Using a Decision Support Algorithm for Referrals to Post-Acute Care
Using a Decision Support Algorithm for Referrals to Post-Acute Care
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DOI：
10.1016/j.jamda.2018.08.016
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发表时间：
2019-04-01
影响因子：
7.6
通讯作者：
Naylor, Mary D.
中科院分区：
文献类型：
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作者：
Bowles, Kathryn H.;Ratcliffe, Sarah J.;Naylor, Mary D.
目标：尽管医院临床医生努力有效转诊需要急性后护理 (PAC) 的患者，但他们的出院计划流程往往差异很大，而且通常不是基于证据的。设计：采用前/后设计的准实验研究。为了改善以患者为中心的出院流程，我们检查了出院转诊专家系统 (DIRECT) 算法的效果，该算法提供临床决策支持 (CDS)，决定哪些患者转诊至 PAC 以及接受何种程度的护理（家庭护理或机构）。设置和参与者：在 2 家医院进行，在前期（对照）收集 DIRECT 数据元素，但出院临床医生对建议视而不见，并提供常规出院护理。在后期（干预）期间，临床医生会在入院后 24 小时内提供转诊建议，并每天更新两次。使用倾向模型来解释治疗前/治疗后患者队列之间的差异。测量：对照组和干预期之间的结果比较包括 PAC 转诊率、患者特征以及相同、7、14 和 30 天的再入院或急诊科就诊。结果：虽然通过 DIRECT 算法建议建议进行 PAC 转诊的患者增加了 24%-25%，但接受 PAC 转诊的患者比例在对照组之间没有显着差异（3302）和干预（5006）时期。然而，与没有接受 DIRECT CDS 的临床医生相比，转诊接受 PAC 服务的患者特征存在显着差异，并且在所有时间间隔内，住院患者的再入院率均显着下降。急诊科回访没有观察到差异。当临床医生同意转诊算法（是/是）时，观察到最大的效果。结论/启示：我们的研究结果表明，及时、自动化、出院 CDS 对于临床医生优化 PAC 转诊以帮助最有可能受益的人具有价值。尽管 CDS 的总体转诊率没有变化，但该算法可能已经识别出最需要的患者，从而显着降低住院患者的再入院率。 (C) 2018 AMDA - 急性后和长期护理医学协会。
Objectives: Although hospital clinicians strive to effectively refer patients who require post-acute care (PAC), their discharge planning processes often vary greatly, and typically are not evidence-based.Design: Quasi-experimental study employing pre-/postdesign. Aimed at improving patient-centered discharge processes, we examined the effects of the Discharge Referral Expert System for Care Transitions (DIRECT) algorithm that provides clinical decision support (CDS) regarding which patients to refer to PAC and to what level of care (home care or facility).Setting and participants: Conducted in 2 hospitals, DIRECT data elements were collected in the pre-period (control) but discharging clinicians were blinded to the advice and provided usual discharge care. During the postperiod (intervention), referral advice was provided within 24 hours of admission to clinicians, and updated twice daily. Propensity modeling was used to account for differences between the pre-/post patient cohorts.Measures: Outcomes compared between the control and the intervention periods included PAC referral rates, patient characteristics, and same-, 7-, 14-, and 30-day readmissions or emergency department visits.Results: Although 24%-25% more patients were recommended for PAC referral by DIRECT algorithm advice, the proportion of patients receiving referrals for PAC did not significantly differ between the control (3302) and intervention (5006) periods. However, the characteristics of patients referred for PAC services differed significantly and inpatient readmission rates decreased significantly across all time intervals when clinicians had DIRECT CDS compared with without. There were no differences observed in return emergency department visits. Largest effects were observed when clinicians agreed with the algorithm to refer (yes/yes).Conclusions/Implications: Our findings suggest the value of timely, automated, discharge CDS for clinicians to optimize PAC referral for those most likely to benefit. Although overall referral rates did not change with CDS, the algorithm may have identified those patients most in need, resulting in significantly lower inpatient readmission rates. (C) 2018 AMDA - The Society for Post-Acute and Long-Term Care Medicine.