Cost effectiveness of temporary isolation rooms in acute care settings in Singapore.

OBJECTIVES: To estimate the change to health service costs and health benefits from a decision to adopt temporary isolation rooms that are effective at isolating the patient within a general ward environment. We assess the cost-effectiveness of a decision to adopt an existing temporary isolation room in a Singapore setting.
METHOD: We performed a model-based cost-effectiveness analysis to evaluate the impact of a decision to adopt temporary isolation rooms for infection prevention. We estimated changes to the costs from implementation, the number of cases of healthcare associated infection, acute care bed days used, they money value of bed days, the number of deaths, and the expected change to life years. We report the probability that adoption was cost-effective by the cost by life year gained, against a relevant threshold. Uncertainty is addressed with probabilistic sensitivity analysis and the findings are tested with plausible scenarios for the effectiveness of the intervention.
RESULTS: We predict 478 fewer cases of HAI per 100,000 occupied bed days from a decision to adopt temporary isolation rooms. This will result in cost savings of $SGD329,432 and there are 1,754 life years gained. When the effectiveness of the intervention is set at 1% of cases of HAI prevented the incremental cost per life year saved is $16,519; below the threshold chosen for cost-effectiveness in Singapore.
CONCLUSIONS: We provide some evidence that adoption of a temporary isolation room is cost-effective for Singapore acute care hospitals. It is plausible that adoption is a positive decision for other countries in the region who may demonstrate fewer resources for infection prevention and control.

Introduction

Healthcare associated infections (HAIs) caused by multidrug resistant organisms (MDROs) are a major concern in hospitals globally [1]. These organisms include methicillin resistant Staphylococcus aureus (MRSA), multi-drug resistant non-fermenters, carbapenem-resistant Enterobacterales (CRE), vancomycin resistant Enterococci and Candida auris. MRSA is a major healthcare-associated pathogen that is endemic in many healthcare settings and is associated with worse health outcomes and economic costs [2, 3]. Emerging threats such as carbapenemase-producing carbapenem-resistant Enterobacterales (CP-CRE) and MCR-1-producing colistin-resistant Enterobacterales have the potential for rapid spread making it critically important for aggressive infection prevention and control measures [3, 4].

Well planned infection prevention and control strategies are critical in preventing MDRO associated HAIs. Singapore is a major travel hub with many people arriving each year to access health services. Decision makers have responded to the threat from MDRO transmission in its healthcare institutions using an extensive range of infection prevention strategies [5]. Universal active surveillance for MRSA and targeted screening for other pathogens play an important role, while detailed manual and non-touch environmental cleaning strategies minimise the risk of spread from surfaces and equipment. Limiting infection transmission through the isolation of patients is another important strategy. There are five specific transmission pathways that could be interrupted by the effective isolation of individuals: patient to healthcare worker (HCW); patient to environment; HCW to patient; environment to patient; and, environment to HCW [6].

Even though the rationale for isolation of patients colonised and or infected with MDROs is strong it appears impractical to provide permanent single-room isolation facilities for all MDRO colonised and/or infected patients in Singapore acute care hospitals. The majority of acute beds in Singapore public hospitals are in ‘Type B’ or ‘Type C’ wards that comprise 4, 6 or 8 beds. Only ICUs, ‘Type A’ wards and specialised isolation rooms are single room with adjoining bathroom and toilet. Temporary isolation spaces were however established for treating COVID-19 patients when the pandemic unfolded in Singapore [7].

We investigate a possible role for temporary ‘pop-up’ isolation rooms that are effective at isolating the patient within a general ward environment. For this paper we consider ‘Rediroom’ a mobile cart that unpacks into an air-filtered isolation room that offers the users hands-free entry [8]. Given that resources for infection control are finite [9] there is a need to identify whether a decision to add this intervention would be cost-effective [10] when compared to current infection prevention efforts.

The study question is by how much are ‘health services costs’ and ‘patient health benefits’ are expected to change from a decision to implement a temporary isolation room into acute care hospitals in Singapore. This will be cosidered in a framework for cost-effectivceness analysis [11]. The finding will be useful for those managing hospitals in Singapore with endemic MDROs, many with increasing incidence, and inadequate isolation capacity [12].

Methods

Target population, setting and outcome measures

The target population for this study are adult admissions to acute care hospitals in Singapore who face risk of health care acquired infection. The Singapore health system has 2.4 acute beds per 1,000 population in nine government supported hospitals, eight for-profit hospitals and one not-for-profit hospital [13]. Block funding by the government is accompanied by some out of pocket charges to patients, but when individuals are unable to pay there is a government financial safety net. Comprehensive specialist acute care services are available. We model outcomes in adult patients for healthcare associated sepsis, pneumonia, surgical site infection, central line associated blood stream infection (CLABSI), intra-abdominal infection and other types of HAI. Recent and high quality data are available for these events from the first Singapore national point prevalence survey [14].

The outcomes evaluated from a decision to adopt temporary isolation rooms are the changes to: number of patients with HAI; bed days used for HAI; monetary value of bed days used; number of deaths; and, number of discounted life years. These outcomes inform estimates of the change to ‘total health service costs’ and ‘life years’ from a decision to implement a temporary isolation room in the acute setting. Change to costs are divided by change to life years to show an incremental cost-effectiveness ratio [11]. All costs are for the financial year ending in March 2021.

Perspective and comparators

The cost perspective is the health service. We compare the adoption of a temporary isolation room to the existing arrangements for infection prevention. The National Infection Prevention Committee, a partnership between Singapore’s hospitals and the Ministry of Health sets national policies. They include the use of bedside alcohol-based hand rub, active surveillance for MRSA, vancomycin-resistant Enterococci and carbapenemase-producing carbapenem-resistant Enterobacterales, bundles for device care and surgical site infection, performance indicators, environmental cleaning protocols and non-touch technology. The time horizon for the analysis is 12 months so no discounting rate applies to costs, but health benefits measured in life years attract discounts of 3% per year [15]. Because the durations of HAI are relatively short the use of preference utility weights to show quality adjusted life year (QALYs) is unnecessary.

Measurement of effectiveness

There are no data to describe the real-world effectiveness of temporary isolation rooms and so scenarios are tested. We assume on average 30% of cases of healthcare associated infection will be avoided, which is consistent with previous studies [16, 17]. We also analyse effectiveness by reducing the estimate in the model until the decision to adopt is not supported against the criterion of cost effectiveness. We seek the minimum effectiveness at which adoption is supported against the criterion of cost-effectiveness.

Health outcomes and costs

Changes to health outcomes are characterised by the reduction in risk of mortality from avoiding a case of HAI. The data for attributable mortality for a case of HAI are from the first national point prevalence survey [14], Table 1.

Table 1

Hospital mortality outcomes for those with and without HAI.

Patient group	Died	Survived
All HAI (n = 469)	134	335
Sepsis (n = 142)	37	105
Pneumonia (n = 105)	45	60
Surgical (n = 115)	22	93
CLABSI (n = 40)	10	30
Intra-abdominal (n = 28)	18	10
Others (n = 39)	29	10
No HAI (n = 3,959)	550	3409

CLABSI = central line associated bloodstream infection

A one-proportion z-test enabled an estimate and 95% confidence interval of the probability of death for each type of HAI, see S1 Appendix. These are not adjusted for other factors that might affect risk of death. The costs of a bed day in the public system were taken from Singapore Ministry of Health [18], Table 2. The costs of adoption comprise a monthly capital cost plus a single-use canopy cost per patient, with the estimates used shown in Table 2. All costs are relevant for 2018.

Table 2

Input parameters for the cost-effectiveness model.

Parameter	Estimate (SD)	Prior Distribution	Source
Cases of HAIs per 10,000 admissions	1,598 (84)	Normal (1598, 84)	[14]
Average length of stay of all patients	6.4 (1.6)	Gamma (16.00, 0.40)	[19]
Probability of HAI type
Sepsis	0.30	Beta (135.58, 312.33)	[14]
Pneumonia	0.22	Beta (90.13, 312.44)
Surgical site infection	0.25	Beta (124.60, 383.54)
CLABSI	0.09	Beta (36.43, 390.73)
Intraabdominal	0.06	Beta (24.90, 392.25)
Others	0.08	Beta (35.47, 391.06)
Excess LOS of each HAI
Sepsis	0.89 (0.40)	Gamma (4.85, 0.18)	[20]
Pneumonia	3.14 (0.56)	Gamma (31.79, 0.10)
Surgical site infection	3.62 (0.64)	Gamma (31.94, 0.11)
CLABSI	2.99 (1.13)	Gamma (7.04, 0.42)
Intraabdominal	1.58 (1.01)	Gamma (42.48, 0.45)
Others	1.92 (0.93)	Gamma (4.28, 0.45)
Probability of death of each HAI
Sepsis	0.26	Beta (34.07, 96.70)	[14]
Pneumonia	0.43	Beta (41.90, 55.87)
Surgical site infection	0.19	Beta (19.77, 83.56)
CLABSI	0.25	Beta (8.76, 26.28)
Intraabdominal	0.36	Beta (9.06, 16.30)
Others	0.26	Beta (8.78, 25.46)
Probability of death in patients without HAI	0.14	Beta (537.18, 3329.53)
Cost per bed-day (in SGD)	823 (277)	Gamma (8.78, 93.77)	[18]
Cost of canopy per admission (in SGD)	975	Fixed	[21]
Capital cost of cart per month (in SGD)	1145	Fixed
Mean age of patients	67.6	Fixed	[14]
Male %	51.9	Fixed	[14]
Life expectancy years
Male	81.5	Fixed	[22]
Female	86.1	Fixed
% admissions isolated	4 to 10	Uniform	#, [23]
% effectiveness	0.30 (0.05)	Beta (24.9, 58.1)	Assumption

Other parameters

Age and gender distribution of the patients and the risks of HAI are taken from the recent prevalence survey [14], and the excess length of stays arising from a case of HAI are taken from a separate published analysis [20]. Life expectancy is taken from the Singapore census [22]. The proportion of admissions that could be isolated if the technology were adopted are the MRSA cases admitted into hospital not routinely isolated. Current infection prevention practices are to prioritise CP-CRE, VRE, C difficile, rotavirus, tuberculosis and other outbreak prone or high impact diseases and these patients once identified are always isolated.

Dealing with uncertainty, threshold for cost-effectiveness and model evaluation

Uncertain parameters are characterised by prior statistical distributions and some values are fixed. All parameters are subject to 10,000 random samples to produce output distributions for the model outcomes. The threshold for cost-effectiveness was the mean GDP per capita, which is USD $59,798 or approximately SGD $80,000 [17]. This approach assumes one year of perfect quality life is worth the per capita gross domestic product [18]. We report the ‘probability that an adoption decision is cost-effective’ [24] and values for this statistic that exceed 50% suggest adoption is a better decision than remaining with current arrangements, yet values close to 50% imply large uncertainty in the decision and more information may be required prior to an implementation decision being made [25].

Scenario analyses

The attributable mortality is unadjusted for other factors that can affect mortality. To investigate the robustness of the model conclusions to this parameter we halve the estimates of attributable mortality, reducing the health benefits from a decision to adopt, and re-examine the findings. A CHEERS checklist has been completed and included as an appendix.

Results

The expected changes to the outcomes from a decision to adopt a temporary isolation room at an assumed effectiveness of 30% reduction in cases are shown in Table 3. On average there will be 478 fewer cases of HAI per 100,000 occupied bed days from a decision to adopt a temporary isolation room. This will release 1,627 bed-days for other uses, and these are valued at SGD$1.33M in savings. One hundred and thirty-six lives will be saved and 1,754 life years gained.

Table 3

Changes to outcomes from a decision to adopt a temporary isolation rooms, per 100,000 occupied bed days.

Mean (sd)	Cases HAI	bed days	Money value of bed days (SGD)	number of deaths	life years
ALL HAI	478 (83)	1627 (338)	$1,325,570 ($548,774)	136 (26)	1754 (333)
Sepsis	145 (27)	127 (64)	$104,330 ($67,669)	38 (9)	483 (114)
Pneumonia	107 (22)	342 (91)	$280,396 ($126,657)	46 (11)	591 (140)
Surgical	117 (22)	414 (108)	$336,915 ($149,410)	22 (6)	289 (79)
CLABSI	41 (10)	121 (55)	$98,173 ($56,511)	10 (4)	132 (49)
Intra-abdominal	28 (7)	547 (168)	$442,796 ($212,695)	10 (4)	130 (49)
Others	40 (21)	76 (57)	$62,958 ($55,843)	10 (6)	130 (79)

CLABSI = central line associated bloodstream infection

The joint distribution of expected change ‘total costs’ and ‘life years’ gained is shown in Fig 1. The mean change to total costs is -$SGD329,432, indicating overall that the cost savings from fewer cases HAI exceed the implementation costs. For this cost saving there are 1,754 life years gained. There is a 67% probability that adoption will be cost saving and 100% probability it will be cost-effective against the threshold value of $SGD80,000 per life year gained.

Fig 1

Joint distribution of the expected change to total costs and health benefits from a decision to adopt temporary isolation rooms, per 100,000 occupied bed days.

The lowest possible value for the effectiveness of the intervention is that 1% of cases of HAI are prevented; the impact of this assumption on the results are shown in Table 4. On average there will be 16 fewer cases of HAI per 100,000 occupied bed days, 54 bed-days are released for other uses, 4.57 lives will be saved and 59 life years gained. The mean change to total costs is $968,967 for a return of 59 years of life. The incremental cost per life year saved is $16,519. There is a zero probability that adoption will be cost saving but a 100% probability that adoption will be cost effective. When mortality benefits are additionally halved the ICER increases to $33,190 per life year gained and the probability that adoption is cost effective remains at 100%. For these scenarios the conclusion is that adoption is a cost-effective decision.

Table 4

Changes to outcomes with 1% effectiveness used.

Mean (sd)	Cases HAI	bed days	Money value of bed days (SGD)	number of deaths	life years
ALL HAI	16 (1)	54 (7)	$44,518 ($16,022)	4.57 (0.43)	59 (6)
Sepsis	5 (0)	4 (2)	$3,488 ($2,117)	1.26 (0.22)	16 (3)
Pneumonia	4 (0)	11 (2)	$9,329 ($3,728)	1.53 (0.24)	20 (3)
Surgical	4 (0)	14 (3)	$11,297 ($4,433)	0.75 (0.17)	10 (2)
CLABSI	1 (0)	4 (2)	$3,293 ($1,781)	0.34 (0.12)	4 (1)
Intraabdominal	1 (0)	18 (5)	$14,976 ($6,443)	0.34 (0.11)	4 (1)
Others	1 (1)	3 (2)	$2,134 ($1,798)	0.34 (0.20)	4 (3)

CLABSI = central line associated bloodstream infection

Discussion

The findings reveal the adoption of a temporary ‘pop-up’ isolation room only needs to reduce the cases of healthcare acquired infection by 1% to be a cost-effective decision in Singapore public hospitals. It is likely that the real world effectiveness will exceed this, and so the economic benefits will likely be larger. If adoption achieves a 30% reduction in cases, the expectation is that health services costs would reduce by approximately $330,000 per 100,000 bed days, and there would be many lives saved and substantial health benefits. Who actually enjoys the benefit from the cost savings will depend on the funding model of the hospital and the country, but it is likely that hospitals, government funders and patients themselves would benefit.

A strength of this study is that we included a full economic evaluation for a potentially important technology, which considered both the costs to hospitals and health benefits to patients, and quantified and presented the value of an adoption decision with transparency. This contrasts the majority of the infection prevention and control economic evaluations published in literature, which are often partial evaluations of only hospitalisation costs [26]. While we only compared the decision to adopt to ‘existing practices’, our analyses can be expanded to additionally consider other novel infection prevention and measures.

This study is based on assumptions applied to a model which has limitations compared to a prospective, pragmatic randomised trial. Yet this design would be impossible to blind and complex and slow to implement. Furthermore the time taken would possibly realise opportunity costs in lost savings and lost health gains [27]. In this study we did not consider other factors which could affect implementation. It is possible that there could be a net loss of total beds in a shared cubicle where the typical distance between beds is 1.5 metres. User acceptability will also impact the success of a strategy featuring temporary isolation rooms which must be aesthetically appropriate, comfortable, functional and not associated with stigma. The rooms need to work within nursing workflows, allied health, medical and portering requirements. The advantages of temporary ‘pop-up’ isolation room as compared to making permanent building reconfigurations are most likely related to costs and speed of deployment.

The quality of the data used for the model parameters is good, with the data gathered for the first national prevalence survey [14] utilised for this analysis. The excess length of stay parameters were estimated using a state-based model that appropriately includes the timing of key events of HAI, death and discharge from hospital [20]. A recent review found analyses that use time fixed methods for the estimation of these outcomes generate biased, inflated, outcomes [28]. The estimates of excess mortality due to infection are naïve as they were not adjusted for other known factors associated with increased mortality. For instance, patients who die with an infection are likely older, with more severe disease and more comorbidities compared to those without HAIs. To address this, we conducted a scenario analysis that halved the probability of death, which in effect halved the health benefits estimated by the model, and found that our conclusions regarding cost-effectiveness were maintained.

As our analyses were robust to uncertainty arising from model parameters and to plausible scenarios, we conclude that our study provides some evidence that the that the adoption of a temporary ‘pop-up’ isolation room is likely to be cost-effective to Singapore public acute care hospitals, and may potentially result in reduction of healthcare costs. It is plausible that adoption of this technology is a good decision for other countries in the region, where infection prevention infrastructure is less developed and unlikely to advance in the short or medium term.

CHEERS 2022 checklist.

(DOCX)

Click here for additional data file.

(DOCX)

Click here for additional data file.

24 May 2022

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,

Monika Pogorzelska-Maziarz

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

2. Thank you for stating the following financial disclosure:

[No grant funding was used for this project. NG was paid consulting fees by GAMA Healthcare to develop a model and prepare a first draft of the manuscript.]

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

c) If any authors received a salary from any of your funders, please state which authors and which funders.

d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3. Thank you for stating the following in the Competing Interests section:

[Martin Kiernan is clinical director for GAMA Healthcare.]

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

4. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

5. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ.

[Note: HTML markup is below. 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: Partly

Reviewer #3: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: No

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). 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

Reviewer #3: Yes

**********

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

Reviewer #3: 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 paper is well written. The data analysis for cost effectiveness is appropriate. However, the analyses was mainly based on the hypothesis to reduce HAIs at 30% from the previous studies and the cost was based on the retrospective data, which leads to the lack of reality.

Reviewer #2: The paper analyzes the cost-effectiveness of a decision to adopt temporary isolation rooms in acute care settings in Asia. The paper is technically sound using publicly available data and seeking to offer an alternative low-cost strategy for managing healthcare-associated infections, but not without some infractions. To improve the manuscript for publication, the authors must resolve the following:

1. Title and Abstract

The title suggests a broader spatial context, but the analysis is limited to one country Singapore and not Asia in general, as portrayed in the title. Compare sentence lines 3 and 4 of the abstract to the title.

The method in the abstract should be re-written for clarity. For example, we performed a model-based cost-effectiveness analysis to evaluate ………………. Outcome measures include……………….. OR We measured outcome XXX by doing ABCD and outcome XXX2 by doing MNOP. Etc.

Again, the conclusion that the intervention is cost-effective for Singapore acute care hospitals is misleading because Figure 1 shows that the cost per life-year gain with the intervention may be positive or negative. Thus, about a 50% chance of cost-saving, meaning the intervention is not a dominant strategy.

2. Methodology

In Table 1, the HAI cases reported were inconsistent with the figures documented in citation No.14. Moreso same reference did not categorically state the number of survival and deaths attributable to HAIs as referenced in Table 1 of the manuscript. Since this paper is a model-based paper, one will expect that the cited reference reports the cited baseline figures, and where they are not, provide an explanation for clarity. For instance, the supplementary file attached to the published citation clarified how the paper authors measured some variables but not for mortality attributable to HAI. (Check Table 2 of citation No.14 to resolve the inconsistencies or provide an explanation for clarity).

The authors decided to limit the study horizon to 1 year and attributed the same for not using a preference utility weight to show QALY. In my opinion, it is the author’s discretion not to expand the study horizon, but to attribute the same for not doing additional analysis is misplaced.

3. Scenario analysis.

“The attributable mortality is unadjusted for other factors that can affect mortality”. The authors believed by halving the estimated HAI-attributable mortality, they have ensured robustness, how? They should provide a reference to justify that statement. In the first place, I did not find the mortality figures in the referenced citation used in Table 1 and the explanation of how HAI mortality was arrived at should be provided.

No mention of heterogeneity characterization. It is obvious that the study subjects vary by type of HAIs with different baseline characteristics or observed variabilities which may affect the study conclusion. An aggregated probability risk of HAIs and mortality with 95% uncertainty intervals should be explored in a deterministic sensitivity analysis (DSA) and the result presented in a Tornado graph to offer more explanation.

At baseline, I assume the mean cost per bed day of SDG 823 is an aggregated mean for all the reported HAI cases (Table 2). How about exploring the HAI case-specific mean cost in the scenario analysis to show which contributes more to the cost of HAIs and consequently the cost savings per LYG? I think the same may apply to the length of stay. Obviously, the mean cost of managing surgical site infection is different from the mean cost of managing either CLABSI, Sepsis, etc.

An alternative will be to collapse Table 2 and present only the aggregated mean parameter values, i.e., Mean cost of HAIs, LOS, risk of HAI, etc. with their 95%CI explored in a scenario analysis.

4. Results and discussion

It is the norm that all parameter values, especially those contributing significantly to the study outcome should be captured in the result and discussion section under both scenarios.

Limiting the cost to only the provider perspective results in underestimation of the potential cost associated with HAIs and this must be discussed. In paragraph two of the discussion, the authors align the strength of their paper to doing a full economic evaluation. The statement is not true because the study perspective is limited, and the methodology is not rigorous enough.

5. General comment

The use of study reporting guidelines is highly recommended for quality reporting assurance. In this case, following the CHEERS checklist is a better way to improve the methodology, results, and discussion sections, and it must be stated clearly in the methods the reporting guideline used in this study.

Reference list No 17 is incomplete and others must be checked for proper formatting.

The title of Table 1 should be checked for type error “with and with HAI”

Also, resolve the formatting of the Abstract and figure in line with the Journal requirements.

Reviewer #3: This is a good piece of work that is more relevant to the current resource management of many countries. Most of the countries prepared temporary isolation rooms in their hospitals to isolate COVID 19 patients. Therefore this is a good idea to reduce cost of managing hospital acquired infections using these temporary isolation rooms. At the same time this cost effectiveness study is a technically sound study . Therefore this is a valuable timely performed study.

**********

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: No

Reviewer #2: No

Reviewer #3: 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.

23 Jun 2022

Thanks for the opportunity to respond to the reviewers comments

++++++++

Thank you for stating the following financial disclosure:

“No grant funding was used for this project. NG was paid consulting fees by GAMA Healthcare to develop a model and prepare a first draft of the manuscript”

Response 1. Here is an amended statement. No grant funding was used for this project. NG was paid consulting fees by GAMA Healthcare to develop a model and prepare a first draft of the manuscript. Martin Kiernan supported many aspects of the study and write up, but he did this without bias and focused on the best interpretation of the data. No other individual from GAMA healthcare influenced the study methods, findings or interpretation.

Thank you for stating the following in the Competing Interests section:

Martin Kiernan is clinical director for GAMA Healthcare.

Response 2. Here is an amended competing interest statement. Martin Kiernan is clinical director for GAMA Healthcare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

Response 3. Here is an amended statement. “All the data used in the study are reported in the manuscript in summary form. The raw HAI PPS surveillance data are not available for public sharing due to privacy considerations.”

5. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016.

Response 4. My orcid ID is assigned to n.graves@qut.edu.au (an old email address). I cannot reassign it to n.graves@duke-nus.edu.sg. Can you help?

Reviewer #1: The paper is well written. The data analysis for cost effectiveness is appropriate. However, the analyses was mainly based on the hypothesis to reduce HAIs at 30% from the previous studies and the cost was based on the retrospective data, which leads to the lack of reality.

Response 5. In addition to assuming 30% of cases of healthcare associated infection will be avoided, we analysed effectiveness by reducing the estimate in the model until the decision to adopt is not supported against the criterion of cost effectiveness. We found the adoption of a temporary ‘pop-up’ isolation room only needs to reduce the cases of healthcare acquired infection by 1% to be a cost-effective decision in Singapore public hospitals.

Reviewer #2: The paper analyzes the cost-effectiveness of a decision to adopt temporary isolation rooms in acute care settings in Asia. The paper is technically sound using publicly available data and seeking to offer an alternative low-cost strategy for managing healthcare-associated infections, but not without some infractions. To improve the manuscript for publication, the authors must resolve the following:

1. Title and Abstract

The title suggests a broader spatial context, but the analysis is limited to one country Singapore and not Asia in general, as portrayed in the title. Compare sentence lines 3 and 4 of the abstract to the title.

Response 6. The title has been changed to this. “Cost Effectiveness of Temporary Isolation Rooms in Acute Care Settings in Singapore”

The method in the abstract should be re-written for clarity. For example, we performed a model-based cost-effectiveness analysis to evaluate ………………. Outcome measures include……………….. OR We measured outcome XXX by doing ABCD and outcome XXX2 by doing MNOP. Etc.

Response 7. The methods section in the abstract has been changed. “We performed a model-based cost-effectiveness analysis to evaluate the impact of a decision to adopt temporary isolation rooms for infection prevention. We estimated changes to the costs from implementation, the number of cases of healthcare associated infection, acute care bed days used, they money value of bed days, the number of deaths, and the expected change to life years. We report the probability that adoption was cost-effective by the cost by life year gained, against a relevant threshold.”

Again, the conclusion that the intervention is cost-effective for Singapore acute care hospitals is misleading because Figure 1 shows that the cost per life-year gain with the intervention may be positive or negative. Thus, about a 50% chance of cost-saving, meaning the intervention is not a dominant strategy.

Response 8. Figure 1 reveals a 100% probability that adoption will be cost effectiveness against a threshold of $SGD80,000 per life year gained. It also reveals a 67% probability that adoption will be cost savings and health increasing. The probability that non-adopting is cost effective is zero.

2. Methodology

In Table 1, the HAI cases reported were inconsistent with the figures documented in citation No.14. More so same reference did not categorically state the number of survival and deaths attributable to HAIs as referenced in Table 1 of the manuscript. Since this paper is a model-based paper, one will expect that the cited reference reports the cited baseline figures, and where they are not, provide an explanation for clarity.

Response 9. The information in Table 1 are reported for the first time. Although collected for the purposes of the prevalence survey - cite [14] - they were not reported in that paper.

For instance, the supplementary file attached to the published citation clarified how the paper authors measured some variables but not for mortality attributable to HAI. (Check Table 2 of citation No.14 to resolve the inconsistencies or provide an explanation for clarity).

Response 10. The appendix in this manuscript is an example of the R script and output used to estimate attributable mortality. It simply shows the method used to estimate attributable mortality. This is the first time this information has been reported, it was not included in cite [14]

The authors decided to limit the study horizon to 1 year and attributed the same for not using a preference utility weight to show QALY. In my opinion, it is the author’s discretion not to expand the study horizon, but to attribute the same for not doing additional analysis is misplaced.

Response 11. As HAI is a relative short duration event (10 to 14 days) we feel 12 months is adequate to capture the consequences. Weighting outcomes by preference based utility scores would not change the conclusions, because the duration of the illness is so short. QALYs and utility weights are more informative for chronic diseases that take years to resolve.

3. Scenario analysis.

“The attributable mortality is unadjusted for other factors that can affect mortality”. The authors believed by halving the estimated HAI-attributable mortality, they have ensured robustness, how? They should provide a reference to justify that statement.

Response 12. All the health benefits arise from mortality avoided from fewer cases of HAI. We suggest the mortality benefits might be overstated somewhat because the attributable mortality is unadjusted for other factors that can affect mortality. We are unable to obtain adjusted estimates, so we took the pragmatic decision to reduce mortality benefits dramatically - by 50% - and test whether the conclusions still supported adoption; and they do. We are fairly certain that the real mortality benefits lie between the baseline estimates and the 50% estimate. Thus we are comfortable our results are robust.

In the first place, I did not find the mortality figures in the referenced citation used in Table 1 and the explanation of how HAI mortality was arrived at should be provided.

Response 13. See Response 9.

No mention of heterogeneity characterization. It is obvious that the study subjects vary by type of HAIs with different baseline characteristics or observed variabilities which may affect the study conclusion. An aggregated probability risk of HAIs and mortality with 95% uncertainty intervals should be explored in a deterministic sensitivity analysis (DSA) and the result presented in a Tornado graph to offer more explanation.

Response 14. We have modelled patients based on the type of HAI they acquired and the model accounts for this by applying different costs, excess stays and risks of mortality. We prefer to report a probabilistic sensitivity analyses that captures all the parameter uncertainties simultaneously; this approach is more useful and more informative for decision making that using fixed value sensitivity analysis and the associated tornado graphs. Fig 1 provides a lot more information that we might glean from a tornado graph. Probabilistic sensitivity analyses is recommended by the CHEERS checklist.

At baseline, I assume the mean cost per bed day of SDG 823 is an aggregated mean for all the reported HAI cases (Table 2). How about exploring the HAI case-specific mean cost in the scenario analysis to show which contributes more to the cost of HAIs and consequently the cost savings per LYG? I think the same may apply to the length of stay. Obviously, the mean cost of managing surgical site infection is different from the mean cost of managing either CLABSI, Sepsis, etc.

Response 15. The cost per bed day of 823 is the mean costs or providing an acute bed day in the Singapore healthcare system. The costs of HAI are shown by multiplying the Excess LOS for each HAI - see Table 2 -with this estimate.

An alternative will be to collapse Table 2 and present only the aggregated mean parameter values, i.e., Mean cost of HAIs, LOS, risk of HAI, etc. with their 95%CI explored in a scenario analysis.

Response 16. I believe Table 2 is appropriate for this study. It shows the values used and distributions for all the model parameters.

4. Results and discussion

It is the norm that all parameter values, especially those contributing significantly to the study outcome should be captured in the result and discussion section under both scenarios.

Response 17. All parameter values used to generate the results are reported in Table 2.

Limiting the cost to only the provider perspective results in underestimation of the potential cost associated with HAIs and this must be discussed. In paragraph two of the discussion, the authors align the strength of their paper to doing a full economic evaluation. The statement is not true because the study perspective is limited, and the methodology is not rigorous enough.

Response 18. Using a broader perspective will add weight to the already strong conclusions. We see limited value to adding in costs for primary care services or even production losses. It would make the paper bulkier and would only re-enforce the cost-effectiveness result by making the cost savings greater. We believe the methods we report are appropriate and rigorous for the stated research question.

5. General comment

The use of study reporting guidelines is highly recommended for quality reporting assurance. In this case, following the CHEERS checklist is a better way to improve the methodology, results, and discussion sections, and it must be stated clearly in the methods the reporting guideline used in this study.

Response 19. A CHEERS checklist has been completed. This text has been added to the methods. “A CHEERS checklist has been completed and included as an appendix.”

Reference list No 17 is incomplete and others must be checked for proper formatting.

Response 20. References have been checked and updated

The title of Table 1 should be checked for type error “with and with HAI”

Response 21. This has been fixed.

Also, resolve the formatting of the Abstract and figure in line with the Journal requirements.

Response 22. The abstract meets journal requirements

Reviewer #3: This is a good piece of work that is more relevant to the current resource management of many countries. Most of the countries prepared temporary isolation rooms in their hospitals to isolate COVID 19 patients. Therefore this is a good idea to reduce cost of managing hospital acquired infections using these temporary isolation rooms. At the same time this cost effectiveness study is a technically sound study . Therefore this is a valuable timely performed study

Submitted filename: response.docx

Click here for additional data file.

7 Jul 2022

Cost Effectiveness of Temporary Isolation Rooms in Acute Care Settings in Singapore

PONE-D-22-11005R1

Dear Dr. Graves,

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,

Monika Pogorzelska-Maziarz

Academic Editor

PLOS ONE

13 Jul 2022

PONE-D-22-11005R1

Cost Effectiveness of Temporary Isolation Rooms in Acute Care Settings in Singapore

Dear Dr. Graves:

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. Monika Pogorzelska-Maziarz

Academic Editor

PLOS ONE