Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department
Objective: While the American Diabetes Association (ADA) screening guidelines have been used widely, the way they are implemented and adapted to a particular setting can impact their practical application and usage. Our primary objective was to validate a best practice advisory (BPA) screening algor...
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| Format: | Article |
| Language: | English |
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eScholarship Publishing, University of California
2025-02-01
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| Series: | Western Journal of Emergency Medicine |
| Online Access: | https://escholarship.org/uc/item/3g00374m |
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| author | Mary H. Smart Janet Y. Lin Brian T. Layden Yuval Eisenberg Kirstie K. Danielson Ruth Pobee Chuxian Tang Brett Rydzon Anjana Bairavi Maheswaran A. Simon Pickard Lisa K. Sharp Angela Kong |
| author_facet | Mary H. Smart Janet Y. Lin Brian T. Layden Yuval Eisenberg Kirstie K. Danielson Ruth Pobee Chuxian Tang Brett Rydzon Anjana Bairavi Maheswaran A. Simon Pickard Lisa K. Sharp Angela Kong |
| author_sort | Mary H. Smart |
| collection | DOAJ |
| description | Objective: While the American Diabetes Association (ADA) screening guidelines have been used widely, the way they are implemented and adapted to a particular setting can impact their practical application and usage. Our primary objective was to validate a best practice advisory (BPA) screening algorithm informed by the ADA guidelines to identify patients eligible for hemoglobin a1c (HbA1c) testing in the emergency department (ED). Methods: This cross-sectional study included adults presenting to a large urban medical center’s ED in May 2021. We used sensitivity, specificity, likelihood ratios, and predictive values to estimate the algorithm’s ability to correctly identify patients eligible for diabetes screening, with manual chart review as the reference standard. Eligibility criteria targeted patients at risk for diabetes who were likely unaware of their elevated HbA1c. We also calculated the area under the receiver operating characteristic curve (AUC). Results: In May 2021, 2,963 (77%) of the 3,850 adults admitted to the ED had a routine lab ordered. Among those, 796 (27%) had a BPA triggered, and of those 631 (79%) had an HbA1c test completed. The algorithm had acceptable sensitivity (0.69, 95% confidence interval [CI] 0.66–0.72), specificity (0.91, CI 0.89–0.92), positive predictive value (0.75, CI 0.72–0.78) and negative predictive value (0.88, CI 0.86–0.89). The positive likelihood ratio (7.39, CI 6.35–8.42) was adequate, and the negative likelihood ratio (0.34, CI 0.30–0.37) was informative. The AUC of 0.74 (CI 0.72–0.77) suggests that the algorithm had acceptable accuracy. Conclusion: Findings suggest that an electronic health record-based algorithm informed by the ADA guidelines is a valid tool for identifying patients presenting to the ED who are eligible for HbA1c testing and may be unaware of having prediabetes or diabetes. The ease of workflow integration and high yield of potentially undiagnosed diabetes and prediabetes makes the BPA algorithm an appealing method for diabetes screening within the ED. |
| format | Article |
| id | doaj-art-9f1be65675e84be694d2c5841ac792d5 |
| institution | Kabale University |
| issn | 1936-900X 1936-9018 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | eScholarship Publishing, University of California |
| record_format | Article |
| series | Western Journal of Emergency Medicine |
| spelling | doaj-art-9f1be65675e84be694d2c5841ac792d52025-08-20T03:31:51ZengeScholarship Publishing, University of CaliforniaWestern Journal of Emergency Medicine1936-900X1936-90182025-02-0126372072810.5811/westjem.20548wjem-26-720Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency DepartmentMary H. Smart0Janet Y. Lin1Brian T. Layden2Yuval Eisenberg3Kirstie K. Danielson4Ruth Pobee5Chuxian Tang6Brett Rydzon7Anjana Bairavi Maheswaran8A. Simon Pickard9Lisa K. Sharp10Angela Kong11University of Illinois Chicago, College of Pharmacy, Department of Pharmacy Systems, Outcomes and Policy, Chicago, IllinoisUniversity of Illinois Chicago, College of Medicine, Department of Emergency Medicine, Chicago, IllinoisUniversity of Illinois Chicago, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Chicago, IllinoisUniversity of Illinois Chicago, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Chicago, IllinoisUniversity of Illinois Chicago, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Chicago, IllinoisUniversity of Illinois Chicago, College of Medicine, Department of Emergency Medicine, Chicago, IllinoisUniversity of Illinois Chicago, College of Medicine, Department of Emergency Medicine, Chicago, IllinoisUniversity of Illinois Chicago, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Chicago, IllinoisUniversity of Illinois Chicago, College of Medicine, Department of Emergency Medicine, Chicago, IllinoisUniversity of Illinois Chicago, College of Pharmacy, Department of Pharmacy Systems, Outcomes and Policy, Chicago, IllinoisUniversity of Illinois Chicago, College of Nursing, Department of Biobehavioral Nursing Science, Chicago, IllinoisUniversity of Illinois Chicago, College of Pharmacy, Department of Pharmacy Systems, Outcomes and Policy, Chicago, IllinoisObjective: While the American Diabetes Association (ADA) screening guidelines have been used widely, the way they are implemented and adapted to a particular setting can impact their practical application and usage. Our primary objective was to validate a best practice advisory (BPA) screening algorithm informed by the ADA guidelines to identify patients eligible for hemoglobin a1c (HbA1c) testing in the emergency department (ED). Methods: This cross-sectional study included adults presenting to a large urban medical center’s ED in May 2021. We used sensitivity, specificity, likelihood ratios, and predictive values to estimate the algorithm’s ability to correctly identify patients eligible for diabetes screening, with manual chart review as the reference standard. Eligibility criteria targeted patients at risk for diabetes who were likely unaware of their elevated HbA1c. We also calculated the area under the receiver operating characteristic curve (AUC). Results: In May 2021, 2,963 (77%) of the 3,850 adults admitted to the ED had a routine lab ordered. Among those, 796 (27%) had a BPA triggered, and of those 631 (79%) had an HbA1c test completed. The algorithm had acceptable sensitivity (0.69, 95% confidence interval [CI] 0.66–0.72), specificity (0.91, CI 0.89–0.92), positive predictive value (0.75, CI 0.72–0.78) and negative predictive value (0.88, CI 0.86–0.89). The positive likelihood ratio (7.39, CI 6.35–8.42) was adequate, and the negative likelihood ratio (0.34, CI 0.30–0.37) was informative. The AUC of 0.74 (CI 0.72–0.77) suggests that the algorithm had acceptable accuracy. Conclusion: Findings suggest that an electronic health record-based algorithm informed by the ADA guidelines is a valid tool for identifying patients presenting to the ED who are eligible for HbA1c testing and may be unaware of having prediabetes or diabetes. The ease of workflow integration and high yield of potentially undiagnosed diabetes and prediabetes makes the BPA algorithm an appealing method for diabetes screening within the ED.https://escholarship.org/uc/item/3g00374m |
| spellingShingle | Mary H. Smart Janet Y. Lin Brian T. Layden Yuval Eisenberg Kirstie K. Danielson Ruth Pobee Chuxian Tang Brett Rydzon Anjana Bairavi Maheswaran A. Simon Pickard Lisa K. Sharp Angela Kong Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department Western Journal of Emergency Medicine |
| title | Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department |
| title_full | Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department |
| title_fullStr | Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department |
| title_full_unstemmed | Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department |
| title_short | Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department |
| title_sort | validating an electronic health record algorithm for diabetes screening eligibility in the emergency department |
| url | https://escholarship.org/uc/item/3g00374m |
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