Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data

Kelsey Chalmers; Valérie Gopinath; Adam G. Elshaug

doi:10.1371/journal.pone.0266154

Peer Review History

Original SubmissionMarch 14, 2022
24 Aug 2022 Decision Letter - Robert Jeenchen Chen, Editor PONE-D-22-07582Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health dataPLOS ONE Dear Dr. Chalmers, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please revise. Please submit your revised manuscript by Oct 08 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes Reviewer #3: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: N/A Reviewer #3: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). 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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This paper supports the process of gathering relevant codes associated with a cohort of patients that is initially pre-defined in some manner. Overall this problem has been addressed repeatedly in the literature. This paper uses a SAS procedure, HPSPLIT, at its core to address the problem. This is indeed a useful function in SAS, but obviously has been invented already and the paper describes a handful of workflow approaches to using the procedure and uses R (rather than the SAS built in visualizations) for showing the results. The problem to be addressed is put in a very restrictive context and those who are not familiar with using claims data would have trouble seeing the value, would recommend in future papers that the perspective be broadened. There are many arbitrary decisions to accommodate technical specifics, such as using only the first 4 digits of ICD codes which are not semantically justified. The reporting of only outcome statistics for the specific samples used for training is a serious limitation Reviewer #2: I think that the tool is not easy to use. One issue is the development of a SAS to R workflow. I suggest to include a default SAS output to upload when a user opens the app. The documentation should be richer with more details. Reviewer #3: I thank the authors for investigating such an important subject; I have the following comments: - The structure of the manuscript was not organized properly, and it was hard to follow. The Materials and Methods section should be before the Results section. - The data described that patients younger than 65 were excluded from the study, so how can the results be generalized to people of all ages? ****** 6. 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Revision 1
8 Nov 2022 Author Response Reviewer 1 Thank you to Reviewer 1 for their time and comments on our paper. > Overall this problem has been addressed repeatedly in the literature. This paper uses a SAS procedure, HPSPLIT, at its core to address the problem. This is indeed a useful function in SAS, but obviously has been invented already and the paper describes a handful of workflow approaches to using the procedure and uses R (rather than the SAS built in visualizations) for showing the results. In this paper, we describe our methods and developed tools for building thorough health service indicators. This is useful and important for other researchers developing service measures (whether related to low-value care or otherwise). We have not come across similar approaches or tools described in the literature. The need for such a solution has become clearer to us after our own internal audits on published indicators showed frequent or important diagnosis codes in claims data had sometimes not been included. The benefit of using R is due to the shiny package, which is not available in SAS, and creating a dashboard that can be used by non-coders and those who do not have direct access to claims data. > The problem to be addressed is put in a very restrictive context and those who are not familiar with using claims data would have trouble seeing the value, would recommend in future papers that the perspective be broadened. We agree with Reviewer 1 that this - low-value service indicators - is a somewhat niche problem. A large number of health service research studies, however, do use administrative data and create cohorts based on service and diagnosis codes (as mentioned in our introduction). We have written our paper and built our tool for a research audience, where we assume at least one collaborator is familiar with claims data and the processes involved in creating these initial indicators/cohorts. > There are many arbitrary decisions to accommodate technical specifics, such as using only the first 4 digits of ICD codes which are not semantically justified. This is a challenge that we came across while developing this process, so thank you to Reviewer 1 for raising this issue. Ultimately this is a process and tool for data exploration and visualization. Like many visualization approaches, decisions around summarizing data have to be made. A simple example is choosing the number of bins to use to display data in a histogram. We decided on using a limit of four characters for ICD diagnosis codes because of the organization of diagnosis information in the ICD codes. For example, M17.1 describes “Unilateral primary osteoarthritis”, M17.11 describes “Unilateral primary osteoarthritis, right knee” and M17.12 describes “Unilateral primary osteoarthritis, left knee”. The actual informative condition for the purpose of this exercise is unilateral primary osteoarthritis, which just requires four characters of the ICD codes. > The reporting of only outcome statistics for the specific samples used for training is a serious limitation Thank you to Reviewer 3 for pointing this out. We had originally decided to report only on the original training set since our goal was to select the diagnosis codes ‘important’ to this sample. After revisiting the paper, we decided to report the sensitivity, specificity and misclassification rates on a validation sample of claims in Table 2 (and have made updates to the results on page 9 to reference these results). Reviewer 2 Thank you to Reviewer 2 for their time and comments on our manuscript. > I think that the tool is not easy to use. One issue is the development of a SAS to R workflow. I suggest to include a default SAS output to upload when a user opens the app. We have revisited the R tool and package and have taken the opportunity to make a number of improvements, including Reviewer 2’s useful suggestion to have an option to upload an example data set. Our other improvements include: - Including checkboxes for Include/Exclude options for codes - Adding a row ID column so sorting is easier - Updating the label input as a type box/drop down menu so previous labels can be saved - Adding colors to the action buttons > The documentation should be richer with more details. As well as the changes made above, we have included more instructions on the application when the user opens it. All of these updates can be observed in the Github repository. Reviewer 3 > I thank the authors for investigating such an important subject. We thank Reviewer 3 for their time and thoughts on our manuscript. > The structure of the manuscript was not organized properly, and it was hard to follow. The Materials and Methods section should be before the Results section. We had originally organized in this way to follow some previous PLOS ONE publications that we had found useful in understanding the purpose/outputs (the results) prior to the details of the Materials and Methods. We do take Reviewer 3’s point, however, and have updated the text so the Materials and Methods are before the Results. > The data described that patients younger than 65 were excluded from the study, so how can the results be generalized to people of all ages? Our goal was to build indicators for services provided to people 65 years and older, and never to generalize to data on people of all ages. Users working with other populations will have to change this age restriction. We have now noted this in the discussion section (p18, lines 1-3): “We also restricted our claims data to services provided to patients aged 65 and over. If users have a different population in their study, they will have to edit this step in the SAS code, in order to find diagnosis codes relevant to their population.” Attachments Attachment Submitted filename: PLOS ONE Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0266154.r002
22 Dec 2022 Decision Letter - Robert Jeenchen Chen, Editor Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data PONE-D-22-07582R1 Dear Dr. Chalmers, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Robert Jeenchen Chen, MD, MPH Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #3: All comments have been addressed Reviewer #4: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #3: Yes Reviewer #4: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #3: Yes Reviewer #4: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #3: No Reviewer #4: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #3: Yes Reviewer #4: No ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #3: (No Response) Reviewer #4: (No Response) ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #3: No Reviewer #4: No ******** https://doi.org/10.1371/journal.pone.0266154.r003
Formally Accepted
4 Jan 2023 Acceptance Letter - Robert Jeenchen Chen, Editor PONE-D-22-07582R1 Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data Dear Dr. Chalmers: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Robert Jeenchen Chen Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0266154.r004

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