Department of Medicine, Yale New Haven Hospital, New Haven, Connecticut, United States.
Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.
Appl Clin Inform. 2023 Oct;14(5):932-943. doi: 10.1055/a-2184-6481. Epub 2023 Sep 29.
Asthma is a common cause of morbidity and mortality in children. Predictive models may help providers tailor asthma therapies to an individual's exacerbation risk. The effectiveness of asthma risk scores on provider behavior and pediatric asthma outcomes remains unknown.
Determine the impact of an electronic health record (EHR) vendor-released model on outcomes for children with asthma.
The Epic Systems Risk of Pediatric Asthma Exacerbation model was implemented on February 24, 2021, for volunteer pediatric allergy and pulmonology providers as a noninterruptive risk score visible in the patient schedule view. Asthma hospitalizations, emergency department (ED) visits, or oral steroid courses within 90 days of the index visit were compared from February 24, 2019, to February 23, 2022, using a difference-in-differences design with a control group of visits to providers in the same departments. Volunteer providers were interviewed to identify barriers and facilitators to model use.
In the intervention group, asthma hospitalizations within 90 days decreased from 1.4% (54/3,842) to 0.7% (14/2,165) after implementation with no significant change in the control group (0.9% [171/19,865] preimplementation to 1.0% [105/10,743] post). ED visits in the intervention group decreased from 5.8% (222/3,842) to 5.5% (118/2,164) but increased from 5.5% (1,099/19,865) to 6.8% (727/10,743) in the control group. The adjusted difference-in-differences estimators for hospitalization, ED visit, and oral steroid outcomes were -0.9% (95% confidence interval [CI]: -1.6 to -0.3), -2.4% (-3.9 to -0.8), and -1.9% (-4.3 to 0.5). In qualitative analysis, providers understood the purpose of the model and felt it was useful to flag high exacerbation risk. Trust in the model was calibrated against providers' own clinical judgement.
This EHR vendor model implementation was associated with a significant decrease in asthma hospitalization and ED visits within 90 days of pediatric allergy and pulmonology clinic visits, but not oral steroid courses.
哮喘是儿童发病率和死亡率的常见原因。预测模型可以帮助提供者根据个体的恶化风险来定制哮喘治疗方案。哮喘风险评分对提供者行为和儿科哮喘结果的影响尚不清楚。
确定电子健康记录(EHR)供应商发布的模型对哮喘儿童结局的影响。
2021 年 2 月 24 日,在志愿儿科过敏和肺病学提供者中实施了 Epic Systems 儿童哮喘恶化风险模型,作为在患者日程视图中可见的非中断风险评分。使用差异中的差异设计,与同一科室的提供者的就诊对照组相比,比较 2019 年 2 月 24 日至 2022 年 2 月 23 日索引就诊后 90 天内的哮喘住院、急诊部(ED)就诊或口服类固醇疗程。对志愿提供者进行访谈,以确定模型使用的障碍和促进因素。
在干预组中,哮喘住院率从实施前的 1.4%(54/3842)降至实施后的 0.7%(14/2165),而对照组无显著变化(实施前为 0.9%[171/19865],实施后为 1.0%[105/10743])。干预组的 ED 就诊次数从 5.8%(222/3842)降至 5.5%(118/2164),但对照组从 5.5%(1099/19865)增至 6.8%(727/10743)。住院、ED 就诊和口服类固醇治疗结果的调整差异差异估计值分别为-0.9%(95%置信区间[CI]:-1.6 至-0.3)、-2.4%(-3.9 至-0.8)和-1.9%(-4.3 至 0.5)。在定性分析中,提供者理解模型的目的,并认为它有助于标记高恶化风险。对模型的信任与提供者自己的临床判断相校准。
这项 EHR 供应商模型实施与儿科过敏和肺病学诊所就诊后 90 天内哮喘住院和 ED 就诊次数的显著减少相关,但与口服类固醇治疗无关。