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Introduction: Financial incentives to stop smoking (FISS) programs have been implemented internationally to encourage people who smoke to quit smoking. However, such programs require that the financial reward structure and its resulting effects on smoking quit rates are considered. We analyzed a number of scenarios for FISS reward schedules for current smoking individuals in Ireland, with a view to identify the potential implications in terms of financial consequences and expected effects. Methods: Using national QuitManager services data 2021–2023, we defined smoking quit rates for smokers currently using the national Health Services Executive stop smoking services in Ireland. Smoking quit rates at 4, 12 and 52 weeks were defined, and additionally defined by sex, age and education level. Using scenarios assuming different FISS reward sizes, structures and targeted population sub-groups, we estimated the number of additional quitters, budget impact, and incremental costeffectiveness ratio. Results: A FISS program, if implemented for a cohort of 3500 smokers can result in a budget impact ranging €250000 – €870000. The cost-effectiveness trade-off between different payment schedules and the expected effect size suggested that FISS are cost-effective even at a moderate effect size. A FISS program implemented to approximately 20000 smokers nationally would cost between €2.0 million and €4.8 million, subject to the chosen reward schedule. Across social groups, FISS is more cost-effective for females, individuals in the youngest age group, and individuals with a medium level of education. Conclusions: This analysis highlights the importance of considering different FISS schedules and potential quit effects, when designing such programs. We highlight that FISS programs should be targeted at certain social groups to achieve highest long-term smoking cessation rates. We also identified important challenges that decision-makers face when designing the reward structure of FISS programs. The acceptability or otherwise of the FISS structures may differ among stakeholders and should be explored. [ABSTRACT FROM AUTHOR]

Background: Health services research often relies on quasi-experimental study designs in the estimation of treatment effects of a policy change or an intervention. The aim of this study is to compare some of the commonly used non-experimental methods in estimating intervention effects, and to highlight their relative strengths and weaknesses. We estimate the effects of Activity-Based Funding, a hospital financing reform of Irish public hospitals, introduced in 2016. Methods: We estimate and compare four analytical methods: Interrupted time series analysis, Difference-in-Differences, Propensity Score Matching Difference-in-Differences and the Synthetic Control method. Specifically, we focus on the comparison between the control-treatment methods and the non-control-treatment approach, interrupted time series analysis. Our empirical example evaluated the length of stay impact post hip replacement surgery, following the introduction of Activity-Based Funding in Ireland. We also contribute to the very limited research reporting the impacts of Activity-Based-Funding within the Irish context. Results: Interrupted time-series analysis produced statistically significant results different in interpretation, while the Difference-in-Differences, Propensity Score Matching Difference-in-Differences and Synthetic Control methods incorporating control groups, suggested no statistically significant intervention effect, on patient length of stay. Conclusion: Our analysis confirms that different analytical methods for estimating intervention effects provide different assessments of the intervention effects. It is crucial that researchers employ appropriate designs which incorporate a counterfactual framework. Such methods tend to be more robust and provide a stronger basis for evidence-based policy-making. [ABSTRACT FROM AUTHOR]

Background: The SARS-CoV-2 pandemic caused severe disruption to scheduled surgery in Ireland but its impact on emergency abdominal surgery (EAS) is unknown. Aims: The primary objective was to identify changes in volume, length of stay (LOS), and survival outcomes following EAS during the pandemic. A secondary objective was to evaluate differences in EAS patient flow including admission source, ITU utilisation, discharge destination, and readmission rates. Methods: Using a national administrative dataset, demographic, comorbidity, and patient flow data on 5611 patients admitted for EAS between 2018 and 2020 were extracted. Pre-pandemic and pandemic timeframes were compared using graphic and regression analyses, and bivariate logistic regression, adjusting for demographics and case-mix. Results: There was a 19.9% decrease in EAS during the 2020 COVID-19 pandemic with no difference in comorbidity, nor in the commonest procedures. Most patients (92.4%) were admitted from home. In-hospital post-operative mortality was unchanged (7.6%). Patients over 80 comprised 16.3% of EAS pre-COVID, but 17.9% during COVID. Average total LOS reduced significantly by 4.9 days and 3.5 days during COVID-19 waves 1 (29 Feb 2020–30 June 2020) and 2 (1 July 2020–30 Nov 2020), respectively. During wave 1, pre-operative LOS reduced (1 day) and ICU LOS was significantly shorter (0.8 days), but similar change was not observed during wave 2. Conclusions: Significant improvements in patient flow following admission for EAS during the pandemic were observed. These changes were not associated with greater mortality nor increased readmission rates and offer important insights into optimal delivery of EAS services. [ABSTRACT FROM AUTHOR]

Background: In the absence of electronic health records, analysis of direct healthcare costs often relies on resource utilisation data collected from patient-reported surveys. This scoping review explored the availability, use and methodological details of self-reported healthcare service utilisation and cost data to assess healthcare costs in Ireland. Methods: Population health surveys were identified from Irish data repositories and details were collated in an inventory to inform the literature search. Irish cost studies published in peer-reviewed and grey sources from 2009 to 2019 were included if they used self-reported data on healthcare utilisation or cost. Two independent researchers extracted studies' details and the PRISMA-ScR guidelines were used for reporting. Results: In total, 27 surveys were identified containing varying details of healthcare utilisation/cost, health status, demographic characteristics and health-related risk and behaviour. Of those surveys, 21 were general population surveys and six were study-specific ad-hoc surveys. Furthermore, 14 cost studies were identified which used retrospective self-reported data on healthcare utilisation or cost from ten of the identified surveys. Nine of these cost studies used ad-hoc surveys and five used data from pre-existing population surveys. Compared to population surveys, ad-hoc surveys contained more detailed information on resource use, albeit with smaller sample sizes. Recall periods ranged from 1 week for frequently used services to 1 year for rarer service use, or longer for once-off costs. A range of perspectives (societal, healthcare and public sector) and costing approaches (bottom-up costing and a mix of top-down and bottom-up) were used. The majority of studies (n = 11) determined unit prices using multiple sources, including national healthcare tariffs, literature and expert views. Moreover, most studies (n = 13) reported limitations concerning data availability, risk of bias and generalisability. Various sampling, data collection and analysis strategies were employed to minimise these. Conclusion: Population surveys can aid cost assessments in jurisdictions that lack electronic health records, unique patient identifiers and data interoperability. To increase utilisation, researchers wanting to conduct cost analyses need to be aware of and have access to existing data sources. Future population surveys should be designed to address reported limitations and capture comprehensive health-related, demographic and resource use data. [ABSTRACT FROM AUTHOR]

Background: Activity-Based Funding (ABF) has been implemented across many countries as a means to incentivise efficient hospital care delivery and resource use. Previous reviews have assessed the impact of ABF implementation on a range of outcomes across health systems. However, no comprehensive review of the methods used to generate this evidence has been undertaken. The aim of this review is to identify and assess the analytical methods employed in research on ABF hospital performance outcomes. Methods: We conducted a scoping review in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Five academic databases and reference lists of included studies were used to identify studies assessing the impact of ABF on hospital performance outcomes. Peer-reviewed quantitative studies published between 2000 and 2019 considering ABF implementation outside the U.S. were included. Qualitative studies, policy discussions and commentaries were excluded. Abstracts and full text studies were double screened to ensure consistency. All analytical approaches and their relative strengths and weaknesses were charted and summarised. Results: We identified 19 studies that assessed hospital performance outcomes from introduction of ABF in England, Korea, Norway, Portugal, Israel, the Netherlands, Canada, Italy, Japan, Belgium, China, and Austria. Quasi-experimental methods were used across most reviewed studies. The most commonly used assessment methods were different forms of interrupted time series analyses. Few studies used difference-in-differences or similar methods to compare outcome changes over time relative to comparator groups. The main hospital performance outcome measures examined were case numbers, length of stay, mortality and readmission. Conclusions: Non-experimental study designs continue to be the most widely used method in the assessment of ABF impacts. Quasi-experimental approaches examining the impact of ABF implementation on outcomes relative to comparator groups not subject to the reform should be applied where possible to facilitate identification of effects. These approaches provide a more robust evidence-base for informing future financing reform and policy. [ABSTRACT FROM AUTHOR]

Background: Colon cancer is the second most common cause of cancer-related death and an important cause of morbidity. The natural history of carcinogenesis, via the adenoma-carcinoma sequence, permits screening, which reduces the relative risk of mortality by up to 16%. The efficacy of a screening programme is limited by the growth of interval colorectal cancers between screening examinations. Quantifying the rate of interval cancers and delineating contributing endoscopic factors are crucial to maximise the benefit of a screening program.Methods: A systematic review was performed in accordance with PRISMA principles. Electronic databases were interrogated with a considered search strategy, and reference lists of retrieved papers were surveyed. For inclusion, studies included the rate of interval cancer (stated or calculated) and reported at least one of a predefined list of endoscopy characteristics. The primary outcome was to establish the rate of interval cancers. The secondary outcome was to determine the association between endoscopy quality measures and interval cancers.Results: The search yielded 2067 papers. Seventy-six full text papers were reviewed. Fifteen papers met the inclusion criteria. In total, there were 117,793 colon cancers, 7281 of which were interval lesions, giving an overall rate of 6.2%. The adenoma detection rate (ADR) of the endoscopist performing the index operation was the most consistent endoscopy factor associated with development of interval cancers. The impact of setting, volume and bowel preparation varied between papers.Conclusion: Interval cancers reduce the efficacy of colorectal screening programmes. Ensuring the quality of the endoscopy process, specifically by increasing the ADR of practitioners, is crucial to the reduction of the rate of interval cancers. [ABSTRACT FROM AUTHOR]

Background: Health services research often relies on quasi-experimental study designs in the estimation of treatment effects of a policy change or an intervention. The aim of this study is to compare some of the commonly used non-experimental methods in estimating intervention effects, and to highlight their relative strengths and weaknesses. We estimate the effects of Activity-Based Funding, a hospital financing reform of Irish public hospitals, introduced in 2016.Methods: We estimate and compare four analytical methods: Interrupted time series analysis, Difference-in-Differences, Propensity Score Matching Difference-in-Differences and the Synthetic Control method. Specifically, we focus on the comparison between the control-treatment methods and the non-control-treatment approach, interrupted time series analysis. Our empirical example evaluated the length of stay impact post hip replacement surgery, following the introduction of Activity-Based Funding in Ireland. We also contribute to the very limited research reporting the impacts of Activity-Based-Funding within the Irish context.Results: Interrupted time-series analysis produced statistically significant results different in interpretation, while the Difference-in-Differences, Propensity Score Matching Difference-in-Differences and Synthetic Control methods incorporating control groups, suggested no statistically significant intervention effect, on patient length of stay.Conclusion: Our analysis confirms that different analytical methods for estimating intervention effects provide different assessments of the intervention effects. It is crucial that researchers employ appropriate designs which incorporate a counterfactual framework. Such methods tend to be more robust and provide a stronger basis for evidence-based policy-making. [ABSTRACT FROM AUTHOR]