Machine learning–optimized discharge timing in typhoid care: Implications for clinical outcomes, cost efficiency, and health system performance

Shekoofeh Sadat Momahhed; Atefehsadat Haghighathoseini

doi:10.1371/journal.pone.0354148

Peer Review History

Original SubmissionApril 1, 2026
12 May 2026 Decision Letter - Hilary Izuchukwu Okagbue, Editor -->PONE-D-26-09410-->-->Machine Learning–Optimized Discharge Timing in Typhoid Care: Implications for Clinical Outcomes, Cost Efficiency, and Health System Performance-->-->PLOS One Dear Dr. Momahhed, 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. ============================== ACADEMIC EDITOR: Major revision is recommended. ============================== Please submit your revised manuscript by Jun 26 2026 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. 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Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions -->Comments to the Author 1. 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: Yes Reviewer #2: Yes ******** -->2. Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: Yes Reviewer #2: No ****** -->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). 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 #1: Yes Reviewer #2: No ****** -->4. 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 #1: Yes Reviewer #2: Yes ****** -->5. 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 #1: The manuscript addresses an important and relevant topic, and the use of machine learning for discharge optimization is promising. However, some areas require further clarification. 1. The authors should further discuss the model’s generalization beyond the study setting and consider external validation. 2. The predictor warrants deeper interpretation, particularly regarding policy implications. Reviewer #2: This is a thoughtful and ambitious study that provides valuable insight into system-level inefficiencies in typhoid patient management. The work highlights an important healthcare challenge and demonstrates the potential of machine learning approaches in improving operational decision-making. However, the study currently draws conclusions that go beyond what the evidence can confidently support. In particular, it tends to blur the distinction between predicting discharge patterns and recommending earlier patient discharge, which requires much stronger clinical validation and safety evaluation. To strengthen the study and improve its clinical credibility, several important steps may be considered: -Validate the model findings against detailed medical records for a subset of patients to confirm the accuracy of typhoid diagnoses and ensure that patients would have been clinically stable at the predicted discharge times. -Conduct a prospective pilot study or randomized controlled trial comparing model-guided discharge practices with standard clinical care. Key safety outcomes such as readmission, mortality, and clinical deterioration should be carefully monitored. -Perform external validation using data from a different hospital system or from another time period to assess the generalizability and robustness of the model. -Develop a clear implementation framework that includes clinical decision rules, monitoring mechanisms, escalation pathways, and accountability structures before considering real-world deployment. -Involve healthcare administrators and policymakers to address the underlying systemic issue—particularly payer-driven prolonged hospital stays—rather than only predicting when such delays may occur. Another important limitation of the study is the absence of statistical testing when comparing machine learning models. While the gradient-boosted classifier achieved an AUROC of 0.862 compared to 0.831 for logistic regression, the reported difference of 0.031 is relatively small and may or may not be statistically meaningful. Without formal statistical evaluation, claims that one model “outperforms” another remain insufficiently supported. A few formatting correctios are appreciated including tables and figures captions, references etc. Several key statistical elements are missing: -Confidence intervals (95% CIs) for AUROC values should be reported so readers can assess the precision and uncertainty of the estimates. Overlapping confidence intervals may indicate that the observed performance difference is not statistically significant. -A formal statistical comparison, such as the DeLong test for correlated ROC curves, should be performed to determine whether the AUROC difference is significant at an accepted threshold (e.g., p < 0.05). -The study should also discuss the practical or clinical significance of the observed performance improvement. ------Although a 3.1% increase in AUROC may appear favorable statistically, its real-world importance depends heavily on the clinical context. In high-stakes settings such as discharge decision-making, even small performance differences can have meaningful implications for patient safety; however, in lower-risk administrative applications, the improvement may be negligible. Overall, the study addresses an important problem and demonstrates promising analytical work, but additional clinical validation, statistical rigor, and implementation planning are necessary before the findings can support changes to patient discharge practices. ****** -->6. 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 #1: Yes: Dr Kingsley Attai Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation. NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications. https://doi.org/10.1371/journal.pone.0354148.r001
Revision 1
21 May 2026 Author Response Thank you for the opportunity to revise our manuscript. We have carefully addressed all mandatory journal requirements, the statistical concerns raised by Reviewer 2, the clinical validity and generalizability questions from Reviewer 1, and the formatting issues noted by the editor. First, regarding the journal’s mandatory requirements: we have moved the ethics statement into the Methods section (line 245), revised the Data Availability statement with full legal and ethical justification for restricted access while keeping our analysis code publicly available on GitHub, and added formal captions for all supplementary figures and tables at the end of the manuscript. Second, to address Reviewer 2’s statistical concerns, we have added 95% bootstrap confidence intervals for AUC-ROC and AUC-PR for all models in Table 4, performed a formal DeLong test comparing LightGBM and logistic regression (AUC difference = +0.0309, 95% CI: 0.0264–0.0355, DeLong z = 13.298, p < 0.0001), and expanded the Discussion to explicitly address the practical clinical significance of this difference in the context of a low-harm administrative screening tool. We have also systematically softened potentially over-claiming language throughout the manuscript—replacing phrases like “eligible for earlier discharge” with “flagged for clinical review” or “identified as potentially having reducible length of stay”—and substantially strengthened the Limitations section to acknowledge the absence of clinical chart review, prospective trials, and external validation, while expanding the Future Research section to explicitly call for RCTs, clinical record validation, and external validation across other Iranian payers and LMIC settings. Finally, we have addressed Reviewer 1’s concerns by adding a dedicated subsection on generalizability to other Iranian payers (Social Security Organization, Armed Forces Medical Services Fund) and other LMIC contexts, and provided deeper policy interpretation of the top predictors—particularly the preferential currency flag—arguing that the model identifies a remediable structural mismatch in discharge protocols across payer pathways rather than merely predicting risk. All tables and figures have been reformatted to PLOS ONE style, reference 28 has been corrected, and the manuscript structure now fully complies with journal requirements. We believe these revisions have substantially strengthened the scientific rigor, clinical transparency, and policy relevance of our work, and we are grateful for the reviewers’ constructive guidance. Attachments Attachment Submitted filename: Response to Reviewers.pdf https://doi.org/10.1371/journal.pone.0354148.r002
6 Jul 2026 Decision Letter - Hilary Izuchukwu Okagbue, Editor <p>Machine Learning–Optimized Discharge Timing in Typhoid Care: Implications for Clinical Outcomes, Cost Efficiency, and Health System Performance PONE-D-26-09410R1 Dear Dr. Momahhed, 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. 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Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: Yes Reviewer #2: 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 #1: Yes Reviewer #2: 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 #1: Yes Reviewer #2: Yes ****** -->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 #1: I have carefully reviewed the revised manuscript and the authors’ responses to the reviewers' comments. The authors have addressed the concerns raised during the previous review round and have made appropriate revisions that have improved the clarity and quality of the manuscript. The study presents a valuable application of machine learning to optimize discharge timing in typhoid care, with important implications for clinical outcomes, healthcare resource utilization, and health system performance. I have no further substantive comments and believe the manuscript is suitable for publication in its current form. Reviewer #2: The authors have adequately addressed the comments raised in a previous round of review. This manuscript is acceptable for publication provided that all the editorial requirements are fulfilled. ****** -->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 #1: No Reviewer #2: Yes: Madhuri Wakode ******** https://doi.org/10.1371/journal.pone.0354148.r003
Formally Accepted
Acceptance Letter - Hilary Izuchukwu Okagbue, Editor PONE-D-26-09410R1 PLOS One Dear Dr. Momahhed, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, 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. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@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 Hilary Izuchukwu Okagbue Academic Editor PLOS One https://doi.org/10.1371/journal.pone.0354148.r004

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