State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states
Abstract Background Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for s...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-12-01
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| Series: | Population Health Metrics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12963-022-00298-z |
| _version_ | 1811315461506203648 |
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| author | Russell Mardon Joanne Campione Jennifer Nooney Lori Merrill Maurice Johnson David Marker Frank Jenkins Sharon Saydah Deborah Rolka Xuanping Zhang Sundar Shrestha Edward Gregg |
| author_facet | Russell Mardon Joanne Campione Jennifer Nooney Lori Merrill Maurice Johnson David Marker Frank Jenkins Sharon Saydah Deborah Rolka Xuanping Zhang Sundar Shrestha Edward Gregg |
| author_sort | Russell Mardon |
| collection | DOAJ |
| description | Abstract Background Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically. Methods We analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts. Results The estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states. Conclusions Despite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care. Trial Registration: Not applicable. |
| first_indexed | 2024-04-13T11:31:49Z |
| format | Article |
| id | doaj.art-73760661133e46d29b8fe0c17b82fa67 |
| institution | Directory Open Access Journal |
| issn | 1478-7954 |
| language | English |
| last_indexed | 2024-04-13T11:31:49Z |
| publishDate | 2022-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Population Health Metrics |
| spelling | doaj.art-73760661133e46d29b8fe0c17b82fa672022-12-22T02:48:33ZengBMCPopulation Health Metrics1478-79542022-12-0120111010.1186/s12963-022-00298-zState-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five statesRussell Mardon0Joanne Campione1Jennifer Nooney2Lori Merrill3Maurice Johnson4David Marker5Frank Jenkins6Sharon Saydah7Deborah Rolka8Xuanping Zhang9Sundar Shrestha10Edward Gregg11WestatWestatWestatWestatWestatWestatWestatUS Centers for Disease Control and PreventionUS Centers for Disease Control and PreventionUS Centers for Disease Control and PreventionUS Centers for Disease Control and PreventionUS Centers for Disease Control and PreventionAbstract Background Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically. Methods We analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts. Results The estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states. Conclusions Despite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care. Trial Registration: Not applicable.https://doi.org/10.1186/s12963-022-00298-zDiabetes mellitusElectronic health recordsEpidemiologic methodsHigh cholesterolHypertensionHealth and Retirement Study |
| spellingShingle | Russell Mardon Joanne Campione Jennifer Nooney Lori Merrill Maurice Johnson David Marker Frank Jenkins Sharon Saydah Deborah Rolka Xuanping Zhang Sundar Shrestha Edward Gregg State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states Population Health Metrics Diabetes mellitus Electronic health records Epidemiologic methods High cholesterol Hypertension Health and Retirement Study |
| title | State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states |
| title_full | State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states |
| title_fullStr | State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states |
| title_full_unstemmed | State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states |
| title_short | State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states |
| title_sort | state level metabolic comorbidity prevalence and control among adults age 50 plus with diabetes estimates from electronic health records and survey data in five states |
| topic | Diabetes mellitus Electronic health records Epidemiologic methods High cholesterol Hypertension Health and Retirement Study |
| url | https://doi.org/10.1186/s12963-022-00298-z |
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