Medical Decision Making最新文献

BackgroundParenthood is a key life goal for many, but infertility affects about 1 in 6 globally. While fertility treatments offer solutions, their high costs limit access. Many health systems provide public funding, yet budget constraints prevent fully funded access, often leaving patients with significant out-of-pocket costs. Policy makers face the challenge of prioritizing individuals for publicly funded treatments, but how to do this remains unclear and underresearched. Worldwide, funding policies vary widely, often adopting controversial access criteria.MethodsWe investigated Belgian population preferences for prioritizing in vitro fertilization (IVF) funding through a discrete-choice experiment with a representative sample of 3,000 Belgians. Attributes included maternal and partner age, infertility cause, civil status, prior biological children, and treatment cost. Using a Bayesian D-optimal design and panel mixed logit model, we assessed criteria relevance. The resulting multiattribute utility function created a priority ranking of couples, which we compared to the ranking under the current Belgian policy, which focuses only on maternal age (<43 y).ResultsAnalysis of 29,670 prioritization choices identified maternal age, infertility cause, and prior biological children as key criteria. Maternal age of 35 y was prioritized highest, age 25 y as high as 40 y, followed by declining priority until 55 y. Biomedical malfunctions were prioritized over same-sex relationships or unhealthy lifestyles, with the latter prioritized lowest. Having no prior biological children was prioritized categorically higher than having 1, 2, or 3 children, all prioritized equally. Preferences were homogeneous across sociodemographic groups.ConclusionsHow to set IVF funding priorities remains a matter of debate. Our study shows that the Belgian population considers multiple criteria beyond maternal age to prioritize couples, calling for further discussion on ethical justifiability and access implications.HighlightsParenthood is a key life goal to many, but about 1 in 6 are affected by infertility. However, in most countries, public funding for fertility treatment is not provided to everyone who could benefit, and hard choices are inevitable.This study used a discrete-choice experiment in a representative sample of the Belgian population to investigate which criteria should be used for prioritization.Results indicated that maternal age, cause of infertility, and the number of prior biological children were the most significant factors in determining public support for IVF funding. Partner age, civil status of the couple, and cost of IVF treatment were not important.People use multiple criteria to set IVF funding priorities, beyond maternal age (the only criterion used in the current Belgian funding policy). Future research should explore the ethical justifiability and practical implications of using cause of infertility and number of prior children as additional

IntroductionThis study introduces a simulation-optimization framework designed to optimize the services of opioid-focused harm reduction vending machines (HRVMs). Given the rising rates of overdose deaths and increased potential for infectious diseases among persons who inject drugs (PWID), HRVMs can become an important harm reduction (HR) strategy by providing essential supplies that mitigate health risks.MethodsWe developed and validated an agent-based simulation-optimization framework to model the impact of HRVM-item allocation on the burden of opioid-related harms, accounting for demand dynamics, item restocking, and regional characteristics. The model evaluated health outcomes-cases of HIV, HCV, and fatal and nonfatal overdose-using disability-adjusted life-years (DALYs). Scenario-based analyses were conducted for different HRVM configurations, considering current legal limits on safer-injection supplies, fentanyl's growing role as a drug of choice, and potential future policy changes.ResultsThe base scenario estimated optimal HRVM capacity allocation at approximately 48.5% fentanyl test strips (FTS), 26.2% naloxone, and 25.3% safer injection kits. However, sensitivity analyses showed significant variations based on fentanyl prevalence and willingness to use FTS. In scenarios of intentional fentanyl use with high FTS utilization, allocation favored FTS, while scenarios with low FTS utilization prioritized naloxone and injection kits. Adding addiction treatment referral services to HRVMs further reduced DALYs and societal costs, primarily by preventing fatal overdoses. Safer injection kits consistently reduced blood-borne infections compared with scenarios without these kits.ConclusionsThe framework could aid in HRVMãrelated service planning and evaluation, highlighting the importance of strategic inventory management and linkages to addiction care for enhanced health outcomes. HRVMs show potential as scalable, cost-effective HR interventions, warranting further research on their impact on service accessibility and health outcomes.HighlightsA novel simulation-optimization framework for designing and evaluating harm reduction vending machines (HRVMs) is presented.Optimal baseline allocation for products in the HRVMs included fentanyl test strips (48.5%), naloxone (26.2%), and safer injection kits (25.3%).Sensitivity analysis indicated optimal allocations vary substantially by local fentanyl prevalence and by individual harm reduction behaviors surrounding the use of fentanyl test strips.HRVM implementation reduces societal costs and disability-adjusted life-years associated with substance use-related harms.

BackgroundSurvival extrapolation is used to predict patients' overall survival beyond clinical trial follow-up. It can significantly affect the results of a cost-effectiveness analysis and subsequent pricing and reimbursement decisions. However, selecting an appropriate model involves subjectivity, leading to discrepancies between methods submitted by manufacturers and those accepted by health technology assessment (HTA) agencies. This review describes the acceptance and criticisms of overall survival extrapolation methods by HTA agencies in England, France, and Australia.MethodsElectronic searches conducted on September 4, 2022, identified HTA evaluations for oncology therapies indicated for the treatment of solid tumors from the National Institute for Health and Care Excellence (NICE) in England, the Haute Autorité de Santé (HAS) in France, and the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia, published between August 2017 and August 2022. Information on the overall survival extrapolation model submitted by the manufacturer was extracted. The acceptance decision of the HTA agency and the key criticisms were also recorded.ResultsA total of 140 HTA evaluations were identified. The initial overall survival extrapolation method was accepted in 21% of cases. The most frequently cited criticisms related to a lack of or inappropriate incorporation of treatment effect waning over time (31%). Other criticisms included choice of parametric distribution, in which multiple distributions were often considered plausible (24%); immaturity of survival data (15%); and concerns about the proportional hazards assumption, which lacked clinical validity (8%).ConclusionThis review highlights the low acceptance of survival extrapolation methods and the areas of discordance between manufacturers and HTA agencies in England, France, and Australia. Low acceptance rates of survival extrapolation methods by HTA bodies can affect pricing and reimbursement decisions of new therapies, delaying patient access.HighlightsThis review found that the survival extrapolation methods initially submitted by companies were accepted in only 21% of cases.The most common areas of discordance between companies and HTA agencies were inappropriate modeling of treatment effect over time, choice of parametric distribution, immaturity of survival data, and concerns about the proportional hazards assumption.There is a need for more consistent guidance on the selection of an appropriate extrapolation method to limit the inherent subjectivity surrounding survival curve selection.

ObjectivesAboriginal and Torres Strait Islander children and adolescents are at higher risk of overweight and obesity, highlighting an inequitable public health concern. The aim of this study was to estimate transition probabilities and validate a model predicting the epidemiologic trajectory of overweight and obesity in Australian Aboriginal and Torres Strait Islander children.MethodsAn individual-level state-transition Markov model was developed to model transitions between healthy weight, overweight, and obesity for Aboriginal and Torres Strait Islander children aged between 2 and 14 y. Age-specific annual transition probabilities were derived from semi-parametric survival analyses using the Longitudinal Study of Indigenous Children. The model used annual cycles over a 12-y time horizon, and the epidemiological predictions of the model were validated using both internal and external data, according to best practice guidelines. The starting age of the model was 2 to 4 y and 4 to 5 y for the internal and external validation, respectively. Aboriginal and Torres Strait Islander children from the Longitudinal Study of Australian Children were used as the external validation cohort.ResultsA total of 1,643 children with 11,514 complete anthropometric measurements were used to estimate transition probabilities. The model predictions showed both good internal and external validity, with most predictions falling within the 95% confidence intervals of measured data. The model was able to reliably capture the epidemiology of overweight and obesity prevalence in early childhood.ConclusionsOur model predictions showed good internal and external validity, ensuring our model is fit for purpose to use to evaluate Aboriginal and Torres Strait Islander-led programs to achieve a healthy weight.HighlightsAboriginal and Torres Strait Islander children experience high rates of overweight and obesity; hence, there is a need for high-quality evidence on both effectiveness and cost-effectiveness of Aboriginal and Torres Strait Islander-led childhood obesity prevention programs to ensure they offer value for money.This is the first study to develop and validate a predictive model using anthropometric data from Aboriginal and Torres Strait Islander children to inform decision making on childhood obesity programs.Our model predictions showed good internal and external validity, ensuring our model is fit for purpose to use to evaluate Aboriginal and Torres Strait Islander-led programs to achieve a healthy weight.The model provides a framework to assist policy makers in identifying when best to intervene in childhood as well as the most effective approaches for maintaining a healthy weight for Aboriginal and Torres Strait Islander children.

BackgroundStatin Choice is a shared decision-making encounter tool embedded in the electronic health record.ObjectiveTo describe the association between the use of Statin Choice, statin prescriptions by clinicians, prescription fills (primary adherence), and statin adherence at 12 mo (secondary adherence).DesignObservational cohort study at the Cleveland Clinic Health System.SubjectsStatin-naïve adults aged 40 to 75 y with a 10-y atherosclerotic cardiovascular disease (ASCVD) risk of ≥5% and a primary care appointment between January 2020 and July 2021.Main MeasuresThe primary exposure was the use of Statin Choice during a clinical encounter. We measured whether the use of Statin Choice was associated with statin prescriptions. We measured statin adherence based on pharmacy fill data at 60 d (primary adherence) and 12 mo (secondary adherence). We used mixed-effects logistic regression to estimate the adjusted odds of statin prescriptions and adherence at the 3 time points by the use of Statin Choice.Key ResultsAmong 17,001 statin-naïve patients, 13% viewed Statin Choice and 7% were prescribed a statin. The median ASCVD risk was 10%. Patients who were shown Statin Choice had 9.04 higher odds of being prescribed a statin compared with patients not shown Statin Choice (95% confidence interval [CI]: 7.86-10.4). Among patients prescribed a statin, the use of Statin Choice was associated with 5.75 higher odds of primary adherence compared with usual care (95% CI: 4.22-7.83). At 12 mo, Statin Choice use was significantly associated with adherence in the unadjusted analysis (OR: 1.58; 95% CI: 1.05-2.08) but was not significant after adjustment for patient factors. Patients shown Statin Choice had an average of 12 mg/dL reduction in low-density lipoprotein cholesterol at 12 mo (95% CI: -16 mg/dL, -10) compared with those not shown Statin Choice.ConclusionIn this observational study, Statin Choice use was strongly associated with statin prescription and fills and weakly associated with adherence to statins for up to 1 y. A randomized trial is needed to confirm causality.HighlightsStatin Choice is an electronic health record-embedded shared decision-making encounter tool available for free in many health care systems.Small randomized controlled trials have found modest associations between the use of Statin Choice and statin adherence using patient-reported data.In our large study using pharmacy fill data, clinician use of Statin Choice during a medical encounter was associated with significantly greater patient adherence with statins up to 1 y later.Exposure to Statin Choice was associated with a significant reduction in low-density lipoprotein cholesterol over 1 y.

BackgroundIncorporating clinician and patient perspectives in the measurement of shared decision making (SDM) is aligned with SDM's inherently dyadic nature. There are no tools measuring SDM in pediatrics from multiple perspectives. The objective of this study was to develop a tool to measure SDM from the perspectives of both clinicians and parents of young children.DesignWe used a stepwise iterative approach to tool development beginning with de novo item generation and followed by augmentation of the item pool by adapting items from existing instruments. After the study team removed redundant items, 3 parents and 3 SDM experts rated the remaining items for their ability to capture SDM in pediatrics; items with the lowest mean ratings were removed. To assess the preliminary tool's face validity, usability, and item understandability, we pretested it, revising it iteratively, with sequential cohorts of English-speaking parents and clinicians from 2 US children's hospitals.ResultsWe generated an initial list of 28 items for the parent and clinician versions of the tool, which we reduced to 20 items after preliminary review. After review by parents and SDM experts, we cut 9 items and added 1 additional item for a total of 12 items. We pretested the preliminary tool with 31 clinicians and 30 parents across 3 sequential cohorts. The final tool contained 12 items and an optional free-text item.LimitationsAll participants were English speaking, limiting its generalizability.ConclusionsWe have developed a usable preliminary tool for measuring the dyadic process of SDM in pediatrics.ImplicationsThis tool represents an important first step toward addressing the measurement of SDM in pediatrics from multiple perspectives.HighlightsIn this study, we have developed the first shared decision making (SDM) tool specifically for use with parents of young children.Although further study is needed to determine the psychometric properties of this tool, it has the potential to address an important gap in our ability to measure SDM in pediatrics from multiple perspectives.

BackgroundRecent studies show that low-risk pancreatic cysts may require less frequent monitoring. Future guidelines will likely adapt their recommendations accordingly. Our goal was to explore the willingness of individuals with a low-risk pancreatic cyst to undergo less frequent surveillance and to identify associated characteristics with such willingness.MethodsThis is a side study of the international PACYFIC study, which prospectively collects data on cyst surveillance, including questionnaires to assess participants' attitude toward surveillance. Individuals with low-risk cysts at baseline, without given standardized information by the study protocol, were enrolled. Their responses to the baseline question, "Would you prefer less frequent surveillance? Yes/No," were correlated with baseline characteristics using multivariable logistic regression, namely, age, country of residence, symptoms, medical and family history, time since first cyst detection, and Hospital Anxiety Depression Scale score.ResultsOf the 215 participants included from the Netherlands (n = 185) and Italy (n = 30), only 47 (22%) were willing to undergo less surveillance. Characteristics positively associated with this willingness were older age (odds ratio [OR] 1.87 per 10 y, 95% confidence interval [CI]: 1.15-3.04) and Italian residency (OR 16.35, 95% CI: 5.65-47.31). A medical history of cancer was negatively associated (OR 0.28, 95% CI: 0.09-0.90). No other associations were observed.ConclusionMost participants appear unwilling to undergo less frequent cyst surveillance. Older age and residing in Italy were associated with a greater willingness toward less rigorous surveillance, while a history of cancer did the opposite. Identifying which individuals are hesitant to undergo less frequent surveillance may help clinicians tailor their counseling and can support implementation of future guideline with fewer surveillance recommendations.HighlightsMost low-risk individuals were reluctant toward less frequent pancreatic cyst surveillance.Older age and residency in Italy were associated with a higher willingness.A medical history of cancer was associated with an unwillingness.Standardized patient information may increase the willingness, but such information has yet to be developed.

BackgroundValues clarification methods may be particularly appropriate for decision support in lung cancer screening (LCS), for which patients must consider a complex tradeoff of benefits and harms. Values clarification methods that are explicit and use theory-based methods may best support decision making.PurposeTo characterize values clarification methods in decision support tools for LCS and explore associations with behavioral and decisional outcomes.Data SourcesPubMed, Cochrane Library, CINAHL, APA PsycINFO, and Embase, supplemented with gray literature and hand searches.Study SelectionStudies evaluating patient-facing LCS decision support tools.Data ExtractionWe extracted information on study characteristics and the decision support tools evaluated in each study, including method of values clarification (explicit, implicit, or none). Study quality was evaluated using an adapted version of the SUNDAE Checklist.Data SynthesisWe identified 48 studies (10,233 participants) evaluating 32 unique decision support tools for LCS. More than 80% of tools included values clarification methods, split between explicit (n = 13) and implicit (n = 13) methods. Only 1 explicit values clarification used a theory-based method. Meta-analysis of randomized controlled trials indicated that using a decision support tool doubled the odds of receiving LCS (pooled odds ratio 1.98, 95% confidence interval 1.21-3.25, 9 studies), a pattern driven by increased uptake of screening following use of tools with explicit or no values clarification. Studies lacking values clarification were of lower quality than those with explicit or implicit methods (P = 0.04).LimitationsAlmost no tools applied theory-based methods for explicit values clarification, limiting conclusions about their impact.ConclusionsLCS decision support tools routinely incorporate values clarification methods and appear to enhance screening uptake. However, theory-based values clarification methods, which may further improve decision support quality, remain underutilized.HighlightsValues clarification is a core aspect of shared decision making. It may be especially valuable for decision making regarding lung cancer screening (LCS), as patients must weigh a complex balance of benefits and harms.This systematic review identified 48 studies assessing 32 unique decision support tools for LCS. More than 80% of these tools incorporated values clarification methods, with an equal distribution of explicit and implicit methods.Among the subset of studies using a randomized controlled trial, the use of a decision support tool doubled the odds of an individual undergoing LCS.Decision support tools designed to support shared decision making in LCS commonly incorporate values clarification methods. However, they infrequently use theory-based methods, which are increasingly thought to provide high-quality decision support.

PurposeIt is unclear whether caregivers help or hinder patients' involvement in decision making and understanding of illness. We thus investigated the extent to which caregivers' preferred level of patient involvement in decision making and understanding of treatment goals are associated with those of patients.MethodsWe used survey data from 229 patients with metastatic cancer and their family caregivers living in Singapore spanning 2 y prior to the patient's death. We used mixed-effects regressions to investigate the associations between 1) caregiver-preferred level of patient involvement (t_-1) and patient preferred and perceived level of involvement in decision making at subsequent assessments (t₁) and 2) patient and caregiver understanding of treatment goals at the same assessments (t₁).ResultsCaregivers who preferred higher levels of patient involvement in decision making at t_-1 were more likely to have patients who also preferred higher levels of involvement (odds ratio [OR] = 1.19; P = 0.03) and who perceived experiencing higher levels of involvement in decision making (OR = 1.24; P < 0.01) at t₁. Compared with an uncertain understanding of treatment goals, caregivers who had an inaccurate understanding at t₁ were more likely to have patients who had an inaccurate understanding (relative risk ratio [RRR] = 8.56; P = 0.03), and caregivers who had an accurate understanding at t₁ were more likely to have patients with an accurate understanding (RRR = 3.02; P = 0.01) at t₁.ConclusionOur findings suggest that caregiver preferences for patient involvement in decision making and understanding of treatment goals are significantly associated with those of patients. Enhancing caregiver education and involvement may be pivotal in improving patient participation and comprehension in the context of metastatic cancer care.HighlightsPatients of caregivers who preferred higher levels of patient involvement in decision making at earlier time points were more likely to prefer and experience higher levels of involvement in decision making at subsequent assessments.Patients of caregivers with an inaccurate understanding of treatment goals were more likely to have an inaccurate understanding, while patients of caregivers with an accurate understanding were also more likely to have an accurate understanding.

IntroductionEffective risk communication is essential for medical professionals to assist patients to make informed decisions. However, risk communication can be challenging as patients receive ambiguous and conflicting information.ObjectivesThis study aimed to examine how uncertainty influences individuals' perceptions and preferences and interacts with message framing in a medical treatment decision scenario.MethodsThe present study included a large representative sample of Australians (N = 805). A randomized experiment was conducted presenting a scenario about hypothetical COVID-19 treatment alternatives with varying uncertainty and framing in treatment information.ResultsThe results showed that conflicting information and loss framing had deleterious effects on participants' willingness to take a treatment and trust in the sources providing the information, compared with information that was precise, ambiguous, or in a gain frame. The effects could be stronger among participants who are risk averse, anxious, and native language speakers.ConclusionThe findings highlight that patients may be more averse to a treatment option and reduce their trust in medical professionals when they are provided with ambiguous information and particularly when information that conflicts with other sources including other medical professionals. It is important for medical professionals to be aware of other information patients have sourced that may conflict with information provided by the medical professionals during the consultation and to assist patients with high levels of risk aversion and anxiety in their decision making.HighlightsConflicting information and loss framing had deleterious effects on participants' willingness to take a treatment.Conflicting information and loss framing also reduced participants' trust in the sources of the information.The deleterious effects were stronger among participants who were native language speakers and were risk averse and anxious.