Title: Assessment of the Impact of Power Business Intelligence on Adenoma Detection Rate:
A Prospective Observational Trial
Version: 2 Date: 25 Feb 2025
Reviewer's report:
1. Improvements in Research Design
Considerations for Randomized Controlled Trials (RCTs): The current research design is
a prospective observational study, which is practical in the real world. However, to more
accurately assess the impact of Power BI on adenoma detection rate (ADR), it is suggested
that future research consider adopting a randomized controlled trial (RCT) design. By randomly
assigning endoscopists to groups using Power BI and those not using it, confounding factors can
be more effectively controlled, reducing bias.
Long-term Follow-up: The current study only compares data from 2021 and 2022. It is suggested
that future research extend the follow-up period to observe the long-term impact of Power BI on
ADR. The ADR may change over time, and long-term data can better reflect the effectiveness
of interventions.
2. Refinement of Data Analysis
Subgroup Analysis: Although the paper has analyzed the performance of low-performing
endoscopists, it is suggested to further refine subgroup analysis, especially by stratifying
endoscopists of different experience levels (e.g., novice vs. senior physicians). This can help
better understand the impact of Power BI on endoscopists of varying experience levels.
Expansion of Multivariable Analysis: The current multivariable analysis has considered factors
such as gender, age, and BMI, but it is suggested to further incorporate other potential
confounding factors, such as patient family history of ADR or colorectal cancer, education level.
These factors may also influence ADR.
3.Further Exploration of Technical Factors
Details of Water-assisted Colonoscopy Techniques: The paper mentions the association between
water-assisted colonoscopy techniques and increased ADR but does not discuss specific water-
assisted techniques (e.g., water exchange vs. water immersion) in detail. It is suggested that
future research further explore the impact of different water-assisted techniques on ADR and
provide more detailed operational guidelines.
4.Optimization of Bowel Preparation: Although the paper mentions the association between
PEG (polyethylene glycol) bowel preparation and increased ADR, split-dose of 4L PEG was
the standard regime for bowel preparation, why wasn’t the regime adopted in the study?
5.Interpretation and Discussion of Results
Potential Limitations of Power BI: The paper mentions that Power BI did not significantly
increase ADR in high-performing institutions but does not delve into its potential limitations.
It is suggested to further analyze the limitations of Power BI in the discussion section, such as
whether its feedback mechanism is not personalized enough or whether endoscopists vary in
their acceptance of feedback. Additionally, exploring whether enhancing Power BI's interface
or functionality could enhance its effectiveness is recommended.
6.Comparison with Other Studies: The paper already mentions some similar studies, but it is
suggested to further compare with research using different feedback tools (e.g., EndoMineR) to
analyze the strengths and weaknesses of different tools and discuss why some tools are more
effective in increasing ADR.
7.Recommendations for Clinical Practice
Training for Low-Performing Endoscopists: The paper mentions that low-performing
endoscopists showed an increase in ADR after using Power BI. It is suggested to further
discuss in the discussion section how to provide personalized training for these endoscopists.
For example, whether simulation training or mentorship could further improve their operational
skills.
8.Updating of References
Citation of Recent Literature: The paper cites numerous relevant literature, but it is suggested to
include more recent studies in the discussion section, particularly regarding the application of
artificial intelligence (AI) and machine learning in colonoscopy. These emerging technologies
may have a significant impact on future ADR improvements.
Title: Assessment of the Impact of Power Business Intelligence on Adenoma Detection Rate:
A Prospective Observational Trial
Version: 2 Date: 25 Feb 2025
Reviewer's report:
1. Improvements in Research Design
Considerations for Randomized Controlled Trials (RCTs): The current research design is
a prospective observational study, which is practical in the real world. However, to more
accurately assess the impact of Power BI on adenoma detection rate (ADR), it is suggested
that future research consider adopting a randomized controlled trial (RCT) design. By randomly
assigning endoscopists to groups using Power BI and those not using it, confounding factors can
be more effectively controlled, reducing bias.
Long-term Follow-up: The current study only compares data from 2021 and 2022. It is suggested
that future research extend the follow-up period to observe the long-term impact of Power BI on
ADR. The ADR may change over time, and long-term data can better reflect the effectiveness
of interventions.
2. Refinement of Data Analysis
Subgroup Analysis: Although the paper has analyzed the performance of low-performing
endoscopists, it is suggested to further refine subgroup analysis, especially by stratifying
endoscopists of different experience levels (e.g., novice vs. senior physicians). This can help
better understand the impact of Power BI on endoscopists of varying experience levels.
Expansion of Multivariable Analysis: The current multivariable analysis has considered factors
such as gender, age, and BMI, but it is suggested to further incorporate other potential
confounding factors, such as patient family history of ADR or colorectal cancer, education level.
These factors may also influence ADR.
3.Further Exploration of Technical Factors
Details of Water-assisted Colonoscopy Techniques: The paper mentions the association between
water-assisted colonoscopy techniques and increased ADR but does not discuss specific water-
assisted techniques (e.g., water exchange vs. water immersion) in detail. It is suggested that
future research further explore the impact of different water-assisted techniques on ADR and
provide more detailed operational guidelines.
4.Optimization of Bowel Preparation: Although the paper mentions the association between
PEG (polyethylene glycol) bowel preparation and increased ADR, split-dose of 4L PEG was
the standard regime for bowel preparation, why wasn’t the regime adopted in the study?
5.Interpretation and Discussion of Results
Potential Limitations of Power BI: The paper mentions that Power BI did not significantly
increase ADR in high-performing institutions but does not delve into its potential limitations.
It is suggested to further analyze the limitations of Power BI in the discussion section, such as
whether its feedback mechanism is not personalized enough or whether endoscopists vary in
their acceptance of feedback. Additionally, exploring whether enhancing Power BI's interface
or functionality could enhance its effectiveness is recommended.
6.Comparison with Other Studies: The paper already mentions some similar studies, but it is
suggested to further compare with research using different feedback tools (e.g., EndoMineR) to
analyze the strengths and weaknesses of different tools and discuss why some tools are more
effective in increasing ADR.
7.Recommendations for Clinical Practice
Training for Low-Performing Endoscopists: The paper mentions that low-performing
endoscopists showed an increase in ADR after using Power BI. It is suggested to further
discuss in the discussion section how to provide personalized training for these endoscopists.
For example, whether simulation training or mentorship could further improve their operational
skills.
8.Updating of References
Citation of Recent Literature: The paper cites numerous relevant literature, but it is suggested to
include more recent studies in the discussion section, particularly regarding the application of
artificial intelligence (AI) and machine learning in colonoscopy. These emerging technologies
may have a significant impact on future ADR improvements.
Please review this paper.
user
Title: Assessment of the Impact of Power Business Intelligence on Adenoma Detection Rate:
A Prospective Observational Trial
Version: 2 Date: 25 Feb 2025
Reviewer's report:
1. Improvements in Research Design
Considerations for Randomized Controlled Trials (RCTs): The current research design is
a prospective observational study, which is practical in the real world. However, to more
accurately assess the impact of Power BI on adenoma detection rate (ADR), it is suggested
that future research consider adopting a randomized controlled trial (RCT) design. By randomly
assigning endoscopists to groups using Power BI and those not using it, confounding factors can
be more effectively controlled, reducing bias.
Long-term Follow-up: The current study only compares data from 2021 and 2022. It is suggested
that future research extend the follow-up period to observe the long-term impact of Power BI on
ADR. The ADR may change over time, and long-term data can better reflect the effectiveness
of interventions.
2. Refinement of Data Analysis
Subgroup Analysis: Although the paper has analyzed the performance of low-performing
endoscopists, it is suggested to further refine subgroup analysis, especially by stratifying
endoscopists of different experience levels (e.g., novice vs. senior physicians). This can help
better understand the impact of Power BI on endoscopists of varying experience levels.
Expansion of Multivariable Analysis: The current multivariable analysis has considered factors
such as gender, age, and BMI, but it is suggested to further incorporate other potential
confounding factors, such as patient family history of ADR or colorectal cancer, education level.
These factors may also influence ADR.
3.Further Exploration of Technical Factors
Details of Water-assisted Colonoscopy Techniques: The paper mentions the association between
water-assisted colonoscopy techniques and increased ADR but does not discuss specific water-
assisted techniques (e.g., water exchange vs. water immersion) in detail. It is suggested that
future research further explore the impact of different water-assisted techniques on ADR and
provide more detailed operational guidelines.
4.Optimization of Bowel Preparation: Although the paper mentions the association between
PEG (polyethylene glycol) bowel preparation and increased ADR, split-dose of 4L PEG was
the standard regime for bowel preparation, why wasn’t the regime adopted in the study?
5.Interpretation and Discussion of Results
Potential Limitations of Power BI: The paper mentions that Power BI did not significantly
increase ADR in high-performing institutions but does not delve into its potential limitations.
It is suggested to further analyze the limitations of Power BI in the discussion section, such as
whether its feedback mechanism is not personalized enough or whether endoscopists vary in
their acceptance of feedback. Additionally, exploring whether enhancing Power BI's interface
or functionality could enhance its effectiveness is recommended.
6.Comparison with Other Studies: The paper already mentions some similar studies, but it is
suggested to further compare with research using different feedback tools (e.g., EndoMineR) to
analyze the strengths and weaknesses of different tools and discuss why some tools are more
effective in increasing ADR.
7.Recommendations for Clinical Practice
Training for Low-Performing Endoscopists: The paper mentions that low-performing
endoscopists showed an increase in ADR after using Power BI. It is suggested to further
discuss in the discussion section how to provide personalized training for these endoscopists.
For example, whether simulation training or mentorship could further improve their operational
skills.
8.Updating of References
Citation of Recent Literature: The paper cites numerous relevant literature, but it is suggested to
include more recent studies in the discussion section, particularly regarding the application of
artificial intelligence (AI) and machine learning in colonoscopy. These emerging technologies
may have a significant impact on future ADR improvements.
assistant