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

动机：医疗保健的提供是高度劳动密集型的，需要一支受过多年培训的多学科劳动力。向病人提供的护理质量关键取决于个别工作人员的可用性和质量，以及他们如何在团队中共同工作。NHS是英格兰最大的雇主，2016年雇佣了100多万人，成本超过500亿英镑(卫生部，2017年)。但NHS薪酬审查机构和英国国家审计署指出，关于现有员工有效分配的证据很少，缺乏长期的劳动力规划(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)。这样的证据和规划对于控制成本和确保患者得到尽可能高质量的护理是重要的。目标和方法：我们建议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劳动力组织方式对卫生保健使用和患者结果的因果影响。我们的第一个项目探索了最资深医生(NHS顾问)的质量和生产率差异的决定因素。越来越明显的是，不同医生的患者结果存在很大差异，即使在同一家医院也是如此。其中一些可能是由于医生之间的病人分配，例如，让最有经验的病人更难治疗。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变异，并确定与医生相关的哪些因素与这种变异有关。我们将使用大规模数据，通过利用医生在职业生涯中在医院之间的流动来区分个别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的主要组织形式，因此了解团队变化的因果影响是很重要的。项目二探讨了预期和意想不到的护理团队中断对患者护理和成本的影响。为此，我们将利用新的数据源，提供5家医院所有病房工作人员轮换的详细数据，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来探索医生资历、生产率和患者结果之间的关系。这些罢工改变了治疗病人的工作人员的组合，导致在这些团队中工作的高级人员(NHS顾问)的比例暂时较高。为了进行我们的研究，我们将利用几个数据来源，包括来自医院流行病学统计的丰富的管理数据，以及来自伦敦一家大型NHS医院集团的最新可用的高度细粒度的数据。应用、好处和影响：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率、医院利用率和患者结果变化中的作用。我们的发现将提供信息和工具，帮助政策制定者提高现有劳动力的效率，提高患者护理的质量，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输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论文。我们还将制作一些新闻发布的非技术性报告，总结针对记者、政策制定者和其他非学术用户的关键调查结果。特别是，我们将针对国家政策制定者，包括英国卫生和社会保障部和健康教育部门，以及个人急性信托基金等医疗保健提供者。我们还将与卫生保健工作者及其代表进行接触。

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.