Measuring quality of diabetes care by linking health care system administrative databases with laboratory data
<p>Abstract</p> <p>Background</p> <p>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 measur...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2010-08-01
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| Series: | BMC Research Notes |
| Online Access: | http://www.biomedcentral.com/1756-0500/3/233 |
| _version_ | 1818063130846035968 |
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| 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 |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Findings</p> <p>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.</p> <p>Conclusions</p> <p>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.</p> |
| first_indexed | 2024-12-10T14:15:13Z |
| format | Article |
| id | doaj.art-197d50cee6184e90a42adaee6e141050 |
| institution | Directory Open Access Journal |
| issn | 1756-0500 |
| language | English |
| last_indexed | 2024-12-10T14:15:13Z |
| publishDate | 2010-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Research Notes |
| spelling | doaj.art-197d50cee6184e90a42adaee6e1410502022-12-22T01:45:22ZengBMCBMC Research Notes1756-05002010-08-013123310.1186/1756-0500-3-233Measuring quality of diabetes care by linking health care system administrative databases with laboratory dataKlomp HelenaDyck Roland FSidhu NirmalCascagnette Paul JTeare Gary F<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Findings</p> <p>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.</p> <p>Conclusions</p> <p>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.</p>http://www.biomedcentral.com/1756-0500/3/233 |
| spellingShingle | 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 BMC Research Notes |
| title | 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_short | 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 |
| url | http://www.biomedcentral.com/1756-0500/3/233 |
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