背景:与药物相关的再入院给患者带来负担,从而挑战了医疗保健系统,增加成本和紧张的资源。然而,到目前为止,关于药物相关再入院指标的研究尚未达成共识.
目的:本Delphi研究旨在开发一套基于共识的指标,用于检测存在药物相关再入院风险的患者。
方法:临床药师专家小组,医师和护理专家参与了两轮Delphi研究.在第1轮中,从文献中获取的31个指标的相关性评分为1至9,中位数评分为7或更高表明相关性。RAND/UCLA方法用于确定共识。在第2轮中,对缺乏共识的指标以及专家提出的一系列新指标进行了重新评级。有人要求为一些指标提供更多细节。主要成果是,共识,以及用于识别30天药物相关再入院风险的拟议指标的完整性。
结果:38名专家参加了第一轮。所有指标都达成了共识,包括25个,排除6个。34名专家参加了第二轮。所有5个新建议的指标都达成了共识,包括4个。专家小组对以下指标进行了优先排序:(1)不同医疗保健提供者之间的沟通不足,(2)复方药(≥7种药物),(3)药物依从性低(每周两次错误或遗漏给药),(4)复杂的用药方案(≥3剂,每天≥2种剂型和≥2种给药途径),和(5)多发病(≥3慢性疾病)。最后一组包括29个指标。
结论:为标记潜在的药物相关再入院而开发的指标集可以指导出院时临床药学服务的优先事项,改善患者预后和资源使用。计划对这些指标进行验证研究。
BACKGROUND: Medication-related readmissions challenge healthcare systems by burdening patients, increasing costs and straining resources. However, to date, there has been no
consensus study on indicators for medication-related readmissions.
OBJECTIVE: This Delphi study aimed to develop a
consensus-based set of indicators for detecting patients at risk of medication-related readmission.
METHODS: An expert panel of clinical pharmacists, physicians and nursing experts participated in a two-round Delphi study. In round 1, 31 indicators taken from the literature were rated for relevance on a scale from 1 to 9, with a median rating of 7 or higher suggesting relevance. The RAND/UCLA method was used to determine
consensus. In round 2, indicators lacking consensus were re-rated together with a series of new indicators generated by the experts. Additional details were sought for some indicators. The main outcomes were the relevance of, consensus on, and completeness of the proposed indicators for identifying risks of 30-day medication-related readmission.
RESULTS: Thirty-eight experts participated in round 1.
Consensus was found for all the indicators, with 25 included and 6 excluded. Thirty-four experts participated in round 2.
Consensus was found for all 5 newly suggested indicators, and 4 were included. The expert panel prioritized the following indicators: (1) insufficient communication between different healthcare providers, (2) polypharmacy (≥7 medications), (3) low rates of medication adherence (twice-weekly mistakes or missing administration), (4) complex medication regimens (≥3 doses, ≥2 dosage forms and ≥2 administration routes per day), and (5) multimorbidity (≥3 chronic conditions). The final set comprised 29 indicators.
CONCLUSIONS: The indicator set developed for flagging potential medication-related readmissions could guide priorities for clinical pharmacy services at hospital discharge, improving patient outcomes and resource use. A validation study of these indicators is planned.