Twichell Sarah A, Rea Corinna J, Melvin Patrice, Capraro Andrew J, Mandel Joshua C, Ferguson Michael A, Nigrin Daniel J, Mandl Kenneth D, Graham Dionne, Zachariah Justin P
Department of Medicine, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
Clinical Research Program, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
Congenit Heart Dis. 2017 Jul;12(4):484-490. doi: 10.1111/chd.12469. Epub 2017 May 11.
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.
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.
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.
儿童高血压的识别情况较差,部分原因是需要计算年龄、性别、身高参考百分位数。本研究调查了一款旨在通过培训讲座计算血压百分位数的电子健康记录(EHR)应用程序引入前后异常血压识别情况的变化。
提取了一家城市学术医院在应用程序引入前一年和引入后一年在初级保健、内分泌科、心脏病科或肾病科诊所就诊的所有3至18岁儿童门诊非紧急就诊的临床数据。纳入至少有一次血压高于年龄、性别、身高参考第90百分位数的门诊患者。异常血压识别定义为与血压相关的ICD-9编码、转诊至肾病科或心脏病科、进行超声心动图或肾脏超声检查以评估血压问题,或进行后续初级保健随访以监测血压。多变量调整逻辑回归比较了应用程序引入前后识别异常血压的几率。在78768次临床就诊中,应用程序引入前有3521次血压异常,应用程序引入后有3358次。13%的血压升高就诊使用了该应用程序。总体而言,应用程序引入前的就诊中有4.9%识别出异常血压,应用程序引入后的就诊中有7.1%识别出异常血压(P <.0001)。实际使用该应用程序时,识别率显著更高(调整后的OR为3.17,95%CI为2.29-4.41,P <.001)。未使用应用程序时,识别率无差异。
血压应用程序的出现适度提高了整个队列中异常血压的识别率,但实际使用该应用程序与显著更高的识别率相关。异常血压识别的预测因素值得进一步研究。