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

OBJECTIVES: Health 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. METHODS: This 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. RESULTS: The 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). CONCLUSIONS: The 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.

Social Decision-Making Analysis: A General Approach to Inform Decisions on Resources in the Public Sector.

OBJECTIVES: Public expenditure aims to achieve social objectives by improving a range of socially valuable attributes of benefit (arguments in a social welfare function). Public expenditure is typically allocated to public sector budgets, where budget holders are tasked with meeting a subset of social objectives. METHODS: Decision makers require an evidence-based assessment of whether a proposed investment is likely to be worthwhile given existing levels of public expenditure. However, others also require some assessment of whether the overall level and allocation of public expenditure are appropriate. This article proposes a more general theoretical framework for economic evaluation that addresses both these questions. RESULTS: Using a stylized example of the economic evaluation of a new intervention in a simplified UK context, we show that this more general framework can support decisions beyond the approval or rejection of single projects. It shows that broader considerations about the level and allocation of public expenditure are possible and necessary when evaluating specific investments, which requires evidence of the range of benefits offered by marginal changes in different types of public expenditure and normative choices of how the attributes of benefit gained and forgone are valued. CONCLUSIONS: The proposed framework shows how to assess the value of a proposed investment and whether and how the overall level of public expenditure and its allocation across public sector budgets might be changed. It highlights that cost-benefit analysis and cost-effectiveness analysis can be viewed as special cases of this framework, identifying the weakness with each.

Children's behavioral and mental health in primary care settings: A survey of self-reported comfort levels and practice patterns among pediatricians.

INTRODUCTION: Despite the well-documented youth mental health crisis, there has been a lag in the development of a specialized workforce to meet needs of young people experiencing these challenges. Little is known about the comfort of primary care pediatricians when faced with children and adolescents with mental health care concerns. METHOD: A brief online survey was conducted to assess patterns of behavioral and mental health concerns in pediatric practices affiliated with a pediatric health system in Alabama. The survey asked about frequency of conditions that providers encountered, comfort treating these conditions, and frequency of external referrals. RESULTS: Pediatric providers reported high volumes of children with mental health concerns and varying levels of comfort treating independently. Providers frequently refer externally. CONCLUSIONS: High rates of referrals could further stress an already overloaded system of specialty care. Interventions must be implemented to ensure a workforce prepared to meet the growing needs of youth requiring support for mental and behavioral health conditions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Methods to Quantify the Importance of Parameters for Model Updating and Distributional Adaptation.

PURPOSE: Decision models are time-consuming to develop; therefore, adapting previously developed models for new purposes may be advantageous. We provide methods to prioritize efforts to 1) update parameter values in existing models and 2) adapt existing models for distributional cost-effectiveness analysis (DCEA). METHODS: Methods exist to assess the influence of different input parameters on the results of a decision models, including value of information (VOI) and 1-way sensitivity analysis (OWSA). We apply 1) VOI to prioritize searches for additional information to update parameter values and 2) OWSA to prioritize searches for parameters that may vary by socioeconomic characteristics. We highlight the assumptions required and propose metrics that quantify the extent to which parameters in a model have been updated or adapted. We provide R code to quickly carry out the analysis given inputs from a probabilistic sensitivity analysis (PSA) and demonstrate our methods using an oncology case study. RESULTS: In our case study, updating 2 of 21 probabilistic model parameters addressed 71.5% of the total VOI and updating 3 addressed approximately 100% of the uncertainty. Our proposed approach suggests that these are the 3 parameters that should be prioritized. For model adaptation for DCEA, 46.3% of the total OWSA variation came from a single parameter, while the top 10 input parameters were found to account for more than 95% of the total variation, suggesting efforts should be aimed toward these. CONCLUSIONS: These methods offer a systematic approach to guide research efforts in updating models with new data or adapting models to undertake DCEA. The case study demonstrated only very small gains from updating more than 3 parameters or adapting more than 10 parameters. HIGHLIGHTS: It can require considerable analyst time to search for evidence to update a model or to adapt a model to take account of equity concerns.In this article, we provide a quantitative method to prioritze parameters to 1) update existing models to reflect potential new evidence and 2) adapt existing models to estimate distributional outcomes.We define metrics that quantify the extent to which the parameters in a model have been updated or adapted.We provide R code that can quickly rank parameter importance and calculate quality metrics using only the results of a standard probabilistic sensitivity analysis.

The Health Impact of Waiting for Elective Procedures in the NHS in England: A Modeling Framework Applied to Coronary Artery Bypass Graft and Total Hip Replacement.

INTRODUCTION: The aim of this study is to demonstrate a practical framework that can be applied to estimate the health impact of changes in waiting times across a range of elective procedures in the National Health Service (NHS) in England. We apply this framework by modeling 2 procedures: coronary artery bypass graft (CABG) and total hip replacement (THR). METHODS: We built a Markov model capturing health pre- and postprocedure, including the possibility of exiting preprocedure to acute NHS care or self-funded private care. We estimate the change in quality-adjusted life-years (QALYs) over a lifetime horizon for 10 subgroups defined by sex and Index of Multiple Deprivation quintile groups and for 7 alternative scenarios. We include 18 wk as a baseline waiting time consistent with current NHS policy. The model was populated with data from routinely collected data sets where possible (Hospital Episode Statistics, Patient-Reported Outcome Measures, and Office for National Statistics Mortality records), supplemented by the academic literature. RESULTS: Compared with 18 wk, increasing the wait time to 36 wk resulted in a mean discounted QALY loss in the range of 0.034 to 0.043 for CABG and 0.193 to 0.291 for THR. The QALY impact of longer NHS waits was greater for those living in more deprived areas, partly as fewer patients switch to private care. DISCUSSION/CONCLUSION: The proposed framework was applied to 2 different procedures and patient populations. If applied to an expanded group of procedures, it could provide decision makers with information to inform prioritization of waiting lists. There are a number of limitations in routine data on waiting for elective procedures, primarily the lack of information on people still waiting. HIGHLIGHTS: We present a modeling framework that allows for an estimation of the health impact (measured in quality-adjusted life-years) of waiting for elective procedures in the NHS in England.We apply our model to waiting for coronary artery bypass graft (CABG) and total hip replacement (THR). Increasing the wait for THR results in a larger health loss than an equivalent increase in wait for CABG.This model could potentially be used to estimate the impact across an expanded group of procedures to inform prioritization of activities to reduce waiting times.

Prime editing in mice with an engineered pegRNA.

CRISPR editing involves double-strand breaks in DNA with attending insertions/deletions (indels) that may result in embryonic lethality in mice. The prime editing (PE) platform uses a prime editing guide RNA (pegRNA) and a Cas9 nickase fused to a modified reverse transcriptase to precisely introduce nucleotide substitutions or small indels without the unintended editing associated with DNA double-strand breaks. Recently, engineered pegRNAs (epegRNAs), with a 3'-extension that shields the primer-binding site of the pegRNA from nucleolytic attack, demonstrated superior activity over conventional pegRNAs in cultured cells. Here, we show the inability of three-component CRISPR or conventional PE to incorporate a nonsynonymous substitution in the Capn2 gene, expected to disrupt a phosphorylation site (S50A) in CAPN2. In contrast, an epegRNA with the same protospacer correctly installed the desired edit in two founder mice, as evidenced by robust genotyping assays for the detection of subtle nucleotide substitutions. Long-read sequencing demonstrated sequence fidelity around the edited site as well as top-ranked distal off-target sites. Western blotting and histological analysis of lipopolysaccharide-treated lung tissue revealed a decrease in phosphorylation of CAPN2 and notable alleviation of inflammation, respectively. These results demonstrate the first successful use of an epegRNA for germline transmission in an animal model and provide a solution to targeting essential developmental genes that otherwise may be challenging to edit.