data-extraction

Name: data-extraction
Availability: InStock
Author: shaitamam-80

Extract clinical study data into analysis-ready datasets using Cochrane and JBI templates.

Updated Nov 16, 2025

Search Tags:#traceability #meta-analysis #data-extraction #systematic-reviews #Cochrane #JBI

Ready to run

npx skills add https://github.com/shaitamam-80/shaitamamMedAIHub --skill data-extraction

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-extraction
Source: https://github.com/shaitamam-80/shaitamamMedAIHub/tree/main/backend/app/core/skills/data-extraction
Command: npx skills add https://github.com/shaitamam-80/shaitamamMedAIHub --skill data-extraction

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps researchers extract and organize data from clinical studies for systematic reviews and meta-analyses, ensuring accuracy, traceability, and consistent reporting.

Core Features & Use Cases

Template-driven extraction: Guides users to fill in study characteristics, outcomes, and effect estimates using Cochrane/JBI templates.
Support for multiple designs: Handles RCTs, cohorts, prevalence studies, and qualitative research with design-specific considerations.
Data integrity & transparency: Distinguishes reported data from calculated values (e.g., SD from SE or CI) and flags uncertainties for follow-up.
Outputs ready for analysis: Produces analysis-ready datasets and documentation for meta-analysis workflows.

Quick Start

Use the data-extraction skill to begin extracting data from a downloaded study PDF or to load a blank extraction template.

Frequently Asked Questions about data-extraction

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I extract data from clinical studies for a systematic review?▼

To extract data for a systematic review, this Skill applies Cochrane and JBI templates to capture study characteristics, outcomes, and effect estimates from clinical studies. It guides the process using design-specific considerations for RCTs, cohorts, and qualitative research.

Can I use Cochrane and JBI templates for data extraction across different study designs?▼

Yes, Cochrane and JBI templates are used here to support data extraction across multiple designs including randomized trials, cohorts, prevalence studies, and qualitative research, ensuring accurate capture of outcomes and time points with design-specific considerations.

How do I extract effect estimates and distinguish reported data from calculated values?▼

To distinguish reported data from calculated values like SD derived from SE or CI, this Skill flags uncertainties and applies built-in validation rules during extraction. It ensures clear differentiation between reported and calculated effect estimates for meta-analysis.

What is the best way to generate analysis-ready datasets for meta-analysis?▼

The best way to generate analysis-ready datasets for meta-analysis is using template-driven extraction that produces structured datasets with traceable sources. This Skill outputs documentation and data structured specifically for meta-analysis workflows.

Does data extraction for systematic reviews support traceability and validation rules?▼

Yes, data extraction for systematic reviews includes built-in validation rules and traceable sources for every captured outcome and effect estimate. This ensures data integrity and transparency throughout the extraction process.

What are the limitations of using structured templates for systematic review data extraction?▼

Structured templates for systematic review data extraction require accurate source differentiation between reported and calculated values to avoid errors. While they support multiple designs, users must manually verify flagged uncertainties to maintain data integrity.