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Effects of continuity of care on hospital admission in patients with type 2 diabetes: analysis of nationwide insurance data

Overview of attention for article published in BMC Health Services Research, March 2015
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Title
Effects of continuity of care on hospital admission in patients with type 2 diabetes: analysis of nationwide insurance data
Published in
BMC Health Services Research, March 2015
DOI 10.1186/s12913-015-0745-z
Pubmed ID
Authors

Kyoung Hee Cho, Sang Gyu Lee, Byungyool Jun, Bo-Young Jung, Jae-Hyun Kim, Eun-Cheol Park

Abstract

A system for managing chronic disease including diabetes mellitus based on primary care clinics has been used in Korea since April 2012. This system can reduce copayments for patients that are managed by a single primary-care provider and lead to improve continuity of care. The aim of this study is to determine whether there is an association between continuity of care for outpatients and hospital admission and identify the continuity index that best explains hospital admissions for patients with type 2 diabetes. We performed a cross-sectional study using 2009 National Health Insurance Sample (NHIS) from the Health Insurance Review & Assessment Services (HIRA) of Korea. The dependent variable was hospital admission due to type 2 diabetes mellitus. Continuity of care was measured using the Usual Provider Care index (UPC), Continuity of Care index (COC), Sequential Continuity of Care index (SECON), and Integrated Continuity of Care index (ICOC). Patients with low COC scores (<0.75) were more likely to be hospitalized [odds ratio, 2.44; 95% CI, 2.17-2.75] compared with the reference group (COC ≥0.75), after adjusting for all covariates. we calculated the area under the receiver operating characteristic (AUROC) curve for each index to find which index had the greatest explanatory ability for hospital admission. The AUROC of the COC was the greatest (0.598), but the AUROC curves for the UPC (0.597), SECON (0.593), and ICOC (0.597) were similar. High continuity of care may reduce the likelihood for hospital admission. The COC had marginally more explanatory power.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 1%
Unknown 79 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 15%
Researcher 12 15%
Student > Master 9 11%
Other 8 10%
Student > Bachelor 7 9%
Other 16 20%
Unknown 16 20%
Readers by discipline Count As %
Medicine and Dentistry 20 25%
Nursing and Health Professions 15 19%
Social Sciences 5 6%
Computer Science 4 5%
Economics, Econometrics and Finance 4 5%
Other 14 18%
Unknown 18 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 March 2015.
All research outputs
#15,064,404
of 18,812,327 outputs
Outputs from BMC Health Services Research
#5,359
of 6,321 outputs
Outputs of similar age
#194,371
of 272,393 outputs
Outputs of similar age from BMC Health Services Research
#1
of 1 outputs
Altmetric has tracked 18,812,327 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,321 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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