Johnson Stephen B, Farach Frank J, Pelphrey Kevin, Rozenblit Leon
Division of Health Informatics, Weill Cornell Medical College, 425 East 61st Street, DV-317, New York, NY 10065, United States.
Prometheus Research, LLC, New Haven, CT, United States.
J Biomed Inform. 2016 Apr;60:286-93. doi: 10.1016/j.jbi.2016.02.014. Epub 2016 Feb 27.
This study assesses data management needs in clinical research from the perspectives of researchers, software analysts and developers.
This is a mixed-methods study that employs sublanguage analysis in an innovative manner to link the assessments. We performed content analysis using sublanguage theory on transcribed interviews conducted with researchers at four universities. A business analyst independently extracted potential software features from the transcriptions, which were translated into the sublanguage. This common sublanguage was then used to create survey questions for researchers, analysts and developers about the desirability and difficulty of features. Results were synthesized using the common sublanguage to compare stakeholder perceptions with the original content analysis.
Individual researchers exhibited significant diversity of perspectives that did not correlate by role or site. Researchers had mixed feelings about their technologies, and sought improvements in integration, interoperability and interaction as well as engaging with study participants. Researchers and analysts agreed that data integration has higher desirability and mobile technology has lower desirability but disagreed on the desirability of data validation rules. Developers agreed that data integration and validation are the most difficult to implement.
Researchers perceive tasks related to study execution, analysis and quality control as highly strategic, in contrast with tactical tasks related to data manipulation. Researchers have only partial technologic support for analysis and quality control, and poor support for study execution.
Software for data integration and validation appears critical to support clinical research, but may be expensive to implement. Features to support study workflow, collaboration and engagement have been underappreciated, but may prove to be easy successes. Software developers should consider the strategic goals of researchers with regard to the overall coordination of research projects and teams, workflow connecting data collection with analysis and processes for improving data quality.
本研究从研究人员、软件分析师和开发者的角度评估临床研究中的数据管理需求。
这是一项混合方法研究，以创新方式运用子语言分析来关联各项评估。我们使用子语言理论对四所大学的研究人员进行的转录访谈进行内容分析。一名业务分析师从转录内容中独立提取潜在的软件功能，并将其转化为子语言。然后，这种通用子语言被用于为研究人员、分析师和开发者创建关于功能的可取性和难度的调查问卷。使用通用子语言综合结果，以比较利益相关者的看法与原始内容分析。
个体研究人员表现出显著的观点多样性，且与角色或研究地点无关。研究人员对他们的技术看法不一，并寻求在集成、互操作性和交互方面的改进，以及与研究参与者的互动。研究人员和分析师一致认为数据集成的可取性较高，移动技术的可取性较低，但在数据验证规则的可取性上存在分歧。开发者一致认为数据集成和验证最难实现。
与数据操作相关的战术任务相比，研究人员认为与研究执行、分析和质量控制相关的任务具有高度的战略性。研究人员在分析和质量控制方面仅获得部分技术支持，在研究执行方面的支持较差。
数据集成和验证软件对于支持临床研究似乎至关重要，但实施成本可能很高。支持研究工作流程、协作和参与的功能一直未得到充分重视，但可能很容易取得成功。软件开发人员应考虑研究人员在研究项目和团队的整体协调、连接数据收集与分析的工作流程以及提高数据质量的流程方面的战略目标。
