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Abstract
Background: Data collection is very important for systematic reviews. Data collection forms should be designed carefully to target the objectives of the review. Instruments for data collection and procedures used to collect data affect the accessibility and accuracy of extracted data.
Objectives: We explored the feasibility of using EpiData software for data collection in a Cochrane systematic review.
Methods: We used EpiDatatocollect data forthe review 'Chinese herbal medicines for hypercholesterolemia’. We designed the data extraction form in MS Word based on the suggested model inthe Cochrane Handbook to include factors that should be considered in research methodology and study outcomes. We converted the Word document into EpiData questionnaires and reviewed and checked the information before creating a data file. The EpiData file was used for data extraction to ensure that all required data were obtained from the included studies. We also designed a Word document to extract text data longer than 80 characters.
Results: Examples of items we extracted are illustrated in Figure1. The extracted EpiData database was converted to a SPSS dataset and used for statistical analysis. It is noteworthy that the number of text characters should not exceed 80 inthe EpiData database; which is why we used aWord document to extract text data such as aims of included studies for tabular presentation in elements such as 'Characteristics of included studies'.
Conclusions: The EpiData application is suitable for review data extraction for quantitative data or text data less than 80 characters. It has many advantages over other tools used for data extraction such as Word or Excel formats. An intuitive user interface madeaccurate data extraction easy. Users can double enter data using the 'match records by fields' option to avoid data entry errors. We found that data extracted usingthe EpiData application could be easily converted to another dataset for statistical analysis.
Objectives: We explored the feasibility of using EpiData software for data collection in a Cochrane systematic review.
Methods: We used EpiDatatocollect data forthe review 'Chinese herbal medicines for hypercholesterolemia’. We designed the data extraction form in MS Word based on the suggested model inthe Cochrane Handbook to include factors that should be considered in research methodology and study outcomes. We converted the Word document into EpiData questionnaires and reviewed and checked the information before creating a data file. The EpiData file was used for data extraction to ensure that all required data were obtained from the included studies. We also designed a Word document to extract text data longer than 80 characters.
Results: Examples of items we extracted are illustrated in Figure1. The extracted EpiData database was converted to a SPSS dataset and used for statistical analysis. It is noteworthy that the number of text characters should not exceed 80 inthe EpiData database; which is why we used aWord document to extract text data such as aims of included studies for tabular presentation in elements such as 'Characteristics of included studies'.
Conclusions: The EpiData application is suitable for review data extraction for quantitative data or text data less than 80 characters. It has many advantages over other tools used for data extraction such as Word or Excel formats. An intuitive user interface madeaccurate data extraction easy. Users can double enter data using the 'match records by fields' option to avoid data entry errors. We found that data extracted usingthe EpiData application could be easily converted to another dataset for statistical analysis.
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