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Under-documentation of chronic kidney disease in the electronic health record in outpatients
Herbert S Chase1, Jai Radhakrishnan, Shayan Shirazian
1Department of Biomedical Informatics, Columbia University, New York, NY, USA. herbert.chase@dbmi.columbia.edu
Insights
Many moderate chronic kidney disease (CKD) patients lack proper electronic health record (EHR) documentation. This under-documentation is linked to reduced guideline-recommended care, highlighting the need for improved provider documentation prompts.
Area of Science:
- Medical Informatics
- Nephrology
- Health Informatics
Background:
- Electronic health records (EHRs) are crucial for patient care documentation.
- Accurate documentation of chronic kidney disease (CKD) is essential for appropriate management.
- Under-documentation of CKD can lead to suboptimal patient care.
Purpose of the Study:
- To evaluate the accuracy of lexical-based tools in identifying CKD documentation within EHRs.
- To determine the prevalence of under-documented moderate CKD in outpatients.
- To assess the association between CKD documentation and guideline-recommended care.
Main Methods:
- Developed and applied two lexical-based classification tools (classifier and word-counter) to EHR notes.
- Selected outpatients with moderate CKD based on reduced estimated glomerular filtration rate.
- Manually verified CKD documentation status for a subset of patients.
Main Results:
- Lexical tools demonstrated high sensitivity (95.4%-99.8%) and specificity (99.8%) for CKD documentation.
- 22% of patients with moderate CKD lacked appropriate documentation in their EHR.
- Under-documented patients received less renin-angiotensin system inhibitor therapy and urine protein quantification.
Conclusions:
- Lexical-based tools can accurately identify CKD documentation in EHRs.
- Significant under-documentation of moderate CKD exists, impacting care quality.
- Implementing provider prompts may improve CKD documentation and guideline adherence.
Objective:
To ascertain if outpatients with moderate chronic kidney disease (CKD) had their condition documented in their notes in the electronic health record (EHR).
Design:
Outpatients with CKD were selected based on a reduced estimated glomerular filtration rate and their notes extracted from the Columbia University data warehouse. Two lexical-based classification tools (classifier and word-counter) were developed to identify documentation of CKD in electronic notes.
Measurements:
The tools categorized patients' individual notes on the basis of the presence of CKD-related terms. Patients were categorized as appropriately documented if their notes contained reference to CKD when CKD was present.
Results:
The sensitivities of the classifier and word-count methods were 95.4% and 99.8%, respectively. The specificity of both was 99.8%. Categorization of individual patients as appropriately documented was 96.9% accurate. Of 107 patients with manually verified moderate CKD, 32 (22%) lacked appropriate documentation. Patients whose CKD had not been appropriately documented were significantly less likely to be on renin-angiotensin system inhibitors or have urine protein quantified, and had the illness for half as long (15.1 vs 30.7 months; p<0.01) compared to patients with documentation.
Conclusion:
Our studies show that lexical-based classification tools can accurately ascertain if appropriate documentation of CKD is present in a EHR. Using this method, we demonstrated under-documentation of patients with moderate CKD. Under-documented patients were less likely to receive CKD guideline recommended care. A tool that prompts providers to document CKD might shorten the time to implementing guideline-based recommendations.
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