Socio-demographic and -economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: a population-based study.
Socio-demographic and -economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: a population-based study.
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DOI：
10.1186/s12889-021-11987-z
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发表时间：
2021-10-23
影响因子：
4.5
通讯作者：
Jacobs DM
中科院分区：
文献类型：
--
作者：
Murray F;Allen M;Clark CM;Daly CJ;Jacobs DM
早期再入院在CMS医院再入院减少计划（HRRP）针对的患者中仍然很常见。关于是否应该根据社会因素调整再入院措施，目前还没有达成共识，美国国内也很少有人口研究研究社会特征如何影响HRRP目标条件的再入院。本研究的目的是确定特定的社会人口统计学和经济学因素是否与HRRP靶向条件下的30天再入院相关：慢性阻塞性肺疾病急性加重、肺炎、急性心肌梗死和心力衰竭。全国再入院数据库用于识别2010年1月1日至2015年9月30日期间因HRRP目标疾病入院的患者。卒中被纳入作为对照条件，因为它不包括在HRRP中。多变量模型被用来评估三个社会和经济特征之间的关系（性别，城市/农村医院指定，估计家庭收入中位数内的患者的邮政编码）和30天的再入院率使用分层两级逻辑模型。使用经调整的模型来评估Medicare与非Medicare人群之间的关系差异。2010年至2015年期间，所有诊断的加权指数住院人数为19，253，997人，30天内再入院人数为3，613，488人。在所有条件下，收入最低的四分位数（≤ 37，999美元）患者30天再入院的几率增加（P < 0.0001）。女性和农村医院与大多数目标条件下30天再入院的几率降低相关（P < 0.05）。在≥65岁的患者中也观察到类似结果。社会人口统计学和经济因素与30天再入院率相关，应纳入工具或干预措施，以改善出院计划和减轻再入院。
Early hospital readmissions remain common in patients with conditions targeted by the CMS Hospital Readmission Reduction Program (HRRP). There is still no consensus on whether readmission measures should be adjusted based on social factors, and there are few population studies within the U.S. examining how social characteristics influence readmissions for HRRP-targeted conditions. The objective of this study was to determine if specific socio-demographic and -economic factors are associated with 30-day readmissions in HRRP-targeted conditions: acute exacerbation of chronic obstructive pulmonary disease, pneumonia, acute myocardial infarction, and heart failure. The Nationwide Readmissions Database was used to identify patients admitted with HRRP-targeted conditions between January 1, 2010 and September 30, 2015. Stroke was included as a control condition because it is not included in the HRRP. Multivariate models were used to assess the relationship between three social and economic characteristics (gender, urban/rural hospital designation, and estimated median household income within the patient’s zip code) and 30-day readmission rates using a hierarchical two-level logistic model. Age-adjusted models were used to assess relationship differences between Medicare vs. non-Medicare populations. There were 19,253,997 weighted index hospital admissions for all diagnoses and 3,613,488 30-day readmissions between 2010 and 2015. Patients in the lowest income quartile (≤$37,999) had an increased odds of 30-day readmission across all conditions (P < 0.0001). Female gender and rural hospital designation were associated with a decreased odds of 30-day readmission for most targeted conditions (P < 0.05). Similar findings were also seen in patients ≥65 years old. Socio-demographic and -economic factors are associated with 30-day readmission rates and should be incorporated into tools or interventions to improve discharge planning and mitigate against readmission.
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