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Personalized diabetes management recommendations at hospital discharge based on a computerized, pre‐hospitalization clinical profile analysis: A prospective, electronic health records–based study

机译:个性化糖尿病管理建议在医院放电的基础上基于计算机化,预留治疗临床分析分析:一项前瞻性,电子健康记录为基础的研究

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Summary Background While glycemic control of hospitalized diabetic patients is straightforward, personalization of management at discharge is challenging. Treatment guidelines base recommendations on the clinical profile of patients. We checked the feasibility of implementing discharge recommendations, based on the clinical profile in the patients' electronic health records (EHR). Methods A decision‐making algorithm was devised according to current guidelines. It was incorporated into the EHR. A prospective follow‐up of eligible diabetes patients was done. Results During 15 months, 835 patients (HbA1c was 6.9% [6.2%‐7.8%]) met our inclusion criteria. The rate of HbA1c acquisition increased from 55% during Q1 to 85%, 86%, 88%, and 87% thereafter. Also, the rate of incorporating personalized management recommendations to discharge letters increased: from 14.9% during Q1 to 42.9%, 43.0%, 47.2%, and 53.4% thereafter. Fifty‐eight (17.3%) of patients who got personalized recommendations upon discharge were found to have HbA1c values that were over 1% deviating from suggested target HbA1c. They got the most stringent recommendations. Twenty‐nine (50%) of them had available follow‐up HbA1c values showing a significant drop in HbA1c: from 9.1% (8.4%‐10.2%) to 8.5% (7.4%‐9.5%), P = .03. Conclusions Personalized, EHR algorithm‐based, management recommendations for diabetes upon discharge from hospitalization are feasible and beneficial.
机译:摘要背景虽然住院糖尿病患者的血糖控制很简单,但放电管理的个性化是挑战性的。治疗指南关于患者临床剖面的基础建议。根据患者电子健康记录(EHR)的临床概况,我们检查了实施卸货建议的可行性。方法根据当前指南设计决策算法。它被纳入EHR。完成了符合条件的糖尿病患者的前瞻性后续。结果在15个月内,835名患者(HBA1C为6.9%[6.2%-7.8%])达到了我们的纳入标准。 HBA1C采集的速率从Q1至85%,86%,88%和87%的55%增加。此外,将个性化管理建议纳入排放信件的速度增加:此后Q1至42.9%的14.9%,此后的42.9%,4.7.2%和53.4%。在出院时获得个性化建议的五十八(17.3%)患者具有超过1%的HBA1C值偏离建议的靶HBA1c。他们得到了最严格的建议。其中二十九(50%)的可用后续HBA1C值显示出HBA1C的显着下降:从9.1%(8.4%-10.2%)至8.5%(7.4%-9.5%),p = .03。结论在住院中排出时,糖尿病的个性化,基于EHR算法的管理建议是可行和有益的。

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