OBJECTIVE: To examine state variability in diabetes care for Medicare beneficiaries and the impact of certain beneficiary characteristics on those variations. RESEARCH DESIGN AND METHODS: Medicare beneficiaries with diabetes, aged 18-75 years, were identified from 1997 to 1999 claims data. Claims data were used to construct rates for three quality of care measures (HbA(1c) tests, eye examinations, and lipid profiles). Person-level variables (e.g., age, sex, race, and socioeconomic status) were used to adjust state rates using logistic regression. RESULTS: A third of 2 million beneficiaries with diabetes aged 18-75 years did not have annual HbA(1c) tests, biennial eye examinations, or biennial lipid profiles. There was wide variability in the measures among states (e.g., receipt of HbA(1c) tests ranged from 52 to 83%). Adjustment using person-level variables reduced the variance in HbA(1c) tests, eye examinations, and lipid profiles by 30, 23, and 27%, respectively, but considerable variability remained. The impact of the adjustment variables was also inconsistent across measures. CONCLUSIONS: Opportunities remain for improvement in diabetes care. Large variations in care among states were reduced significantly by adjustment for characteristics of state residents. However, much variability remained unexplained. Variability of measures within states and variable impact of the adjustment variables argues against systems effects operating with uniformity on the three measures. These findings suggest that a single approach to quality improvement is unlikely to be effective. Further understanding variability will be important to improving quality.
OBJECTIVE: To examine state variability in diabetes care for Medicare beneficiaries and the impact of certain beneficiary characteristics on those variations. RESEARCH DESIGN AND METHODS: Medicare beneficiaries with diabetes, aged 18-75 years, were identified from 1997 to 1999 claims data. Claims data were used to construct rates for three quality of care measures (HbA(1c) tests, eye examinations, and lipid profiles). Person-level variables (e.g., age, sex, race, and socioeconomic status) were used to adjust state rates using logistic regression. RESULTS: A third of 2 million beneficiaries with diabetes aged 18-75 years did not have annual HbA(1c) tests, biennial eye examinations, or biennial lipid profiles. There was wide variability in the measures among states (e.g., receipt of HbA(1c) tests ranged from 52 to 83%). Adjustment using person-level variables reduced the variance in HbA(1c) tests, eye examinations, and lipid profiles by 30, 23, and 27%, respectively, but considerable variability remained. The impact of the adjustment variables was also inconsistent across measures. CONCLUSIONS: Opportunities remain for improvement in diabetes care. Large variations in care among states were reduced significantly by adjustment for characteristics of state residents. However, much variability remained unexplained. Variability of measures within states and variable impact of the adjustment variables argues against systems effects operating with uniformity on the three measures. These findings suggest that a single approach to quality improvement is unlikely to be effective. Further understanding variability will be important to improving quality.
Authors: Carolyn T Thorpe; Joshua M Thorpe; Amy J H Kind; Christie M Bartels; Christine M Everett; Maureen A Smith Journal: J Am Geriatr Soc Date: 2012-03-16 Impact factor: 5.562
Authors: David C Lee; Judith A Long; Stephen P Wall; Brendan G Carr; Samantha N Satchell; R Scott Braithwaite; Brian Elbel Journal: Am J Public Health Date: 2015-07-16 Impact factor: 9.308
Authors: Ross Bailie; Damin Si; Cindy Shannon; James Semmens; Kevin Rowley; David J Scrimgeour; Tricia Nagel; Ian Anderson; Christine Connors; Tarun Weeramanthri; Sandra Thompson; Robyn McDermott; Hugh Burke; Elizabeth Moore; Dallas Leon; Richard Weston; Haylene Grogan; Andrew Stanley; Karen Gardner Journal: BMC Health Serv Res Date: 2010-05-19 Impact factor: 2.655
Authors: Roberto Gnavi; Roberta Picariello; Ludmi la Karaghiosoff; Giuseppe Costa; Carlo Giorda Journal: Diabetes Care Date: 2009-08-12 Impact factor: 17.152