Time Saving in Literature Reviews with CAPTIS

Article metadata retrieval and consolidation was faster via CAPTIS in 4 out of 5 Devices, with an average time reduction of 62% seen overall.

CAPTIS identified a higher number of duplicates in 2 out of 5 devices when compared to the manual deduplication method. Medical writers spent 0 minutes on CAPTIS vs 6-30 minutes when manually identifying duplicates depending upon the number of hits.

CAPTIS automatically searches and consolidates full-text PDFs of open access articles, leaving users a much shorter list of articles for which full-texts are needed. In comparison, doing this activity manually entails searching for the full-text PDF of every single article included in L1, renaming, and saving PDFs which were available, and marking those which need to be purchased.

Searches for full-text articles were done post-L1 Title and Abstract screening. However, considering that the same set of articles was reviewed independently by two different writers (CAPTIS versus manual), there were slight variations in the number of articles included in L1. To accurately estimate the potential time savings for full-text search and save, we normalized the number of articles included in L1 in both the workflows by considering the manual L1 included article count to be the same as that in the CAPTIS workflow. Further, we extrapolated the estimated time taken for searching and saving full-texts manually by dividing the amount of time taken for this activity upon the number of full-texts searched for and multiplying the resultant “time per article” value to the adjusted number of articles.

CAPTIS users consistently spent less time finding full texts or categorizing articles for purchase since the platform automatically downloads all available/free full-texts. Users saved an average of 45% of time for this activity when using CAPTIS.

Table 4: Percentage time savings for full-text search and save

Comparison between Level 1 Review (Title and Abstract Screening) and Level 2 full-text appraisal duration for CAPTIS vs. Manual processes were not calculated since these two steps constitute the “analysis” portion of the entire literature review process. Time variations in these two steps were observed, as expected, since two different reviewers reviewed the same dataset. This can be attributed to the fact that these tasks are subjective in nature, i.e., time taken to screen and appraise articles will vary amongst different reviewers depending on their level of experience and knowledge in the respective therapeutic area.

Let’s look at the average percentage of time each task took in the manual review process.

With reductions of 62%, 100% and 45% (as calculated in the sections above) applied to Article metadata (reference and abstract) retrieval and consolidation, deduplication and full-text PDF search and save activities (non-analysis components of the literature review), respectively, we saw an overall reduction of 62% for non-analysis tasks leading to an overall reduction of 28% on the overall literature review.

CAPTIS utilization resulted in an overall time reduction of 62% for non-analysis tasks (Article metadata (reference and abstract) retrieval and consolidation, deduplication, and full-text PDF search) leading to an overall reduction of 28% on the overall literature review.

We compared time savings with benchmark values for manual tasks. We assumed around 400 articles as the initial number of articles retrieved, with a 25% inclusion rate (i.e., 100 articles passed L1 title and abstract screening). We further assumed 1.5 min/article for manually capturing article metadata, 0.5 min/article for deduplication and 5 min/article for full-text search and save. These benchmark values assume a realistic normal-paced working day for a typical medical writer. With time savings of 62%, 100% and 45% applied for article metadata (reference and abstract) retrieval and consolidation, deduplication and full-text PDF search and save activities, respectively, we can expect savings of 13.28 hours on the non-analysis components of the literature review.

Table 5: Additional Possible Conclusions

How does CAPTIS help writers save so much time?

1. Article Metadata Retrieval: While databases like PubMed are fairly easy to export data out of, CAPTIS makes an easy task of Google Scholar articles too. Google Scholar is notorious for not having an export option for abstracts, with medical writers having to manually copy and paste each abstract.
2. Deduplication: Users save 100% of the time they would have spent on deduplicating articles since CAPTIS automatically deduplicates their entire article list for them. CAPTIS also allows users to manually mark duplicates, if required.
3. Full-text search and save: From the entire list of articles that need to be searched for full-texts, CAPTIS takes care of all the open-access articles for which full-texts are freely available. Meaning, the task of searching, downloading, renaming, saving the available PDFs, and marking those articles which require to be purchased is significantly reduced, since users now only need to look at the articles for which full texts could not be located (because they were either paid, or not available on the original webpage from which the article came from).

Download a copy of this CAPTIS Time Saving Study now to review at a later date.

Your medical writing team can benefit from CAPTIS with faster turnaround times for systematic literature reviews and more accurate end-to-end MDR/IVDR documentation support. To learn more and view a comprehensive demo of CAPTIS, reach out to info@celegence.com today or contact us online to connect with a Celegence representative.