Measuring quality of diabetes care by linking health care system administrative databases with laboratory data

Abstract Background Chronic complications of diabetes can be reduced through optimal glycemic and lipid control as evaluated through measurement of glycosylated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C). We aimed to produce measures of quality of diabetes care in Saskatchewan...

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Published in:BMC Research Notes
Main Authors: Klomp Helena, Dyck Roland F, Sidhu Nirmal, Cascagnette Paul J, Teare Gary F
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2010
Subjects:
R
Online Access:https://doi.org/10.1186/1756-0500-3-233
https://doaj.org/article/197d50cee6184e90a42adaee6e141050
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spelling ftdoajarticles:oai:doaj.org/article:197d50cee6184e90a42adaee6e141050 2023-05-15T16:15:35+02:00 Measuring quality of diabetes care by linking health care system administrative databases with laboratory data Klomp Helena Dyck Roland F Sidhu Nirmal Cascagnette Paul J Teare Gary F 2010-08-01T00:00:00Z https://doi.org/10.1186/1756-0500-3-233 https://doaj.org/article/197d50cee6184e90a42adaee6e141050 EN eng BMC http://www.biomedcentral.com/1756-0500/3/233 https://doaj.org/toc/1756-0500 doi:10.1186/1756-0500-3-233 1756-0500 https://doaj.org/article/197d50cee6184e90a42adaee6e141050 BMC Research Notes, Vol 3, Iss 1, p 233 (2010) Medicine R Biology (General) QH301-705.5 Science (General) Q1-390 article 2010 ftdoajarticles https://doi.org/10.1186/1756-0500-3-233 2022-12-31T00:37:21Z Abstract Background Chronic complications of diabetes can be reduced through optimal glycemic and lipid control as evaluated through measurement of glycosylated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C). We aimed to produce measures of quality of diabetes care in Saskatchewan and to identify sub-groups at particular risk of developing complications. Findings Prevalent adult cases of diabetes in 2005/06 were identified from administrative databases and linked with A1C and LDL-C tests measured in centralized laboratories. A1C results were performed in 33,927 of 50,713 (66.9%) diabetes cases identified in Saskatchewan, and LDL-C results were performed in 12,031 of 24,207 (49.7%) cases identified within the province's two largest health regions. The target A1C of <= 7.0% and the target LDL-C of <2.5 mmol/L were achieved in 48.3% and 45.1% of diabetes cases respectively. The proportions were lower among those who were female, First Nations, non-urban, younger and in lower income quintiles. The same groups experienced poorer glycemic control (exception females), and poorer lipid control (exception First Nations people). Among non-Aboriginal people, younger diabetic females were least likely to receive lipid lowering agents. Conclusions Linkage of laboratory with administrative data is an effective method of assessing quality of diabetes care on a population basis and to identify sub-groups requiring particular attention. We found that less than 50% of Saskatchewan people with diabetes achieved optimal glycemic and lipid control. Disparities were most evident among First Nations people and young women. The indicators described can be used to provide standardized information that would support quality improvement initiatives. Article in Journal/Newspaper First Nations Directory of Open Access Journals: DOAJ Articles BMC Research Notes 3 1
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Medicine
R
Biology (General)
QH301-705.5
Science (General)
Q1-390
spellingShingle Medicine
R
Biology (General)
QH301-705.5
Science (General)
Q1-390
Klomp Helena
Dyck Roland F
Sidhu Nirmal
Cascagnette Paul J
Teare Gary F
Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
topic_facet Medicine
R
Biology (General)
QH301-705.5
Science (General)
Q1-390
description Abstract Background Chronic complications of diabetes can be reduced through optimal glycemic and lipid control as evaluated through measurement of glycosylated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C). We aimed to produce measures of quality of diabetes care in Saskatchewan and to identify sub-groups at particular risk of developing complications. Findings Prevalent adult cases of diabetes in 2005/06 were identified from administrative databases and linked with A1C and LDL-C tests measured in centralized laboratories. A1C results were performed in 33,927 of 50,713 (66.9%) diabetes cases identified in Saskatchewan, and LDL-C results were performed in 12,031 of 24,207 (49.7%) cases identified within the province's two largest health regions. The target A1C of <= 7.0% and the target LDL-C of <2.5 mmol/L were achieved in 48.3% and 45.1% of diabetes cases respectively. The proportions were lower among those who were female, First Nations, non-urban, younger and in lower income quintiles. The same groups experienced poorer glycemic control (exception females), and poorer lipid control (exception First Nations people). Among non-Aboriginal people, younger diabetic females were least likely to receive lipid lowering agents. Conclusions Linkage of laboratory with administrative data is an effective method of assessing quality of diabetes care on a population basis and to identify sub-groups requiring particular attention. We found that less than 50% of Saskatchewan people with diabetes achieved optimal glycemic and lipid control. Disparities were most evident among First Nations people and young women. The indicators described can be used to provide standardized information that would support quality improvement initiatives.
format Article in Journal/Newspaper
author Klomp Helena
Dyck Roland F
Sidhu Nirmal
Cascagnette Paul J
Teare Gary F
author_facet Klomp Helena
Dyck Roland F
Sidhu Nirmal
Cascagnette Paul J
Teare Gary F
author_sort Klomp Helena
title Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
title_short Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
title_full Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
title_fullStr Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
title_full_unstemmed Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
title_sort measuring quality of diabetes care by linking health care system administrative databases with laboratory data
publisher BMC
publishDate 2010
url https://doi.org/10.1186/1756-0500-3-233
https://doaj.org/article/197d50cee6184e90a42adaee6e141050
genre First Nations
genre_facet First Nations
op_source BMC Research Notes, Vol 3, Iss 1, p 233 (2010)
op_relation http://www.biomedcentral.com/1756-0500/3/233
https://doaj.org/toc/1756-0500
doi:10.1186/1756-0500-3-233
1756-0500
https://doaj.org/article/197d50cee6184e90a42adaee6e141050
op_doi https://doi.org/10.1186/1756-0500-3-233
container_title BMC Research Notes
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