes control of the project participants (increase of optimally controlled diabetes from 37.2% to 50.6%) were likewise significant (P<0.000 andP=0.014). A significantly higher rating of the post-implementation PACIC subsets ‘problem solving’ (P=0.027) and ‘follow-up’ (P=0.025) was noted among those participants whose HbA1c improved. The quality of chronic care in general and primary diabetes care in particular may be improved, as measured through the PACIC and glycaemic control, in resource-constrained settings applying selected elements of a CACCM and without causing much strain on an already-burdened healthcare system.


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