Antonio Ceriello1,2,3, Maria Chiara Rossi4, Salvatore De Cosmo5, Giuseppe Lucisano4, Roberto Pontremoli6, Paola Fioretto7, Carlo Giorda8, Antonio Pacilli5, Francesca Viazzi6, Giuseppina Russo9, Antonio Nicolucci. 1. Insititut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain aceriell@clinic.cat. 2. Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain. 3. Department of Cardiovascular and Metabolic Diseases, IRCCS MultiMedica, Sesto San Giovanni, Milan, Italy. 4. Center for Outcomes Research and Clinical Epidemiology (CORESEARCH), Pescara, Italy. 5. Department of Medical Sciences, Scientific Institute "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Foggia, Italy. 6. Department of Cardionephrology, IRCCS Azienda Ospedaliera Universitaria San Martino-IST, Genoa, Italy. 7. Department of Medicine, University of Padua, Padua, Italy. 8. Diabetes and Metabolism Unit, Department of Internal Medicine, ASL Turin 5, Chieri, Turin, Italy. 9. Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy.
Abstract
OBJECTIVE: An association between variability in clinical parameters (HbA1c, blood pressure, cholesterol, and uric acid) and risk of complications in type 2 diabetes has been reported. In this analysis, we investigated to what extent such variability is associated with overall quality of care. RESEARCH DESIGN AND METHODS: The quality of care summary score (Q-score) represents a validated, overall quality of care indicator ranging between 0 and 40; the higher the score, the better the quality of care provided by the diabetes center. We identified patients with five or more measurements of clinical parameters after the assessment of the Q-score. Multiple linear regression analyses assessed the role of the Q-score in predicting the variability of the different parameters. RESULTS: Overall, 273,888 patients were analyzed. The variability of all the parameters systematically increased with decreasing Q-score values. At multivariate linear regression analysis, compared with a Q-score >25, a score <15 was associated with a significantly larger variation in HbA1c, blood pressure, uric acid, total cholesterol, and LDL cholesterol and a lower variation in HDL cholesterol. The analysis of standardized β coefficients show that the Q-score has a larger impact on the variability of HbA1c (0.34; P < 0.0001), systolic blood pressure (0.21; P < 0.0001), total cholesterol (0.21; P < 0.0001), and LDL cholesterol (0.20; P < 0.0001). CONCLUSIONS: The variability of risk factors for diabetic complications is associated with quality of care. Quality of care improvement initiatives should be targeted to increase the achievement of the recommended target while reducing such variability.
OBJECTIVE: An association between variability in clinical parameters (HbA1c, blood pressure, cholesterol, and uric acid) and risk of complications in type 2 diabetes has been reported. In this analysis, we investigated to what extent such variability is associated with overall quality of care. RESEARCH DESIGN AND METHODS: The quality of care summary score (Q-score) represents a validated, overall quality of care indicator ranging between 0 and 40; the higher the score, the better the quality of care provided by the diabetes center. We identified patients with five or more measurements of clinical parameters after the assessment of the Q-score. Multiple linear regression analyses assessed the role of the Q-score in predicting the variability of the different parameters. RESULTS: Overall, 273,888 patients were analyzed. The variability of all the parameters systematically increased with decreasing Q-score values. At multivariate linear regression analysis, compared with a Q-score >25, a score <15 was associated with a significantly larger variation in HbA1c, blood pressure, uric acid, total cholesterol, and LDL cholesterol and a lower variation in HDL cholesterol. The analysis of standardized β coefficients show that the Q-score has a larger impact on the variability of HbA1c (0.34; P < 0.0001), systolic blood pressure (0.21; P < 0.0001), total cholesterol (0.21; P < 0.0001), and LDL cholesterol (0.20; P < 0.0001). CONCLUSIONS: The variability of risk factors for diabetic complications is associated with quality of care. Quality of care improvement initiatives should be targeted to increase the achievement of the recommended target while reducing such variability.
Authors: Liane J Tinsley; Nathan D Wong; Jane E B Reusch; Suzanne V Arnold; Mikhail N Kosiborod; Yuanyuan Tang; Lori M Laffel; Sanjeev N Mehta Journal: J Diabetes Complications Date: 2020-04-21 Impact factor: 2.852
Authors: Martin B Whyte; Mark Joy; William Hinton; Andrew McGovern; Uy Hoang; Jeremy van Vlymen; Filipa Ferreira; Julie Mount; Neil Munro; Simon de Lusignan Journal: Diabetes Obes Metab Date: 2022-04-18 Impact factor: 6.408
Authors: Da Young Lee; Jaeyoung Kim; Sanghyun Park; So Young Park; Ji Hee Yu; Ji A Seo; Nam Hoon Kim; Hye Jin Yoo; Sin Gon Kim; Kyung Mook Choi; Sei Hyun Baik; Kyungdo Han; Nan Hee Kim Journal: J Clin Med Date: 2021-12-18 Impact factor: 4.241