The impact of medical labour on variation in patient outcomes: evidence from English public hospitals

动机：提供医疗保健是高度劳动密集型的工作，需要经过多年培训的多学科工作人员。向患者提供的护理质量在很大程度上取决于个人工作人员的可用性和质量，以及他们如何在团队中协同工作。NHS是英国最大的雇主，2016年雇佣了100多万人，成本超过500亿英镑（Department of Health, 2017）。但NHS薪酬审查机构和英国国家审计署注意到，现有工人有效分配的证据很少，长期劳动力规划缺乏（NHS薪酬审查机构，2017；医生和牙医薪酬审查机构，2017；国家审计署，2016）。这类证据和规划对于控制成本和确保患者获得尽可能高质量的护理非常重要。目的和方法：我们提出的研究将使用计量经济学技术和丰富的管理数据来确定卫生保健工作人员组织卫生保健使用和患者结果的方式的因果影响。我们的第一个项目探讨了最资深的医生（NHS顾问）的质量和生产力变化的决定因素。越来越明显的是，即使在同一家医院，医生对病人的治疗结果也存在很大差异。其中一些可能是由于医生对病人的分配，例如，让最有经验的医生更难治疗病人。但这似乎并不是唯一的驱动因素。我们的研究将试图量化这种差异，并确定哪些与医生相关的因素与这种差异有关。我们将使用大规模的数据，通过利用医生在整个医院的职业生涯中的流动，来分离出个人医生和他们工作的医院的影响。我们的第二个和第三个项目检查团队生产。团队是医疗保健工作人员组织的主要形式，因此了解团队变化的因果关系非常重要。项目二探讨了预期和意外中断对护理团队对患者护理和成本的影响。为此，我们将利用新的数据来源，提供5家医院所有病房的工作人员轮班的详细数据，这些数据可以与治疗和患者结果联系起来。项目三将通过分析2016年和2017年初级医生的一系列罢工，探索医生资历、生产力和患者预后之间的关系。这些罢工改变了治疗病人的人员组合，导致在这些团队中工作的高级员工（NHS顾问）的比例暂时更高。为了开展我们的研究，我们将利用几个数据源，包括来自医院事件统计的丰富行政数据和来自伦敦一家大型NHS医院集团的新获得的高粒度数据。应用、效益和影响：我们的最终目标是让政策制定者更好地了解劳动力在生产力、医院利用率和患者治疗结果变化中的作用。我们的研究结果将提供信息和工具，帮助决策者提高现有劳动力的效率，提高患者护理质量，并为未来的劳动力规划提供信息。我们将通过制作一系列将结果传达给多个受众的产出来最大限度地发挥影响。我们将向顶级经济期刊提交一系列学术文章。我们还将制作一些非技术报告，这些报告总结了针对记者、政策制定者和其他非学术用户的主要发现。特别是，我们将针对国家政策制定者，包括英格兰卫生和社会保健和健康教育部，以及卫生保健提供者，如个人急性信托。我们还将与卫生保健工作者及其代表接触。

Motivation: The provision of healthcare is highly labour intensive, requiring a multi-disciplinary workforce with many years of training. Quality of care provided to patients depends crucially on both the availability and quality of individual staff and how they work together in teams. The NHS is the largest employer in England, employing more than a million people at a cost of more than £50 billion in 2016 (Department of Health, 2017). But NHS pay review bodies and the UK National Audit Office have noted that evidence on the efficient allocation of existing workers is scarce and long-term workforce planning is lacking (NHS Pay Review Body, 2017; Review Body on Doctor's and Dentist's Remuneration, 2017; National Audit Office, 2016). Such evidence and planning are important in order to contain costs and ensure that patients receive the highest possible quality of care. Aims and methodology: Our proposed research will use econometric techniques and rich administrative data to identify the causal effects of the way in which the health care workforce is organised on healthcare use and patient outcomes. Our first project explores the determinants of variation in the quality and productivity of the most senior doctors (NHS consultants). It is becoming clear that there is wide variation across doctors in their patient outcomes, even within the same hospital. Some of this may be due to patient allocation across doctors, for example, giving the most experienced harder to treat patients. But this does not appear to be the only driver. Our research will seek to quantify this variation and to determine what factors associated with the doctors are associated with this variation. We will use large scale data in order to separate out the effect of the individual doctor and the hospitals in which they work by exploiting movement in doctors across hospitals during their careers. Our second and third projects examine team production. Teams are the dominant form of organisation of staff in healthcare and it is therefore important to understand the causal effects of changes to teams. Project two examines explores the impacts of anticipated and unanticipated disruptions to nursing teams on patient care and costs. To do so, we will exploit new data sources that provide detailed data on staff rotas across all wards in 5 hospitals, which can be linked to treatments and patient outcomes. Project three will explore the relationship between doctor seniority, productivity and patient outcomes by analysing a series of strikes by junior doctors in 2016 and 2017. These strikes changed the mix of staff treating patients, leading to a temporarily higher proportion of senior staff (NHS consultants) working in these teams. To conduct our research we will exploit several data sources, including rich administrative data from the Hospital Episode Statistics and newly available, highly granular, data from one large London NHS hospital group. Applications, benefits and impact: Our ultimate aim is to allow policymakers to better understand the role of the workforce in variation in productivity, hospital utilisation and patient outcomes. Our findings will provide information and tools that help policymakers improve the efficiency of the existing workforce, raise the quality of patient care, and inform future workforce planning. We will maximise impact by producing a range of outputs that communicate the results to multiple audiences. We will submit a series of academic articles to top economic journals. We will also produce a number of press-released non-technical reports, which summarise the key findings directed at journalists, policymakers and other non-academic users. In particular, we will target national policymakers, including the Department of Health and Social Care and Health Education England, and health care providers, such as individual Acute Trusts. We will also engage with health care workers and their representatives.