Department of Value-based Healthcare, St. Antonius Hospital, P.O. Box 2500, 3430, EM, Nieuwegein, the Netherlands.
Radboud university medical center, Radboud Institute for Health Sciences, Scientific Center for Quality of Healthcare (IQ healthcare), P.O. Box 9101, 6500, HB, Nijmegen, the Netherlands.
BMC Health Serv Res. 2020 Mar 19;20(1):232. doi: 10.1186/s12913-020-05090-z.
Measuring and improving outcomes is a central element of value-based health care. However, selecting improvement interventions based on outcome measures is complex and tools to support the selection process are lacking. The goal was to present strategies for the systematic identification and selection of improvement interventions applied to the case of aortic valve disease and to combine various methods of process and outcome assessment into one integrated approach for quality improvement.
For this case study a concept-driven mixed-method approach was applied for the identification of improvement intervention clusters including: (1) benchmarking outcomes, (2) data exploration, (3) care delivery process analysis, and (4) monitoring of ongoing improvements. The main outcome measures were long-term survival and 30-day mortality. For the selection of an improvement intervention, the causal relations between the potential improvement interventions and outcome measures were quantified followed by a team selection based on consensus from a multidisciplinary team of professionals.
The study resulted in a toolbox: the Intervention Selection Toolbox (IST). The toolbox comprises two phases: (a) identifying potential for improvement, and (b) selecting an effective intervention from the four clusters expected to lead to the desired improvement in outcomes. The improvements identified for the case of aortic valve disease with impact on long-term survival in the context of the studied hospital in 2015 include: anticoagulation policy, increased attention to nutritional status of patients and determining frailty of patients before the treatment decision.
Identifying potential for improvement and carefully selecting improvement interventions based on (clinical) outcome data demands a multifaceted approach. Our toolbox integrates both care delivery process analyses and outcome analyses. The toolbox is recommended for use in hospital care for the selection of high-impact improvement interventions.
衡量和改善结果是基于价值的医疗保健的核心要素。然而，基于结果衡量标准选择改进干预措施是复杂的，并且缺乏支持选择过程的工具。目的是提出一种系统识别和选择改进干预措施的策略，应用于主动脉瓣疾病，并将各种过程和结果评估方法结合为一个综合的质量改进方法。
为了进行这项案例研究，采用了一种基于概念的混合方法，用于确定改进干预措施集群，包括：（1）基准结果，（2）数据探索，（3）护理提供过程分析，以及（4）持续改进监测。主要结果测量是长期生存和 30 天死亡率。为了选择改进干预措施，我们量化了潜在改进干预措施与结果衡量标准之间的因果关系，然后根据多学科专业人员团队的共识进行团队选择。
该研究产生了一个工具包：干预选择工具包（IST）。该工具包包括两个阶段：（a）确定改进的潜力，（b）从四个集群中选择一种有效的干预措施，预计这些干预措施将导致预期的结果改善。在 2015 年研究医院背景下，针对主动脉瓣疾病确定的可提高长期生存的改进措施包括：抗凝政策、增加对患者营养状况的关注以及在治疗决策前确定患者的脆弱性。
确定改进的潜力并根据（临床）结果数据仔细选择改进干预措施需要一种多方面的方法。我们的工具包整合了护理提供过程分析和结果分析。该工具包推荐用于医院护理，以选择高影响力的改进干预措施。
