Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care
Abstract Background Electronic health record (EHR) data is increasingly used to identify patients with chronic kidney disease (CKD). EHR queries used to capture CKD status, identify comorbid conditions, measure awareness by providers, and track adherence to guideline-concordant processes of care hav...
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| Format: | Article |
| Language: | English |
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BMC
2019-01-01
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| Series: | BMC Nephrology |
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| Online Access: | http://link.springer.com/article/10.1186/s12882-018-1156-2 |
| _version_ | 1828756746143793152 |
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| author | Martin Frigaard Anna Rubinsky Lo Lowell Anna Malkina Leah Karliner Michael Kohn Carmen A Peralta |
| author_facet | Martin Frigaard Anna Rubinsky Lo Lowell Anna Malkina Leah Karliner Michael Kohn Carmen A Peralta |
| author_sort | Martin Frigaard |
| collection | DOAJ |
| description | Abstract Background Electronic health record (EHR) data is increasingly used to identify patients with chronic kidney disease (CKD). EHR queries used to capture CKD status, identify comorbid conditions, measure awareness by providers, and track adherence to guideline-concordant processes of care have not been validated. Methods We extracted EHR data for primary-care patients with two eGFRcreat 15-59 mL/min/1.73 m^2 at least 90 days apart. Two nephrologists manually reviewed a random sample of 50 charts to determine CKD status, associated comorbidities, and physician awareness of CKD. We also assessed the documentation of a CKD diagnosis with guideline-driven care. Results Complete data were available on 1767 patients with query-defined CKD of whom 822 (47%) had a CKD diagnosis in their chart. Manual chart review confirmed the CKD diagnosis in 34 or 50 (68%) patients. Agreement between the reviewers and the EHR diagnoses on the presence of comorbidities was good (κ > 0.70, p < 0.05), except for congestive heart failure, (κ = 0.45, p < 0.05). Reviewers felt the providers were aware of CKD in 23 of 34 (68%) of the confirmed CKD cases. A CKD diagnosis was associated with higher odds of guideline-driven care including CKD-specific laboratory tests and prescriptions for statins. After adjustment, CKD diagnosis documentation was not significantly associated with ACE/ARB prescription. Conclusions Identifying CKD status by historical eGFRs overestimates disease prevalence. A CKD diagnosis in the patient chart was a reasonable surrogate for provider awareness of disease status, but CKD awareness remains relatively low. CKD in the patient chart was associated with higher rates of albuminuria testing and use of statins, but not use of ACE/ARB. |
| first_indexed | 2024-12-10T23:22:14Z |
| format | Article |
| id | doaj.art-80a085405c0d4ad49aa3f66f1d2c53c9 |
| institution | Directory Open Access Journal |
| issn | 1471-2369 |
| language | English |
| last_indexed | 2024-12-10T23:22:14Z |
| publishDate | 2019-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Nephrology |
| spelling | doaj.art-80a085405c0d4ad49aa3f66f1d2c53c92022-12-22T01:29:42ZengBMCBMC Nephrology1471-23692019-01-012011910.1186/s12882-018-1156-2Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary careMartin Frigaard0Anna Rubinsky1Lo Lowell2Anna Malkina3Leah Karliner4Michael Kohn5Carmen A Peralta6Kidney health research collaborative (KHRC), University of CaliforniaKidney health research collaborative (KHRC), University of CaliforniaNephrology and Hypertension at Parnassus, University of California San FranciscoNephrology and Hypertension at Parnassus, University of California San FranciscoNephrology and Hypertension at Parnassus, University of California San FranciscoNephrology and Hypertension at Parnassus, University of California San FranciscoNephrology and Hypertension at Parnassus, University of California San FranciscoAbstract Background Electronic health record (EHR) data is increasingly used to identify patients with chronic kidney disease (CKD). EHR queries used to capture CKD status, identify comorbid conditions, measure awareness by providers, and track adherence to guideline-concordant processes of care have not been validated. Methods We extracted EHR data for primary-care patients with two eGFRcreat 15-59 mL/min/1.73 m^2 at least 90 days apart. Two nephrologists manually reviewed a random sample of 50 charts to determine CKD status, associated comorbidities, and physician awareness of CKD. We also assessed the documentation of a CKD diagnosis with guideline-driven care. Results Complete data were available on 1767 patients with query-defined CKD of whom 822 (47%) had a CKD diagnosis in their chart. Manual chart review confirmed the CKD diagnosis in 34 or 50 (68%) patients. Agreement between the reviewers and the EHR diagnoses on the presence of comorbidities was good (κ > 0.70, p < 0.05), except for congestive heart failure, (κ = 0.45, p < 0.05). Reviewers felt the providers were aware of CKD in 23 of 34 (68%) of the confirmed CKD cases. A CKD diagnosis was associated with higher odds of guideline-driven care including CKD-specific laboratory tests and prescriptions for statins. After adjustment, CKD diagnosis documentation was not significantly associated with ACE/ARB prescription. Conclusions Identifying CKD status by historical eGFRs overestimates disease prevalence. A CKD diagnosis in the patient chart was a reasonable surrogate for provider awareness of disease status, but CKD awareness remains relatively low. CKD in the patient chart was associated with higher rates of albuminuria testing and use of statins, but not use of ACE/ARB.http://link.springer.com/article/10.1186/s12882-018-1156-2Chronic kidney diseaseElectronic health record phenotypeValidation |
| spellingShingle | Martin Frigaard Anna Rubinsky Lo Lowell Anna Malkina Leah Karliner Michael Kohn Carmen A Peralta Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care BMC Nephrology Chronic kidney disease Electronic health record phenotype Validation |
| title | Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| title_full | Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| title_fullStr | Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| title_full_unstemmed | Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| title_short | Validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| title_sort | validating laboratory defined chronic kidney disease in the electronic health record for patients in primary care |
| topic | Chronic kidney disease Electronic health record phenotype Validation |
| url | http://link.springer.com/article/10.1186/s12882-018-1156-2 |
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