Surgical capacity, productivity and efficiency at the district level in Sub-Saharan Africa: A three-country study

Mengyang Zhang; Jakub Gajewski; Chiara Pittalis; Mark Shrime; Henk Broekhuizen; Martilord Ifeanyichi; Morgane Clarke; Eric Borgstein; Chris Lavy; Grace Drury; Adinan Juma; Nyengo Mkandawire; Gerald Mwapasa; John Kachimba; Michael Mbambiko; Kondo Chilonga; Leon Bijlmakers; Ruairi Brugha

doi:10.1371/journal.pone.0278212

Peer Review History

Original SubmissionMarch 11, 2022
30 Jun 2022 Decision Letter - Majid Soleimani-damaneh, Editor PONE-D-22-07365Surgical capacity, productivity and efficiency at the district level in Sub-Saharan Africa: a three-country studyPLOS ONE Dear Dr. Zhang, 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 Aug 14 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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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This paper deals with the determinants of hospital efficiency in district hospitals in three African countries, Tanzania, Malawi, and Zambia. The authors determine the hospital efficiency scores for three counties. They discussed that hospital efficiency, combining capacity measures and surgical outputs, is a better indicator of surgical performance than capacity measures, which could be misleading if used alone for surgical planning. They concluded that investment in the surgical workforce, in particular, plays a central role in improving district hospital surgical productivity and efficiency. Overall, the aim of this paper may be attractive for the practitioner of the DEA model; but first, the authors should address the following comments. One of the features of the DEA models is that of providing the benchmark (target unit) for inefficient units, While the authors do not discuss the key concept of target unit for inefficient DMUs. The authors must suggest the target unit for inefficient DMUs to learn and improve by following it. P. 6 L. 1 Hospital efficiency The authors obtain the efficiency scores using the constant returns to scale (CRS) DEA model while utilizing the variable returns to scale (VRS) DEA model would be more common. P. 6 L. 7 Typo Chames et al. → Charnes et al. P. 12 L. 2 Congestion in the resources The authors state as follows: The above statements show that the congestion may be present in the inputs. The authors must deal with identifying and managing congestion using DEA. P. 14 L. 6 The mortality rate The authors state as follows: “The mortality rate in the sample was very low (0.08%), hence it is excluded in the DEA.” The mortality rate in the concept of DEA is an undesirable output that should be considered in the efficiency score of the hospitals. S1 Table. Full result of DEA by country The authors only identify the returns to scale (RTS) status of hospitals without any interpretation. Why do all DMUs show constant RTS or increasing RTS? The authors must discuss this concept in detail. Reviewer #2: This paper presents the application of data envelopment analysis (DEA) in the hospital ward. In fact, this paper investigates the determinants of hospital efficiency in district hospitals in three African countries. For this purpose, the initial DEA models (CCR, BCC) have been used. Here are some of my comments on the paper: 1) The DEA literature needs to be better articulated. References need to be updated. 2) Explain the reasons for choosing production indicators. Input factors must also be stated. 3) For better results, I suggest using the SBM-model as well ****** 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: Amin Mostafaee 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. Attachments Attachment Submitted filename: Report PONE-D-22-07365.pdf https://doi.org/10.1371/journal.pone.0278212.r001
Revision 1
11 Aug 2022 Author Response Reviewer 1 1. This paper deals with the determinants of hospital efficiency in district hospitals in three African countries, Tanzania, Malawi, and Zambia. The authors determine the hospital efficiency scores for three counties. They discussed that hospital efficiency, combining capacity measures and surgical outputs, is a better indicator of surgical performance than capacity measures, which could be misleading if used alone for surgical planning. They concluded that investment in the surgical workforce, in particular, plays a central role in improving district hospital surgical productivity and efficiency. Overall, the aim of this paper may be attractive for the practitioner of the DEA model; but first, the authors should address the following comments: One of the features of the DEA models is that of providing the benchmark (target unit) for inefficient units, While the authors do not discuss the key concept of target unit for inefficient DMUs. The authors must suggest the target unit for inefficient DMUs to learn and improve by following it. Thank you for the comments. There is no reference point for inefficient facilities, hence our approach needed to be adjusted. Rather than focusing on specific inefficient hospitals, we highlight the problems of hospitals with low efficiency (DEA score < 0.5). As what’s shown in Table 4, compared with highly efficient hospitals, those hospitals had lower values scores in surgical staff but relatively higher score in supplies, which were consistent in three countries. Hence, in Discussion we suggested that investment in surgical staff would be a better choice for the national surgical planning. 2. P. 6 L. 1 Hospital efficiency The authors obtain the efficiency scores using the constant returns to scale (CRS) DEA model while utilizing the variable returns to scale (VRS) DEA model would be more common. Thank you for your comments. Yes, the use of VRS can provide additional details. Due to the text length requirement, we haven’t included the VRS results in the main context but in the Supporting Information where we also presented the details of efficiency score using variable returns to scale and the nonincreasing returns to scale. 3. P. 6 L. 7 Typo Chames et al. → Charnes et al. Thank you for pointing it out. It has been corrected. 4. P. 12 L. 2 Congestion in the resources The authors state as follows: “Our findings question this assumption, demonstrating that surgical production factors do not contribute equally to outputs; and there can even be an inverse relationship between surgical capacity and efficiency. All hospitals that scored high on surgical capacity (PIPES index) scored low for efficiency, which suggests that the provision of more resources to a hospital may not make it more productive.” The above statements show that the congestion may be present in the inputs. The authors must deal with identifying and managing congestion using DEA. Thank you for your comments. The DEA efficiency suggests the best allocation of different inputs under certain assumptions given the current output level. Slacks that indicate the over input will lead to inefficiency. Due to the length requirement, we haven’t included the slacks discussion in the paper, because the core interest of this paper is to show the difference in measuring hospital performance (the difference in input weights using different measurement), thereby drawing more attention to the measurement selection and healthcare development at the district level. In addition, the common set of weights (CSW) in DEA was included to improve the accuracy of the input weights, the result of which was shown in Table 5. The result of input slacks are added into S3 Data envelopment analysis result in Supporting Information. 5. P. 14 L. 6 The mortality rate The authors state as follows: “The mortality rate in the sample was very low (0.08%), hence it is excluded in the DEA.” The mortality rate in the concept of DEA is an undesirable output that should be considered in the efficiency score of the hospitals. We would like to point out that the low mortality rate is very low in the sample of hospitals in our study, and it is rather homogeneous across the sample. If 99.2% of DMUs have no morality rate, then there is little difference in the output (mortality) and we cannot run the DEA regression for a reliable result. 6. S1 Table. Full result of DEA by country The authors only identify the returns to scale (RTS) status of hospitals without any interpretation. Why do all DMUs show constant RTS or increasing RTS? The authors must discuss this concept in detail. Thank you for your comments. We have added an explanation for the DEA results. Table S1 shows the efficiency score under the constant returns to scale, variable returns to scale, and the nonincreasing returns to scale. The Stata command also calculates the returns to scale (the last column of Table S1) by calculating the marginal productivity. If the marginal productivity equals to 1, it is IRS. If the marginal productivity equals to 0, it is CRS. All related outputs were shown in Table S1. The explanation about the marginal values has been added to the table note. Reviewer 2 This paper presents the application of data envelopment analysis (DEA) in the hospital ward. In fact, this paper investigates the determinants of hospital efficiency in district hospitals in three African countries. For this purpose, the initial DEA models (CCR, BCC) have been used. Here are some of my comments on the paper: 1) The DEA literature needs to be better articulated. References need to be updated. 2) Explain the reasons for choosing production indicators. Input factors must also be stated. 3) For better results, I suggest using the SBM-model as well Thank you for your comments. We have addressed them in the new version of the manuscript: 1) Except the reference of the methodology and command, other DEA related references are replaced by the new publications. 2) The production factors are the factors used in the PIPES index survey defined by an organisation name Surgeons Overseas. In order to compare the difference in using different measures for measuring production performance, these five production factors were included in the DEA regression. The output factor used in the DEA is the surgical volume, which is also widely used as an indicator of hospital performance. As we explained in the paper, the mortality rate is too low to include in the DEA. The surgical volume is the only output factor for which we have collected data. 3) The fitness and efficiency of the DEA model was considered when we prepared the manuscript. Due to the manuscript length requirement, it was not possible to provide all details. The comment set of weights (CSW) method was used to calculate the optimal input weights by setting the bounds of variables and improving nonlinearity. More details were shown in the Supporting Information. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0278212.r002
5 Oct 2022 Decision Letter - Majid Soleimani-damaneh, Editor PONE-D-22-07365R1Surgical capacity, productivity and efficiency at the district level in Sub-Saharan Africa: a three-country studyPLOS ONE Dear Dr. Zhang, 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 19 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. 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. 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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 Response) ****** 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: (No Response) ****** 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 incorporated some comments from the first round of review, but I am not convinced by the responses to the comments # 1 and # 4. Reviewer #2: The authors have considered all my points in the revised article, so I think the revised article can be accepted. ****** 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: Yes: Amin Mostafaee 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. 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Revision 2
26 Oct 2022 Author Response Reviewer 1 The authors have incorporated some comments from the first round of review, but I am not convinced by the responses to the comments # 1 and # 4. Thank you for your comments. Those two comments should be related to target units for inefficient DMUs and resources congestion. Responding to the first point, we would like to reiterate that this study aimed to compare the difference between hospital performance measures by examining the determinant of hospital efficiency using data envelopment analysis (DEA). To ensure consistency in the analyses, the production factors used in the PIPES capacity index were used in the DEA. We found that one reason the PIPES index and hospital efficiency presented almost opposite results was different weights assigned to the production factors. As what is shown in Table 5, the PIPES capacity index assigns higher weights to procedures, equipment and supplies that are less likely to be improved in a short time. DEA method weights infrastructure and personnel higher. As to the ‘target units for inefficient DMUs’, we think what the reviewer meant was the efficient hospital with DEA score equal to one. Table 4 compared the difference in each production factor between high-efficiency hospitals (DEA score=1) and low-efficiency hospitals (DEA score<1), which provided information about ‘the target unit for inefficient DMUs to learn’. However, surgical efficiency is different from production efficiency. According to the production theory, any input, such as capital, wage, and raw materials, can be divided by units and then change the amount of inputs to produce the final good most efficiently. Surgical capacity, in turn, is hard to change. In Table 4, low-efficiency hospitals had higher infrastructure, procedures, equipment, and supplies than efficient ones. In theory, these inputs should be reduced in production for higher efficiency. But in practice, it is almost impossible to reduce infrastructure, equipment or supplies, and advanced skills surgeons have learned. Therefore, the only one possible way is to increase the personnel, i.e. more surgeons, doctors, and NPCs, since low-efficiency hospitals have lower personnel than efficient ones. And training NPCs has been proven as a good way in the literature to improve the number of surgically trained cadres in settings such as our study. That is why the conclusion was that “… investment in the surgical workforce, in particular, plays a central role in improving district hospital surgical productivity and efficiency”. In response to the point about congestion, similar assumptions apply. Those district hospitals are the frontline providers of surgical services in rural areas. And Figure 3 illustrated that the performance results measured by efficiency score and surgical volume were similar. If more personnel can become the one input increased in those low-efficiency hospitals, then the slacks of other types of production factors will not be a restriction of efficiency but help to improve the output – providing more surgical services to rural populations. Reviewer 2 The authors have considered all my points in the revised article, so I think the revised article can be accepted. Thank you so much for your comments. Attachments Attachment Submitted filename: Response to Reviewers 2.docx https://doi.org/10.1371/journal.pone.0278212.r004
14 Nov 2022 Decision Letter - Majid Soleimani-damaneh, Editor Surgical capacity, productivity and efficiency at the district level in Sub-Saharan Africa: a three-country study PONE-D-22-07365R2 Dear Dr. Zhang, 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, Majid Soleimani-damaneh Academic Editor PLOS ONE Attachments Attachment Submitted filename: PONE.docx https://doi.org/10.1371/journal.pone.0278212.r005
Formally Accepted
18 Nov 2022 Acceptance Letter - Majid Soleimani-damaneh, Editor PONE-D-22-07365R2 Surgical capacity, productivity and efficiency at the district level in Sub-Saharan Africa: a three-country study Dear Dr. Zhang: 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. Majid Soleimani-damaneh Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0278212.r006

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