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Data analysts play a critical role in empowering health systems to make changes that drive long-lasting improvement. With big data sets to collate, interpret, and translate, health systems rely on data analysts to transform numbers on a spreadsheet into meaningful insights that lead to change. In 2020, with the unexpected onset of COVID-19, the role of a data analyst has become increasingly fundamental to a health system’s ability to react quickly and effectively to the pandemic.
虽然数据分析人员在促进卫生系统内部改善方面发挥着至关重要的作用,但他们并不总是拥有所需的工具和支持。For example, a2018 surveyof data analysts by data science companyKaggleshows they spend the majority of their time cleaning data rather than analyzing it. As a result of overwhelming data support needs—exacerbated by the pandemic due to increased data-sharing and emerging analytic needs—healthcare data analysts spend most of their time on tasks that don’t lead to real care transformation.
Data analysts have many responsibilities, including interpreting large data sets, creating graphs andmodels, and understanding interoperability. However, this often means data analysts are all-consumed with secondary tasks, making it difficult to focus on their primary goal—assisting organizational leaders in achieving optimal healthcare management.
为了解锁数据,推动持续的、有意义的调整,并快速响应市场变化,数据分析师可以继续专注于顶级的授权工作,使用强大的分析工具,减轻基本责任。Sophisticated data and analytics tools can help cleanse dirty data, optimize data sharing and access, and centralize data into one place (e.g., the Health CatalystData Operating System (DOS™)). The value of analytics tools goes beyond the applications because it frees up analysts’ time to focus on improvement and more rapidly identify trends to drive business strategy.
Acquiring the following four skills, on top of having data and analytics support tools in place, will help data analysts perform at the top of their license, avoid getting bogged down by rudimentary tasks, and guide their organizations towards data-driven, meaningful improvement:
Smart healthcare organizations rely onhealthcare analyticsto guide care improvement and delivery decisions based on data insights. Throughout the process of transforming data into information, data analysts must rely on their foundational competencies to unleash the data within their organization’sanalytics platform, a big investment for any health system.
Ensuring data analysts havesix specific competenciesallows healthcare organizations to generate a return on investment for their data platform and maximize the data within the analytics platform to direct the improvement-oriented changes:
在数据分析师掌握了管理和分析数据的基本技能、知识和经验之后,什么能让他们更进一步?Data analysts transition from good to great when they keep theend goal in mindthroughout an entire project and derive objective information for decision makers along the way.
Data analysts can adopt two principles to begin with the end in mind:
Rising costs, an increasing focus onpopulation health, alternative payment models, and COVID-19 are a few reasons why healthcare is anything but simple. To manage this complexity, digitization is no longer an option but an imperative. At the heart of a digitized health system lies a need for healthcare data analysts to understand the system’s pressures, so their analyses help leaders develop strategies to improve care delivery and keep facility doors open and profitable. Analysts forecast volume, build dashboards, and more, but their real value lies in their ability to operate with aproblem-solving mindset.
Too often, low-level tasks (e.g., building dashboards, training other employees about new technologies, and generating one-off reports) encumber data analysts, leaving little time for problem solving. Although these tasks are part of the job, a data analyst must be proactive in freeing herself from focusing only on low-level work by continually asking herself if she is providing leaders with valuable information that drives change.
Data analysts must use data to understand a health system’s problems from an operational, clinical, and financial angle. With a comprehensive understanding of the problem, the data analyst is prepared to offer greater insights that lead to the right course of resolution.
As data becomes more abundant in healthcare, especially when organizations are emphasizing interoperability to learn more about COVID-19, so does the need for data detectives. A healthcare data analyst assumes the role ofdata detectiveby identifying new opportunities, determining how to pursue them, and leveraging data across all initiatives. The data detective pieces togetherreal-world conceptswithin a database to build accurate representations of a health system’s patient population with data. Then, the data detective analyzes and identifies potential target areas for improvement within the data construct and couples this analysis with a subject matter expert’s viewpoint to decide the best course of action.
Donning the data detective hat includes data analysis, seeking expertise from team members, and critically thinking about possible outcomes or scenarios based on expansive information from across the system to solve small and large problems spanning the organization.
As health systems feel more pressure toimprove outcomeswith limited resources, respond to COVID-19, and generaterevenue数据分析师使卫生系统保持在正确的轨道上,并在领导人走错方向时告知他们。如果数据分析师能够避免被次要任务(如数据准备和管理)所消耗,他们就可以将数据转换为有意义的信息。这些信息指导领导人作出合理的财务和临床决策,使卫生系统即使在大流行的可怕时期也能达到最高的运营效率。
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