Economic costs of obesity: a systematic review.

INTRODUCTION: Obesity is a growing public health problem leading to substantial economic impact. This study aimed to summarize the economic impact of obesity and to critically analyze the methods used in the cost-of-illness (COI) studies on obesity. METHODS: We conducted systematic search in PubMed and Scopus from September 1, 2016, to July 22, 2022. Original COI studies estimating the economic cost of obesity and/or overweight in at least one country, published in English were included. To facilitate the comparison of estimates across countries, we converted the cost estimates of different years to 2022 purchasing power parity (PPP) values using each country's consumer price index (CPI) and PPP conversion rate. RESULTS: Nineteen studies were included. All studies employed a prevalence-based approach using Population Attributable Fraction (PAF) methodology. About half of the included studies (53%) were conducted in high-income countries while the others (47%) were conducted in middle-income countries. The economic burden of obesity ranged between PPP 15 million in Brazil to PPP 126 billion in the USA, in the year 2022. Direct medical costs accounted for 0.7% to 17.8% of the health system expenditure. Furthermore, the total costs of obesity ranged from 0.05% to 2.42% of the country's gross domestic product (GDP). Of the seven studies that estimated both direct and indirect costs, indirect costs accounted for the largest portion of five studies. Nevertheless, a variety in methodology across studies was identified. The number of co-morbidities included in the analysis varied across studies. CONCLUSIONS: Although there was a variety of methodologies across studies, consistent evidence indicated that the economic burden of obesity was substantial. Obesity prevention and control should be a public health priority, especially among countries with high prevalence of obesity.

Economic evaluation of prenatal screening for fetal aneuploidies in Thailand.

Historically, there has been a lack of cost-effectiveness data regarding the inclusion of universal non-invasive prenatal testing (NIPT) for trisomy 21, 18, and 13 in the benefit package of the Universal Health Coverage (UHC) in Thailand. Therefore, this study aimed to perform the cost-benefit analysis of prenatal screening tests and calculate the budget impact that would result from the implementation of a universal NIPT program. A decision-tree model was employed to evaluate cost and benefit of different prenatal chromosomal abnormalities screenings: 1) first-trimester screening (FTS), 2) NIPT, and 3) definitive diagnostic (amniocentesis). The comparison was made between these screenings and no screening in three groups of pregnant women: all ages, < 35 years, and ≥ 35 years. The analysis was conducted from societal and governmental perspectives. The costs comprised direct medical, direct non-medical, and indirect costs, while the benefit was cost-avoidance associated with caring for children with trisomy and the loss of productivity for caregivers. Parameter uncertainties were evaluated through one-way and probabilistic sensitivity analyses. From a governmental perspective, all three methods were found to be cost-beneficial. Among them, FTS was identified as the most cost-beneficial, especially for pregnant women aged ≥ 35 years. From a societal perspective, the definitive diagnostic test was not cost-effective, but the other two screening tests were. The most sensitive parameters for FTS and NIPT strategies were the productivity loss of caregivers and the incidence of trisomy 21. Our study suggested that NIPT was the most cost-effective strategy in Thailand, if the cost was reduced to 47 USD. This evidence-based information can serve as a crucial resource for policymakers when making informed decisions regarding the allocation of resources for prenatal care in Thailand and similar context.

Cost-Utility Analysis of Deep Learning and Trained Human Graders for Diabetic Retinopathy Screening in a Nationwide Program.

INTRODUCTION: Deep learning (DL) for screening diabetic retinopathy (DR) has the potential to address limited healthcare resources by enabling expanded access to healthcare. However, there is still limited health economic evaluation, particularly in low- and middle-income countries, on this subject to aid decision-making for DL adoption. METHODS: In the context of a middle-income country (MIC), using Thailand as a model, we constructed a decision tree-Markov hybrid model to estimate lifetime costs and outcomes of Thailand's national DR screening program via DL and trained human graders (HG). We calculated the incremental cost-effectiveness ratio (ICER) between the two strategies. Sensitivity analyses were performed to probe the influence of modeling parameters. RESULTS: From a societal perspective, screening with DL was associated with a reduction in costs of ~ US$ 2.70, similar quality-adjusted life-years (QALY) of + 0.0043, and an incremental net monetary benefit of ~ US$ 24.10 in the base case. In sensitivity analysis, DL remained cost-effective even with a price increase from US$ 1.00 to US$ 4.00 per patient at a Thai willingness-to-pay threshold of ~ US$ 4.997 per QALY gained. When further incorporating recent findings suggesting improved compliance to treatment referral with DL, our analysis models effectiveness benefits of ~ US$ 20 to US$ 50 depending on compliance. CONCLUSION: DR screening using DL in an MIC using Thailand as a model may result in societal cost-savings and similar health outcomes compared with HG. This study may provide an economic rationale to expand DL-based DR screening in MICs as an alternative solution for limited availability of skilled human resources for primary screening, particularly in MICs with similar prevalence of diabetes and low compliance to referrals for treatment.

Does health economics research align with the disease burden in the Middle East and North Africa region? A systematic review of economic evaluation studies on public health interventions.

INTRODUCTION: Economic evaluation studies demonstrate the value of money in health interventions and enhance the efficiency of the healthcare system. Therefore, this study reviews published economic evaluation studies of public health interventions from 26 Middle East and North Africa (MENA) countries and examines whether they addressed the region's major health problems. METHODS: PubMed and Scopus were utilized to search for relevant articles published up to June 26, 2021. The reviewers independently selected studies, extracted data, and assessed the quality of studies using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: The search identified 61 studies. Approximately half (28 studies; 46%) were conducted in Israel and Iran. The main areas of interest for economic evaluation studies were infectious diseases (21 studies; 34%), cancers (13 studies; 21%), and genetic disorders (nine studies; 15%). Five (8%), 39 (64%), 16 (26%), and one (2%) studies were classified as excellent, high, average, and poor quality, respectively. The mean of CHEERS checklist items reported was 80.8% (SD 14%). Reporting the structure and justification of the selected model was missed in 21 studies (37%), while price and conversion rates and the analytical methods were missed in 21 studies (34%). CONCLUSIONS: The quantity of economic evaluation studies on public health interventions in the MENA region remains low; however, the overall quality is high to excellent. There were obvious geographic gaps across countries regarding the number and quality of studies and gaps within countries concerning disease prioritization. The observed research output, however, did not reflect current and upcoming disease burden and risk factors trends in the MENA region.

A Systematic Review on Economic Evaluation Studies of Diagnostic and Therapeutic Interventions in the Middle East and North Africa.

INTRODUCTION: Due to the increase in healthcare budget constraint, economic evaluation (EE) evidence is increasingly required to inform resource allocation decisions. This study aimed to systematically review quantity, characteristics, and quality of full EE studies on diagnostic and therapeutic interventions conducted in 26 Middle East and North Africa (MENA) countries. METHODS: PubMed and Scopus databases were comprehensively searched to identify the published EE studies in the MENA region. The quality of reviewed studies was evaluated using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: The search identified 69 studies. The cost-utility approach was adopted in 49 studies (71 %). More than half (38 studies; 55 %) were conducted in Iran and Turkey. Sixteen countries (62 %) did not have any EE studies. The most frequently analyzed therapeutic areas were infectious diseases (19 studies; 28 %), cardiovascular diseases (11 studies; 16 %), and malignancies (10 studies; 14 %). Ten studies (14 %), 46 (67 %), 12 (17 %), and 1 study (1 %) were classified as excellent, high, moderate, and poor quality, respectively. The mean of items reported was 85.10 % (standard deviation 13.32 %). Characterizing heterogeneity, measurement of effectiveness, time horizon, and discount rate were missed in 21 (60 %), 22 (32 %), 20 (29 %) and 15 (25 %) studies, respectively. Data on effectiveness and utility relied primarily on studies conducted outside the region. CONCLUSIONS: The quantity of EE studies in the MENA region remains low; however, overall quality is high to excellent. The availability of local data, capacity building, and national guidelines are vital to improve both the quantity and quality of EE studies in the region.

Cost-Utility Analysis of Drug Treatments in Patients with Polypoidal Choroidal Vasculopathy in Thailand.

PURPOSE: The aim of this study was to estimate the cost-utility and budget impact of pharmacological treatments for the eye with polypoidal choroidal vasculopathy (PCV) in Thailand. METHODS: A Markov model-based cost-utility analysis (CUA) and budget impact analysis were conducted. The lifetime cost and outcomes of PCV treatments were estimated. We discounted costs and outcomes at 3% per annum. Parameters were estimated using data from published literatures, local cost and utility data, and epidemiology data among Thai patients. Univariate and probabilistic sensitivity analyses were performed to account for parameter uncertainty. RESULTS: Intravitreal bevacizumab (IVB) resulted in the lowest lifetime cost, followed by IVB plus verteporfin photodynamic therapy (IVB+vPDT) and intravitreal aflibercept (IVA). The combination of IVB or intravitreal ranibizumab (IVR) and verteporfin photodynamic therapy (IVB+vPDT or IVR+vPDT) yielded the highest quality-adjusted life-years (QALY). When compared with IVB from a societal perspective, the incremental cost-effectiveness ratio for patients with PCV receiving IVB+vPDT, IVR+vPDT, IVA were 10,304; 54,135; and 82,738 the United States dollar (USD) per QALY gained, respectively. At the Thai societal willingness to pay threshold of 4884 USD, IVB had the highest probability of being cost-effective (99%) followed by IVB+vPDT (1%). IVB+vPDT could be a cost-effective strategy and required a budget of 12.61 million USD over five fiscal years when the price of verteporfin reduced by approximately 45%. CONCLUSION: None of the drug treatments for PCV was cost-effective in the Thai context. The decreased price of verteporfin is required to support the inclusion of IVB+vPDT in the Thai National List of Essential Medicines for the treatment of PCV.

Cost-Utility Analysis of Vasoconstrictors Plus Albumin in the Treatment of Thai Patients with Type 1 Hepatorenal Syndrome.

PURPOSE: Type 1 hepatorenal syndrome (type 1 HRS) or hepatorenal syndrome-acute renal injury (HRS-AKI) leads to high short-term mortality rates in patients with cirrhosis. Vasoconstrictor therapy effectively improves survival of these patients and has been a bridge to liver transplantation. The aim of this study was to assess the cost-utility of terlipressin plus albumin (T+A) and noradrenaline plus albumin (N+A) compared to best supportive care (BSC) for treating type 1 HRS patients in Thailand. METHODS: A cost-utility analysis using a six-state Markov model was performed from societal and payer perspectives over a lifetime horizon. The clinical outcomes, costs, and utility parameters were obtained from literature, network meta-analyses, and expert opinion. One-way and probabilistic sensitivity analyses were conducted to account for uncertainty. RESULTS: The T+A yielded the highest cost (848,325 Thai Baht (THB)) and health outcomes (2.82 life-years (LY) and 2.27 quality-adjusted life-years (QALY)). Compared to BSC, incremental cost-effectiveness ratios (ICERs) of the T+A and N+A were 377,566 and 412,979 THB per QALY gained, respectively. If N+A is administered outside the intensive care unit, the ICER was 308,964 THB per QALY. The treatment cost after liver transplantation from year 3 onwards was the most influential factor for ICERs, followed by the cost of terlipressin, duration of noradrenaline treatment, and cost of albumin. At the Thai societal willingness-to-pay threshold of 160,000 THB per QALY gained, the probabilities of being cost-effective for T+A, N+A, and BSC were 11%, 20%, and 69%, respectively. CONCLUSION: The T+A and N+A treatments would not be cost-effective compared to BSC in the Thai setting.

Cost-Effectiveness Analysis of Community Case Management of Childhood Diarrhea in Burundi.

OBJECTIVE: This study aimed to evaluate the cost-effectiveness of community case management (CCM) program of childhood diarrhea by providing oral rehydration salts and zinc through community health workers in Burundi. METHODS: A cost-effectiveness analysis study using a Markov modeling approach was undertaken to assess the CCM program of diarrhea from both provider and societal perspectives. The CCM program was compared with the routine management of childhood diarrhea at health facilities. Primary data on the cost of childhood diarrhea management were collected. Both economic and health outcomes were assessed for a period of 5 years, and a discount rate of 3% was applied. One-way and probabilistic sensitivity analyses were performed. RESULTS: The CCM program was found to be both less costly and more effective resulting to a negative value of incremental cost-effectiveness ratios, indicating that the program was dominant producing cost savings. Compared with the routine treatment of diarrhea at health facilities, the CCM program would avert 2749 additional disability-adjusted life years over a period of 5 years. The economic burden was reduced of US$1 056 699 and US$2 328 531 from the provider and societal perspectives, respectively. The cost-effectiveness estimates were mostly sensitive to the discount rate and the cost of outpatient visits at health facilities. The intervention remained dominant with a 100% probability of cost savings within 10 000 simulations of the sensitivity analysis. CONCLUSIONS: Providing inexpensive diarrheal treatment (oral rehydration salts and zinc) in communities is an attractive cost-effective intervention. Evidence from this study should be used to scale up the coverage of this life- and cost-saving intervention.

Economic Evaluations of Artificial Intelligence in Ophthalmology.

ABSTRACT: Artificial intelligence (AI) is expected to cause significant medical quality enhancements and cost-saving improvements in ophthalmology. Although there has been a rapid growth of studies on AI in the recent years, real-world adoption of AI is still rare. One reason may be because the data derived from economic evaluations of AI in health care, which policy makers used for adopting new technology, have been fragmented and scarce. Most data on economics of AI in ophthalmology are from diabetic retinopathy (DR) screening. Few studies classified costs of AI software, which has been considered as a medical device, into direct medical costs. These costs of AI are composed of initial and maintenance costs. The initial costs may include investment in research and development, and costs for validation of different datasets. Meanwhile, the maintenance costs include costs for algorithms upgrade and hardware maintenance in the long run. The cost of AI should be balanced between manufacturing price and reimbursements since it may pose significant challenges and barriers to providers. Evidence from cost-effectiveness analyses showed that AI, either standalone or used with humans, was more cost-effective than manual DR screening. Notably, economic evaluation of AI for DR screening can be used as a model for AI to other ophthalmic diseases.

Economic impact of medical genetic testing on clinical applications in Thailand.

BACKGROUND: Although the clinical benefits of medical genetic testing have been proven, there has been limited evidence on its economic impact in Thai setting. Thus, this study aimed to evaluate the economic impact of genetic testing services provided by the Center for Medical Genomics (CMG) in Thailand. METHODS: Cost-benefit analysis was conducted from provider and societal perspectives. Cost and output data of genetic testing services provided by the CMG during 2014 to 2018 and published literature reviews were applied to estimate the costs and benefits. Monetary benefits related to genetic testing services were derived through human capital approach. RESULTS: The total operation cost was 126 million baht over five years with an average annual cost of 21 million baht per year. The net benefit, benefit-to-cost ratio, and return on investment were 5,477 million baht, 43 times, and 42 times, respectively. Productivity gain was the highest proportion (50.57%) of the total benefit. CONCLUSIONS: The provision of genetic testing services at the CMG gained much more benefits than the cost. This study highlighted a good value for money in the establishment of medical genomics settings in Thailand and other developing countries.