bluuebunny/crossref_metadata_2025_split huggingface dataset:
OP33 Child And Adolescent Mental Health Care Models: A Scoping Review
Authors: Zechmeister-Koss Ingrid , Jeindl Reinhard , Hofer Viktoria 
Published: December 2023

IntroductionMental illnesses are among the most common health problems in children and adolescents worldwide, and their prevalence has recently increased. At the same time, many countries face gaps in care and a shortage of services. To address these challenges, countries are developing child and adolescent mental health (CAMH) strategies and adopting their models of care. This paper aimed to give an international overview of these strategies and care models to support decision makers and stimulate mutual learning and improved CAMH care.MethodsWe identified core topics within published CAMH strategies and care model documents from seven selected countries within the Global North, which represented different healthcare systems, geographical regions, and public health traditions to maximize variety. We systematically extracted data on the identified topics and summarized them narratively by applying qualitative content analyses.ResultsThe documents addressed the following core topics: awareness raising activities; prevention and promotion; detection; treatment; telemedicine; care pathways; transitional psychiatry; vulnerable patient groups; user participation; infrastructure; workforce development; implementation; digital tools for case management; and data acquisition and research. A stand-alone CAMH strategy exists in most countries.Recommendations on CAMH care often followed a public mental health approach and placed a high priority on mental health promotion and cross-sectional organization and funding of CAMH care services. Key principles of future CAMH care included: increased flexibility of care settings; early intervention; an open and non-judgmental attitude among staff; and strengths orientation instead of focusing on deficits and diagnoses.ConclusionsReducing the prevalence of mental illness and current shortcomings in care requires action at the policy level (e.g., developing a CAMH strategy with a focus on mental health promotion and installing cross-sectoral governance), organizational level (e.g., reorganizing treatment settings and pathways of care), and individual level (e.g., strengthening user involvement and workforce development). Applying the recommended approaches in other countries will likely require redesign, ideally with a participatory approach and evaluation alongside piloting.
OP34 Application Of A Case-Mix Analysis In COVID-19 Management At A University Hospital In Malaysia
Authors: Azzeri Amirah , Jaafar Mohd Hafiz , Dahlui Maznah 
Published: December 2023

IntroductionThe COVID-19 pandemic significantly affected healthcare systems. The most immediate effect was the increased demand for healthcare resources. This study aimed to conduct a case-mix analysis at one of the teaching hospitals in Malaysia to understand the economic implications of the pandemic.MethodsAdmissions related to COVID-19, either as a primary or secondary diagnosis, were extracted and given ICD-10 codes for diagnosis and ICD9-CM codes for procedures. The combined ICD-10 and ICD9-CM codes were imported into a case-mix grouper to generate the case-mix codes. The codes used for COVID-19 were A-4-13-I, A-4-13-II, and A-4-13-III for mild, moderate, and severe disease, respectively. Clinical pathways were collected and healthcare resource utilization was estimated by combining top-down and bottom-up costing approaches. Discounting and inflation were based on guidelines and official rates. The cost data were reported in US dollars (price year 2021).ResultsA total of 4,889 patients with a COVID-19 diagnosis were admitted to the hospital in 2021. Of these, 4,813 patients (98%) had a primary diagnosis of COVID-19. The remaining 76 patients (2%) were admitted for other medical reasons but were found to be positive for SARS-Cov-2 during admission. Therefore, for these patients, infection with the virus was considered a secondary diagnosis during the treatment episode.Among the 4,813 patients, 3,909 (81%) were admitted with mild COVID-19 (A-4-13-I), 630 (13%) had moderate COVID-19 (A-4-13-II), and 274 (6%) had severe disease (A-4-13-III). More than half (56%) of the patients with a secondary diagnosis of COVID-19 were admitted for elective procedures. The average length of hospital stay (LOS) for mild disease was 9 days, with cumulative hospital costs of USD1,543. The average LOS for both moderate and severe disease was 21 days, and the cumulative hospital costs were USD23,527 and USD26,731 respectively. The total costs incurred for COVID-19 were estimated at USD19,259,153.ConclusionsCOVID-19 has considerable economic implications. This study provided information as part of a health technology assessment in the hospital to inform evidence-based healthcare decisions.
OP46 The Decision Uncertainty Toolkit: Risk Measures And Visual Outputs To Support Health Technology Decision-making During Public Health Crises
Authors: Kirwin Erin , McCabe Chris , Round Jeff 
Published: December 2023

IntroductionDuring public health crises such as the COVID-19 pandemic, decision-makers have relied on infectious disease models to predict and estimate the impact of various health technologies. The difficulties associated with capturing and representing uncertainty using infectious disease models leads to a high risk of making decisions that are misaligned to policy objectives. Even when uncertainty is adequately captured in the analysis, the tools for communicating the risks and harms of making wrong decisions have proved inadequate, which can lead to the suboptimal adoption of critical health technologies including vaccines and antivirals. We aim to adapt and extend health economic methods for the characterization, estimation, and communication of uncertainty to infectious disease modeling.MethodsEconomic and infectious disease models share many features, including the comparison of policy alternatives on outcomes important to decision-makers (such as hospital census, total infections), but each takes a different approach to analysis of uncertainty. We extend best practices from health economics to infectious disease modeling and develop a suite of tools and visualization techniques which represent parameter uncertainty and the risk these unknowns present to decision-makers.ResultsIn consultation with decision-makers and infectious disease modeling experts we developed the ‘Decision Uncertainty Toolkit’ of model outputs and visuals. Visual tools for uncertainty are developed to: (i) accurately capture uncertainty in key infectious disease model outputs, and (ii) support intuitive and direct interpretation by infectious disease modelers and decision-makers. We also developed quantitative measures for the downside risk of policy alternatives, specified to capture both the probability and magnitude of losses relative to policy targets for a range of infectious disease model outputs. Together, these outputs can support decision-making by quantifying outcome uncertainty and the risks associated with policy alternatives.ConclusionsWe developed the toolkit visuals and risk measures alongside infectious disease modelers and decision makers. The toolkit is designed to improve decision-maker understanding of decision risk in order to improve outcomes during future public health crises.
OP55 Did It Matter? Developing A Common Framework For Characterizing Impact Of Patient Involvement In Health Technology Assessment
Authors: Gousset Veronica Lopez , Silva Aline Silveira , Holtorf Anke-Peggy , Toledo-Chávarri Ana , Single Ann 
Published: December 2023

IntroductionWhile the impact of health technology assessments (HTAs) is often not evaluated, some HTA bodies measure the impact of patient involvement in their processes. Evaluating how patient involvement is perceived by all stakeholders may help to improve practices and avoid activities that unduly burden patient and HTA communities. Frameworks and tools have been designed to analyze the impact of patient engagement along the healthcare development lifecycle. Reporting on the impact of patient involvement in HTA-specific activities, however, continues to be infrequent, unstandardized, and not comprehensive.Having a common framework to characterize and report on the impact of patient involvement may enable this practice to be optimized and harmonized across HTA contexts.MethodsThe Patient and Citizen Involvement Interest Group (PCIG) within Health Technology Assessment International set out to contextualize this impact and support reporting. A questionnaire was developed, piloted, and rolled out to collect multistakeholder personal perceptions of the impact of patient involvement in individual HTAs. Questions included: “What difference did you feel patient involvement made in the HTA activity?” and “What would have been missed without patient involvement?”. From January 2019 to September 2021, 24 responses (including one joint submission) were collected through the PCIG’s network from HTA bodies (11), patient representatives (12), and industry representatives (2) from North America (5), South America (3), Europe (13), and Australia (3).ResultsCommon themes were extracted from these experiences to characterize the impact of patient participation in HTA processes. Based on these commonalities, a harmonized framework consisting of three “domains” is proposed: impact on the decision-making process; impact on patient stakeholders; and impact on the HTA body. The framework includes a set of items under each domain to support reporting.ConclusionsBy having common language and measures, the HTA community can harmonize processes across jurisdictions to evaluate and communicate the value of patient involvement in HTA. Improving consistent reporting may facilitate more efficient process improvement for meaningful integration of patient stakeholders into HTA decision-making.
OP57 Consumer Engagement In Health Technology Assessment: An Australian Journey To Date
Authors: Watson Jo , Wortley Sally 
Published: December 2023

IntroductionAustralian health technology assessment (HTA) committees and processes at the national level have needed to consider an increasing focus on patient involvement and interactions within their scope. As various approaches have been explored, the visibility and impacts of patient involvement and consumer representation has evolved markedly over the most recent five years.MethodsProgram activities were developed from review of contemporary HTA models of practice across various HTA sectors internationally alongside input from individual patients and patient groups. Practical application of program pilots was influenced by specific requirements of the Office of HTA, the coordination of HTA Committee procedures and timelines, and involvement of HTA Committee consumer members.ResultsThe development of capacity building programs for HTA consumer committee members, the growth of external activity and communications targeting patient groups and networks, and the establishment of an expert position to develop the HTA Consumer Evidence and Engagement Unit within the Department’s Office of HTA, are all examples of the work delivered in this period to better integrate patient evidence and inputs into HTA processes and decision-making. Activities over the next period will seek to establish formal frameworks for meaningful involvement that can demonstrate these contributions to evaluations and decision-making.ConclusionsVarious examples of patient involvement and participation in processes have evolved over time. The scope and impacts of these experiences have illustrated important participatory demands and resourcing needs, as well potential benefits for deliberations. The Australian Government and Departmental frameworks for HTA currently seek to enhance the development of patient evidence inputs and participation. These developments will be informed by the Australian context and comprehensive consultation with Australian patient groups and their networks. Strategies for improvements are anticipated to be relevant across all HTA processes and Committees within HTA areas.
OP58 Challenges In Maintaining Up To Date Health Technology Assessments in Rare Diseases: Lessons From Fabry Disease In Australia
Authors: Nicholls Kathleen , Denaro Charles , Tchan Michel , Ellaway Carolyn , Bratkovic Drago , Palmer Hazel , Campbell Sheridan , Fookes Megan , Thomas Mark 
Published: December 2023

IntroductionFabry disease is a rare, inherited X-linked lysosomal storage disease characterized by a wide spectrum of heterogeneously progressive clinical phenotypes, and which results in progressive kidney disease, cardiomyopathy, cerebrovascular disease, and reduced life expectancy. Disease-specific therapy aims to improve symptoms, stabilize current disease and delay progression. In Australia treatment access requires that patients meet pre-specified criteria, which have been in place for more than 15 years. Patient questions prompted the patient organization, Fabry Australia, to investigate why these criteria had remained unchanged despite significant progress in the understanding and management of Fabry disease.MethodsA panel comprising two members of Fabry Australia and its Medical Advisory Committee conducted a review of the literature. The aim of this was to inform the clinical quality of the Australian treatment access criteria with reference to international guidelines and contemporary data. The findings from the literature were applied to develop consensus recommendations for classification and Fabry-specific treatment initiation criteria in diagnosed patients.ResultsEvidence supports earlier treatment with reduced barriers to access in some circumstances. Australian access criteria are misaligned with this. They do not distinguish between classical and non-classical Fabry phenotypes, neglect the impact of quality of life and gastrointestinal symptoms, and impose symptom-severity related criteria, which may lead to unnecessary treatment initiation delay. An updated framework is presented. It differentiates phenotypes, facilitates more timely access to Fabry-specific treatment for classical males, and supports relevant organ involvement criteria in classical females and patients with non-classical disease.ConclusionsA well-performing health technology assessment system facilitates patient access to cost-effective treatments that improve health outcomes. Timely treatment initiation is important to avoid irreversible organ damage in Fabry patients. Patients’ questions about out-dated access criteria has prompted research and uncovered barriers that are no longer clinically valid. The perspectives of the patient as a stakeholder in their disease management should not be overlooked when assessing the value of health technologies in the rare disease setting.
OP60 Community Funding Prioritization Of Drug Treatments: A Discrete Choice Experiment
Authors: Fifer Simon , West Bronwyn , Kong Samson 
Published: December 2023

IntroductionAllocating government resources for drug treatments continues to be a challenge in health care, particularly given the increasing number of high-cost personalized drug treatments, finite resources, and aging population. Since taxpayers fund government health budgets, it is important to understand how they think funding should be distributed, considering attributes such as cost of drug treatments, risk of dying, commonality of medical conditions, and quality of life changes with drug treatments. The aim of this study was to understand what attributes of a medical condition and treatment determine a community’s willingness to fund new drug treatments. Two decision-making contexts were explored: the allocation of funds from a health budget and a willingness-to-pay (WTP) perspective.MethodsA representative sample of 500 Australian adults completed an online survey. The survey comprised two discrete choice experiments (DCEs) with different framing: an allocation of government funds and a WTP for drug treatments. The government allocation DCE allowed a choice between two hypothetical alternatives, each describing the medical condition and the drug treatment, while the WTP for funding showed one hypothetical alternative with an option to not fund the drug treatment. Seven DCE attributes, informed by a literature review, were displayed in each choice set relating to the medical condition (risk of dying, prevalence, and ages affected) and to the drug treatment (change in quality of life, additional life-years, availability of other drug treatments, and cost to the government and the taxpayer).ResultsThe resulting DCE model will establish the funding prioritization choices made by the general community. We expect changes in quality of life and risk of dying to be very important attributes. Of key interest for this study is how the difference in the decision-making context impacts preferences. We expect taxpayers to employ a stricter rule set in funding decisions when paying out of pocket (WTP exercise).ConclusionsThe findings from this research have implications for decision makers when aligning funding decisions with community preferences and values.
OP63 Incorporating Machine Learning Methods In Health Economic Evaluations: A Case Study On Depression Prevention
Authors: Lokkerbol Joran 
Published: December 2023

IntroductionNew methodologies such as machine learning are becoming widely available and are increasingly used. However, more guidance on their role in the context of economic evaluations would be beneficial.MethodsWe developed a machine learning model to predict recurrent depressive episodes and incorporated the model outcomes in a health economic model to assess the cost effectiveness of offering targeted prevention of recurrent depression. We considered the impact on cost effectiveness (defined as cost per quality-adjusted life-year) for machine learning models with different thresholds for classifying a patient as being at risk, resulting in different precision-recall pairs.ResultsTargeted prevention of recurrent depression could enhance the cost effectiveness of depression treatment by preventing a small number of recurrent depressive episodes in patients where the estimated risk of recurrence is relatively high. More depressive episodes could be prevented with the trade-off of less cost effectiveness for the healthcare system.ConclusionsHealth economic modeling approaches can be augmented with machine learning methods, which broadens the areas in which evidence can be generated for policy makers to base their budget allocation. The precision of such predictive machine learning models must be high enough to be able to improve a care-as-usual healthcare system. Machine learning models generally let you set the level of precision acquired, at the cost of a possibly low recall, thereby limiting the impact on the healthcare system as a whole. More and better data for training these machine learning models will allow developed models to better distinguish patients who will and won’t develop a recurrent depressive episode, and for higher recall given a desired precision threshold. This will translate into a more substantial improvement in the treatment of depressive disorders in the healthcare system.
OP74 Analysis Of Literature And Research Foci In Overdiagnosis Based On Citespace
Authors: Yan Juntao , Wei Yan , Yang Yi , Liu Shimeng , Chen Yingyao 
Published: December 2023

IntroductionWith the rapid development of innovative health technologies, evidence increasingly shows that overdiagnosis is harmful to a person’s health and that it is a global public health issue. This study aimed to analyze the current research status and corresponding foci in the field of overdiagnosis in Chinese and English databases using bibliometric methods.MethodsA search was conducted in the English Web of Science Core Collection database and the Chinese China National Knowledge Infrastructure database for literature published from inception to 31 December 2021. CiteSpace (version 5.8 R1) software was used to perform bibliometric analysis on the countries, institutions, and keyword clusters of the included literature on overdiagnosis and to draw a corresponding visual knowledge map.ResultsA total of 2,841 English and 43 Chinese publications were included. There was an increasing trend in the annual publication volume of both Chinese and English literature, with the publication volume of English research increasing significantly since 2010. In terms of countries and institutions, the top ten in English research on overdiagnosis were all from high income countries. The cooperation among these countries and institutions was close, unlike in China where the cooperation was relatively limited. Analysis of keyword clustering showed that the potential research foci for English literature on overdiagnosis included breast cancer, thyroid cancer, prostate cancer, lung cancer, and other tumor types, whereas the clustering in Chinese records was relatively scattered and mainly focused on overdiagnosis of thyroid cancer.ConclusionsThe research topics in the Chinese literature on overdiagnosis lag significantly behind English research. It is suggested that more research on overdiagnosis and related fields should be actively promoted and conducted in China in the future.
OP83 Diagnostic Accuracy And Cost Effectiveness Of Automated Ankle Brachial Pressure Index Measurement For Peripheral Arterial Disease In People With Leg Ulceration
Authors: Boyers Dwayne , Cruickshank Moira , Aucott Lorna , Kennedy Charlotte , Manson Paul , Bachoo Paul , Brazzelli Miriam 
Published: December 2023

IntroductionLeg ulcers are usually treated with compression therapy unless there is evidence of peripheral arterial disease (PAD). Compression may lead to vascular complications in people with PAD. Timely diagnosis and appropriate treatment are important to ensure the best patient outcomes. PAD is usually assessed using a manual ankle brachial pressure index (ABPI). Automated devices may reduce time to diagnosis and treatment of leg ulcers. This study investigated the diagnostic accuracy, clinical effectiveness, and cost effectiveness of automated ABPI measurement, compared with manual doppler testing, to detect PAD in people with leg ulcers.MethodsWe conducted a systematic review of studies of any design assessing automated devices in any population. Meta-analyses were conducted where possible. A decision tree and Markov model was used to capture lifetime costs, quality-adjusted life-years (QALYs), and cost effectiveness from a UK National Health Service perspective. Sensitivity analyses captured the uncertainty surrounding model assumptions and probabilistic sensitivity analyses described parameter uncertainty. Value of information analysis was conducted to identify future research priorities.ResultsA total of 22 studies provided diagnostic accuracy data for five automated devices, but there were no studies in people with leg ulcers. Meta-analysis of 12 studies demonstrated a pooled sensitivity of 64 percent (95% confidence interval [CI]: 57, 71) and a specificity of 96 percent (95% CI: 92, 98) for detecting PAD. Automated devices were cheaper to complete due to shorter test times, but the increased risk of inappropriate or delayed treatment due to inaccurate test results offset the cost savings and reduced the QALYs for automated devices.ConclusionsGiven the current limited evidence base, automated devices would only be cost effective if they can demonstrate substantial reductions in time to diagnosis in clinical practice. Value of information analysis identified the following research priorities: (i) to determine diagnostic accuracy in a population with leg ulcers; (ii) to determine the impact of test results on ulcer healing times, and (iii) to determine the risk of providing inappropriate treatment based on inaccurate test results.