This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

PONE-D-23-10824Health Care Utilization 9 months Pre- and Post- COVID-19 Hospitalization among Patients Discharged AlivePLOS ONE

Dear Dr. Zaidan,

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.

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The authors employed a nationally-representative database from the United States to examine healthcare utilization patterns up to nine months after patients were discharged home following COVID-19 hospitalization. While the findings demonstrate an increase in healthcare utilization post-discharge for individuals hospitalized due to COVID-19 compared to their pre-pandemic healthcare utilization, the authors must address several crucial concerns before this manuscript can be considered suitable for publication.

As highlighted by the reviewer, it is advisable for the authors to conduct additional analyses comparing healthcare utilization across various sub-groups. The authors must implement sufficient statistical testing in order to substantiate their interpretation of the study's findings. Furthermore, the authors are urged to carefully consider and address the study limitations pointed out by the reviewers.

==============================

Please submit your revised manuscript by Jul 28 2023 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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We look forward to receiving your revised manuscript.

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Raymond Nienchen Kuo, Ph.D

Academic Editor

PLOS ONE

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2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548925/

https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-023-02313-x

https://www.jamda.com/article/S1525-8610(21)00762-3/fulltext

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

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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

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

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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: Yes

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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

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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 authors use a large health system in the US to describe patterns in health care use among individuals who were hospitalized with COVID-19 in the early phases of the pandemic, prior to widespread vaccine access or the newer variants. Although they describe and exposure and outcome, formal comparisons are not included. It would be of potential interest if, for example, they compared post-hospitalization use to other conditions (e.g., sepsis, influenza), pre- vs. post-HCU, or even formally assessed trends in HCU over time. At times the authors refer to people who were hospitalized but not discharged home as being excluded, but most of Table 2 describes alternative dispositions for patients who were not discharged home. Perhaps another formal comparison would be of interest in that regard, e.g., predictors of home vs. not-home discharge.

It is important to note in more detail that health care use in the US is not driven solely by patient need for medical care. It involves a complex interplay of multiple factors, including health insurance, access to care, available medical care, and referrals. Patients cannot access medical care they (or their clinicians) do not know they would benefit from (e.g., increasing evidence for increased risk of diabetes following infection suggests some patients might benefit from endocrinology evaluation; GI complications are also apparent, as are fertility issues, but few were aware of these issues at the time of the study); second, patients who have exhausted available resources do eventually stop going to as many medical appointments, even in cases where their health remains severely impaired. Please comment.

With regards to healthcare encounters, is it possible to include home health encounters?

Did the authors consider looking for potential effect modification by sex? Or by ICU admission during the index hospitalization? What % of cases were re-infections, and if an important %, what if any difference is there in HCU by reinfection?

The authors describe covariates, although no adjusted models were run. Perhaps baseline patient characteristics might a more accurate term. With regards to these variables, why gender (instead of sex), what were the race categories (and were they patient reported or something else), and what about other important potential confounders, e.g., education, insurance, occupation, number o vaccinations? Finally, inclusion of comorbid conditions only in the prior 12 months likely significantly underestimated true co-morbid conditions, is it possible to expand the look-back window to several years?

Table 1: What % were covered by commercial vs. other health insurance?

Table 2 seems more appropriate for study flow- these patients were excluded from the cohort.

There are more limitations than the authors list, including the following:

- Use of only patients insured by a large commercial company or Medicare Advantage with at least 2 months of pre-COVID data means the study population includes people who have relatively good access to medical care. The authors do not report what % had commercial insurance, but those people would have been healthy (and young enough) to have employment. How representative is this of the overall population?

- What about care people may have received in other locations, e.g., out of network?

- The study time is limited to largely pre-vaccination stages of the pandemic, and during early variants, when monoclonals were available and used more widely – would these findings be generalizable or informative now?

Line 181 – There is an interesting but unfounded (by reproducible studies) assumption that patients are ‘merely anxious or depressed’ after SARS-CoV-2 infection, implying they should be able to use CBT or positive self-talk to resolve their symptoms. In an effort to discourage these and other similar implications, please remove the phrase “decline in mental health” from line 181 and instead simply report the numbers.

Reviewer #2: This study provides evidence of healthcare utilization (HCU) trends of COVID-19 patients 9 months post-diagnosis using a sample of the U.S. COVID-19 patient population. The cohort creation process is transparent and the paper is well written. However, the current analysis is not sufficient to merit publication at PLOS ONE. First, it is not entirely clear what is the biggest contribution of the study. Given that there are other studies that extend the time horizon of long COVID HCU to twelve months (Roth et al., 2022), the authors should argue how these results may be more informative to other longitudinal studies of HCU and long COVID on the basis of the quality of their analysis, as opposed to the long time span of the COVID-19 post-diagnosis period only. It is not surprising that HCU rises post-diagnosis; the authors could also try to timestamp when this increased HCU subsides for different age groups (Koumpias et al., 2022).

The authors should consider these easily executable revisions below to enhance the rigor of the analytical approach.

Major comments:

The biggest concern is the lack of any account of patient insurance status. The confluence of Medicare-eligible and Medicare non-eligible population in the study cohort leads to overestimation of the influence of a COVID-19 diagnosis on HCU because the latter group (<65years old) is less likely to engage in HCU due to relatively higher costs they may face. Therefore, the authors should report HCU separately for commercially-insured (<65yrs old) and Medicare/Medicare Advantage patients.

It is also mentioned that this is a descriptive analysis; yet no statistical tests are being used, whatsoever. At a minimum, the authors shoould report whether pre-, post-diagnosis levels are statistically different using t-tests. For instance, the first sentence of the introduction reads: "In our nationally-representative study of patients discharged home after a COVID-19 hospitalization, we found that HCU remained significantly high 9 months after discharge from index hospitalization." It appears highly likely that the increase in HCU is detectable at conventional levels of statistical significance, too. After conducting the statistical analysis, this statement could be revised to explicitly state whether increased HCU remained higher in a statistically significant way.

Another concern is that HCU is driven by intensity of hospitalization which varies in a way that the authors do not sufficiently account for. Separating the results by specialty is certainly a step towards that direction. It would be most informative to show how the trends of post-diagnosis HCU for different subgroups of varying hospitalization intensity. In fact, the authors should consider shedding light to any differential HCU responses by LOS. (e.g. by LOS quartiles). This would make a genuine contribution by further illustrating post-discharge differences in HCU based on severity of COVID-19 infection. However, the authors do not mention changes in patient LOS until page 9. Given that there is relatively less evidence on LOS changes than HCU changes following COVID-19 diagnosis, this novel finding should be discussed earlier if not employed as another variable in cross-tabulations of HCU pre- and post-diagnosis.

Minor comments:

Another source of measurement error causing underestimation of the association of COVID-19 with post-diagnosis HCU is due to sample attrition from death or loss of insurance. To examine the sensitivity of their findings to this potential issue, the authors should use a balanced panel of patients who contribute person-days both pre-diagnosis and during the third post-diagnosis time interval (6-9) as a supplementary robustness check.

Related, the authors should explore whether information regarding COVID-19 diagnosis is available in the secondary and subsequent diagnosis lines and to what extent this leads to significant undercount of COVID-19 patients. It would be very helpful to complement the results a discussion of the frequency of COVID-19 diagnosis non-primary line reporting.

Re: Data Availability - Unsure whether data is available after all given that this is the proprietary OptumInsights de-identified Clinformatics Data Mart. This may need to be corrected.

Finally, are the results robust to the inclusion of the outcome in its raw form, measured in levels? It would be useful to show whether the transformation to person-days has any influence on the results.

A quick literature review identified the following journal articles pertinent to this study:

References:

- Koumpias AM, Schwartzman D, Fleming O. Long-haul COVID: healthcare utilization and medical expenditures 6 months post-diagnosis. BMC Health Services Research. 2022 Aug 8;22(1):1010.

- Roth SE, Govier DJ, Marsi K, Cohen-Cline H. Differences in outpatient health care utilization 12 months after COVID-19 infection by race/ethnicity and community social vulnerability. International Journal of Environmental Research and Public Health. 2022 Mar 15;19(6):3481.

- Zhou X, Andes LJ, Rolka DB, Imperatore G. Changes in health care utilization among Medicare beneficiaries with diabetes two years into the COVID-19 pandemic. Ajpm Focus. 2023 Jun 1:100117.

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Reviewer #1: No

Reviewer #2: No

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PONE-D-23-10824R1Health Care Utilization 9 months Pre- and Post- COVID-19 Hospitalization among Patients Discharged AlivePLOS ONE

Dear Dr. Zaidan,

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 submit your revised manuscript by Nov 30 2023 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.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Raymond Nienchen Kuo, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

We acknowledge the effort and dedication you have exhibited in responding to the initial reviews and improving your manuscript. However, it has come to our attention that there are still several significant issues raised by Reviewer #1 that necessitate further elucidation. One such area pertains to how this study could potentially bridge the existing knowledge gap related to inpatient care related to COVID-19 infection. It would be constructive to elaborate on this aspect in your manuscript.

In addition, we suggest that you provide a concise description of the data source that was used in your research. It would also be beneficial to discuss the potential impact of your sample's characteristics on the generalizability of your study findings. This will allow readers to understand the context and implications of your research better.

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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 #1: (No Response)

Reviewer #2: All comments have been addressed

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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 #1: Partly

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

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: No

Reviewer #2: No

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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: The authors have responded to some questions and comments to the best of their ability, and comparison of 9 months pre- vs. post HCU hospitalization for COVID was added, which his helpful. However, there remain significant limitations within the available data that perhaps cannot be addressed. Overall, however, it is not surprising that people who were hospitalized required more health care after hospitalization and they did poorly in general, even among those who were only eligible because they survived at least a year after hospital discharge. One key question that this study cannot answer is whether or to what degree hospitalization for COVID may differ from other causes of hospitalization.

Can the authors clearly explain what this study adds beyond a prior publication (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548925/) how it adds materially to our understanding of health care use post hospitalization for COVID (specifically, compared to other reasons for hospitalization).

Otherwise, I have the following additional comments/questions:

Please provide a brief description of the kinds of patients who would be included in Optum’s Clinformatics Data Mart – what % of the US population are generally included? Are these people generally of similar, worse, or better health than the general population? What kinds of medical centers contribute data, e.g., typically community vs. academic? What % are rural?

Readers have a general idea of, for example, the patient population and generalizability for VHA studies, but that is not the case here. For provide a similar summary for patients in this cohort.

Page 7 line 127 – Please clarify that this was the primary admission diagnosis (In Figure 1, I see that this appears to be a hospital admission diagnosis, is that correct?)

In the discussion/limitations, please include the risk of introducing survivor bias by requiring that people have at least 12 months of follow-up. Why not allow variable follow-up and simply account for it in analysis, and not risk survivor bias?

What are the test characteristics for the ICD code for accurate case identification? (e.g., sensitivity, specificity, PPV, NPV)

I initially misread Figure to read that 63,161 people were excluded due to loss of insurance prior to hospital discharge. Please restructure Figure 1 to list the N excluded (%), similar to reporting for clinical trials.

Table 1: Lack of insurance information is an important limitation. How were the comorbid conditions identified (i.e., in a supplement, include ICD codes, etc)

Table 2: Please move the units for each measure of HCU to the row label to make them more clear and please provide more explanation of the measures of health care utilization. E.g., “ED visits per 10,000 person-days”. Are the reported pre- vs. post-hospitalization HCU reflective of the mean or median or some other measure? Please include the appropriate measure of variability around that reported summary (e.g., SD, IQR, etc). Is hospital LOS per capita as well? Why was 9 months before and after chosen? Why not a year? (A year would be easier to compare to other information, e.g., the baseline proportion of people with an ED visit per year, to assess generalizability)

Please confirm that post hospitalization HCU measures do not include the index hospitalization.

Tables 1, 2, and 3 are currently in the Methods section, but shouldn’t they be referred to and located in the Results section?

Results:

Why might people who were in the ICU have shorter length of stay? (How does that translate into a RR>1? Am I interpreting that result incorrectly?)

Discussion:

For people in other countries, please provide some context for health care utilization. In general, how much might an outpatient visit cost, out of pocket? What % of a hospitalization might patients have to pay out of pocket, and approximately how much might that be in absolute USD? This provides context for what might drive patient behavior, specifically health-seeking behaviors. Might some patients avoid outpatient care if it cost $25/visit, while an ED visit or in-patient hospitalization might have $0 out of pocket costs?

Is it possible to include any information about why patients were re-hospitalized? E.g., admission for ACS, neurological, PNA, dyspnea, or other causes?

For consistency, I suggest using the terms male and female throughout, since sex was likely the measured variable in available data, not gender.

Reviewer #2: (No Response)

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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: 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.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PONE-D-23-10824R2Health Care Utilization 9 months Pre- and Post- COVID-19 Hospitalization among Patients Discharged AlivePLOS ONE

Dear Dr. Zaidan,

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 submit your revised manuscript by Mar 28 2024 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.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Robert Jeenchen Chen, MD, MPH

Academic Editor

PLOS ONE

Additional Editor Comments:

Please revise.

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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 #2: All comments have been addressed

Reviewer #3: (No Response)

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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 #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: 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 #2: No

Reviewer #3: No

**********

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 #2: Yes

Reviewer #3: 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 #2: (No Response)

Reviewer #3: This study by Zaidan et al, described the increase in Health Care Utilization (HCU) in patients post COVID-19 hospital discharge (follow-up = 9 months). The manuscript is well written and includes appropriate analyses and tables.

The tables should be referred to in the results & not the methods.

They also have numerous subscripts within the title of the tables that are unnecessary. Just need a table legend without the addition of subscripts within the title (Minor point).

I am slightly confused about the inclusion/exclusion criteria. In the "Cohort Selection" section of the methods, the authors state that "Our samples included all adults hospitalized with primary diagnosis of COVID-19 who were discharged home (with or without HOME HEALTH care)..." However, in Figure 1 they state that "Not discharged home or with HOME HEALTH" was part of the exclusion criteria. This needs to be clarified, were those with HOME HEALTH included of excluded. This may have an impact on the amount of HCU. If HOME HEALTH participants were included then this would likely have an impact on HCU.

Similarly, another potentially observation that could inform future pandemic preparedness would be analysis on whether particular co-morbidities were associated with increased HCU post-COVID discharge.

Please define OFFICE (mentioned in the results (e.g. p13; line 232, p14; line 248) which was not described within the results.

A limitation of this work is perhaps the limited ability to extrapolate these findings to a larger cohort (throughout the USA), given that this cohort is likely to have a higher socioeconomic status (given the degree of insurance cover) and are of older age (72 years). If the authors were to divide the cohort by age (in a sub analysis) this would add more weight to generalizing to a larger population.

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Reviewer #2: No

Reviewer #3: No

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Health Care Utilization 9 months Pre- and Post- COVID-19 Hospitalization among Patients Discharged Alive

PONE-D-23-10824R3

Dear Dr. Zaidan,

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Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

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Reviewer #3: No

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Reviewer #2: Yes: Antonios Marios Koumpias

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