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评估和识别提供物质使用障碍住院治疗的退伍军人事务部(VA)设施中计划外出院率的变化。

Evaluating and identifying changes in the rate of unplanned discharge among Department of Veterans Affairs (VA) facilities providing substance use disorder residential care.

机构信息

Veterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA; Geisel School of Medicine at Dartmouth College, 1 Rope Ferry Road, Hanover, NH 03755, USA.

Veterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA.

出版信息

J Subst Use Addict Treat. 2024 Dec;167:209514. doi: 10.1016/j.josat.2024.209514. Epub 2024 Sep 10.

Abstract

INTRODUCTION

Quality improvement (QI) methods play a critical role in ensuring that patients receive high-quality and timely care. Healthcare systems should use valid and reliable measures to inform QI efforts. Mental health settings including substance use disorder (SUD) residential programs have been slow to develop and incorporate quality measurement into routine practice. Unplanned discharge is of particular concern because this event is associated with harm including suicide. Healthcare systems require criteria that they can use to operationalize unplanned discharge as a quality measure in SUD residential programs.

METHODS

The study included all discharges from the Department of Veterans Affairs (VA) residential SUD programs between 2018 and 2022. The study calculated crude and adjusted rates of irregular discharge. The study used the first two years of observation (2018-2019) in a logistic regression model to determine the parameter estimates for three important covariates, age, risk for homelessness, and principal diagnosis. The study tested permutations of bin size (N) and days (D) per bin to identify a single set of parameters to enable small and large facilities to have sufficient power to detect out-of-control processes (i.e., significant worsening or improvement in rates). Aligned with standard nomenclature, the study calculated the control limits based on three standard deviations (SD). Values that fell above or below three SD were statistically significant.

RESULTS

The cohort included 56 facilities (26,361 discharges). Irregular discharge was associated with younger age (18-40 years) and a principal diagnosis of a drug use disorder. Testing parameter values of 100 discharges (N) over 120 days (D) would yield enough power to detect modest relative changes to the irregular discharge rate for small and large facilities while testing frequently enough to make the evaluations temporally relevant. Because secular trends such as staff changes over time will impact results, the quality control method should allow for real-time feedback to those most proximal to the event.

CONCLUSIONS

The study created a set of parameters and a methodology that residential SUD programs can use to operationalize unplanned discharge locally. These data could assist programs in conducting QI work to address unplanned discharge and related harms.

摘要

简介

质量改进(QI)方法在确保患者获得高质量和及时的护理方面起着至关重要的作用。医疗保健系统应使用有效和可靠的措施为 QI 工作提供信息。精神卫生机构,包括物质使用障碍(SUD)住院项目,在开发和将质量衡量纳入常规实践方面一直进展缓慢。非计划性出院尤其令人关注,因为这一事件与包括自杀在内的伤害有关。医疗保健系统需要制定他们可以用来将非计划性出院作为 SUD 住院项目质量衡量标准的标准。

方法

该研究包括 2018 年至 2022 年期间退伍军人事务部(VA)住院 SUD 项目的所有出院患者。该研究计算了不规则出院的粗率和调整率。该研究使用前两年的观察数据(2018-2019 年),在逻辑回归模型中确定三个重要协变量的参数估计值,即年龄、无家可归风险和主要诊断。该研究测试了 bin 大小(N)和 bin 天数(D)的排列,以确定一组单一的参数,使小和大的设施都有足够的能力来检测失控过程(即,发生率显著恶化或改善)。与标准命名法一致,该研究基于三个标准差(SD)计算控制限。落在三个 SD 以上或以下的值具有统计学意义。

结果

该队列包括 56 个设施(26361 例出院患者)。不规则出院与年龄较小(18-40 岁)和药物使用障碍的主要诊断有关。测试 100 次出院(N),持续 120 天(D)的参数值,将为小和大的设施提供足够的能力来检测不规则出院率的适度相对变化,同时进行足够频繁的测试,以使评估具有时间相关性。由于随着时间的推移,如工作人员的变化等季节性趋势会影响结果,因此质量控制方法应该允许对最接近事件的人员提供实时反馈。

结论

该研究创建了一套参数和方法,供住院 SUD 项目在当地实施非计划性出院。这些数据可以帮助项目开展 QI 工作,以解决非计划性出院和相关伤害问题。

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