Barriers to data quality resulting from the process of coding health information to administrative data: a qualitative study.
Barriers to data quality resulting from the process of coding health information to administrative data: a qualitative study.
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DOI：
10.1186/s12913-017-2697-y
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发表时间：
2017-11-22
影响因子：
2.8
通讯作者：
Quan H
中科院分区：
文献类型：
--
作者：
Lucyk K;Tang K;Quan H
行政卫生数据越来越多地用于研究和监测，为决策提供信息，因为其样本量大，地理覆盖面广，综合性强，并可能进行纵向跟踪。在加拿大各省内，每个人都被分配了独特的个人健康号码，以便在该管辖区内连接行政健康记录。因此，有必要确保这些数据的高质量，并确保海图信息得到准确编码，以满足这一目的。我们的目标是探索潜在的障碍，存在高质量的数据编码，通过定性调查的角色和职责的医疗图表编码。我们对来自加拿大阿尔伯塔的28名医疗图表编码员进行了半结构化访谈。我们使用主题分析和开放编码的每个成绩单，以了解行政卫生数据生成的过程，并确定其质量的障碍。生成行政卫生数据的过程非常复杂，涉及到各种各样的工作人员。因此，在这个过程中有多个点对高质量数据提出了挑战。对于编码人员来说，影响数据质量的主要障碍是图表文档、图表信息解释的可变性以及高配额期望。这项研究说明了高质量编码的障碍的复杂性，在行政数据生成的背景下。这项研究的结果可能对数据用户，研究人员和决策者有用，他们希望更好地了解其数据的局限性或采取干预措施以提高数据质量。本文的在线版本（10.1186/s12913 - 017 - 2697-y）包含补充材料，可供授权用户使用。
Administrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders. We conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality. The process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations. This study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality. The online version of this article (10.1186/s12913-017-2697-y) contains supplementary material, which is available to authorized users.
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10.1186/s13049-016-0242-3
发表时间：
2016-04-16
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作者：
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通讯作者：
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