Busch Alisa B, Epstein Arnold M, McGuire Thomas G, Normand Sharon-Lise T, Frank Richard G
McLean Hospital, Mailstop 226, 115 Mill St., Belmont, MA 02478, USA,
J Ment Health Policy Econ. 2015 Sep;18(3):115-24.
Examining health care system characteristics possibly associated with 30-day readmission may reveal opportunities to improve healthcare quality as well as reduce costs.
Examine the relationship between 30-day mental health readmission for persons with schizophrenia and county-level community treatment characteristics.
Observational study of 18 state Medicaid programs (N=274 counties, representing 103,967 enrollees with schizophrenia 28,083 of whom received more than 1 mental health hospitalization) using Medicaid administrative and United States Area Health Resource File data from 2005. Medicaid is a federal-state program and major health insurance provider for low income and disabled individuals, and the predominant provider of insurance for individuals with schizophrenia. The Area Health Resource File provides county-level estimates of providers. We first fit a regression model examining the relationship between 30-day mental health readmission and enrollee characteristics (e.g., demographics, substance use disorder [SUD], and general medical comorbidity) from which we created a county-level demographic and comorbidity case-mix adjuster. The case-mix adjuster was included in a second regression model examining the relationship between 30-day readmission and county-level factors: (i) quality (antipsychotic/visit continuity, post-hospital follow-up); (ii) mental health hospitalization (length of stay, admission rates); and (iii) treatment capacity (e.g., population-based estimates of outpatient providers/clinics). We calculated predicted probabilities of readmission for significant patient and county-level variables.
Higher county rates of mental health visits within 7-days post-hospitalization were associated with lower readmission probabilities (e.g., county rates of 7-day follow up of 55% versus 85%, readmission predicted probability (PP) [95%CI]=16.1% [15.8%-16.4%] versus 13.3% [12.9%-13.6%]). In contrast, higher county rates of mental health hospitalization were associated with higher readmission probabilities (e.g., country admission rates 10% versus 30%, readmission predicted probability=11.3% [11.0%-11.6%] versus 16.7% [16.4%-17.0%]). Although not our primary focus, enrollee comorbidity was associated with higher predicted probability of 30-day mental health readmission: PP [95%CI] for enrollees with SUD=23.9% [21.5%-26.3%] versus 14.7% [13.9%-15.4%] for those without; PP [95% CI] for those with=three chronic medical conditions=25.1% [22.1%-28.2%] versus none=17.7% [16.3%-19.1].
County rates of hospitalization and 7-day follow-up post hospital discharge were associated with readmission, along with patient SUD and general medical comorbidity. This observational design limits causal inference and utilization patterns may have changed since 2005. However, overall funding for U.S. Medicaid programs remained constant since 2005, reducing the likelihood significant changes. Last, our inability to identify community capacity variables associated with readmission may reflect imprecision of some variables as measured in the Area Health Resource File. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE AND FOR HEALTH POLICIES: Healthcare policy and programming to reduce 30-day mental health readmissions should focus on county-level factors that contribute to hospitalization in general and improving transitions to community care, as well as patient comorbidity.
Given the likely importance of local care systems, to reduce readmission future research is needed to refine community-level capacity variables that are associated with reduced readmissions; and to evaluate models of care coordination in this population.
研究可能与30天再入院相关的医疗保健系统特征,或许能揭示改善医疗质量以及降低成本的机会。
探讨精神分裂症患者30天心理健康再入院与县级社区治疗特征之间的关系。
利用2005年医疗补助管理数据和美国地区卫生资源文件数据,对18个州的医疗补助项目进行观察性研究(N = 274个县,代表103,967名精神分裂症参保者,其中28,083人接受过不止一次心理健康住院治疗)。医疗补助是一项联邦-州项目,是低收入和残疾个体的主要医疗保险提供者,也是精神分裂症患者的主要保险提供者。地区卫生资源文件提供县级医疗服务提供者的估计数据。我们首先拟合了一个回归模型,研究30天心理健康再入院与参保者特征(如人口统计学特征、物质使用障碍[SUD]和一般医疗合并症)之间的关系,并据此创建了一个县级人口统计学和合并症病例组合调整因子。该病例组合调整因子被纳入第二个回归模型,以研究30天再入院与县级因素之间的关系:(i)质量(抗精神病药物/就诊连续性、出院后随访);(ii)心理健康住院治疗(住院时间、入院率);以及(iii)治疗能力(如基于人口的门诊医疗服务提供者/诊所估计数)。我们计算了重要患者和县级变量的再入院预测概率。
住院后7天内县级心理健康就诊率较高与再入院概率较低相关(例如,7天随访率为55%对85%,再入院预测概率[95%置信区间]=16.1% [15.8%-16.4%]对13.3% [12.9%-13.6%])。相反,县级心理健康住院率较高与再入院概率较高相关(例如,县级入院率为10%对30%,再入院预测概率=11.3% [11.0%-11.6%]对16.7% [16.4%-17.0%])。虽然不是我们的主要关注点,但参保者合并症与30天心理健康再入院的较高预测概率相关:有SUD的参保者的预测概率[95%置信区间]=23.9% [21.5%-26.3%],而无SUD的参保者为14.7% [13.9%-15.4%];有三种慢性疾病的参保者的预测概率[95%置信区间]=25.1% [22.1%-28.2%],而无慢性疾病的参保者为17.7% [16.3%-19.1%]。
县级住院率和出院后7天随访与再入院相关,患者的SUD和一般医疗合并症也与之相关。这种观察性设计限制了因果推断,自2005年以来利用模式可能已发生变化。然而,自2005年以来美国医疗补助项目的总体资金保持不变,降低了发生重大变化的可能性。最后,我们无法识别与再入院相关的社区能力变量,这可能反映了地区卫生资源文件中某些变量测量的不精确性。对医疗保健提供与使用以及卫生政策的启示:旨在减少30天心理健康再入院的医疗保健政策和规划应关注导致总体住院的县级因素、改善向社区护理的过渡以及患者合并症。
鉴于地方护理系统可能具有重要性,为减少再入院,未来需要开展研究以完善与降低再入院相关的社区层面能力变量;并评估该人群的护理协调模式。