USING DATA ANALYTICS TO EXPLORE THE CONNECTION AND IMPACT OF SOCIAL SCIENCE AND ECONOMICS IN THE WORLD OF HEALTHCARE

该项目的目标是将社会科学与经济学联系起来，使医疗保健尽可能有效、安全、以患者为中心并具有成本效益。该项目扩展了以前的研究和领域，如传统的医疗保健信息学和经济学，通过研究这些方面的组合，而不是单独研究它们。为了实现该项目的目标，将探索一系列数据分析技术，首先将临床、成本和护理数据联系起来，然后从成功和不成功的情况中了解驱动因素，最后建立一个强大的决策工具，以协助提供高效和有效的高质量护理。本项目将考虑烧伤护理领域作为一个基本案例，探索社会科学和经济学在医疗保健领域的联系和影响。这一选择是由几个因素驱动的，包括烧伤的性质——烧伤护理影响到来自不同社会阶层的所有年龄组的患者——以及获得全面的患者和成本数据库（该项目将获得最全面的关于烧伤的临床和经济学数据，涵盖英格兰和威尔士nhs专业烧伤护理服务的入院情况）。以一种有意义的方式连接这两个数据库将是该项目的第一个里程碑。在此之后，下一步将是用烧伤患者的护理途径和社会阶层指标的信息来增加数据库。这个全面的数据库将作为使用一系列数据分析技术探索关键驱动因素、关系和数据模式的坚实基础。参与该项目的利益相关者（学术界，工业界和政府）热衷于回答一些问题，包括：预测烧伤死亡率的关键驱动因素是什么？我们预测死亡率的准确性如何？在过去十年中（这是我们临床数据的时间跨度），我们可以从护理途径的成功率和成本的演变中了解到什么？成功的患者护理路径与相关成本之间的关系是什么？病人的社会特征（如社会阶层）是如何影响治疗质量的？我们能否将患者分为成本组和/或社会组，以实现可靠的成本预测？我们能否提出比目前政府实施的更有效、更经济、更安全的个性化护理途径？我们如何利用本研究中获得的知识来开发一种实用的决策工具，以帮助提供以患者为中心和具有成本效益的护理？该项目的研究结果将在科学领域（用于描述和预测有效护理途径的新见解和数据分析模型，烧伤患者的死亡率，患者群体的成本水平），工业领域（促进实施更有效的烧伤患者护理的实用决策工具），和政府（对成功护理途径的关键驱动因素的新见解和改进的患者成本分组策略，以支持NHS基于患者层面成本的烧伤服务的委托和报酬）。这些发现也将成为未来将医疗保健部门与社会科学联系起来的数据分析研究的基础和灵感。

The goal of this project is to connect social science with economics to make healthcare as effective, safe, patient-centred, and cost-efficient as possible. This project extends previous research and domains, such as traditional healthcare informatics and economics, by investigating the combination of these aspects rather than examining them isolated from each other. To reach the goal of the project, a range of data analytics techniques will be explored to first link clinical, cost and care data, then understand the driving factors from both successful and unsuccessful scenarios, and finally build a robust decision tool to assist the delivery of efficient and effective high-quality care. This project will consider the field around burn injury care as a base case to explore the connection and impact of social science and economics in the world of healthcare. This choice is motivated by several factors including the nature of burns injuries - burns care affects patients across all age groups from different social classes - and access to a comprehensive patient and cost database (the project will have access to the most comprehensive collection of clinical and economics data concerning burn injury covering England and Wales admissions to NHS-specialised burn care services). Connecting these two databases in a meaningful way will be the first milestone of the project. Following this, the next step will be to augment the database with information about care pathways for burns injury patients and social class indicators. This comprehensive database will serve as a solid foundation to explore key drivers, and relationships and patterns in the data using a range of data analytics techniques. The stakeholders involved in this project (academia, industry, and government) are keen to answer a number of questions including:What are the key drivers when predicting burns mortality and how accurately can we predict mortality?What can we learn about decisions made in the past decade (this is the timespan of our clinical data) in terms of the success rate of care pathways and evolution of costs?What is the relationship between a successful patients care path and the associated costs?How do the social characteristics - such as social class of - a patient mediate the quality of care received?Can we divide patients into cost and/or social groups to enable robust cost predictions?Can we suggest personalized care pathways that are more effective and cost-efficient, and safer than the pathways implemented by the government at the moment?How can we make use of the knowledge gained in this study to develop a practical decision tool to assist the delivery of patient centred and cost efficient care?The findings of this project will have an impact across the domains of science (novel insights and data analytics models for characterising and predicting efficient care pathways, mortality of burns injury patients, patient groups in terms of costs levels), industry (a practical decision tool to facilitate the implementation of more efficient delivery of care of burns injury patients), and government (novel insights into key drivers for successful care pathways and an improved strategy for cost grouping of patients to support the NHS in the commissioning and remuneration of burn services based on patient-level costing). The findings will also serve as the foundation and inspiration for future data analytics studies linking the healthcare sector with social science.