Health Informatics and Management, College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA.
J Am Med Inform Assoc. 2019 May 1;26(5):383-391. doi: 10.1093/jamia/ocy181.
Growth in big data and its potential impact on the healthcare industry have driven the need for more data scientists. In health care, big data can be used to improve care quality, increase efficiency, lower costs, and drive innovation. Given the importance of data scientists to U.S. healthcare organizations, I examine the qualifications and skills these organizations require for data scientist positions and the specific focus of their work.
A content analysis of U.S. healthcare data scientist job postings was conducted using an inductive approach to capture and categorize core information about each posting and a deductive approach to evaluate skills required. Profiles were generated for 4 job focus areas.
There is a spectrum of healthcare data scientist positions that varies based on hiring organization type, job level, and job focus area. The focus of these positions ranged from performance improvement to innovation and product development with some positions more broadly defined to address organizational-specific needs. Based on the job posting sample, the primary skills these organizations required were statistics, R, machine learning, storytelling, and Python.
These results may be useful to organizations as they deepen our understanding of the qualifications and skills required for data scientist positions and may aid organizations in identifying skills and knowledge areas that have been overlooked in position postings.
大数据的增长及其对医疗保健行业的潜在影响促使对更多数据科学家的需求增加。在医疗保健领域,大数据可用于提高护理质量、提高效率、降低成本和推动创新。鉴于数据科学家对美国医疗机构的重要性,我研究了这些组织对数据科学家职位的要求和他们工作的具体重点。
使用归纳法对美国医疗保健数据科学家职位的职位发布进行内容分析,以捕获和分类每个职位的核心信息,并采用演绎法评估所需的技能。为 4 个工作重点领域生成了简介。
存在一系列医疗保健数据科学家职位,其因招聘组织类型、工作级别和工作重点领域而异。这些职位的重点范围从绩效改进到创新和产品开发,有些职位的定义更为广泛,以满足组织的特定需求。根据职位发布样本,这些组织主要需要的技能是统计学、R、机器学习、故事讲述和 Python。
这些结果可能对组织有用,因为它们加深了我们对数据科学家职位所需的资格和技能的理解,并可能帮助组织识别在职位发布中被忽视的技能和知识领域。