How to summarize approx 2000 documents into a single total counted document?

Efficiently Summarizing Large Volumes of Document Data: A Practical Guide

Introduction

Managing extensive datasets—such as summaries of medical instrument usage over several years—can be a daunting task, especially when the data is scattered across numerous individual documents. In this article, we explore effective methods to automate the process of extracting and summarizing such information, significantly reducing manual effort and minimizing errors.

Scenario Overview

Suppose you have approximately 2,000 single-page documents stored in Microsoft Word format on a Windows 11 PC. Each document contains information about instruments used in a medical procedure, including a table with entries like:

| Item Description | Quantity | Cost Rs. |
|——————|———-|———-|
| Abc item | 1 / 2 / 3 | X Rs. |
| Xyz item | 1 / 2 / 3 | Y Rs. |

Your goal is to compile a comprehensive summary that totals the quantity and cost for each instrument type across all documents. Manually extracting each record would be time-consuming and prone to inaccuracies, prompting the need for an automated solution.

Proposed Solution

To achieve an efficient and accurate summary, consider the following approach:

1. Convert Word Documents to Data-Friendly Format

2. Batch Conversion to Text or PDF: Use tools like Microsoft Word’s batch processing features or dedicated converters to transform documents into plain text or PDF files.

3. Leverage Automation Tools: Utilize batch scripting or third-party tools to streamline this conversion process.

4. Extract Data Using Programming or Specialized Software

5. Python Scripting: Use Python with libraries such as python-docx, tabula-py (for PDFs), or pandas to automate data extraction.

6. Data Parsing Workflow:

   • Loop through each document.
   • Identify and parse the relevant table data.
   • Normalize entries to ensure consistent formatting.

7. Aggregate Data for Summary

8. Data Structuring: Store the extracted data in a structured format—such as a pandas DataFrame.

9. Grouping and Summing:

   • Aggregate totals for each instrument type by summing quantities and costs.
   • Generate a summary report in your preferred format (Excel, CSV, or a Word document).

10. Automation and Integration

11. Develop a script or macro that automates the entire workflow.

12. Schedule periodic runs if ongoing data collection is needed.

Tools