OBJECTIVE: To examine the association of the Patient Assessment of Chronic Illness Care (PACIC) with glycaemic control and the modulating effect of patient activation on this association. DESIGN, SETTING AND PARTICIPANTS: A population-based prospective cohort study of people with type 2 diabetes in Queensland, Australia, using data from self-report questionnaires, collected annually from 2008 (N = 3761) to 2010 (N = 3040). MAIN MEASURES: Predictors were the 20-item PACIC (dichotomized at the score of 3), and the 13-item Patient Activation Measure (PAM), dichotomized into activation levels 1 and 2 versus levels 3 and 4. Analyses were restricted to participants whose PACIC and PAM categories did not change over 2 years of follow-up. Outcome variable was self-reported HbA1c of ≤ 7% (53 mmol/mol) versus >7%. STATISTICAL ANALYSES: An inverse probability-weighted Poisson regression with a log-link function and a binary response outcome variable (HbA1c) was used to obtain risk ratios (RRs), and the interaction between PACIC and PAM was statistically modelled, taking into consideration patient characteristics and baseline glycaemic status. RESULTS: The effect of the PACIC was not seen in the activated participants (adjusted RR: 1.1; 95% CI: 0.96-1.2; P = 0.20) but was strongly observed in participants with low activation (adjusted RR: 2.3; 95% CI: 1.6-3.1; P < 0.001). Similarly, there was a positive association between patient activation and glycaemic control when the PACIC was low (adjusted RR: 1.6; 95% CI: 1.3-2.0; P < 0.001). CONCLUSIONS: Better patient-assessed chronic care received consistently over time facilitates achievement of better glycaemic control in patients with low activation.
OBJECTIVE: To examine the association of the Patient Assessment of Chronic Illness Care (PACIC) with glycaemic control and the modulating effect of patient activation on this association. DESIGN, SETTING AND PARTICIPANTS: A population-based prospective cohort study of people with type 2 diabetes in Queensland, Australia, using data from self-report questionnaires, collected annually from 2008 (N = 3761) to 2010 (N = 3040). MAIN MEASURES: Predictors were the 20-item PACIC (dichotomized at the score of 3), and the 13-item Patient Activation Measure (PAM), dichotomized into activation levels 1 and 2 versus levels 3 and 4. Analyses were restricted to participants whose PACIC and PAM categories did not change over 2 years of follow-up. Outcome variable was self-reported HbA1c of ≤ 7% (53 mmol/mol) versus >7%. STATISTICAL ANALYSES: An inverse probability-weighted Poisson regression with a log-link function and a binary response outcome variable (HbA1c) was used to obtain risk ratios (RRs), and the interaction between PACIC and PAM was statistically modelled, taking into consideration patient characteristics and baseline glycaemic status. RESULTS: The effect of the PACIC was not seen in the activated participants (adjusted RR: 1.1; 95% CI: 0.96-1.2; P = 0.20) but was strongly observed in participants with low activation (adjusted RR: 2.3; 95% CI: 1.6-3.1; P < 0.001). Similarly, there was a positive association between patient activation and glycaemic control when the PACIC was low (adjusted RR: 1.6; 95% CI: 1.3-2.0; P < 0.001). CONCLUSIONS: Better patient-assessed chronic care received consistently over time facilitates achievement of better glycaemic control in patients with low activation.
Authors: Janie Houle; François Lauzier-Jobin; Marie-Dominique Beaulieu; Sophie Meunier; Simon Coulombe; José Côté; François Lespérance; Jean-Louis Chiasson; Louis Bherer; Jean Lambert Journal: BMJ Open Diabetes Res Care Date: 2016-05-11
Authors: Edward Zimbudzi; Clement Lo; Sanjeeva Ranasinha; Gregory R Fulcher; Stephen Jan; Peter G Kerr; Kevan R Polkinghorne; Grant Russell; Rowan G Walker; Sophia Zoungas Journal: BMJ Open Date: 2017-10-22 Impact factor: 2.692
Authors: Heidi A van Vugt; Anne Meike Boels; Inge de Weerdt; Eelco Jp de Koning; Guy Ehm Rutten Journal: Patient Prefer Adherence Date: 2018-12-28 Impact factor: 2.711