BACKGROUND: Factors contributing to patient-reported experiences of diabetes self-management support are not understood well, particularly over time. OBJECTIVES: The aim of the study was to identify the contribution of patient characteristics to patient-reported quality of SMS. METHODS: Using secondary data from a prospective clinical trial (n = 339) comparing three approaches of providing diabetes self-management support (Group Medical Visits, Automated Telephone Support, and Usual Care) in a diverse, underserved population, the influence of patient characteristics (e.g., age, gender, income, and health status) was examined on Patient Assessment of Chronic Illness Care ratings. RESULTS: At baseline, older age (p = .014), being female (p = .038), and having lower income (p = .001) were associated with lower ratings. Income and interactions involving income combined explained 12% of the variance in baseline ratings. Compared with White patients, African American and Asian patients tended to have higher baseline ratings (p = .076 and p = .045, respectively). Race or ethnicity influenced perceptions throughout the trial, explaining 5% of the variance at baseline and 2% of the variance in 1-year changes in Patient Assessment of Chronic Illness Care ratings. As expected, over 1 year, ratings increased more for patients in both intervention groups compared with the control group (p < .001). DISCUSSION: Ratings of healthcare quality are influenced by patient characteristics independent of the nature of the care provided. Understanding more precisely how these differences are associated with differences in clinical processes will be particularly important for efforts aiming to integrate patient-reported measures into assessments of healthcare quality during routine clinical care and clinical trials.
RCT Entities:
BACKGROUND: Factors contributing to patient-reported experiences of diabetes self-management support are not understood well, particularly over time. OBJECTIVES: The aim of the study was to identify the contribution of patient characteristics to patient-reported quality of SMS. METHODS: Using secondary data from a prospective clinical trial (n = 339) comparing three approaches of providing diabetes self-management support (Group Medical Visits, Automated Telephone Support, and Usual Care) in a diverse, underserved population, the influence of patient characteristics (e.g., age, gender, income, and health status) was examined on Patient Assessment of Chronic Illness Care ratings. RESULTS: At baseline, older age (p = .014), being female (p = .038), and having lower income (p = .001) were associated with lower ratings. Income and interactions involving income combined explained 12% of the variance in baseline ratings. Compared with White patients, African American and Asian patients tended to have higher baseline ratings (p = .076 and p = .045, respectively). Race or ethnicity influenced perceptions throughout the trial, explaining 5% of the variance at baseline and 2% of the variance in 1-year changes in Patient Assessment of Chronic Illness Care ratings. As expected, over 1 year, ratings increased more for patients in both intervention groups compared with the control group (p < .001). DISCUSSION: Ratings of healthcare quality are influenced by patient characteristics independent of the nature of the care provided. Understanding more precisely how these differences are associated with differences in clinical processes will be particularly important for efforts aiming to integrate patient-reported measures into assessments of healthcare quality during routine clinical care and clinical trials.
Authors: Darren A Dewalt; Nancy D Berkman; Stacey Sheridan; Kathleen N Lohr; Michael P Pignone Journal: J Gen Intern Med Date: 2004-12 Impact factor: 5.128
Authors: Sherita Hill Golden; Arleen Brown; Jane A Cauley; Marshall H Chin; Tiffany L Gary-Webb; Catherine Kim; Julie Ann Sosa; Anne E Sumner; Blair Anton Journal: J Clin Endocrinol Metab Date: 2012-06-22 Impact factor: 5.958
Authors: C N Sadur; N Moline; M Costa; D Michalik; D Mendlowitz; S Roller; R Watson; B E Swain; J V Selby; W C Javorski Journal: Diabetes Care Date: 1999-12 Impact factor: 19.112
Authors: K R Lorig; P Ritter; A L Stewart; D S Sobel; B W Brown; A Bandura; V M Gonzalez; D D Laurent; H R Holman Journal: Med Care Date: 2001-11 Impact factor: 2.983