key: cord-0777305-0xcecw0o authors: Cleary, S. M.; Wilkinson, T.; Tamandjou Tchuem, C.; Docrat, S.; Solanki, G. title: Cost-effectiveness of intensive care for hospitalized Covid-19 patients: experience from South Africa date: 2020-11-03 journal: nan DOI: 10.1101/2020.10.30.20222802 sha: c033ef181693488076f38a1baf37d2d494ecd4ea doc_id: 777305 cord_uid: 0xcecw0o Background: Amidst the shortages of critical care resources in the public sector resulting from the COVID-19 pandemic, the South African Government embarked on an initiative to purchase critical bed capacity from the private sector. Within an already under-funded public health sector, it is imperative that the costs and effects of potential interventions to care are assessed and weighed against the opportunity costs of their required investment. Objective: To assess the cost-effectiveness of ICU management for admitted COVID-19 patients across the public and private health sector in South Africa. Methods: Using a Markov modelling framework and a health system perspective, the costs and health outcomes of inpatient management of severe and critical COVID-19 patients in (1) general ward and intensive care (GW+ICU) and (2) general ward only were assessed. Disability adjusted life years (DALYs) were evaluated as health outcomes, and the cost per admission from public and private sectors was determined. The models made use of four variables: mortality rates, utilisation of inpatient days for each management approach, disability weights associated to the severity of the disease, and the unit cost per general ward day and per ICU day in public and private hospitals. The unit costs were multiplied by utilisation estimates to determine the cost per admission. DALYs were calculated as the sum of years of life lost (YLL) and years lived with disability (YLD). An incremental cost-effectiveness ratio (ICER) - representing the difference in costs and health outcomes of the two management strategies - was calculated and compared to a cost-effectiveness threshold to determine the value for money of ICU management. Results: A cost per admission of ZAR 75,127 was estimated for inpatient management of severe and critical COVID-19 patients in general wards only as opposed to ZAR 103,030 in GW+ICU. DALYs were 1.48 and 1.10 in the general ward only and GW+ICU, respectively. The ratio of difference in costs and health outcomes between the two management strategies produced an ICER equal to ZAR 73 091 per DALY averted, a value above the cost-effectiveness threshold of ZAR 38 465. Conclusions: This study indicated that purchasing additional ICU capacity from the private sector may not be a cost-effective use of limited health resources. The real time, rapid, pragmatic, and transparent nature of this analysis demonstrates a potential approach for further evidence generation for decision making relating to the COVID-19 pandemic response and the wider priority setting agenda in South Africa. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020. 10.30.20222802 doi: medRxiv preprint . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Abstract Background: Amidst the shortages of critical care resources in the public sector resulting from the COVID-19 pandemic, the South African Government embarked on an initiative to purchase critical bed capacity from the private sector. Within an already under-funded public health sector, it is imperative that the costs and effects of potential interventions to care are assessed and weighed against the opportunity costs of their required investment. Objective: To assess the cost-effectiveness of ICU management for admitted COVID-19 patients across the public and private health sector in South Africa. Methods: Using a Markov modelling framework and a health system perspective, the costs and health outcomes of inpatient management of severe and critical COVID-19 patients in (1) general ward and intensive care (GW+ICU) and (2) general ward only were assessed. Disability adjusted life years (DALYs) were evaluated as health outcomes, and the cost per admission from public and private sectors was determined. The models made use of four variables: mortality rates, utilisation of inpatient days for each management approach, disability weights associated to the severity of the disease, and the unit cost per general ward day and per ICU day in public and private hospitals. The unit costs were multiplied by utilisation estimates to determine the cost per admission. DALYs were calculated as the sum of years of life lost (YLL) and years lived with disability (YLD). An incremental cost-effectiveness ratio (ICER) -representing the difference in costs and health outcomes of the two management strategieswas calculated and compared to a cost-effectiveness threshold to determine the value for money of ICU management. A cost per admission of ZAR 75,127 was estimated for inpatient management of severe and critical COVID-19 patients in general wards only as opposed to ZAR 103,030 in GW+ICU. DALYs were 1.48 and 1.10 in the general ward only and GW+ICU, respectively. The ratio of difference in costs and health outcomes between the two management strategies produced an ICER equal to ZAR 73 091 per DALY averted, a value above the costeffectiveness threshold of ZAR 38 465. Conclusions: This study indicated that purchasing additional ICU capacity from the private sector may not be a cost-effective use of limited health resources. The 'real time', rapid, pragmatic, and transparent nature of this analysis demonstrates a potential approach for further . CC-BY-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020.10.30.20222802 doi: medRxiv preprint The COVID-19 pandemic has intensified demands on the health care system and resulted in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the South African public sector. A major area of concern, globally and in South Africa, was the sufficiency of ICU capacity for the management of critically ill COVID-19 patients. Against an ICU bed availability of 3,318 (1,178 public and 2,140 private), the South African Portfolio Committee on Health highlighted a shortfall in ICU beds in the country; where the peak daily demand for ICU beds was projected to be between 4,100 beds (optimistic scenario) and 14,767 (pessimistic scenario). Intensive care services are very expensive and are one of the largest drivers of hospital costs, even in public hospitals where the cost per patient per ICU day has been estimated at R22,700. [2] Discovery Health, the largest medical scheme in the country, at the time reported that the average cost of all COVID-19 hospital admissions across its members was R84,708. The average cost of an ICU admission for its members was substantially higher -at R169,525 -and these admissions were also reported to have the "highest variation in cost". [3] Overprovision of ICU beds and subsequent cost escalation through potentially inappropriate use in the private sector was a key finding of the recent Competition Commission Health Market Inquiry. [4] There are a range of health care interventions to manage the progression of the COVID-19 pandemic. Amongst others, resources are required to carry out education, screening, testing, isolation and contact tracing programs, provision of personal protective equipment (PPE) to health workers, treatment in general/high care wards; and in the most critical cases, treatment in ICU. Given the expected downturn in an already weak economy [5] is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020.10.30.20222802 doi: medRxiv preprint efficiently, and that the costs and effects of potential interventions and approaches to care are assessed and weighed against the opportunity costs of their required investment. Traditional economic evaluations can be time consuming with lengthy turnaround times. The rapid pace at which the pandemic unfolded and the imperative it created for policy decisions to be made quickly required the turnaround times for research and analysis informing policy to be shortened substantially. The objective of this study was to assess the cost-effectiveness of ICU management for admitted COVID-19 patients across the public and private health sector in South Africa using a "real time", pragmatic and transparent health economic modelling approach. MOSAIC, a health economic modelling collective established to respond to the need for prompt policy guidance for the South African response to COVID-19, carried out this costutility/effectiveness analysis of ICU care. The study was conducted using the principles of the International Decision Support Initiative Reference Case for economic evaluation. [6] is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. ; https://doi.org/10.1101/2020.10.30.20222802 doi: medRxiv preprint productivity of the public health system in South Africa. [7] If the ICER is lower than the defined CET then the marginal opportunity cost of the treatment strategy (in terms of lost health) is expected to be lower than the health benefits of the treatment strategy, indicating that the treatment strategy is likely to represent a cost-effective use of limited resources. [6] The time horizon for the analysis was from admission to discharge or death; while estimates of ongoing morbidity post discharge were included within DALYs, no costs after discharge were estimated. The years of life lost (YLL) from Covid-19 mortality was informed by a secondary actuarial analysis and was not discounted. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 3, 2020. As outlined in Figure 2 , the results of the initial search were screened by title and abstract. The full texts of potentially relevant articles were retrieved and assessed for inclusion. When articles reported information from the same study sites but at two different time periods, only the articles with the updated statistics were included in this analysis. A total of sixteen observational studies (cross-sectional or cohort) and case series that reported the outcomes of hospitalized COVID-19 patients were included within quantitative synthesis. Average weighted estimates of the case fatality rate among ICU patients and non-ICU patients/patients dying in general ward were calculated using the formula: Deaths (Deaths + recovered) ⁄ . (2) Utilisation Utilisation includes the proportions of hospitalized individuals that are critical versus severe and length of stay data for each patient type by type of management (utilization of ICU days by critical patients, utilization of general ward days for severe patients, and for critical patients before/after ICU). These variables were extracted from seven articles [8] [9] [10] [11] [12] [13] [14] [15] [16] identified in the above-mentioned systematic search. Average weighted estimates for each variable were calculated. Finally, the proportion of patients using public versus private hospitals was based on the proportion of South Africans with medical scheme membership. [17] (3) Unit costs The model considers the costs of inpatient care in public and private hospitals through the inclusion of unit costs per general ward day and per ICU day. These are multiplied against the abovementioned length of stay estimates to generate a cost per admission. Private sector unit costs are based on the tariff rates in the "Guidelines on Public Private Collaboration in Response to COVID-19" published by the Department of Health. [18] Public sector unit costs were calculated using the Health Systems Trust District Health Barometer (HST-DHB) (12 th Edition -2016/17) datafile [19] which provides hospital-level estimates of expenditure per patient day equivalent (PDE) for all categories of public sector hospitals. These costs were inflated to 2020 prices using the Consumer Price Index [20] and a weighted average unit cost was calculated through weighting unit costs by the percentage of useable beds across levels of care. Because the HST-DHB data do not provide an estimate of the unit cost per ICU day, we estimated this by inflating the average weighted cost by the cost differential between ICU and general ward tariffs in the private sector. DALYs are calculated through the summation of YLL and YLD. YLL were informed by a South African actuarial analysis that utilised age-and co-morbidity adjusted mortality rates observed internationally and applied these to the South African population. [21] This resulted in an average estimate of 5.4 YLL per death due to the relatively younger population in South Africa. A wide range of this parameter was tested in sensitivity analysis to reflect the relative uncertainty associated with transferring international mortality data to the South African context. Duration of morbidity is currently unknown for COVID-19; assumptions were therefore made for these parameters. Disability weights for severe/critical COVID-19 patients were based on relevant estimates for similar conditions from the 2017 Global Burden of Disease study. [22] Simple sensitivity analyses were run across all variables to assess the impact of changes on the ICER. Where possible, ranges for sensitivity analysis were based on upper and lower confidence intervals, high or low values or interquartile ranges found within the systematic literature review. For the remaining variables, a 50% increase/decrease was implemented, except for where this would move the variable out of feasible range (e.g. mortality rates can only fall within the range 0-1). Thereafter, threshold analyses were run to estimate the percentage change in variables that would render ICU cost-effective, using the published South African cost-effectiveness threshold (CET) [7] as the cut-off for this determination. Finally, an additional scenario was modelled in order to incorporate the effect of administration of the steroid dexamethasone. This analysis entailed the inclusion of the cost of a course of dexamethasone (ZAR 160.85 for twenty 4 mg vials as per 2020 Essential Medicines List price), as well as rate ratio reductions in deaths from ICU (0.65) or from general wards (0.80) as provided in estimates from a UK based randomized controlled trial. [23] Ethical considerations: This is a modelled cost-effectiveness/utility analysis using published secondary data; no ethical approval was therefore required. Table 2 provides a summary of the variables used in the model, together with the ranges on variables used for sensitivity analysis. As highlighted in the table, there are two key unknowns for this economic evaluation that both apply to the GW strategy. The first is the proportion of critical patients dying without access to ICU. This estimate has been based on the high value found in the meta-analysis for critical patients dying from ICU (88% mortality) with ranges for sensitivity analysis including 70% and 100% mortality. The other unknown is the length of stay for these critical patients, which is assumed to be the same as for critical patients managed in ICU. 13 [18] Tariff per ICU day private 25,142.55 12,571. 28 37,713.83 Published tariff rates (±50%) [18] Utilisation LoS in general ward in severe patients 21.25 7.25 43.00 Literature review (IQR) [11, 12] LoS in ICU in critical patients 8.80 4.30 13.30 Literature review (IQR) [8-10, 13, 14] LoS in general ward in critical patients in absence of ICU 8.80 4.30 13.30 Assumed to be the same as critical patients treated in ICU Assumption LoS in general ward in critical patients before/after ICU 1.00 0.00 3.00 Literature review (IQR) [12] Proportion needing ICU 0.21 0.05 0.50 Literature review (low and high value) [12] [13] [14] [15] [24] [25] [26] [27] Proportion reliant on public health system 0.83 0.42 1.00 Percentage of population without Medical Scheme coverage (-50%;1) [28] Proportion of severe patients dying 0.11 0.00 0.13 Literature review (low and high value) [12, [14] [15] [16] 24] Proportion of critical patients dying from ICU 0.54 0.24 0.88 Literature review (low and high value) [8-10, 12-16, 24, 29, 30] Proportion of critical patients dying without access to ICU 0.88 0.70 1.00 Assumed high value on critical patients dying from ICU (-20%;1) Assumption Disability weight in severe patients 0.13 0.09 0.19 Disability weight for severe lower respiratory tract infection (95% CI) [22] Disability weight in critical patients 0.41 0.27 0.56 Disability weight for severe pneumoconiosis (95% CI) [22] Duration of illness in severe patients 0. [21] Other Cost-effectiveness threshold per DALY averted 38,465.46 Used to assess value for money; if ICER