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The World Health Organization’s (WHO’s) Choosing Interventions that are Cost-Effective (CHOICE) programme has been a global leader in the field of economic evaluation, specifically cost-effectiveness analysis for almost 20 years. WHO-CHOICE takes a \"generalized\" approach to cost-effectiveness analysis that can be seen as a quantitative assessment of current and future efficiency within a health system. This supports priority setting processes, ensuring that health stewards know how to spend resources in order to achieve the highest health gain as one consideration in strategic planning. This approach is unique in the global health landscape. This paper provides an overview of the methodological approach, updates to analytic framework over the past 10 years, and the added value of the WHO-CHOICE approach in supporting decision makers as they aim to use limited health resources to achieve the Sustainable Development Goals (SDGs) by 2030.

Background Health technology assessment uses explicit economic evaluation evidence to support health benefits package design. However, the limited availability of technical expertise, data, and methods has restricted the production of economic evaluation evidence in low- and middle-income countries. Zambia has initiated a roadmap to support its policy of reviewing and implementing its national benefits package. This study characterises economic evaluation evidence to support this process's evidence mapping, synthesis, and appraisal stages. Methods This systematic review applies deductive analysis and the preferred reporting items for systematic review and meta-analyses. Four databases were searched to identify studies from 1993 that coincided with Zambia's health benefits package reform. Results A total of 61 studies met the inclusion criteria. Most of the studies were first authored by nonlocal authors, and the number of local-based authors in each study was low. Almost all funding for economic evaluation research was not local, and only a few studies sought local ethical clearance to conduct research. Infectious diseases were the highest disease control priority for the studies, with HIV research having the highest output. Most of the studies were cost-effectiveness studies that utilised trial-based data and a combination of program, published, and unpublished data for analysis. The studies generally utilised direct cost and applied the ingredient-based costing approach. Natural units were predominantly used for outcomes alongside DALYs. Most studies reported using a 3% discount rate for both costs and outcomes, with only a few reporting methods for sensitivity analysis. Conclusion Economic evaluation evidence in Zambia has increased, revealing limited local research leadership, methodological inconsistencies, and a focus on infectious diseases. These findings are crucial for revising Zambia's benefits package and may guide researchers and decision-makers in improving the transparency and quality of future research.

ObjectivesPrioritization of health technologies for insurance coverage is usually based on explicit and implicit criteria. This study presents the development of the multi-criteria decision analysis (MCDA) model, the Iranian Health Insurance Benefit Optimization Model (IR-HIBOM), to inform the design of basic health insurance benefit packages.MethodsAn initial set of twenty-nine potential allocation criteria was identified through a review of available evidence and other relevant literature. Review of this set by three specialized panels yielded a final set of thirteen criteria. A cross-sectional survey using the best–worst scaling method was then fielded to 163 health system experts to evaluate their preferences regarding the relative importance of the allocation criteria. The mixed logit method was employed to determine the weight of the relative importance of each criterion. Subsequently, a multilevel criteria scoring framework was defined based on a review of similar models and input from a panel of five expert members of the study team. Finally, model’s appraisal was conducted.ResultsThirteen criteria, including relative safety, efficacy, disease severity, access to alternative health technologies, budget impacts, cost-effectiveness, quality of evidence, population size, age, job absenteeism, economic status, daily care needs, and ease-of-use/acceptance were selected. Cost-effectiveness and ease-of-use criteria had the highest and lowest relative importance weights, with 30.5 percent and 1 percent, respectively. Furthermore, scores were determined for the several levels of each criterion, and decision rules were defined for the cost-effectiveness and budget impact criteria. The final model’s appraisal, based on weighted scores of thirteen selected technologies, indicated that it was valid and applicable.ConclusionsThe IR-HIBOM demonstrated its potential utility in the health resource allocation.

Background: Patient satisfaction is an important measure of health service and a key indicator of the quality of health service. Studies focus on how to improve quality rather than patient satisfaction. This study was conducted to identify patients' satisfaction with the pharmaceutical service package of Health Insurance Corporation of Khartoum State in Jabal-Awliya locality, Khartoum, Sudan.  Methods: A cross-sectional study was conducted between January and August 2020. Data were collected using a structured questionnaire. Satisfaction was estimated using the Likert Scale. The association between patient's satisfaction and patient care indicators, namely: average dispensing time, percentage of medicine dispensed and labelled, and patient correct dose knowledge were assessed using Chi- square test, where a p-value < 0.05 was considered significant.   Results: Out of 378 participants, the mean age was 47 with a comparable frequency of male and female participants (49.3% and 50.7% respectively). The mean satisfaction was 62.2% (3.11 ± 0.68). Most of the participants were satisfied with the way the pharmacist dealt with them (3.7, ± 0.778), while a low mean of satisfaction was reported regarding the availability of medicine within the pharmaceutical benefit package (2.06, ± 1.17). Average dispensing time was 5.78 minutes (p = 0.002), a low percentage of medicine actually dispensed and labelled was observed at 67% and 58% respectively (p = 0.00). A higher patient knowledge was reported 96.6% (p = 0.00), and the majority of the patients were able to pay 65% (p = 0.00).  Conclusion: The current study demonstrates a comparable satisfaction score. However, medication unavailability is the main factor that affects patient satisfaction.

Background: Countries around the world are using health technology assessment (HTA) for health benefit package design. Evidence-informed deliberative processes (EDPs) are a practical and stepwise approach to enhance legitimate health benefit package design based on deliberation between stakeholders to identify, reflect and learn about the meaning and importance of values, informed by evidence on these values. This paper reports on the development of practical guidance on EDPs, while the conceptual framework of EDPs is described in a companion paper. Methods: The first guide on EDPs (2019) is further developed based on academic knowledge exchange, surveying 27 HTA bodies and 66 experts around the globe, and the implementation of EDPs in several countries. We present the revised steps of EDPs and how selected HTA bodies (in Australia, Brazil, Canada, France, Germany, Scotland, Thailand and the United Kingdom) organize key issues of legitimacy in their processes. This is based on a review of literature via PubMed and HTA bodies’ websites. Results: HTA bodies around the globe vary considerable in how they address legitimacy (stakeholder involvement ideally through participation with deliberation; evidence-informed evaluation; transparency; and appeal) in their processes. While there is increased attention for improving legitimacy in decision-making processes, we found that the selected HTA bodies are still lacking or just starting to develop activities in this area. We provide recommendations on how HTA bodies can improve on this. Conclusion: The design and implementation of EDPs is in its infancy. We call for a systematic analysis of experiences of a variety of countries, from which general principles on EDPs might subsequently be inferred.

The need for more local technical capacity in Health Technology Assessment (HTA) is a leading challenge to its use in low- and middle-income countries. Zambia has been considering using HTA to support its universal health coverage initiative, which includes health benefits package design and implementation. This study assesses the local HTA capacity for the steering committee tasked with supporting the design and implementation of the national health benefits package in Zambia. The study applied a cross-sectional web-based survey design and the consensus-based Checklist for Reporting of Survey Studies. Data were collected from the steering committee of the benefits package working group, tasked with leading the design process of the health benefits package using the Instrument for the Assessment of Skills to Conduct a Health Technology Assessment tool. The majority of respondents had not served on a selection and reimbursement committee. Clinical effectiveness skills in structuring a search strategy, handling missing data, conducting qualitative evidence synthesis, and grading the certainty of evidence were low. Skills for leadership, networking, conflict management, and project coordination, public and patient involvement were mid-level to low. Most of the respondents were aware of ethical issues with health technologies. Health economics skills in economic evaluations and decision analytic modeling, equity and health system efficiency measurement, budget impact analysis, and quality of life were identified for capacity strengthening. Available technical capacities to revise and implement the national benefits package were lower in health economics, synthesis for clinical effectiveness evidence, ethics, patient and public involvement, and soft skills, in that order.

Background Expenses related to employee’s health benefit packages are rising. Hence, organisations are looking for complementary health financing arrangements to provide more financial protection for employees. This study aims to develop criteria to choose the most appropriate complementary health insurance company based on the experience of a large organisation in Iran. Methods This study was conducted in 2021 in Iran, in the Foundation of Martyrs and Veterans Affairs to find as many applicable criteria as possible. To develop a comprehensive list of criteria, we used triangulation in data sources, including review of relevant national and international documents, in-depth interviews of key informants, focus group discussion, and examining similar but unpublished checklists used by other organisations in Iran. The list of criteria was prioritised during focus group discussions. We used the best-worst method as a multi-criteria decision making method and a qualitative consensus among the key informants to value the importance of each of the finalised criteria. Findings Out of 85 criteria, we selected 28 criteria to choose an insurer for implementing complementary private health insurance. The finalised criteria were fell into six domains: (i) Previous experience of the applicants; (ii) Communication with clients; (iii) Financial status; (iv) Health care providers’ network; (v) Technical infrastructure and workforce; (vi) and Process of reviewing claims and reimbursement. Conclusion We propose a quantitative decision-making checklist to choose the best complimentary private health insurance provider. We invite colleagues to utilise, adapt, modify, or develop these criteria to suit their organisational needs. This checklist can be applied in any low- and middle-income country where the industry of complementary health insurance is blooming.

Background China started to cover novel medicines for the treatment of major cancers, such as trastuzumab for breast cancer by the government health insurance programs since 2016. Limited data have been published on the use of cancer medications and little is known about how government health insurance coverage of novel anti-cancer medicines benefited patients in the real world. This study aimed to generate evidence to inform the health security authorities to optimize the government health insurance coverage of novel anti-cancer medicines as a more inclusive and equal policy, through which each of the needed patient can get access to the novel anti-cancer medicines regardless of the ability to pay. Methods The study targeted one of the government health insurance newly covered novel medicines for breast cancer and the breast cancer patients. The analyses were based on the data collected from one tertiary public hospital in Fujian province of China. We conducted interrupted time series analysis with a segmented regression model and multivariate analyses with a binary logistic regression model to analyze the impact of the government health insurance coverage on medicines utilization and the determinants of patient’s medication choice. Results The average proportion of patients who initiated medication with novel medicines increased from 37.4% before the government health insurance coverage to 69.2% afterwards. Such an increase was observed in all patient sub-groups. The monthly proportion of patients who initiated medication with novel medicines increased sharply by 18.3 % (95 %CI,10.4-34.0 %,  p  = 0.01) in September 2017, the afterwards trend continuously increased (95 %CI,1.03–3.60,  p  = 0.02). The critical determinants of patient's medication choice were mostly connected with the patient's health insurance benefits packages. Conclusions The government health insurance coverage of novel anti-breast-cancer medicines benefited the patients generally. The utilization of novel medicines such as trastuzumab continuously increased. The insurance coverage benefited well the patients in the high-risk age groups. However, rural patients, patients enrolled in the “resident program”, and patients from low-income residential areas and non-local patients benefited less from this policy. Improving the benefits package of the low-income patients and the “resident program” beneficiary would be of considerable significance for a more inclusive and equal health insurance coverage of novel anti-cancer medicines.

Background: Cost-effectiveness (CE) is a common prioritization criterion in health benefits package (HBP) design. However, to assess CE is a time- and data-demanding process, so most HBP exercises rely wholly or partially on global evidence. Extensive investment has been made in analyses, models, and tools to support cost-effectiveness analyses (CEAs) for HBPs. However, little attention has been paid to how national HBP assessors should both understand and select costeffectiveness estimates. A structured, national process to select assessment methods is essential for ensuring the accuracy, ownership, and transparency of HBP design. This can be supported by ‘adaptive’ health technology assessment (aHTA) principles, which focus on structured methodological choices based on the time, data, and capacity available. The objective of this paper was to apply aHTA framing to CEA methods selection for HBPs, and to make recommendations on how countries may consider systematically making these choices going forward. Methods: We first reviewed the definitions and categorization of different aHTA methods. We then conducted a scoping review of previous HBP assessments to understand how CEA methods used in HBPs fit into the aHTA framework, and a follow-up survey of authors to fill gaps. Results of the literature review and survey were interpreted and narratively synthesized. Results: We found that previous HBP assessments used four aHTA methods, sometimes simultaneously: expert opinion (n=3/20), review (n=12/20), model adaptation (n=6/20), and new model (n=2/20). The literature review and survey found that aHTA methods for HBPs take between 1-13 months; require different data sources depending on the method(s) used; and generally, require capacity in health economics, medicine, public health, and cost-effectiveness modelling. We supplement our report with a discussion of key considerations for methods selection. Conclusion: Trading off time, data, and capacity needs for different CE assessment methods can help to support structured, local design of HBP assessments.

Abstract In low- and middle-income countries (LMICs), making the best use of scarce resources is essential to achieving universal health coverage. The design of health benefits packages creates the opportunity to select interventions on the basis of explicit objectives. Distributional cost-effectiveness analysis (DCEA) provides a framework to evaluate interventions based on two objectives: increasing population health and reducing health inequality. We conduct aggregate DCEA of potential health benefits package interventions to demonstrate the feasibility of this approach in LMICs, using the case of the Malawian health benefits package. We use publicly available survey and census data common to LMICs and describe what challenges we encountered and how we addressed them. We estimate that diseases targeted by the health benefits package are most prevalent in the poorest population quintile and least prevalent in the richest quintile. The survey data we use indicate socioeconomic patterns in intervention uptake that diminish the population health gain and inequality reduction from the package. We find that a similar set of interventions would be prioritized when impact on health inequality is incorporated alongside impact on overall population health. However, conclusions about the impact of individual interventions on health inequalities are sensitive to assumptions regarding the health opportunity cost, the utilization of interventions, the distribution of diseases across population groups and the level of aversion to inequality. Our results suggest that efforts to improve access to the Essential Health Package could be targeted to specific interventions to improve the health of the poorest fastest but that identifying these interventions is uncertain. This exploratory work has shown the potential for applying the DCEA framework to inform health benefits package design within the LMIC setting and to provide insight into the equity impact of a health benefits package.