Continuity of care for newly diagnosed diabetic patients: A population-based study

Abstract

This study explores whether continuity of care is associated with health care outcomes and medical care use among patients with newly diagnosed diabetes. A retrospective cohort analysis was performed using the Taiwanese National Health Insurance database, and cases were followed up from January 2010 to December 2012. Four thousand and seven patients with newly diagnosed diabetes were followed for 3 years. The continuity of care was measured using the continuity of care index (COCI) and the usual provider continuity score (UPCS) with high and low dichotomous categories. The probabilities of dementia, hospitalization, emergency room visits, and death were used as health care outcomes. Medical care use was defined as the number of hospital admissions, length of hospital stays, and number of emergency room visits. Adjusted odds ratios (ORs) were obtained using multivariate logistic regression; adjusted ORs for the probabilities of dementia, hospital admissions, and emergency room visits in the higher COCI patient group were 0.582 (p < 0.05), 0.623 (p < 0.001), and 0.650 (p < 0.001), respectively. Negative binomial regression models for medical resource use indicated that the group with higher COCI scores used fewer medical resources compared with the group with lower COCI scores. The findings of UPCS analysis showed that those in the high COCI group also fell into the high UPCS group. In this study, continuity of care was associated with favorable health care outcomes and less medical care uses among newly diagnosed diabetic patients. Long-term relationships between patients and health care providers should be enhanced to provide improved continuity of care.

Effects of continuity of care on health outcomes among patients with diabetes mellitus and/or hypertension: a systematic review

“…Explanations for why a certain method was used were rarely provided. Two studies used multiple continuity of care calculations and the findings were consistent among different measurements [ 45 , 56 ]. Among studies that assessed the effect of continuity of care by categorization, there was no consistent definition for cut-off.…”

“…Details of the definitions and formulae of all continuity of care measurement tools used in the reviewed studies are listed in Additional file 2 . The two most frequently used continuity of care instruments were the continuity of care index (CoCI) (20 studies) [ 7 , 10 , 13 , 18 , 25 , 26 , 29 , 33 , 39 – 41 , 45 , 47 , 53 – 56 , 59 – 61 ] and usual provider continuity index (UPCI) (12 studies) [ 27 , 36 – 38 , 42 , 44 , 45 , 48 , 49 , 52 , 56 , 58 ]. CoCI measures the dispersion of visits of a patient to different providers [ 63 ], which is calculated by , where k is the number of providers, is the number of visits to provider i and N is the total number of visits of the patient.…”

“…Continuity of care was reported by six out of seven studies to reduce mortality [ 38 , 39 , 42 , 44 , 45 , 48 , 52 ]. The effect of continuity of care on HbA1c was frequently evaluated in studies focusing on DM patients, but findings were less consistent, with six of the twelve studies showing statistically significant improvements [ 33 , 34 , 36 , 42 , 46 , 51 ].…”

Quality performance and associated factors in Swiss diabetes care – A cross-sectional study

“…In Switzerland, the study of Frei et al 2013 also found no association with consultation count, which might be due to the fact that in Switzerland a structured invitation mechanism for follow-up appointments is uncommon. Another known factor associated with increased quality of diabetes care is continuity of care [37,38]. We did not explicitly measure continuity of care, but we found a negative association between number of treating GPs and all three process indicators, and a negative association with the outcome indicator of cholesterol.…”

Social Determinants of Diabetes-Related Preventable Hospitalization in Taiwan: A Spatial Analysis

“…Therefore, the accessibility and opportunity of social participation for social network and social support become very important. Patients with newly diagnosed diabetes in Taiwan were 61 years old on average with the standard deviation of 10 years [ 56 ], suggesting a substantial need for elderly social services. This study chimed harmoniously with the above-mentioned advocacies and demonstrated the importance of ESS densities on DRPH rates.…”