Development of SW Interface between Healthcare Standards—DASTA and HL7

Round 1

Reviewer 1 Report

Thanks for addressing the comments.

Authors have provided comprehensive list of related work

They have also included a lot of details about HL7 standard, data formats and protocols.

Clearly highlighted the benefits of robot based preparation and dispensing systems.

Author Response

Thank you so much for your opinion. We are really grateful your comment. We really appreciate the time you spent to provide us such a positive review.

Reviewer 2 Report

Authors need improvements in few areas of their article.

Authors must add all comments answers in their revised version. 

comments file is attached.

Comments for author File: Comments.pdf

Author Response

Authors need improvements in few areas of their article.

Authors must add all comments answers in their revised version.

Major Modifications Needed

This paper mainly proposed various developments and algorithms of human daily routine standards with respect to its health. They used various information flow and material flow to examine patient’s situations. Overall idea is really nice, but, authors must add following comments answers in their revised version.

1. (In Abstract); Authors must concise their writing and mentioned about key contributions only.

Thank you so much for this comment. We have tried to mention key contributions in abstract.

2. (In Introduction) Add few lines in which all real-world problems of patient’s health observations are monitored in various fields such as signal/image processing, e-commerce, smart homes, surveillance systems and many others. Also, include following references [1-7] to strengthen your literature work.

[1] “New shape descriptor in the context of edge continuity,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 101-109, 2019.

[2] “Three-stage network for age estimation,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 122-126, 2019.

[3] “Influence of kernel clustering on an RBFN,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 4, pp. 255-260, 2019.

[4] “Engine speed reduction for hydraulic machinery using predictive algorithms,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 16-31, 2019.

[5] “Analytical analysis of single-stage pressure relief valves,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 32-53, 2019.

[6] “A review on the artificial neural network approach to analysis and prediction of seismic damage in infrastructure,” Int. J. Hydromechatronics, Vol. 2, no. 4, pp. 178-196, 2019.

[7] “WHITE STAG Model: Wise Human Interaction Tracking and Estimation (WHITE) using Spatio-temporal and Angular-geometric (STAG) Descriptors, Multimedia Tools and Applications, 2020.

Thank you so much for this recommendation. We really appreciate the time you spent to provide us a really useful references. We carefully studied that literature and we added new part where we deal with other emerging technologies that can be used in healthcare.

3. (In Introduction) (Add few lines for different sensors used in patient’s health observations such as RGB camera, depth camera, wearable sensors and must include all below references.

[1] “Vision-based Human Activity recognition system using depth silhouettes: A Smart home system for monitoring the residents, Journal of Electrical Engineering and Technology, 2019.

[2] “A novel statistical method for scene classification based on multi-object categorization and logistic regression, Sensors, 2020.

[3] “Human actions tracking and recognition based on body parts detection via Artificial neural network,” IEEE International Conference on Advancements in computational sciences, 2020.

[4] Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart homes,Indoor and Built Environment, Vol. 22, pp. 271-279, 2013.

[5] “Wearable Sensors based Human Behavioral Pattern Recognition using Statistical Features and Reweighted Genetic Algorithm, Multimedia Tools and Applications, 2019.

[6] “Wearable Inertial Sensors for Daily Activity Analysis Based on Adam Optimization and the Maximum Entropy Markov Model”, Entropy, vol. 22, no. 5, pp.1-19, 2020.

[7] A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments, Sensors, vol. 14(7), pp. 11735-11759, 2014.

Thank you for this comment. We really appreciate the time you spent to provide us a really useful references. We carefully studied that literature and we added new part where we deal with other emerging technologies that can be used in healthcare.

4. (Related work) It must be separate section and make 2 to 3 sub-sections inside it. For example; metadata extraction, sensors-based medication, cloud middleware services for healthcare.

Thank you so much for this recommendation. The part Related work was separated into 2 sections.

5. (Overview of HL7) Figures2 and 3 are very much common and no need to add. If possible, add algorithm at this stage.

Thank you for this comment. Based on your suggestion we removed these Figures.

6. (The usage of HL7 in the case of Automated) Information becoming redundant in Table 1 and 2. So just add into one Table.

Thank you so much for this suggestion. Tables were joined, it is one table now.

7. (Data exchange in HL7) Algorithm is needed here to explain Data exchange and formulation is missing of state to state transitions.

Thank you for this comment. The algorithm that illustrates Data exchange was added.

8. (Option 1 –HL7 module for NIS/LIS) In Fig. 8. ack. must be treated in other blocks connection. Revise this figure.

Thank you for this comment. It was revised based on your suggestions.

9. (5.2.5. Visualization of the message generated) Quality of Figures12 -17 are really weak and hard to read. Make visual improvement.

Thank you so much for this comment. We agree, it was really hard to read. Based on your suggestion we did visual improvement of that figures.

We would like to thank you again, we sincerely appreciate for your time and considerations. Thank you for your suggestions.

Reviewer 3 Report

The paper is not organized well and it is like a report to compare two standards instead of a peer-review journal paper.

Author Response

Dear reviewer, we really appreciate your comment and time you spent to make a review of our paper. We are really sorry that it was not good enough for you. To be honest, it was really hard to reflect your comment. We were able to enrich our article with valuable information based on other reviewers.

We would like to thank you again, we sincerely appreciate for your time and considerations. Thank you for your suggestions.

Round 2

Reviewer 2 Report

Author Response

Thank you so much for your opinion. We are really grateful your comment and provided valuable recommendations how to improve our paper. Thanks to this the quality of the paper has been highly enriched.

We really appreciate the time you spent to provide us such a positive review.

Reviewer 3 Report

This version of the paper is improved a lot. My comments are listed below:

1. Abstract should mainly introduce the objective, workflow, and main findings of this paper. So, it is unnecessary to show an example (lines 14 to 17) in the abstract. This can be mentioned in the introduction section. Furthermore, it is better to show the limitations of current research, which is the reason to write this paper. Moreover, it is necessary to provide more information in the abstract about the performed analyses used in this paper.
2. In Line 40, please add the citations for “common technologies in the world”.
3. In Line 58, “consider” should be “considers”.
4. In Line 91, “e. “ should be “e.g.”.
5. Related work is better to be a new section (Section 2).
6. For the related work, a table to summarize and categorize your literature review is better to just list them one-by-one.
7. In Line 292, the abbreviation of “hospital information system” should be HIS. I guess that NIS is network information system.
8. In Line 328, is the indents wrong?
9. In Line 339, “Health Level Seven” can be written into “HL7”.
10. By using HL7 instead of DASTA, is the ratio of medication errors reduced? If so, is there any data to show the improvement of accuracy?

Author Response

This version of the paper is improved a lot. My comments are listed below:

Thank you so much for your comment. We really appreciate the time you spent to provide us such a positive review.

Abstract should mainly introduce the objective, workflow, and main findings of this paper. So, it is unnecessary to show an example (lines 14 to 17) in the abstract. This can be mentioned in the introduction section. Furthermore, it is better to show the limitations of current research, which is the reason to write this paper. Moreover, it is necessary to provide more information in the abstract about the performed analyses used in this paper.

Thank you so much for this recommendation. Based on it we rewrote abstract and removed parts you mentioned.

In Line 40, please add the citations for “common technologies in the world”.

Thank you so much for your comment. This part has been reworded, it could be misleading. However, technologies, respectively. techniques mean that a clinical pharmacist is rarely involved in the medication process, patient verification and a record of administration are not sufficient, so the possibility to verify the correctness of administration is limited (there is usually no clear and complete record of medication administration); stock records of medicines are administratively very demanding and therefore confusing and unreliable; medication preparation time is time consuming. From a technological point of view, the problem is that these actions are not sufficiently supported.

In Line 58, “consider” should be “considers”.

Thank you so much, it is corrected.

In Line 91, “e. “ should be “e.g.”.

Thank you so much, it is corrected.

Related work is better to be a new section (Section 2).

Thank you so much for this suggestion. It is in new section, now.

For the related work, a table to summarize and categorize your literature review is better to just list them one-by-one.

Thank you so much for this suggestion. Based on your recommendation it is listed in 2 tables. We think that this presentation is much better then previous one.

In Line 292, the abbreviation of “hospital information system” should be HIS. I guess that NIS is network information system.

Thank you so much, it is corrected.

In Line 328, is the indents wrong?

Thank you so much, it is corrected.

In Line 339, “Health Level Seven” can be written into “HL7”.

Thank you so much, it is corrected.

By using HL7 instead of DASTA, is the ratio of medication errors reduced? If so, is there any data to show the improvement of accuracy?

Thank you so much for this comment. It cannot be said unequivocally that using HL7 instead of DASTA reduces the error rate. It is not a question of the standard, but of other related processes. Due to the fact that DASTA is a Czech standard, it is difficult to associate it with some technologies that work on HL7. The safety of the drug delivery process increases with the introduction of new technologies and innovative approaches. The current safest and most effective practice is the automated preparation of drug therapies for individual patients centralized in a hospital pharmacy using robotically prepared single doses of drugs. Every movement of such a single dose around the hospital is completely transparent and maximally safe for the patient. For reasons of efficiency, registration and safety, this approach is combined with the use of automated warehouses for the management of non-dispensable drugs.

We are really grateful to your comments and provided valuable recommendations how to improve our paper. Thanks to this the quality of the paper has been highly enriched.

Dear reviewer, we really appreciate your time you spent to make a 2 reviews of our paper.

Round 3

Reviewer 3 Report

The authors address all my comments.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Overall idea is really novel,however, 

authors still need major modifications. 

Add all modification in revised version.

Comments of file is attached.

Major Modifications Needed

In this article, authors mainly proposed various techniques and algorithms to extract data necessary for robotic preparation for patient’s healthcare. Overall concept is very generous, however, need few modifications as;

1. (In Abstract); Authors must focus on unique factor of their work and add at least few sentences for results and performance.
2. (In Introduction) Add new paragraph in which all real-world problems of extraction of data from robotic are examined in various applications such as healthcare, e-commerce, smart homes, surveillance systems and many others. Also, include following references [1-7] to strengthen your literature work.

[1] “New shape descriptor in the context of edge continuity,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 101-109, 2019.

[2] “Engine speed reduction for hydraulic machinery using predictive algorithms,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 16-31, 2019.

[3] “Analytical analysis of single-stage pressure relief valves,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 32-53, 2019.

[4] “Three-stage network for age estimation,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 122-126, 2019.

[5] “Influence of kernel clustering on an RBFN,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 4, pp. 255-260, 2019.

[6] “A review on the artificial neural network approach to analysis and prediction of seismic damage in infrastructure,” Int. J. Hydromechatronics, Vol. 2, no. 4, pp. 178-196, 2019.

[7] “WHITE STAG Model: Wise Human Interaction Tracking and Estimation (WHITE) using spatio-temporal and Angular-geometric (STAG) Descriptors, Multimedia Tools and Applications, 2020.

3. (In Introduction) Need improvement in writing and lack of information. Also, references need major concern in overall paper, Update it

• Add one paragraph for different sensors like video cameras, wearable sensors and wireless devices play role in extraction of sensors data and must include all below references.

[1] “Vision-based Human Activity recognition system using depth silhouettes: A Smart home system for monitoring the residents, Journal of Electrical Engineering and Technology, 2019.

[2] Development of a life logging system via depth imaging-based human activity recognition for smart homes,” in Proceedings of the International Symposium on Sustainable Healthy Buildings, pp. 91-95, 2012.

[3] “Human actions tracking and recognition based on body parts detection via Artificial neural network,” IEEE International Conference on Advancements in computational sciences, 2020..

[4] Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart homes, Indoor and Built Environment, Vol. 22, pp. 271-279, 2013.

[5] “Wearable Sensors based Human Behavioral Pattern Recognition using Statistical Features and Reweighted Genetic Algorithm, Multimedia Tools and Applications, 2019.

[6] Shape and motion features approach for activity tracking and recognition from Kinect video camera, in Proceedings 29th International Conference on Advanced Information Networking and Applications Workshops, pp. 445-450, 2015.

[7] A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments, Sensors, vol. 14(7), pp. 11735-11759, 2014.

4. (In Introduction) Add few lines in which “all classes of real-time sensor data tracking and detection using human-machine system are mentions such like object localization, human gait recognition, spatiotemporal contents detection, motion recognition, text recognition and etc. and all following reference in it.

 [1] “RGB-D images for object segmentation, localization and recognition in indoor scenes using feature descriptor and Hough voting”, IEEE conference on applied sciences and technology, 2020.

 [2] “Depth Silhouettes Context: A new robust feature for human tracking and activity recognition based on embedded HMMs,” in Proceedings 12th IEEE International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 294-299, 2015.

 [3] “Robust human activity recognition from depth video using spatiotemporal multi-fused features, Pattern recognition, vol. 61, pp. 295-308, 2017.

 [4] “Wearable Sensors for Activity Analysis using SMO-based Random Forest over Smart home and Sports Datasets”, IEEE ICACS conference, 2020.

 [5] “Depth Images-based Human Detection, Tracking and Activity Recognition Using Spatiotemporal Features and Modified HMM, Journal of Electrical Engineering and Technology, pp. 1921-1926, 2016.

 [6] “An Accurate Facial expression detector using multi-landmarks selection and local transform features,” IEEE ICACS conference, 2020.

 [7] “Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map,” KSII Transactions on internet and information systems, vol. 9(5), pp. 1856-1869, 2015.

 [8] “A hybrid feature extraction approach for human detection, tracking and activity recognition using depth sensors, Arabian Journal for Science and Engineering, vol. 41(3), pp. 1043-1051, 2016.

 [9] Feature selection for gait recognition, IEEE symposium on Humanities, science and engineering research, 2012.

5. (Communication protocols in healthcare) Contribution lines are missing here. Authors must mention about contribution area of this article.

6. (1) Preprocessing part is not clear. Need more details by drawing Figure.

7. (1.1), Make different case-study here instead of mentioning one example for deep discussion

8. (1. Option 1), Figure 2 need more details and elaborate sub-parts of each block.

9. (2.2), Draw a sample form to make system more clear.

10. (In Test performed and Results), Dataset descriptions are not enough clear.

11. (In Test performed and Results), Discuss some failure case at last of experimental results.

Comments for author File: Comments.pdf

Author Response

Dear reviewer,

Thank you so much for your valuable comments and recommendations. We really appreciate time you spent to make a review of our paper. Based on your remarks we have tried to do our best to enrich our article as you suggested. The changes are indicated in an updated version by green color. We really hope that these modifications and addition of some parts will contribute to accept the paper.

Overall idea is really novel, however, authors still need major modifications. Add all modification in revised version. Comments of file is attached.

Major Modifications Needed

In this article, authors mainly proposed various techniques and algorithms to extract data necessary for robotic preparation for patient’s healthcare. Overall concept is very generous, however, need few modifications as;

(In Abstract); Authors must focus on unique factor of their work and add at least few sentences for results and performance.

Thank you so much for this comment. We agree. Based on your recommendation we totally changed the abstract of the paper. We hope that it will be more indicative of the actual focus of the paper and the reasons why we decided to deal with this issue.

(In Introduction) Add new paragraph in which all real-world problems of extraction of data from robotic are examined in various applications such as healthcare, e-commerce, smart homes, surveillance systems and many others. Also, include following references [1-7] to strengthen your literature work.

[1] “New shape descriptor in the context of edge continuity,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 101-109, 2019.

[2] “Engine speed reduction for hydraulic machinery using predictive algorithms,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 16-31, 2019.

[3] “Analytical analysis of single-stage pressure relief valves,” Int. J. Hydromechatronics, Vol. 2, no. 1, pp. 32-53, 2019.

[4] “Three-stage network for age estimation,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 2, pp. 122-126, 2019.

[5] “Influence of kernel clustering on an RBFN,” CAAI Transactions on Intelligence Technology, Vol. 4, no. 4, pp. 255-260, 2019.

[6] “A review on the artificial neural network approach to analysis and prediction of seismic damage in infrastructure,” Int. J. Hydromechatronics, Vol. 2, no. 4, pp. 178-196, 2019.

[7] “WHITE STAG Model: Wise Human Interaction Tracking and Estimation (WHITE) using spatio-temporal and Angular-geometric (STAG) Descriptors, Multimedia Tools and Applications, 2020.

Thank you for this comment. We really appreciate the time you spent to provide us a really useful references. We carefully studied that literature and with all respect to your recommendations, honestly we think that the proposed references is not related to the topic addressed in this article.

Anyway, based on your remarks, we add new paragraph wit related work.

(In Introduction) Need improvement in writing and lack of information. Also, references need major concern in overall paper, Update it

Add one paragraph for different sensors like video cameras, wearable sensors and wireless devices play role in extraction of sensors data and must include all below references.

[1] “Vision-based Human Activity recognition system using depth silhouettes: A Smart home system for monitoring the residents, Journal of Electrical Engineering and Technology, 2019.

[2] Development of a life logging system via depth imaging-based human activity recognition for smart homes,” in Proceedings of the International Symposium on Sustainable Healthy Buildings, pp. 91-95, 2012.

[3] “Human actions tracking and recognition based on body parts detection via Artificial neural network,” IEEE International Conference on Advancements in computational sciences, 2020..

[4] Human activity recognition via recognized body parts of human depth silhouettes for residents monitoring services at smart homes, Indoor and Built Environment, Vol. 22, pp. 271-279, 2013.

[5] “Wearable Sensors based Human Behavioral Pattern Recognition using Statistical Features and Reweighted Genetic Algorithm, Multimedia Tools and Applications, 2019.

[6] Shape and motion features approach for activity tracking and recognition from Kinect video camera, in Proceedings 29th International Conference on Advanced Information Networking and Applications Workshops, pp. 445-450, 2015.

[7] A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments, Sensors, vol. 14(7), pp. 11735-11759, 2014.

Thank you for this comment. We really appreciate the time you spent to provide us a really useful references. We carefully studied that literature and with all respect to your recommendations, honestly we think that the proposed references is not related to the topic addressed in this article.

Anyway, based on your remarks, we add new paragraph wit related work.

(In Introduction) Add few lines in which “all classes of real-time sensor data tracking and detection using human-machine system are mentions such like object localization, human gait recognition, spatiotemporal contents detection, motion recognition, text recognition and etc. and all following reference in it.

[1] “RGB-D images for object segmentation, localization and recognition in indoor scenes using feature descriptor and Hough voting”, IEEE conference on applied sciences and technology, 2020.

[2] “Depth Silhouettes Context: A new robust feature for human tracking and activity recognition based on embedded HMMs,” in Proceedings 12th IEEE International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 294-299, 2015.

[3] “Robust human activity recognition from depth video using spatiotemporal multi-fused features, Pattern recognition, vol. 61, pp. 295-308, 2017.

[4] “Wearable Sensors for Activity Analysis using SMO-based Random Forest over Smart home and Sports Datasets”, IEEE ICACS conference, 2020.

[5] “Depth Images-based Human Detection, Tracking and Activity Recognition Using Spatiotemporal Features and Modified HMM, Journal of Electrical Engineering and Technology, pp. 1921-1926, 2016.

[6] “An Accurate Facial expression detector using multi-landmarks selection and local transform features,” IEEE ICACS conference, 2020.

[7] “Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map,” KSII Transactions on internet and information systems, vol. 9(5), pp. 1856-1869, 2015.

[8] “A hybrid feature extraction approach for human detection, tracking and activity recognition using depth sensors, Arabian Journal for Science and Engineering, vol. 41(3), pp. 1043-1051, 2016.

[9] Feature selection for gait recognition, IEEE symposium on Humanities, science and engineering research, 2012.

Thank you for this comment. We really appreciate the time you spent to provide us a really useful references. We carefully studied that literature and with all respect to your recommendations, honestly we think that the proposed references is not related to the topic addressed in this article.

Anyway, based on your remarks, we add new paragraph wit related work.

(Communication protocols in healthcare) Contribution lines are missing here. Authors must mention about contribution area of this article.

 Thank you for this comment. We added the contribution to the paper.

(1) Preprocessing part is not clear. Need more details by drawing Figure.

Thank you so much for your remark. We have tried to explain and describe this part in more detail.

(1.1), Make different case-study here instead of mentioning one example for deep discussion

Thank you for this comment. We carefully studied related case-studies and we add new section called related work where we have tried to summarize the state of the art regarding healthcare standards.

(In Test performed and Results), Dataset descriptions are not enough clear. (In Test performed and Results), Discuss some failure case at last of experimental results.

Thank you so much for your remarks. For the purpose of this paper, we decided to use Option 3, as an illustrative way how to easily transfer data from one standard to another. For future work, the final version of this SW will work with data provided by the real NIS, or will acquire data via the API (a variant preferred by NIS vendors/administrators). In the final phase, we should therefore create an integration bridge that retrieves NIS data through the API and provides the necessary conversion and communication of messages to make them usable for Swisslog robotics. In the final phase, this should most likely be Option 2.

We would like to use more testing scenarios and compare all mentioned options in our next work after the all necessary steps will be done. We really hope that the missing recommendations won’t be a problem for you to reject the paper. Our effort is to present all these remarks in the following article.

We would like to thank you again and apologize for your time you spent with reviewing of the revised version of our manuscript. Thank you for your contribution.

Reviewer 2 Report

Get it proofread by a native english speaker. Minor editing required. for example - lines 17-21, break it into multiple sentences.

Introduction should include more details on DASTA and HL7. there is very little explanation of what HL7 is, what is the data format used in HL7, etc.

In section 3.1.2. Why convert messages to the HL7 standard?, you don't really explain why you are doing the conversion. what is the main motivation to convert data from DASTA to HL7?

line 125 - when you say sufficient level of quality, what % are you talking about? are there some data in DASTA which are not convertible to HL7?

In Figure 2, 3 and 4 what is CAPL? is it part if swisslog system? explain what it is.

Explain what are the trade-offs among option1, 2, 3 and 4. in terms of - easy of implementation, resources needed, reliability, etc

Provide implementation details. what software did you use to implement your system? did you use any particular tool for conversion of xml to HL7 format?

Overall I question the novelty of this paper. If i search for XML to HL7 conversion in google, i get so many links to tools and source code. for example this - https://github.com/nextgenhealthcare/connect-examples/tree/master/Code%20Templates/Convert%20XML%20to%20HL7. What is that you are proposing here which unique and not been done before?

Author Response

Dear reviewer,

Thank you so much for your valuable comments and recommendations. We really appreciate time you spent to make a review of our paper. Based on your remarks we have tried to do our best to enrich our article as you suggested. The changes are indicated in an updated version by green color. We really hope that these modifications and addition of some parts will contribute to accept the paper.

1.Get it proofread by a native english speaker. Minor editing required. for example - lines 17-21, break it into multiple sentences.

Thank you so much for your remarks. The article was read again independently by the author's team and various errors and typos were removed. Subsequently, the article was subjected to proof-reading by an expert through a translation agency.

2. Introduction should include more details on DASTA and HL7. there is very little explanation of what HL7 is, what is the data format used in HL7, etc.

Thank you so much for your remark. We considered this option, but in the end we decided not to include a descriptive part dealing with the standard itself. We're aware of this bug, and based on your feedback, we've added a section that focuses more on the HL7 standard.

3. In section 3.1.2. Why convert messages to the HL7 standard?, you don't really explain why you are doing the conversion. what is the main motivation to convert data from DASTA to HL7?

Thank you for this comment, we tried to explain the reason and add a paragraph to that section.
The main reason why to convert data from Czech DASTA to international HL7 standard is fact that systems for automated and safe medication process communicate at HL7 standard instead of DASTA which is used in Czech hospitals information systems.

4. In Figure 2, 3 and 4 what is CAPL? is it part if swisslog system? explain what it is.

Thank you for this comment, we tried to explain the reason and add a paragraph to that section. Yes, CAPL is part of Swisslog system. The CADP (Centralized automated drug preparation; it can be mentioned also as CAPL)

5. Explain what are the trade-offs among option1, 2, 3 and 4. in terms of - easy of implementation, resources needed, reliability, etc

Thank you so much for your remarks. For the purpose of this paper, we decided to use Option 3, as an illustrative way how to easily transfer data from one standard to another. For future work, the final version of this SW will work with data provided by the real NIS, or will acquire data via the API (a variant preferred by NIS vendors/administrators). In the final phase, we should therefore create an integration bridge that retrieves NIS data through the API and provides the necessary conversion and communication of messages to make them usable for Swisslog robotics. In the final phase, this should most likely be Option 2.

We would like to use more testing scenarios and compare all mentioned options in our next work after the all necessary steps will be done. We really hope that the missing recommendations won’t be a problem for you to reject the paper. Our effort is to present all these remarks in the following article.

6. Overall I question the novelty of this paper. If i search for XML to HL7 conversion in google, i get so many links to tools and source code. for example this - https://github.com/nextgenhealthcare/connect-examples/tree/master/Code%20Templates/Convert%20XML%20to%20HL7. What is that you are proposing here which unique and not been done before?

Thank you for this comment. The main aim of the paper is about finding the way how to ensure communication between systems based on different standards. For this reason, a web interface that very simply simulates the process of a doctor’s prescribing of a drug and its automated preparation in a hospital pharmacy. The newly-created interface between DASTA and HL7.

We would like to thank you again and apologize for your time you spent with reviewing of the revised version of our manuscript. Thank you for your contribution.

Reviewer 3 Report

In my opinion the issue of medical data transformation to international standards along with the processes improvement or/and technological (IT) innovations are absolutely interesting and valuable for being studied in many ways, indeed.

Unfortunately I see this study as not acceptable for being published. My objections are as follow:

• I cannot see any research problem determined, there is no study aim specified
• theres is no contribution to the theory in any field, neither HC management, informatics, public management, BPM or so
• title of the study is not clear, too many abbreviations, which are not clear to readers 
• similarly, abstract is full of abbreviations along with name of a company
• HL7 standard, which possibly can be a main object of the study is discussed very poorly
• the question is, if this is an industrial paper or scientific study, in my opinion this in not a scientific study

Author Response

Dear reviewer,

Thank you so much for your valuable comments and recommendations. We really appreciate time you spent to make a review of our paper. Based on your remarks we have tried to do our best to enrich our article as you suggested. The changes are indicated in an updated version by green color. We really hope that these modifications and addition of some parts will contribute to accept the paper.

In my opinion the issue of medical data transformation to international standards along with the processes improvement or/and technological (IT) innovations are absolutely interesting and valuable for being studied in many ways, indeed.

Unfortunately, I see this study as not acceptable for being published. My objections are as follow:

1. I cannot see any research problem determined, there is no study aim specified

Thank you for this comment. We really appreciate the time you spent to provide us a really useful references. We carefully studied related literature and we add new section called related work where we have tried to summarize the state of the art regarding this issue. We really hope that this review can prove that there is a research part.

2. theres is no contribution to the theory in any field, neither HC management, informatics, public management, BPM or so

From our point of view, there should be a contribution to the science field of Health technology and Informatics. As was declared, there are many studies deal with issue of healthcare standards.

3. title of the study is not clear, too many abbreviations, which are not clear to readers

Thank you so much for this comment. We agree, it might be a little bit confusing. Based on your recommendation we totally changed the title of the paper to be clearer one.

4. similarly, abstract is full of abbreviations along with name of a company

Thank you so much for this comment. We agree. Based on your recommendation we totally changed the abstract of the paper. We hope that it will be more indicative of the actual focus of the paper and the reasons why we decided to deal with this issue.

5. HL7 standard, which possibly can be a main object of the study is discussed very poorly

Thank you so much for your remark. We considered this option, but in the end we decided not to include a descriptive part dealing with the standard itself. We're aware of this bug, and based on your feedback, we've added a section that focuses more on the HL7 standard.

6. the question is, if this is an industrial paper or scientific study, in my opinion this in not a scientific study

We are really grateful to your opinion. We added some new sections, we updated some passages as you suggested. At this updated paper, we have tried to clearly describe the solved issue in which a problem is first identified and based on performed experiments, the software interface has been developed that purport to solve that issue. We really hope that these modifications and addition of some parts will help to accept the paper.

We would like to thank you again and apologize for your time you spent with reviewing of the revised version of our manuscript. Thank you for your contribution.

Round 2

Reviewer 1 Report

Comments are not properly answered. 

very weak discussion. 

Reviewer 2 Report

Authors have addressed some of the comments. I believe the article is well presented. Given the practical importance of interoperability among medical information systems, this article has potential but needs improvements.

We can identify 3 contributions in this paper

1. A system architecture for interoperability of DASTA and HL7. Not enough discussion on trade-offs between different architectures with qualitative and quantitative data.
2. Method for converting DASTA format to HL7. authors should include more comprehensive experiments and results. Should talk about any in-compatibilites between two data formats and how to handle those cases.
3. A web interface for presenting the output of a simulated CAPL system. How would HL7 output assimilate with the DASTA system?

Reviewer 3 Report

I see you answered all my objections pretty well, the study in its current state can be published, I suppose.