Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.

“Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.” is a core task performed by Clinical Data Managers. Among the occupation's 21 rated tasks, workers place it 12th by importance (#10 most important). About 90% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Evaluate the quality or accuracy of data. in Processing Information

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E2. Exposure with tools — software built on top of a language model (not the model alone) could cut the time by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.50. Automation potential label: T3.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.002% share of AI-use records mapped to this task

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Other tasks in this occupation

• Design and validate clinical databases, including designing or testing logic checks. · importance 4.5
• Process clinical data, including receipt, entry, verification, or filing of information. · importance 4.4
• Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems. · importance 4.3
• Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes. · importance 4.3
• Monitor work productivity or quality to ensure compliance with standard operating procedures. · importance 4.0
• Prepare appropriate formatting to data sets as requested. · importance 4.0
• Prepare data analysis listings and activity, performance, or progress reports. · importance 4.0
• Design forms for receiving, processing, or tracking data. · importance 4.0
• Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols. · importance 3.8
• Analyze clinical data using appropriate statistical tools. · importance 3.7
• Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency. · importance 3.7
• Develop technical specifications for data management programming and communicate needs to information technology staff. · importance 3.6
• Write work instruction manuals, data capture guidelines, or standard operating procedures. · importance 3.6
• Track the flow of work forms, including in-house data flow or electronic forms transfer. · importance 3.5

See all tasks on the Clinical Data Managers page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-16278,
  title  = {Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-16278}
}