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The effect of an electronic health record-based tool on abnormal pediatric blood pressure recognition
Sarah A Twichell1, Corinna J Rea1, Patrice Melvin2
1Department of Medicine, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
Insights
An electronic health record (EHR) app modestly improved recognition of high blood pressure in children. Actual use of the app significantly boosted abnormal blood pressure recognition rates in pediatric encounters.
Area of Science:
- Pediatric Health
- Cardiovascular Medicine
- Health Informatics
Background:
- High blood pressure (BP) recognition in children is often poor due to complex percentile calculations.
- Electronic Health Record (EHR) systems can streamline clinical workflows.
Purpose of the Study:
- To evaluate the impact of an EHR app designed for BP percentile calculation on abnormal BP recognition in children.
- To compare recognition rates before and after app implementation.
Main Methods:
- Retrospective analysis of clinical data from pediatric encounters (3-18 years) before and after EHR app introduction.
- Defined abnormal BP recognition by specific codes, referrals, or diagnostic tests.
- Used logistic regression to compare recognition odds, analyzing app usage impact.
Main Results:
- Overall abnormal BP recognition increased from 4.9% to 7.1% post-app introduction (P < .0001).
- App utilization in elevated BP visits was 13%.
- Actual app use significantly increased recognition (adjusted OR 3.17), while non-use showed no difference.
Conclusions:
- The introduction of the BP EHR app led to a modest increase in abnormal BP recognition.
- Direct utilization of the EHR app was strongly associated with significantly higher recognition rates.
- Further investigation into predictors of abnormal BP recognition is warranted.
Background:
Recognition of high blood pressure (BP) in children is poor, partly due to the need to compute age-sex-height referenced percentiles. This study examined the change in abnormal BP recognition before versus after the introduction of an electronic health record (EHR) app designed to calculate BP percentiles with a training lecture.
Methods And Results:
Clinical data were extracted on all ambulatory, non-urgent encounters for children 3-18 years old seen in primary care, endocrinology, cardiology, or nephrology clinics at an urban, academic hospital in the year before and the year after app introduction. Outpatients with at least 1 BP above the age-gender-height referenced 90th percentile were included. Abnormal BP recognition was defined as a BP related ICD-9 code, referral to nephrology or cardiology, an echocardiogram or renal ultrasound to evaluate BP concern, or a follow-up primary care visit for BP monitoring. Multivariable adjusted logistic regression compared odds of recognition before and after app introduction. Of 78 768 clinical encounters, 3521 had abnormal BP in the pre- and 3358 in the post-app period. App use occurred in 13% of elevated BP visits. Overall, abnormal BP was recognized in 4.9% pre-app period visits and 7.1% of visits post-app (P < .0001). Recognition was significantly higher when the app was actually used (adjusted OR 3.17 95% CI 2.29-4.41, P < .001). Without app use recognition was not different.
Conclusions:
BP app advent modestly increased abnormal BP recognition in the entire cohort, but actual app use was associated with significantly higher recognition. Predictors of abnormal BP recognition deserve further scrutiny.
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