A cost-utility and budget impact analysis of allogeneic hematopoietic stem cell transplantation for severe thalassemic patients in Thailand

<p>Abstract</p> <p>Background</p> <p>Hematopoietic stem cell transplantation (HSCT) is the only curative treatment available to severe thalassemic patients. The treatment, however, is very costly, particularly in the context of low and middle income countries, and no studies have been carried out to explore its economic justifiability. This study aimed to estimate the cost-utility of HSCT compared with blood transfusions combined with iron chelating therapy (BT-ICT) for severe thalassemia in Thailand, and to investigate the affordability of HSCT using a budget impact analysis.</p> <p>Methods</p> <p>A Markov model was used to estimate the relevant costs and health outcomes over the patients' lifetimes taking a societal perspective as recommended by Thailand's health technology assessment guidelines. All future costs and outcomes were discounted at a rate of 3% per annum. Primary outcomes of interest were lifetime costs, quality adjusted life years (QALYs) gained, and the incremental cost-effectiveness ratio (ICER) in Thai baht (THB) per QALY gained.</p> <p>Results</p> <p>Compared to BT-ICT, the incremental cost-effectiveness ratio increased with patient age from 80,700 to 183,000 THB per QALY gained for related HSCT and 209,000 to 953,000 THB per QALY gained for unrelated HSCT among patients aged 1 to 15 years (US$1= 34 THB). The governmental budget impact analysis showed that providing 200 related HSCT to patients aged 1 to 10 years, in accordance with the current infrastructure limitations, would initially require approximately 90 million additional THB per year.</p> <p>Conclusions</p> <p>At a societal willingness to pay of 100,000 THB per QALY gained, related HSCT was likely to be a cost-effective and affordable treatment for young children with severe thalassemia in Thailand.</p

The social role of C-reactive protein point-of-care testing to guide antibiotic prescription in Northern Thailand

New and affordable point-of-care testing (POCT) solutions are hoped to guide antibiotic prescription and to help limit antimicrobial resistance (AMR)—especially in low- and middle-income countries where resource constraints often prevent extensive diagnostic testing. Anthropological and sociological research has illuminated the role and impact of rapid point-of-care malaria testing. This paper expands our knowledge about the social implications of non-malarial POCT, using the case study of a C-reactive-protein point-of-care testing (CRP POCT) clinical trial with febrile patients at primary-care-level health centres in Chiang Rai province, northern Thailand. We investigate the social role of CRP POCT through its interactions with (a) the healthcare workers who use it, (b) the patients whose routine care is affected by the test, and (c) the existing patient-health system linkages that might resonate or interfere with CRP POCT. We conduct a thematic analysis of data from 58 purposively sampled pre- and post-intervention patients and healthcare workers in August 2016 and May 2017. We find widespread positive attitudes towards the test among patients and healthcare workers. Patients’ views are influenced by an understanding of CRP POCT as a comprehensive blood test that provides specific diagnosis and that corresponds to notions of good care. Healthcare workers use the test to support their negotiations with patients but also to legitimise ethical decisions in an increasingly restrictive antibiotic policy environment. We hypothesise that CRP POCT could entail greater patient adherence to recommended antibiotic treatment, but it could also encourage riskier health behaviour and entail potentially adverse equity implications for patients across generations and socioeconomic strata. Our empirical findings inform the clinical literature on increasingly propagated point-of-care biomarker tests to guide antibiotic prescriptions, and we contribute to the anthropological and sociological literature through a novel conceptualisation of the patient-health system interface as an activity space into which biomarker testing is introduced

A Comparison of Patients' Local Conceptions of Illness and Medicines in the Context of C-Reactive Protein Biomarker Testing in Chiang Rai and Yangon.

Antibiotic resistance is not solely a medical but also a social problem, influenced partly by patients' treatment-seeking behavior and their conceptions of illness and medicines. Situated within the context of a clinical trial of C-reactive protein (CRP) biomarker testing to reduce antibiotic over-prescription at the primary care level, our study explores and compares the narratives of 58 fever patients in Chiang Rai (Thailand) and Yangon (Myanmar). Our objectives are to 1) compare local conceptions of illness and medicines in relation to health-care seeking and antibiotic demand; and to 2) understand how these conceptions could influence CRP point-of-care testing (POCT) at the primary care level in low- and middle-income country settings. We thereby go beyond the current knowledge about antimicrobial resistance and CRP POCT, which consists primarily of clinical research and quantitative data. We find that CRP POCT in Chiang Rai and Yangon interacted with fever patients' preexisting conceptions of illness and medicines, their treatment-seeking behavior, and their health-care experiences, which has led to new interpretations of the test, potentially unforeseen exclusion patterns, implications for patients' self-assessed illness severity, and an increase in the status of the formal health-care facilities that provide the test. Although we expected that local conceptions of illness diverge from inbuilt assumptions of clinical interventions, we conclude that this mismatch can undermine the intervention and potentially reproduce problematic equity patterns among CRP POCT users and nonusers. As a partial solution, implementers may consider applying the test after clinical examination to validate rather than direct prescription processes

Cost of treating inpatient falciparum malaria on the Thai-Myanmar border.

BACKGROUND: Despite demonstrated benefits and World Health Organization (WHO) endorsement, parenteral artesunate is the recommended treatment for patients with severe Plasmodium falciparum malaria in only one fifth of endemic countries. One possible reason for this slow uptake is that a treatment course of parenteral artesunate is costlier than quinine and might, therefore, pose a substantial economic burden to health care systems. This analysis presents a detailed account of the resources used in treating falciparum malaria by either parenteral artesunate or quinine in a hospital on the Thai-Myanmar border. METHODS: The analysis used data from four studies, with random allocation of inpatients with falciparum malaria to treatment with parenteral artesunate or quinine, conducted in Mae Sot Hospital, Thailand from 1995 to 2001. Detailed resource use data were collected during admission and unit costs from the 2008 hospital price list were applied to these. Total admission costs were broken down into five categories: 1) medication; 2) intravenous fluids; 3) disposables; 4) laboratory tests; and 5) services. RESULTS: While the medication costs were higher for patients treated with artesunate, total admission costs were similar in those treated with quinine, US$243 (95$ 190 (95% CI: 131.0-263.2) (P=0.375). For cases classified as severe malaria (59%), the total cost of admission was US$298 (95$ 284 (95% CI: 181.3-407) in the artesunate group (P=0.869). CONCLUSION: This analysis finds no evidence for a difference in total admission costs for malaria inpatients treated with artesunate as compared with quinine. Assuming this is generalizable to other settings, the higher cost of a course of artesunate should not be considered a barrier for its implementation in the treatment of malaria

How context can impact clinical trials : a multi-country qualitative case study comparison of diagnostic biomarker test interventions

Background Context matters for the successful implementation of medical interventions, but its role remains surprisingly understudied. Against the backdrop of antimicrobial resistance, a global health priority, we investigated the introduction of a rapid diagnostic biomarker test (C-reactive protein, or CRP) to guide antibiotic prescriptions in outpatient settings and asked, “Which factors account for cross-country variations in the effectiveness of CRP biomarker test interventions?” Methods We conducted a cross-case comparison of CRP point-of-care test trials across Yangon (Myanmar), Chiang Rai (Thailand), and Hanoi (Vietnam). Cross-sectional qualitative data were originally collected as part of each clinical trial to broaden their evidence base and help explain their respective results. We synthesised these data and developed a large qualitative data set comprising 130 interview and focus group participants (healthcare workers and patients) and nearly one million words worth of transcripts and interview notes. Inductive thematic analysis was used to identify contextual factors and compare them across the three case studies. As clinical trial outcomes, we considered patients’ and healthcare workers’ adherence to the biomarker test results, and patient exclusion to gauge the potential “impact” of CRP point-of-care testing on the population level. Results We identified three principal domains of contextual influences on intervention effectiveness. First, perceived risks from infectious diseases influenced the adherence of the clinical users (nurses, doctors). Second, the health system context related to all three intervention outcomes (via the health policy and antibiotic policy environment, and via health system structures and the ensuing utilisation patterns). Third, the demand-side context influenced the patient adherence to CRP point-of-care tests and exclusion from the intervention through variations in local healthcare-seeking behaviours, popular conceptions of illness and medicine, and the resulting utilisation of the health system. Conclusions Our study underscored the importance of contextual variation for the interpretation of clinical trial findings. Further research should investigate the range and magnitude of contextual effects on trial outcomes through meta-analyses of large sets of clinical trials. For this to be possible, clinical trials should collect qualitative and quantitative contextual information for instance on their disease, health system, and demand-side environment. Trial registration: ClinicalTrials.gov Identifiers NCT02758821 and NCT01918579

Cost effectiveness and resource allocation of Plasmodium falciparum malaria control in Myanmar: a modelling analysis of bed nets and community health workers.

BACKGROUND: Funding for malaria control and elimination in Myanmar has increased markedly in recent years. While there are various malaria control tools currently available, two interventions receive the majority of malaria control funding in Myanmar: (1) insecticide-treated bed nets and (2) early diagnosis and treatment through malaria community health workers. This study aims to provide practical recommendations on how to maximize impact from investment in these interventions. METHODS: A simple decision tree is used to model intervention costs and effects in terms of years of life lost. The evaluation is from the perspective of the service provider and costs and effects are calculated in line with standard methodology. Sensitivity and scenario analysis are undertaken to identify key drivers of cost effectiveness. Standard cost effectiveness analysis is then extended via a spatially explicit resource allocation model. FINDINGS: Community health workers have the potential for high impact on malaria, particularly where there are few alternatives to access malaria treatment, but are relatively costly. Insecticide-treated bed nets are comparatively inexpensive and modestly effective in Myanmar, representing a low risk but modest return intervention. Unlike some healthcare interventions, bed nets and community health workers are not mutually exclusive nor are they necessarily at their most efficient when universally applied. Modelled resource allocation scenarios highlight that in this case there is no "one size fits all" cost effectiveness result. Health gains will be maximized by effective targeting of both interventions

Geographic Resource Allocation Based on Cost Effectiveness: An Application to Malaria Policy.

Healthcare services are often provided to a country as a whole, though in many cases the available resources can be more effectively targeted to specific geographically defined populations. In the case of malaria, risk is highly geographically heterogeneous, and many interventions, such as insecticide-treated bed nets and malaria community health workers, can be targeted to populations in a way that maximises impact for the resources available. This paper describes a framework for geographically targeted budget allocation based on the principles of cost-effectiveness analysis and applied to priority setting in malaria control and elimination. The approach can be used with any underlying model able to estimate intervention costs and effects given relevant local data. Efficient geographic targeting of core malaria interventions could significantly increase the impact of the resources available, accelerating progress towards elimination. These methods may also be applicable to priority setting in other disease areas

Artemisinin resistance--modelling the potential human and economic costs.

BACKGROUND: Artemisinin combination therapy is recommended as first-line treatment for falciparum malaria across the endemic world and is increasingly relied upon for treating vivax malaria where chloroquine is failing. Artemisinin resistance was first detected in western Cambodia in 2007, and is now confirmed in the Greater Mekong region, raising the spectre of a malaria resurgence that could undo a decade of progress in control, and threaten the feasibility of elimination. The magnitude of this threat has not been quantified. METHODS: This analysis compares the health and economic consequences of two future scenarios occurring once artemisinin-based treatments are available with high coverage. In the first scenario, artemisinin combination therapy (ACT) is largely effective in the management of uncomplicated malaria and severe malaria is treated with artesunate, while in the second scenario ACT are failing at a rate of 30%, and treatment of severe malaria reverts to quinine. The model is applied to all malaria-endemic countries using their specific estimates for malaria incidence, transmission intensity and GDP. The model describes the direct medical costs for repeated diagnosis and retreatment of clinical failures as well as admission costs for severe malaria. For productivity losses, the conservative friction costing method is used, which assumes a limited economic impact for individuals that are no longer economically active until they are replaced from the unemployment pool. RESULTS: Using conservative assumptions and parameter estimates, the model projects an excess of 116,000 deaths annually in the scenario of widespread artemisinin resistance. The predicted medical costs for retreatment of clinical failures and for management of severe malaria exceed US$32 million per year. Productivity losses resulting from excess morbidity and mortality were estimated at US$385 million for each year during which failing ACT remained in use as first-line treatment. CONCLUSIONS: These 'ballpark' figures for the magnitude of the health and economic threat posed by artemisinin resistance add weight to the call for urgent action to detect the emergence of resistance as early as possible and contain its spread from known locations in the Mekong region to elsewhere in the endemic world

Using machine learning to guide targeted and locally-tailored empiric antibiotic prescribing in a children's hospital in Cambodia [version 1; referees: 2 approved]

Background: Early and appropriate empiric antibiotic treatment of patients suspected of having sepsis is associated with reduced mortality. The increasing prevalence of antimicrobial resistance reduces the efficacy of empiric therapy guidelines derived from population data. This problem is particularly severe for children in developing country settings. We hypothesized that by applying machine learning approaches to readily collect patient data, it would be possible to obtain individualized predictions for targeted empiric antibiotic choices. Methods and Findings: We analysed blood culture data collected from a 100-bed children's hospital in North-West Cambodia between February 2013 and January 2016. Clinical, demographic and living condition information was captured with 35 independent variables. Using these variables, we used a suite of machine learning algorithms to predict Gram stains and whether bacterial pathogens could be treated with common empiric antibiotic regimens: i) ampicillin and gentamicin; ii) ceftriaxone; iii) none of the above. 243 patients with bloodstream infections were available for analysis. We found that the random forest method had the best predictive performance overall as assessed by the area under the receiver operating characteristic curve (AUC). The random forest method gave an AUC of 0.80 (95%CI 0.66-0.94) for predicting susceptibility to ceftriaxone, 0.74 (0.59-0.89) for susceptibility to ampicillin and gentamicin, 0.85 (0.70-1.00) for susceptibility to neither, and 0.71 (0.57-0.86) for Gram stain result. Most important variables for predicting susceptibility were time from admission to blood culture, patient age, hospital versus community-acquired infection, and age-adjusted weight score. Conclusions: Applying machine learning algorithms to patient data that are readily available even in resource-limited hospital settings can provide highly informative predictions on antibiotic susceptibilities to guide appropriate empiric antibiotic therapy. When used as a decision support tool, such approaches have the potential to improve targeting of empiric therapy, patient outcomes and reduce the burden of antimicrobial resistance

Point-of-care C-reactive protein testing to reduce inappropriate use of antibiotics for non-severe acute respiratory infections in Vietnamese primary health care: a randomised controlled trial

Background Inappropriate antibiotic use for acute respiratory tract infections is common in primary health care, but distinguishing serious from self-limiting infections is diffi cult, particularly in low-resource settings. We assessed whether C-reactive protein point-of-care testing can safely reduce antibiotic use in patients with non-severe acute respiratory tract infections in Vietnam. Method We did a multicentre open-label randomised controlled trial in ten primary health-care centres in northern Vietnam. Patients aged 1–65 years with at least one focal and one systemic symptom of acute respiratory tract infection were assigned 1:1 to receive either C-reactive protein point-of-care testing or routine care, following which antibiotic prescribing decisions were made. Patients with severe acute respiratory tract infection were excluded. Enrolled patients were reassessed on day 3, 4, or 5, and on day 14 a structured telephone interview was done blind to the intervention. Randomised assignments were concealed from prescribers and patients but not masked as the test result was used to assist treatment decisions. The primary outcome was antibiotic use within 14 days of follow-up. All analyses were prespecifi ed in the protocol and the statistical analysis plan. All analyses were done on the intention-totreat population and the analysis of the primary endpoint was repeated in the per-protocol population. This trial is registered under number NCT01918579. Findings Between March 17, 2014, and July 3, 2015, 2037 patients (1028 children and 1009 adults) were enrolled and randomised. One adult patient withdrew immediately after randomisation. 1017 patients were assigned to receive C-reactive protein point-of-care testing, and 1019 patients were assigned to receive routine care. 115 patients in the C-reactive protein point-of-care group and 72 patients in the routine care group were excluded in the intention-to-treat analysis due to missing primary endpoint. The number of patients who used antibiotics within 14 days was 581 (64%) of 902 patients in the C-reactive protein group versus 738 (78%) of 947 patients in the control group (odds ratio [OR] 0·49, 95% CI 0·40–0·61; p<0·0001). Highly signifi cant diff erences were seen in both children and adults, with substantial heterogeneity of the intervention eff ect across the 10 sites (I²=84%, 95% CI 66–96). 140 patients in the C-reactive protein group and 137 patients in the routine care group missed the urine test on day 3, 4, or 5. Antibiotic activity in urine on day 3, 4, or 5 was found in 267 (30%) of 877 patients in the C-reactive protein group versus 314 (36%) of 882 patients in the routine treatment group (OR 0·78, 95% CI 0·63–0·95; p=0·015). Time to resolution of symptoms was similar in both groups. Adverse events were rare, with no deaths and a total of 14 hospital admissions (six in the C-reactive protein group and eight in the control group). Interpretation C-reactive protein point-of-care testing reduced antibiotic use for non-severe acute respiratory tract infection without compromising patients’ recovery in primary health care in Vietnam. Health-care providers might have become familiar with the clinical picture of low C-reactive protein, leading to reduction in antibiotic prescribing in both groups, but this would have led to a reduction in observed eff ect, rather than overestimation. Qualitative analysis is needed to address diff erences in context in order to implement this strategy to improve rational antibiotic use for patients with acute respiratory infection in low-income and middle-income countries