Inform Resource Allocation Decisions Research Articles

Exploration of preferences among people with COPD to inform resource allocation: a discrete choice experiment study

IntroductionTreatment options for chronic obstructive pulmonary disease (COPD) are numerous but adherence remains a key challenge. We performed a discrete choice experiment (DCE) of patients’ preferences in accessing care for...

Inferred attractiveness gravity-based models for estimating realized access at rural hospitals

Operating obstetric units in rural America is financially challenging in part due to low birth volume. Birth volume at a hospital decreases when birthers bypass it to go to a farther hospital. Beyond financial considerations, it is important from a healthcare equity perspective for hospitals to know whether certain subgroups of birthers avoid utilizing the hospital’s services. This can better inform resource allocation decisions targeting those subgroups. In this paper, we use a nonlinear programming optimization model, inferred attractiveness gravity-based model (GBM), to estimate realized access to obstetric care at hospitals in Montana. We compare three variations of GBM and benchmark our results to a regression-based conditional logit model. Results indicate that hospital attractiveness varies across the level of obstetric care provided and depends on the subgroup of birthers considered. While all GBMs produced smaller errors for hospitals with higher birth volumes, our novel variant was more accurate for low-volume hospitals. Bootstrapping analyses and resolving the models for population subgroups indicated large variations in hospital attractiveness. Research findings contribute to new knowledge about equity in access to obstetric care, the importance of considering population heterogeneity in GBMs, and the benefit of using hospital demand-based thresholds for GBMs in rural settings.

Innovation Pipeline: A framework for value-based decision making.

The concept of value-based healthcare and focus on health outcomes is not new. While these ideas have been shared for decades, health systems still struggle to implement value-based decision making. This article describes the Innovation Pipeline, a framework that embeds value-based decision making in a healthcare organization. The Innovation Pipeline outlines the measurable evidence requirements needed to demonstrate organizational definitions of value. This evidence of value allows health leaders to make decisions supported by rigorous data, evidence, and evaluation, ensuring initiatives that bring organizational value progress from good ideas that require testing to evidence-based services embedded and sustained in operational workflows. The Innovation Pipeline is rigorous and customizable to all levels of the health system and designed to streamline evidence-generation activities, focusing on collecting evidence needed to demonstrate value and inform funding and resource allocation decisions.

Assessing the Health and Welfare Benefits of Interventions Using the Wider Societal Impacts Framework

ObjectivesHealth technology assessment bodies advocate capturing the value of interventions in terms of their benefits to health and broader welfare. The wider societal impacts (WSI) framework considers how changes in health alter a person’s net contribution to society—that is, what they produce minus what they consume. In this research, we review this framework and explore the scope to differentiate WSI by equity-relevant sociodemographic characteristics. MethodsThis research updates previous calculations using publicly available data from population-based surveys in the United Kingdom. We then estimate for 199 chronic conditions: (1) WSI for the average person with the condition and (2) gain in WSI for an improvement of 0.1 in health-related quality of life score. ResultsThe nature and availability of information varied across population-based surveys and precluded analyses to examine WSI by population subgroup. Our updated estimates mirrored earlier findings that consideration of the broader societal impacts of health would reprioritize interventions compared with assessment on health alone. For example, for the same improvement in health, a woman experiencing diseases of the circulatory system has the highest potential gain in WSI (£354/month) whereas a man experiencing HIV has the lowest potential gain (£233/month). ConclusionsThe WSI framework provides a simple, indirect method to inform resource allocation decisions. Understanding the equity implications of this approach was hindered by differences in the information collected across population-based surveys. Findings demonstrate the potential reprioritization that may occur if the broader welfare benefits of health interventions were used to inform coverage decisions.

Brand perception and its relationships to satisfaction with a virtual sporting event

PurposeThe purpose of this study is to use structural equation modeling to examine the interaction between the variables of corporate image, credibility, trust and satisfaction in the context of a virtual sporting event. The aim is to determine whether these variables have significant relationships with each other and which of them has the greatest influence on the prediction of participants' satisfaction.Design/methodology/approachA structured questionnaire was used, based on previously validated scales. The survey was administered using the LimeSurvey platform. The sample consisted of a total of 588 participants of the Medellín virtual marathon.FindingsThe results of the study reveal significant findings regarding the relationships between the variables of corporate image, credibility, trust, and satisfaction in virtual sporting events. In particular, it is highlighted that trust emerges as the most influential factor in participants' satisfaction, which offers an insightful understanding of the importance of this variable in the user experience in virtual sporting events.Research limitations/implicationsThis study emphasizes the importance of brand analysis in the sports environment, stressing that the actions undertaken by managers should highlight both the corporate image and the connections with users, given their fundamental role in customer satisfaction. Likewise, the study of these variables within the sports context provides new knowledge and fills existing gaps within the academy. Limitations include the sample and the lack of consideration of all brand variables.Practical implicationsThe need to cultivate a strong and well-managed image to build trust with participants is emphasized for organizers of virtual sporting events. It is crucial to work on establishing long-term credibility, especially in the relatively new context of virtual racing. Maintaining, and building the virtual career offering is essential to strengthening relationships, demonstrating a robust corporate image. In addition, since trust and credibility have a significant impact on participant satisfaction in this type of event, managers must communicate the assurance that virtual careers offer an experience free of uncertainty and risk, which is particularly attractive to a new customer base interested in this format.Originality/valueThis article presents an original contribution by investigating the relationships between corporate image, credibility, trust, and satisfaction in the context of virtual sporting events. It employs a structural equation model to assess the significance and predictive capacity of these variables. Notably, the study identifies trust as the most influential factor in predicting participant satisfaction. These findings offer valuable insights into the relative importance of brand variables in shaping user satisfaction within the virtual sporting event domain. By shedding light on these dynamics, the research aids event managers in making informed resource allocation decisions, contributing to a nuanced understanding of brand impact in this context.

A quality appraisal of economic evaluations of community water fluoridation: A systematic review.

To critically appraise the methodological conduct and reporting quality of economic evaluations (EE) of community water fluoridation (CWF). A systematic literature search was conducted in general databases and specialist directories of the economic literature. The Consensus on Health Economic Criteria list (CHEC) appraised the methodological quality while the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) assessed the reporting quality of included studies. A total of 1,138 records were identified, of which 18 met the inclusion criteria. Cost analysis emerged as the most prevalent type of EE, though a growing trend towards conducting full EEs is observed. CHEC revealed the items most frequently unfulfilled were the study design, measurement and valuation of costs and outcomes, while CHEERS also identified reporting deficiencies in these aspects. Furthermore, the review highlights subtleties in methodological aspects that may not be discerned by CHEC, such as the estimation of the impact of fluoridation and the inclusion of treatment savings within cost estimates. While numerous studies were conducted before publication of these assessment instruments, this review reveals that a noteworthy subset of studies exhibited good methodological conduct and reporting quality. There has been a steady improvement in the methodological and reporting quality over time, with recently published EEs largely adhering to best practice guidelines. The evidence presented will assist policymakers in leveraging the available evidence effectively to inform resource allocation decisions. It may also serve as a resource for researchers to enhance the methodological and reporting standards of future EEs of CWF.

Healthcare use and costs in the last six months of life by level of care and cause of death

BackgroundExisting knowledge on healthcare use and costs in the last months of life is often limited to one patient group (i.e., cancer patients) and one level of healthcare (i.e., secondary care). Consequently, decision-makers lack knowledge in order to make informed decisions about the allocation of healthcare resources for all patients. Our aim is to elaborate the understanding of resource use and costs in the last six months of life by describing healthcare use and costs for all causes of death and by all levels of formal care.MethodUsing five national registers, we gained access to patient-level data for all individuals who died in Norway between 2009 and 2013. We described healthcare use and costs for all levels of formal care—namely primary, secondary, and home- and community-based care —in the last six months of life, both in total and differentiated across three time periods (6-4 months, 3-2 months, and 1-month before death). Our analysis covers all causes of death categorized in ten ICD-10 categories.ResultsDuring their last six months of life, individuals used an average of healthcare resources equivalent to €46,000, ranging from €32,000 (Injuries) to €64,000 (Diseases of the nervous system and sense organs). In terms of care level, 63% of healthcare resources were used in home- and community-based care (i.e., in-home nursing, practical assistance, or nursing home care), 35% in secondary care (mostly hospital care), and 2% in primary care (i.e., general practitioners). The amount and level of care varied by cause of death and by time to death. The proportion of home- and community-based care which individuals received during their last six months of life varied from 38% for cancer patients to 92% for individuals dying with mental diseases. The shorter the time to death, the more resources were needed: nearly 40% of all end-of-life healthcare costs were expended in the last month of life across all causes of death. The composition of care also differed depending on age. Individuals aged 80 years and older used more home- and community-based care (77%) than individuals dying at younger ages (40%) and less secondary care (old: 21% versus young: 57%).ConclusionsOur analysis provides valuable evidence on how much healthcare individuals receive in their last six months of life and the associated costs, broken down by level of care and cause of death. Healthcare use and costs varied considerably by cause of death, but were generally higher the closer a person was to death. Our findings enable decision-makers to make more informed resource-allocation decisions and healthcare planners to better anticipate future healthcare needs.

Data-driven decision making: Shaping the future of business efficiency and customer engagement

Data-driven decision-making (DDDM) is a critical approach that organizations are adopting to enhance their operational efficiency and customer engagement. This abstract explores the significance of DDDM in shaping the future of businesses. Data-driven decision-making (DDDM) is revolutionizing the way businesses operate and engage with customers. By leveraging data analytics, organizations can extract valuable insights to inform strategic decisions, improve operational efficiency, and enhance customer experiences. This abstract examines the role of DDDM in shaping the future of business efficiency and customer engagement. DDDM enables organizations to optimize their processes and resources through data analysis. By identifying patterns and trends in data, businesses can streamline operations, reduce costs, and improve productivity. For example, predictive analytics can help forecast demand, allowing businesses to adjust their inventory levels accordingly and avoid stockouts or overstock situations. Additionally, data-driven insights can inform resource allocation decisions, ensuring that resources are allocated efficiently to maximize returns. DDDM also plays a crucial role in enhancing customer engagement. By analyzing customer data, businesses can gain a deeper understanding of customer behavior, preferences, and needs. This enables businesses to tailor their products and services to better meet customer expectations, leading to higher customer satisfaction and loyalty. For example, personalized marketing campaigns based on customer data can significantly improve engagement and conversion rates. As the volume and complexity of data continue to grow, DDDM will become even more essential for businesses. Advancements in technology, such as artificial intelligence and machine learning, will further enhance the capabilities of DDDM, allowing businesses to derive even more value from their data. However, organizations must also address challenges such as data privacy and security to ensure that DDDM is implemented ethically and responsibly. In conclusion, DDDM is reshaping the future of business efficiency and customer engagement. By embracing DDDM, organizations can unlock the full potential of their data and gain a competitive edge in today's data-driven world.

Investigating methods of sharing data between police, health, education, and social services: Semi-structured interviews with police service areas in Wales

The Crime and Disorder Act (1998) requires the police, local authorities, NHS, and other organisations to share intelligence and collectively work to reduce violent crime. This paper aimed to explore opinions on linking police data with other agency data. Interviews were undertaken with individuals from police forces in Wales, UK. Barriers to sharing data with other organisations involve differences in the systems used to store police data and uncertainties around what is allowed to be shared. Overcoming barriers would allow data linkage across organisations leading to deeper insights into the causes of violence, and therefore intelligence that supports crime prevention. Background The Crime and Disorder Act of 1998 requires the police, local authorities, the NHS, and other organisations to work together on collective approaches to reduce crime and to analyse shared data to inform resource allocation decisions. Data sharing has been conducted on a per-project basis, but it is rare for whole population data to be linked across organisations. The purpose of this study was to investigate the feasibility of linking national data from the police with national data from other agencies including health data from General Practitioners, hospitals, and Emergency Departments (EDs). In addition, this study explored the views and opinions from police service areas in Wales on using a single software system to cover all police service areas for public protection purposes and to facilitate sharing data with other agencies. Methods Semi-structured interviews were conducted with 36 individuals from the 4 police services in Wales along with representatives from the Violence Prevention Unit (VPU) and the Police Liaison Unit (PLU). The interviews were analysed using codebook thematic analysis to generate key themes from qualitative responses. Results Two key themes and seven sub-themes were developed from the qualitative data. The key themes include the following: (1) Opinions on the systems used in the police for public protection including thoughts on the current system and moving to using one system. (2) Opinions on data sharing including what data should be shared, benefits of data sharing, barriers to data sharing (within the police and across organisations), and overcoming barriers to data sharing. Interviewees identified that a proprietary relational database, Niche, was the most used system for public protection, was highly regarded, and individuals felt that if all forces moved to the same system this would be a positive development. However, work needs to be undertaken to ensure there is a minimum dataset entered in each area as there is high variability in data quality. Barriers included not knowing what was possible to share and fear of sharing. An unambiguous framework endorsed at a high level of what data should and shouldn’t be shared was recommended to overcome this. Conclusions The main barriers to shared police data included a lack of clarity around data governance and what is appropriate to share. It was felt that sharing should be the default position and with support these barriers could be removed. Data sharing between agencies would require high-level support and unambiguous guidelines as to what data can be shared, with whom, and in what format.

Genetic kidney disease has a higher likelihood and cost of inpatient admissions compared to other aetiologies

PurposeThere is increasing recognition of monogenic aetiologies for kidney disease. We sought to identify whether genetic kidney disease (GKD) has distinct hospitalization patterns compared to other forms of chronic kidney disease (CKD). MethodsHealth service utilization analysis was undertaken in a CKD cohort study across public hospital services in Queensland, Australia. CKD due to clinically coded potential monogenic causes was compared to all other causes in terms of annual frequency, cost, and type of hospital admission. ResultsWe analyzed 7 years of hospital admissions data (809,188 admissions) among 29,046 patients. Compared to non-genetic CKD, GKD was associated with a higher likelihood and cost of admissions. GKD had consistently more admissions (mean excess annual number of admissions increasing from 5.2 in year 1 to 13.4 in year 7) and more costly admissions (mean excess annual cost increasing from $5,265 in year 1 to $12,993 in year 7). This gap in hospitalization likelihood and cost increased over time for both surgical and medical admission episodes, but not for all (immunological, cancer) causes of admissions. ConclusionUnderstanding the nature and extent of differences in healthcare needs between GKD and other CKD will enable better secondary prevention and inform resource allocation decisions to reduce healthcare system pressures attributable to knowable causes.

Factors Influencing the Institutionalization of Health Technology Assessment: A Scoping Literature Review

ABSTRACT There is global interest in institutionalizing Health Technology Assessment (HTA) to inform resource allocation decisions. However, institutionalization of HTA remains limited particularly in low- and lower-middle-income countries. We conducted this scoping review to synthesize evidence on factors that influence the institutionalization of HTA at the macro (national)-level across countries globally. We searched for relevant literature in six databases namely PubMed, Embase, CINAHL, Scopus, EconLit, and Google Scholar. We conducted the last search on December 31, 2021. We identified 77 articles that described factors that influence institutionalization of HTA across 135 high-, middle-, and low-income countries. We analyzed these articles thematically. We identified five sets of factors that influence the institutionalization of HTA across countries of different income levels. These factors include: (1) organizational resources such as organizational structures, and skilled human, financial, and information resources; (2) legal frameworks, policies, and guidelines for HTA; (3) learning and advocacy for HTA; (4) stakeholder-related factors such as stakeholders’ interests, awareness, and understanding; and (5) collaborative support for HTA through international networks and non-governmental and multi-lateral organizations. Countries seeking to institutionalize HTA should map the availability of the factors identified in this review. Developing these factors wherever necessary can influence a country’s capacity to institutionalize the conduct and use of HTA.

Logical Inconsistencies in the Health Years in Total and Equal Value of Life-Years Gained

ObjectivesThis study aimed to assess whether recently proposed alternatives to the quality-adjusted life-year (QALY), intended to address concerns about discrimination, are suitable for informing resource allocation decisions. MethodsWe consider 2 alternatives to the QALY: the health years in total (HYT), recently proposed by Basu et al, and the equal value of life-years gained (evLYG), currently used by the Institute for Clinical and Economic Review. For completeness we also consider unweighted life-years (LYs). Using a hypothetical example comparing 3 mutually exclusive treatment options, we consider how calculations are performed under each approach and whether the resulting rankings are logically consistent. We also explore some further challenges that arise from the unique properties of the HYT approach. ResultsThe HYT and evLYG approaches can result in logical inconsistencies that do not arise under the QALY or LY approaches. HYT can violate the independence of irrelevant alternatives axiom, whereas the evLYG can produce an unstable ranking of treatment options. HYT have additional issues, including an implausible assumption that the utilities associated with health-related quality of life and LYs are “separable,” and a consideration of “counterfactual” health-related quality of life for patients who are dead. ConclusionsThe HYT and evLYG approaches can result in logically inconsistent decisions. We recommend that decision makers avoid these approaches and that the logical consistency of any approaches proposed in future be thoroughly explored before considering their use in practice.

Enhancing Performance and Security in the Metaverse: Latency Reduction Using Trust and Reputation Management

In the rapidly evolving landscape of distributed systems, security stands as a significant challenge, especially in the face of network node attacks. Such threats introduce profound complexities into the dynamics of security protocols, trust management, and resource allocation, issues further amplified by the metaverse’s exponential growth. This paper proposes an innovative solution, offering unique technical contributions to address these multi-faceted challenges. We unveil a trust-based resource allocation framework designed to facilitate the secure and efficient sharing of computational resources within the metaverse. This system has the potential to markedly diminish latency, thereby enhancing overall performance. In parallel, we introduce a reputation system that systematically monitors latency across a spectrum of metaverse entities, providing valuable insights for making informed resource allocation decisions. Moreover, we advocate for a decentralized trust management system, specifically designed to withstand potential security breaches without reliance on a centralized authority. This significantly fortifies both system security and user trust. Alongside this, we unveil an inventive proof-of-trust consensus mechanism that fosters trust and collaboration among metaverse entities during resource allocation, thereby cultivating a more secure ecosystem. Our proposed model poses a robust challenge to malicious entities, and it substantially bolsters the security architecture. The simulation results lend substantial credence to the effectiveness of our approach, demonstrating significant improvements in latency reduction, scalability, and the detection of malicious nodes, thereby outperforming existing methodologies.

Estimating the number of people living with dementia at different stages of the condition in India: A Delphi process.

Numerous studies have previously estimated the dementia prevalence in India. However, as these estimates use different methodologies and sampling strategies, generating definitive prevalence estimates can be difficult. A Delphi process involving eight clinical and academic experts provided prevalence estimates of dementia within India, split by sex and age. The experts were also asked to estimate the number of people potentially living at different stages of the condition. A priori criteria were used to ascertain the point in which consensus was achieved. Our consensus estimates generated a dementia prevalence of 2.8% (95% CI = 1.9 to 3.6) for those aged 60years and above in India. Consensus was achieved across age and sex prevalence estimates, with the exception of one (females aged 60-64). Our experts estimated that 42.9% of people living with dementia in India had a mild severity. The findings indicate that there could be approximately 3.9 million people living with dementia in India, of which 1.7 million could be living with dementia of mild severity. Such estimates can better help researchers and policy makers to estimate the true cost and impact of dementia in India and can inform resource allocation decisions.

Determining the efficiency path to universal health coverage: cost-effectiveness thresholds for 174 countries based on growth in life expectancy and health expenditures

Assessment of the efficiency of interventions is paramount to achieving equitable health-care systems. One key barrier to the widespread use of economic evaluations in resource allocation decisions is the absence of a widely accepted method to define cost-effectiveness thresholds to judge whether an intervention is cost-effective in a particular jurisdiction. We aimed to develop a method to estimate cost-effectiveness thresholds on the basis of health expenditures per capita and life expectancy at birth and empirically derive these thresholds for 174 countries. We developed a conceptual framework to assess how the adoption and coverage of new interventions with a given incremental cost-effectiveness ratio will affect the rate of increase of health expenditures per capita and life expectancy at the population level. The cost-effectiveness threshold can be derived so that the effect of new interventions on the evolution of life expectancy and health expenditure per capita is set within predefined goals. To provide guidance on cost-effectiveness thresholds and secular trends for 174 countries, we projected country-level health expenditure per capita and life expectancy increases by income level based on World Bank data for the period 2010-19. Cost-effectiveness thresholds per quality-adjusted life-year (QALY) ranged between US$87 (Democratic Republic of the Congo) and $95 958 (USA) and were less than 0·5 gross domestic product (GDP) per capita in 96% of low-income countries, 76% of lower-middle-income countries, 31% of upper-middle-income countries, and 26% of high-income countries. Cost-effectiveness thresholds per QALY were less than 1 GDP per capita in 168 (97%) of the 174 countries. Cost-effectiveness thresholds per life-year ranged between $78 and $80 529 and between 0·12 and 1·24 GDP per capita, and were less than 1 GDP per capita in 171 (98%) countries. This approach, based on widely available data, can provide a useful reference for countries using economic evaluations to inform resource-allocation decisions and can enrich international efforts to estimate cost-effectiveness thresholds. Our results show lower thresholds than those currently in use in many countries. Institute for Clinical Effectiveness and Health Policy (IECS).

Managerial competence and innovation performance: The mediating role of willingness to change, entrepreneurial orientation and culture

Small and medium-sized enterprises (SMEs) significantly influence Saudi Arabia’s economic stability and growth. However, this industry faces significant managerial competence (MC) and innovation performance (IP) obstacles. Based on the findings of previous studies, i.e., Kellermanns and Eddleston (2006), De Clercq et al. (2015), Vafaei-Zadeh et al. (2019) and Renwarin et al. (2023) and the dire need for further exploration, the researchers developed the conceptual framework and model for confirmation in the context of Saudi Arabia. The study aims to investigate the direct and indirect linkages between MC and IP, mediated by a willingness to change (WTC), entrepreneurial orientation (EO), and entrepreneurial culture (EC) among SMEs in Saudi Arabia. The study used responses from 368 managers of Saudi Arabian SMEs. The structural equation modeling (SEM) analysis results confirmed that MC has a significant positive effect on WTC, IP, EO and EC. Besides, the factors such as WTC, EO, and EC positively and significantly affect IP. Finally, the mediation analysis through path analysis suggests a mediating role of WTC, EO and EC between MC and IP. The findings of this study can assist SME managers in making informed resource allocation decisions that can lead to maximum outcomes for their businesses. Besides, this study can help SME managers overcome challenges while improving their organizations’ innovation performance.

Expanding health technology assessment towards broader value: Ireland as a case study.

Healthcare innovations often represent important improvements in population welfare, but at what cost, and to whom? Health technology assessment (HTA) is a multidisciplinary process to inform resource allocation. HTA is conventionally anchored on health maximization as the only relevant output of health services. If we accept the proposition that health technologies can generate value outside the healthcare system, resource allocation decisions could be suboptimal from a societal perspective. Incorporating "broader value" in HTA as derived from social values and patient experience could provide a richer evaluative space for informing resource allocation decisions. This article considers how HTA is practiced and what its current context implies for adopting "broader value" to evaluating health technologies. Methodological challenges are highlighted, as is a future research agenda. Ireland serves as an example of a healthcare system that both has an explicit role for HTA and is evolving under a current program of reform to offer universal, single-tier access to public services. There are various ways in which HTA processes could move beyond health, including considering the processes of care delivery and/or expanding the evaluative space to some broader concept of well-being. Methods to facilitate the latter exist, but their adaptation to HTA is still emerging. We recommend a multi-stakeholder working group to develop and advance an international agenda for HTA that captures welfare/benefit beyond health.

The subjective expected utility approach and a framework for defining project risk in terms of novelty and feasibility – A response to Franzoni and Stephan (2023), ‘uncertainty and risk-taking in science’

In their Discussion Paper, Franzoni and Stephan (F&S, 2023) discuss the shortcomings of existing peer review models in shaping the funding of risky science. Their discussion offers a conceptual framework for incorporating risk into peer review models of research proposals by leveraging the Subjective Expected Utility (SEU) approach to decouple reviewers' assessments of a project's potential value from its risk. In my Response, I build on F&S's discussion and attempt to shed light on three additional yet core considerations of risk in science: 1) how risk and reward in science are related to assessments of a project's novelty and feasibility; 2) how the sunk cost literature can help articulate why reviewers tend to perceive new research areas as riskier than continued investigation of existing lines of research; and 3) how drawing on different types of expert reviewers (i.e., based on domain and technical expertise) can result in alternative evaluation assessments to better inform resource allocation decisions. The spirit of my Response is to sharpen our understanding of risk in science and to offer insights on how future theoretical and empirical work—leveraging experiments— can test and validate the SEU approach for the purposes of funding more risky science that advances the knowledge frontier.

Assessing the potential of HTA to inform resource allocation decisions in low-income settings: The case of Malawi.

Health technology assessment (HTA) offers a set of analytical tools to support health systems' decisions about resource allocation. Although there is increasing interest in these tools across the world, including in some middle-income countries, they remain rarely used in low-income countries (LICs). In general, the focus of HTA is narrow, mostly limited to assessments of efficacy and cost-effectiveness. However, the principles of HTA can be used to support a broader series of decisions regarding new health technologies. We examine the potential for this broad use of HTA in LICs, with a focus on Malawi. We develop a framework to classify the main decisions on health technologies within health systems. The framework covers decisions on identifying and prioritizing technologies for detailed assessment, deciding whether to adopt an intervention, assessing alternative investments for implementation and scale-up, and undertaking further research activities. We consider the relevance of the framework to policymakers in Malawi and we use two health technologies as examples to investigate the main barriers and enablers to the use of HTA methods. Although the scarcity of local data, expertise, and other resources could risk limiting the operationalisation of HTA in LICs, we argue that even in highly resource constrained health systems, such as in Malawi, the use of HTA to support a broad range of decisions is feasible and desirable.

The Cost of Neurodevelopmental Disability: Scoping Review of Economic Evaluation Methods.

The provision of effective care models for children with neurodevelopmental delay or disability can be challenging in resource constrained healthcare systems. Economic evaluations have an important role in informing resource allocation decisions. This review systematically examined the scope and methods of economic models evaluating interventions for supporting neurodevelopment among children with common neurodevelopmental disorders and identified methods of economic models and presented policy implications. This scoping review employed the Arksey and O’Malley framework and aligned with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Four electronic databases were systematically searched to identify eligible model-based economic evaluations of neurodevelopmental care models published since 2000. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist was used to assess quality of reporting. Data were systematically extracted, tabulated, and qualitatively synthesised across diagnostic categories. Searches identified 1431 unique articles. Twelve studies used a decision analytic model to evaluate care for neurodevelopmental disorders and were included in the review. Included studies focused on attention-deficit/hyperactivity disorder (ADHD, n=6), autism spectrum disorder (ASD, n=3), cerebral palsy (n=2), and dyslexia (n=1). The most used decision analytic modelling approach was a Markov model (n=6), followed by a decision tree (n=3), and a combination of decision tree and Markov model (n=3). Most studies (n=7) adopted a societal perspective for reporting costs. None of the reviewed studies modelled impact on families and caregivers. Four studies reported cost-savings, three identified greater quality of life, and three identified cost increases.