Essential emergency and critical care as a health system response to critical illness and the COVID19 pandemic: what does it cost?

Essential Emergency and Critical Care (EECC) is a novel approach to the care of critically ill patients, focusing on first-tier, effective, low-cost, life-saving care and designed to be feasible even in low-resourced and low-staffed settings. This is distinct from advanced critical care, usually conducted in ICUs with specialised staff, facilities and technologies. This paper estimates the incremental cost of EECC and advanced critical care for the planning of care for critically ill patients in Tanzania and Kenya.The incremental costing took a health systems perspective. A normative approach based on the ingredients defined through the recently published global consensus on EECC was used. The setting was a district hospital in which the patient is provided with the definitive care typically provided at that level for their condition. Quantification of resource use was based on COVID-19 as a tracer condition using clinical expertise. Local prices were used where available, and all costs were converted to USD2020.The costs per patient day of EECC is estimated to be 1 USD, 11 USD and 33 USD in Tanzania and 2 USD, 14 USD and 37 USD in Kenya, for moderate, severe and critical COVID-19 patients respectively. The cost per patient day of advanced critical care is estimated to be 13 USD and 294 USD in Tanzania and USD 17 USD and 345 USD in Kenya for severe and critical COVID-19 patients, respectively.EECC is a novel approach for providing the essential care to all critically ill patients. The low costs and lower tech approach inherent in delivering EECC mean that EECC could be provided to many and suggests that prioritizing EECC over ACC may be a rational approach when resources are limited.

Rapid Point-of-Care Testing for Genital Tract Inflammatory Cytokine Biomarkers to Diagnose Asymptomatic Sexually Transmitted Infections and Bacterial Vaginosis in Women: Cost Estimation and Budget Impact Analysis.

BACKGROUND: Screening for genital inflammation can reveal asymptomatic cases of sexually transmitted infections (STIs) and bacterial vaginosis (BV), useful in settings where only syndromic management is available. This study aimed to estimate the incremental cost of screening using a new cytokine biomarker rapid test and determine the budget impact of providing this service in primary health facilities in South Africa. METHODS: Costs of adding genital inflammation screening to existing family planning services were estimated for women (15-49 years) attending 3 different family planning clinics in US $2016. The predicted unit cost per patient screened from a provider's perspective was calculated using bottom-up and top-down approaches and was used to analyze the budget impact of scaling up and providing this service in primary health facilities countrywide. Univariate sensitivity analyses tested the robustness of the findings. RESULTS: The incremental cost per woman screened for genital inflammation ranged between US $3.19 and US $4.79. The scaled-up costs ranged between US $7,245,775 and US $22,212,636 countrywide, annually. This was based on the number of women of reproductive age currently seeking contraceptive care at all primary health care facilities, as a proxy for those most susceptible to asymptomatic STIs/BV. The cost estimates were sensitive to changes in personnel costs, utilization rate, and population coverage rates. CONCLUSIONS: This screening tool is likely to increase case detection, contributing to better STI/BV management and control, in addition to reducing women's risk of HIV acquisition. The incremental cost estimates could make implementation affordable.

Examining the unit costs of COVID-19 vaccine delivery in Kenya.

BACKGROUND: Vaccines are considered the path out of the COVID-19 pandemic. The government of Kenya is implementing a phased strategy to vaccinate the Kenyan population, initially targeting populations at high risk of severe disease and infection. We estimated the financial and economic unit costs of procuring and delivering the COVID-19 vaccine in Kenya across various vaccination strategies. METHODS: We used an activity-based costing approach to estimate the incremental costs of COVID-19 vaccine delivery, from a health systems perspective. Document reviews and key informant interviews(n = 12) were done to inform the activities, assumptions and the resources required. Unit prices were derived from document reviews or from market prices. Both financial and economic vaccine procurement costs per person vaccinated with 2-doses, and the vaccine delivery costs per person vaccinated with 2-doses were estimated and reported in 2021USD. RESULTS: The financial costs of vaccine procurement per person vaccinated with 2-doses ranged from $2.89-$13.09 in the 30% and 100% coverage levels respectively, however, the economic cost was $17.34 across all strategies. Financial vaccine delivery costs per person vaccinated with 2-doses, ranged from $4.28-$3.29 in the 30% and 100% coverage strategies: While the economic delivery costs were two to three times higher than the financial costs. The total procurement and delivery costs per person vaccinated with 2-doses ranged from $7.34-$16.47 for the financial costs and $29.7-$24.68 for the economic costs for the 30% and 100% coverage respectively. With the exception of procurement costs, the main cost driver of financial and economic delivery costs was supply chain costs (47-59%) and advocacy, communication and social mobilization (29-35%) respectively. CONCLUSION: This analysis presents cost estimates that can be used to inform local policy and may further inform parameters used in cost-effectiveness models. The results could potentially be adapted and adjusted to country-specific assumptions to enhance applicability in similar low-and middle-income settings.

Examining health facility financing in Kenya in the context of devolution.

BACKGROUND: How health facilities are financed affects their performance and health system goals. We examined how health facilities in the public sector are financed in Kenya, within the context of a devolved health system. METHODS: We carried out a cross-sectional study in five purposely selected counties in Kenya, using a mixed methods approach. We collected data using document reviews and in-depth interviews (no = 20). In each county, we interviewed county department of health managers and health facility managers from two and one purposely selected public hospitals and health center respectively. We analyzed qualitive data using thematic analysis and conducted descriptive analysis of quantitative data. RESULTS: Planning and budgeting: Planning and budgeting processes by hospitals and health centers were not standardized across counties. Budgets were not transparent and credible, but rather were regarded as "wish lists" since they did not translate to actual resources. Sources of funds: Public hospitals relied on user fees, while health centers relied on donor funds as their main sources of funding. Funding flows: Hospitals in four of the five study counties had no financial autonomy. Health centers in all study counties had financial autonomy. Flow of funds to hospitals and health centers in all study counties was characterized by unpredictability of amounts and timing. Health facility expenditure: Staff salaries accounted for over 80% of health facility expenditure. This crowded out other expenditure and led to frequent stock outs of essential health commodities. CONCLUSION: The national and county government should consider improving health facility financing in Kenya by 1) standardizing budgeting and planning processes, 2) transitioning public facility financing away from a reliance on user fees and donor funding 3) reforming public finance management laws and carry out political engagement to facilitate direct facility financing and financial autonomy of public hospitals, and 4) assess health facility resource needs to guide appropriate levels resource allocation.

Examining the implementation of the Linda Mama free maternity program in Kenya.

BACKGROUND: In 2013, Kenya introduced a free maternity policy in all public healthcare facilities. In 2016, the Ministry of Health shifted responsibility for the program, now called Linda Mama, to the National Hospital Insurance Fund (NHIF) and expanded access beyond public sector. This study aimed to examine the implementation of the Linda Mama program. METHODS: We conducted a mixed-methods cross-sectional study at the national level and in 20 purposively sampled facilities across five counties in Kenya. We collected data using in-depth interviews (n = 104), administered patient-exit questionnaires (n = 108), and carried out document reviews. Qualitative data were analysed using a framework approach while quantitative data were analysed descriptively. RESULTS: Linda Mama was designed and resulted in improved accountability and expand benefits. In practice however, beneficiaries did not access some services that were part of the revised benefit package. Second, out of pocket payments were still being incurred by beneficiaries. Health facilities in most counties had lost financial autonomy and had no access to reimbursements from NHIF for services provided; but those with financial autonomy were able to boost facility revenue and enhance service delivery. Further, fund disbursements from NHIF were characterised by delays and unpredictability. Implementation experiences reveal that there was inadequate communication, claim processing challenges and reimbursement rates were deemed insufficient. CONCLUSIONS: Our findings show that there are challenges associated with the implementation of the Linda Mama program and highlights the need for process evaluations for programs to track implementation, ensure continuous learning, and provide opportunities for course correcting programs' implementation.

Cost Effectiveness of Strategies for Caring for Critically Ill Patients with COVID-19 in Tanzania.

BACKGROUND: The resources for critical care are limited in many settings, exacerbating the significant morbidity and mortality associated with critical illness. Budget constraints can lead to choices between investing in advanced critical care (e.g. mechanical ventilators in intensive care units) or more basic critical care such as Essential Emergency and Critical Care (EECC; e.g. vital signs monitoring, oxygen therapy, and intravenous fluids). METHODS: We investigated the cost effectiveness of providing EECC and advanced critical care in Tanzania in comparison with providing 'no critical care' or 'district hospital-level critical care' using coronavirus disease 2019 (COVID-19) as a tracer condition. We developed an open-source Markov model ( https://github.com/EECCnetwork/POETIC_CEA ) to estimate costs and disability-adjusted life-years (DALYs) averted, using a provider perspective, a 28-day time horizon, patient outcomes obtained from an elicitation method involving a seven-member expert group, a normative costing study, and published literature. We performed a univariate and probabilistic sensitivity analysis to assess the robustness of our results. , RESULTS: EECC is cost effective 94% and 99% of the time when compared with no critical care (incremental cost-effectiveness ratio [ICER] $37 [-$9 to $790] per DALY averted) and district hospital-level critical care (ICER $14 [-$200 to $263] per DALY averted), respectively, relative to the lowest identified estimate of the willingness-to-pay threshold for Tanzania ($101 per DALY averted). Advanced critical care is cost effective 27% and 40% of the time, when compared with the no critical care or district hospital-level critical care scenarios, respectively. CONCLUSION: For settings where there is limited or no critical care delivery, implementation of EECC could be a highly cost-effective investment. It could reduce mortality and morbidity for critically ill COVID-19 patients, and its cost effectiveness falls within the range considered 'highly cost effective'. Further research is needed to explore the potential of EECC to generate even greater benefits and value for money when patients with diagnoses other than COVID-19 are accounted for.

The impact of COVID-19 on health financing in Kenya.

Sudden shocks to health systems, such as the COVID-19 pandemic may disrupt health system functions. Health system functions may also influence the health system's ability to deliver in the face of sudden shocks such as the COVID-19 pandemic. We examined the impact of COVID-19 on the health financing function in Kenya, and how specific health financing arrangements influenced the health systems capacity to deliver services during the COVID-19 pandemic.We conducted a cross-sectional study in three purposively selected counties in Kenya using a qualitative approach. We collected data using in-depth interviews (n = 56) and relevant document reviews. We interviewed national level health financing stakeholders, county department of health managers, health facility managers and COVID-19 healthcare workers. We analysed data using a framework approach. Purchasing arrangements: COVID-19 services were partially subsidized by the national government, exposing individuals to out-of-pocket costs given the high costs of these services. The National Health Insurance Fund (NHIF) adapted its enhanced scheme's benefit package targeting formal sector groups to include COVID-19 services but did not make any adaptations to its general scheme targeting the less well-off in society. This had potential equity implications. Public Finance Management (PFM) systems: Nationally, PFM processes were adaptable and partly flexible allowing shorter timelines for budget and procurement processes. At county level, PFM systems were partially flexible with some resource reallocation but maintained centralized purchasing arrangements. The flow of funds to counties and health facilities was delayed and the procurement processes were lengthy. Reproductive and child health services: Domestic and donor funds were reallocated towards the pandemic response resulting in postponement of program activities and affected family planning service delivery. Universal Health Coverage (UHC) plans: Prioritization of UHC related activities was negatively impacted due the shift of focus to the pandemic response. Contrarily the strategic investments in the health sector were found to be a beneficial approach in strengthening the health system. Strengthening health systems to improve their resilience to cope with public health emergencies requires substantial investment of financial and non-financial resources. Health financing arrangements are integral in determining the extent of adaptability, flexibility, and responsiveness of health system to COVID-19 and future pandemics.

The autonomy of public health facilities in decentralised contexts: insights from applying a complexity lens in Kenya.

The financing of public health facilities influences their performance. A key feature that defines health facility financing is the degree of financial autonomy. Understanding the factors that influence public health facility financial autonomy is pertinent to developing strategies to addressing challenges that arise from constrained autonomy. In this paper, we apply a complexity lens to draw on a body of research that we have conducted in Kenya over the past decade, from the onset of devolution reforms, to unpack the determinants of public health facility financial autonomy in a context of decentralisation and provide suggestions for pertinent considerations when designing interventions to address financial autonomy challenges. We find that the factors that affect public health facility autonomy are not only structural, but also procedural, and political and interact in complex ways. These factors include; the public finance management (PFM) laws, sense-making by actors in the health system, political interests in control over resources, subnational level PFM capacity, PFM implementation bottlenecks and broader operational autonomy. Drawing from this analysis, we recommend that efforts at resolving public health facility financial autonomy include: PFM capacity development for subnational levels of government in decentralised settings, the use of a political lens that recognises interests and seeks to align incentives in engagement and solution finding for health facility financial autonomy, the audit of PFM processes to establish and resolve implementation bottlenecks that impinge on public health facility autonomy, and the resolution of operational autonomy to as a facilitator of financial autonomy.

A Data-Driven Analysis of the Economic Cost of Non-Pharmaceutical Interventions: A Cross-Country Comparison of Kenya, Singapore, and Thailand.

Objective: To estimate the economic impact of border closure and social distancing by estimating the decline of gross domestic product (GDP) in Kenya, Singapore and Thailand. Methods: We analysed secondary data retrospectively. To calculate impact of NPIs on GDP, the relationship between GDP and stock market index was examined using ordinary least squares (OLS). Then, autoregressive and moving averages (ARMA) model was used to examine the impact of NPI on stock market index. The change in GDP due to NPIs was derived by multiplying coefficients of OLS and ARMA models. Results: An increase in stock market index correlated with an increase in GDP, while both social distancing and border closure negatively correlated with stock market index. Implementation of NPIs correlated with the decline in GDP. Thai border closure had a greater decline in GDP than social distancing; Kenya exhibited the same trends; Singapore had the opposite trend. Conclusion: We quantified the magnitude of economic impact of NPIs in terms of GDP decline by linking stock market index and GDP. This approach may be applicable in other settings.

Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya.

BACKGROUND: A few studies have assessed the epidemiological impact and the cost-effectiveness of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection. METHODS: We conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (>18 years) population prioritising roll-out in those over 50-years (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at US$7 per dose and vaccine delivery costs of US$3.90-US$6.11 per dose. The cost-effectiveness threshold was US$919.11. FINDINGS: Slow roll-out at 30% coverage largely targets those over 50 years and resulted in 54% fewer deaths (8132 (7914-8373)) than no vaccination and was cost saving (incremental cost-effectiveness ratio, ICER=US$-1343 (US$-1345 to US$-1341) per disability-adjusted life-year, DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757-872) and 5% (282 (251-317) but was not cost-effective, using Kenya's cost-effectiveness threshold (US$919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=US$-1607 (US$-1609 to US$-1604) per DALY averted) compared with slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective. INTERPRETATION: With prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective.

Impact of free maternity policies in Kenya: an interrupted time-series analysis.

BACKGROUND: User fees have been reported to limit access to services and increase inequities. As a result, Kenya introduced a free maternity policy in all public facilities in 2013. Subsequently in 2017, the policy was revised to the Linda Mama programme to expand access to private sector, expand the benefit package and change its management. METHODS: An interrupted time-series analysis on facility deliveries, antenatal care (ANC) and postnatal care (PNC) visits data between 2012 and 2019 was used to determine the effect of the two free maternity policies. These data were from 5419 public and 305 private and faith-based facilities across all counties, with data sourced from the health information system. A segmented negative binomial regression with seasonality accounted for, was used to determine the level (immediate) effect and trend (month-on-month) effect of the policies. RESULTS: The 2013 free-maternity policy led to a 19.6% and 28.9% level increase in normal deliveries and caesarean sections, respectively, in public facilities. There was also a 1.4% trend decrease in caesarean sections in public facilities. A level decrease followed by a trend increase in PNC visits was reported in public facilities. For private and faith-based facilities, there was a level decrease in caesarean sections and ANC visits followed by a trend increase in caeserean sections following the 2013 policy.Furthermore, the 2017 Linda Mama programme showed a level decrease then a trend increase in PNC visits and a 1.1% trend decrease in caesarean sections in public facilities. In private and faith-based facilities, there was a reported level decrease in normal deliveries and caesarean sections and a trend increase in caesarean sections. CONCLUSION: The free maternity policies show mixed effects in increasing access to maternal health services. Emphasis on other accessibility barriers and service delivery challenges alongside user fee removal policies should be addressed to realise maximum benefits in maternal health utilisation.

Modelling the cost-effectiveness of essential and advanced critical care for COVID-19 patients in Kenya.

BACKGROUND: Case management of symptomatic COVID-19 patients is a key health system intervention. The Kenyan government embarked to fill capacity gaps in essential and advanced critical care (ACC) needed for the management of severe and critical COVID-19. However, given scarce resources, gaps in both essential and ACC persist. This study assessed the cost-effectiveness of investments in essential and ACC to inform the prioritisation of investment decisions. METHODS: We employed a decision tree model to assess the incremental cost-effectiveness of investment in essential care (EC) and investment in both essential and ACC (EC +ACC) compared with current healthcare provision capacity (status quo) for COVID-19 patients in Kenya. We used a health system perspective, and an inpatient care episode time horizon. Cost data were obtained from primary empirical analysis while outcomes data were obtained from epidemiological model estimates. We used univariate and probabilistic sensitivity analysis to assess the robustness of the results. RESULTS: The status quo option is more costly and less effective compared with investment in EC and is thus dominated by the later. The incremental cost-effectiveness ratio of investment in essential and ACC (EC+ACC) was US$1378.21 per disability-adjusted life-year averted and hence not a cost-effective strategy when compared with Kenya's cost-effectiveness threshold (US$908). CONCLUSION: When the criterion of cost-effectiveness is considered, and within the context of resource scarcity, Kenya will achieve better value for money if it prioritises investments in EC before investments in ACC. This information on cost-effectiveness will however need to be considered as part of a multicriteria decision-making framework that uses a range of criteria that reflect societal values of the Kenyan society.

Examining unit costs for COVID-19 case management in Kenya.

INTRODUCTION: We estimated unit costs for COVID-19 case management for patients with asymptomatic, mild-to-moderate, severe and critical COVID-19 disease in Kenya. METHODS: We estimated per-day unit costs of COVID-19 case management for patients. We used a bottom-up approach to estimate full economic costs and adopted a health system perspective and patient episode of care as our time horizon. We obtained data on inputs and their quantities from data provided by three public COVID-19 treatment hospitals in Kenya and augmented this with guidelines. We obtained input prices from a recent costing survey of 20 hospitals in Kenya and from market prices for Kenya. RESULTS: Per-day, per-patient unit costs for asymptomatic patients and patients with mild-to-moderate COVID-19 disease under home-based care are 1993.01 Kenyan shilling (KES) (US$18.89) and 1995.17 KES (US$18.991), respectively. When these patients are managed in an isolation centre or hospital, the same unit costs for asymptomatic patients and patients with mild-to-moderate disease are 6717.74 KES (US$63.68) and 6719.90 KES (US$63.70), respectively. Per-day unit costs for patients with severe COVID-19 disease managed in general hospital wards and those with critical COVID-19 disease admitted in intensive care units are 13 137.07 KES (US$124.53) and 63 243.11 KES (US$599.51). CONCLUSION: COVID-19 case management costs are substantial, ranging between two and four times the average claims value reported by Kenya's public health insurer. Kenya will need to mobilise substantial resources and explore service delivery adaptations that will reduce unit costs.

Addressing Challenges in Health Technology Assessment Institutionalization for Furtherance of Universal Health Coverage Through South-South Knowledge Exchange: Lessons From Bhutan, Kenya, Thailand, and Zambia.

Health Technology Assessment (HTA), a tool for priority setting, has emerged as a means of ensuring the sustainability of a Universal Health Coverage (UHC) system. However, setting up an effective HTA system poses multiple challenges and knowledge exchange can play a crucial role in helping countries achieve their UHC targets. This article reports the results of the discussion during a preconference session at the 2019 HTAsiaLink Conference, an annual gathering of HTA agencies in Asia, which supports knowledge transfer and exchange among HTA practitioners. As part of this discourse, 3 main HTA challenges were identified based on experiences of selected countries in Asia and Africa, namely Bhutan, Kenya, Thailand, and Zambia: availability of funding, building technical capacity, and achieving buy-in among stakeholders for successful translation of HTA research into UHC policy. The potential solutions identified through this South-South engagement included establishing a legal mandate for HTA, building local technical capacity through partnerships and enhancing strategic communication with stakeholders to increase awareness, among others. South-South Knowledge Exchange can therefore be instrumental in sharing lessons learned from common challenges and offer potential solutions to address capacity building initiatives for HTA in LMICs.

Stark choices: exploring health sector costs of policy responses to COVID-19 in low-income and middle-income countries.

OBJECTIVES: COVID-19 has altered health sector capacity in low-income and middle-income countries (LMICs). Cost data to inform evidence-based priority setting are urgently needed. Consequently, in this paper, we calculate the full economic health sector costs of COVID-19 clinical management in 79 LMICs under different epidemiological scenarios. METHODS: We used country-specific epidemiological projections from a dynamic transmission model to determine number of cases, hospitalisations and deaths over 1 year under four mitigation scenarios. We defined the health sector response for three base LMICs through guidelines and expert opinion. We calculated costs through local resource use and price data and extrapolated costs across 79 LMICs. Lastly, we compared cost estimates against gross domestic product (GDP) and total annual health expenditure in 76 LMICs. RESULTS: COVID-19 clinical management costs vary greatly by country, ranging between <0.1%-12% of GDP and 0.4%-223% of total annual health expenditure (excluding out-of-pocket payments). Without mitigation policies, COVID-19 clinical management costs per capita range from US$43.39 to US$75.57; in 22 of 76 LMICs, these costs would surpass total annual health expenditure. In a scenario of stringent social distancing, costs per capita fall to US$1.10-US$1.32. CONCLUSIONS: We present the first dataset of COVID-19 clinical management costs across LMICs. These costs can be used to inform decision-making on priority setting. Our results show that COVID-19 clinical management costs in LMICs are substantial, even in scenarios of moderate social distancing. Low-income countries are particularly vulnerable and some will struggle to cope with almost any epidemiological scenario. The choices facing LMICs are likely to remain stark and emergency financial support will be needed.

A Systematic Review of Methodological Variation in Healthcare Provider Perspective Tuberculosis Costing Papers Conducted in Low- and Middle-Income Settings, Using An Intervention-Standardised Unit Cost Typology.

BACKGROUND: There is a need for easily accessible tuberculosis unit cost data, as well as an understanding of the variability of methods used and reporting standards of that data. OBJECTIVE: The aim of this systematic review was to descriptively review papers reporting tuberculosis unit costs from a healthcare provider perspective looking at methodological variation; to assess quality using a study quality rating system and machine learning to investigate the indicators of reporting quality; and to identify the data gaps to inform standardised tuberculosis unit cost collection and consistent principles for reporting going forward. METHODS: We searched grey and published literature in five sources and eight databases, respectively, using search terms linked to cost, tuberculosis and tuberculosis health services including tuberculosis treatment and prevention. For inclusion, the papers needed to contain empirical unit cost estimates for tuberculosis interventions from low- and middle-income countries, with reference years between 1990 and 2018. A total of 21,691 papers were found and screened in a phased manner. Data were extracted from the eligible papers into a detailed Microsoft Excel tool, extensively cleaned and analysed with R software (R Project, Vienna, Austria) using the user interface of RStudio. A study quality rating was applied to the reviewed papers based on the inclusion or omission of a selection of variables and their relative importance. Following this, machine learning using a recursive partitioning method was utilised to construct a classification tree to assess the reporting quality. RESULTS: This systematic review included 103 provider perspective papers with 627 unit costs (costs not presented here) for tuberculosis interventions among a total of 140 variables. The interventions covered were active, passive and intensified case finding; tuberculosis treatment; above-service costs; and tuberculosis prevention. Passive case finding is the detection of tuberculosis cases where individuals self-identify at health facilities; active case finding is detection of cases of those not in health facilities, such as through outreach; and intensified case finding is detection of cases in high-risk populations. There was heterogeneity in some of the reported methods used such cost allocation, amortisation and the use of top-down, bottom-up or mixed approaches to the costing. Uncertainty checking through sensitivity analysis was only reported on by half of the papers (54%), while purposive and convenience sampling was reported by 72% of papers. Machine learning indicated that reporting on 'Intervention' (in particular), 'Urbanicity' and 'Site Sampling', were the most likely indicators of quality of reporting. The largest data gap identified was for tuberculosis vaccination cost data, the Bacillus Calmette-Guérin (BCG) vaccine in particular. There is a gap in available unit costs for 12 of 30 high tuberculosis burden countries, as well as for the interventions of above-service costs, tuberculosis prevention, and active and intensified case finding. CONCLUSION: Variability in the methods and reporting used makes comparison difficult and makes it hard for decision makers to know which unit costs they can trust. The study quality rating system used in this review as well as the classification tree enable focus on specific reporting aspects that should improve variability and increase confidence in unit costs. Researchers should endeavour to be explicit and transparent in how they cost interventions following the principles as laid out in the Global Health Cost Consortium's Reference Case for Estimating the Costs of Global Health Services and Interventions, which in turn will lead to repeatability, comparability and enhanced learning from others.

Correction to: A Systematic Review of Methodological Variation in Healthcare Provider Perspective Tuberculosis Costing Papers Conducted in Low- and Middle-Income Settings, Using An Intervention-Standardised Unit Cost Typology.

In the original version of this article, Fig. 3 was published in an incorrect format. The correct figure is published with this correction.