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The Effect of Patient Decision Aid Attributes on Patient Outcomes: A Network Meta-Analysis of a Systematic Review.
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-19 DOI: 10.1177/0272989X251318640
Dawn Stacey, Meg Carley, Janet Gunderson, Shu-Ching Hsieh, Shannon E Kelly, Krystina B Lewis, Maureen Smith, Robert J Volk, George Wells

Background: Patient decision aids (PtDAs) are effective interventions to help people participate in health care decisions. Although there are quality standards, PtDAs are complex interventions with variability in their attributes.

Purpose: To determine and compare the effects of PtDA attributes (e.g., content elements, delivery timing, development) on primary outcomes for adults facing health care decisions.

Data sources: A systematic review of randomized controlled trials (RCTs) comparing PtDAs to usual care.

Study selection: Eligible RCTs measured at least 1 primary outcome: informed values choice, knowledge, accurate risk perception, decisional conflict subscales, and undecided.

Data analysis: A network meta-analysis evaluated direct and indirect effects of PtDA attributes on primary outcomes.

Data synthesis: Of 209 RCTs, 149 reported eligible outcomes. There was no difference in outcomes for PtDAs using implicit compared with explicit values clarification. Compared with PtDAs with probabilities, PtDAs without probabilities were associated with poorer patient knowledge (mean difference [MD] -3.86; 95% credible interval [CrI] -7.67, -0.03); there were no difference for other outcomes. There was no difference in outcomes when PtDAs presented information in ways that decrease cognitive demand and mixed results when PtDAs used strategies to enhance communication. Compared with PtDAs delivered in preparation for consultations, PtDAs used during consultations were associated with poorer knowledge (MD -4.34; 95% CrI -7.24, -1.43) and patients feeling more uninformed (MD 5.07; 95% CrI 1.06, 9.11). Involving patients in PtDA development was associated with greater knowledge (MD 6.56; 95% CrI 1.10, 12.03) compared with involving health care professionals alone.

Limitations: There were no direct comparisons between PtDAs with/without attributes.

Conclusions: Improvements in knowledge were influenced by some PtDA content elements, using PtDA content before the consultation, and involving patients in development. There were few or no differences on other outcomes.

Highlights: This is the first known network meta-analysis conducted to determine the contributions of the different attributes of patient decision aids (PtDAs) on patient outcomes.There was no difference in outcomes when PtDAs used implicit compared with explicit values clarification.There were greater improvements in knowledge when PtDAs included information on probabilities, PtDAs were used in preparation for the consultation or development included patients on the research team.There was no difference in outcomes when PtDAs presented information in ways that decrease cognitive demand and mixed results when PtDAs used strategies to enhance communication.

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引用次数: 0
Expected Value of Sample Information Calculations for Risk Prediction Model Validation.
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-18 DOI: 10.1177/0272989X251314010
Mohsen Sadatsafavi, Andrew J Vickers, Tae Yoon Lee, Paul Gustafson, Laure Wynants

Background: The purpose of external validation of a risk prediction model is to evaluate its performance before recommending it for use in a new population. Sample size calculations for such validation studies are currently based on classical inferential statistics around metrics of discrimination, calibration, and net benefit (NB). For NB as a measure of clinical utility, the relevance of inferential statistics is doubtful. Value-of-information methodology enables quantifying the value of collecting validation data in terms of expected gain in clinical utility.

Methods: We define the validation expected value of sample information (EVSI) as the expected gain in NB by procuring a validation sample of a given size. We propose 3 algorithms for EVSI computation and compare their face validity and computation time in simulation studies. In a case study, we use the non-US subset of a clinical trial to create a risk prediction model for short-term mortality after myocardial infarction and calculate validation EVSI at a range of sample sizes for the US population.

Results: Computation methods generated similar EVSI values in simulation studies, although they differed in numerical accuracy and computation times. At 2% risk threshold, procuring 1,000 observations for external validation, had an EVSI of 0.00101 in true-positive units or 0.04938 in false-positive units. Scaled by heart attack incidence in the United States, the population EVSI was 806 in true positives gained, or 39,500 in false positives averted, annually. Validation studies with >4,000 observations had diminishing returns, as the EVSIs were approaching their maximum possible value.

Conclusion: Value-of-information methodology quantifies the return on investment from conducting an external validation study and can provide a value-based perspective when designing such studies.

Highlights: In external validation studies of risk prediction models, the finite size of the validation sample leads to uncertain conclusions about the performance of the model. This uncertainty has hitherto been approached from a classical inferential perspective (e.g., confidence interval around the c-statistic).Correspondingly, sample size calculations for validation studies have been based on classical inferential statistics. For measures of clinical utility such as net benefit, the relevance of this approach is doubtful.This article defines the expected value of sample information (EVSI) for model validation and suggests algorithms for its computation. Validation EVSI quantifies the return on investment from conducting a validation study.Value-based approaches rooted in decision theory can complement contemporary study design and sample size calculation methods in predictive analytics.

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引用次数: 0
Recalibrating an Established Microsimulation Model to Capture Trends and Projections of Colorectal Cancer Incidence and Mortality.
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-06 DOI: 10.1177/0272989X251314050
Jie-Bin Lew, Qingwei Luo, Joachim Worthington, Han Ge, Emily He, Julia Steinberg, Michael Caruana, Dianne L O'Connell, Eleonora Feletto, Karen Canfell

Background: Changing colorectal cancer (CRC) incidence rates, including recent increases for people younger than 50 y, need to be considered in planning for future cancer control and screening initiatives. Reliable estimates of the impact of changing CRC trends on the National Bowel Cancer Screening Program (NBCSP) are essential for programmatic planning in Australia. An existing microsimulation model of CRC, Policy1-Bowel, was updated to reproduce Australian CRC trends data and provide updated projections of CRC- and screening-related outcomes to inform clinical practice guidelines for the prevention of CRC.

Methods: Policy1-Bowel was recalibrated to reproduce statistical age-period-cohort model trends and projections of CRC incidence for 1995-2045 in the absence of the NBCSP as well as published data on CRC incidence trends, stage distribution, and survival in 1995-2020 in Australia. The recalibrated Policy1-Bowel predictions were validated by comparison with published Australian CRC mortality trends for 1995-2015 and statistical projections to 2040. Metamodels were developed to aid the calibration process and significantly reduce the computational burden.

Results: Policy1-Bowel was recalibrated, and best-fit parameter sets were identified for lesion incidence, CRC stage progression rates, detection rates, and survival rates by age, sex, bowel location, cancer stage, and birth year. The recalibrated model was validated and successfully reproduced observed CRC mortality rates for 1995-2015 and statistical projections for 2016-2030.

Conclusion: The recalibrated Policy1-Bowel model captures significant additional detail on the future incidence and mortality burden of CRC in Australia. This is particularly relevant as younger cohorts with higher CRC incidence rates approach screening ages to inform decision making for these groups. The metamodeling approach allows fast recalibration and makes regular updates to incorporate new evidence feasible.

Highlights: In Australia, colorectal cancer incidence rates are increasing for people younger than 50 y but decreasing for people older than 50 y, and colorectal cancer survival is improving as new treatment technologies emerge.To evaluate the future health and economic impact of screening and inform policy, modeling must include detailed trends and projections of colorectal cancer incidence, mortality, and diagnosis stage.We used novel techniques including integrative age-period cohort projections and metamodel calibration to update Policy1-Bowel, a detailed microsimulation of colorectal cancer and screening in Australia.

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引用次数: 0
Development of a Microsimulation Model to Project the Future Prevalence of Childhood Cancer in Ontario, Canada. 开发微观模拟模型,预测加拿大安大略省儿童癌症的未来发病率。
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-04 DOI: 10.1177/0272989X251314031
Alexandra Moskalewicz, Sumit Gupta, Paul C Nathan, Petros Pechlivanoglou

Background: Estimates of the future prevalence of childhood cancer are informative for health system planning but are underutilized. We describe the development of a pediatric oncology microsimulation model for prevalence (POSIM-Prev) and illustrate its application to produce projections of incidence, survival, and limited-duration prevalence of childhood cancer in Ontario, Canada, until 2040.

Methods: POSIM-Prev is a population-based, open-cohort, discrete-time microsimulation model. The model population was updated annually from 1970 to 2040 to account for births, deaths, net migration, and incident cases of childhood cancer. Prevalent individuals were followed until death, emigration, or the last year of simulation. Median population-based outcomes with 95% credible intervals (CrIs) were generated using Monte Carlo simulation. The methodology to derive model inputs included generalized additive modeling of cancer incidence, parametric survival modeling, and stochastic population forecasting. Individual-level data from provincial cancer registries for years 1970 to 2019 informed cancer-related model inputs and internal validation.

Results: The number of children (aged 0-14 y) diagnosed with cancer in Ontario is projected to rise from 414 (95% CrI: 353-486) in 2020 to 561 (95% CrI: 481-653) in 2039. The 5-y overall survival rate for 2030-2034 is estimated to reach 90% (95% CrI: 88%-92%). By 2040, 24,088 (95% CrI: 22,764-25,648) individuals with a history of childhood cancer (diagnosed in Ontario or elsewhere) are projected to reside in the province. The model accurately reproduced historical trends in incidence, survival, and prevalence when validated.

Conclusions: The rising incidence and prevalence of childhood cancer will create increased demand for both acute cancer care and long-term follow-up services in Ontario. The POSIM-Prev model can be used to support long-range health system planning and future health technology assessments in jurisdictions that have access to similar model inputs.

Highlights: This article describes the development of a population-based, discrete-time microsimulation model that can simulate incident and prevalent cases of childhood cancer in Ontario, Canada, until 2040.Use of an open cohort framework allowed for estimation of the potential impact of net migration on childhood cancer prevalence.In addition to supporting long-term health system planning, this model can be used in future health technology assessments, by providing a demographic profile of incident and prevalent cases for model conceptualization and budget impact purposes.This modeling framework is adaptable to other jurisdictions and disease areas where individual-level data for incidence and survival are available.

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引用次数: 0
Changes in Risk Tolerance for Ovarian Cancer Prevention Strategies during the COVID-19 Pandemic: Results of a Discrete Choice Experiment. COVID-19大流行期间卵巢癌预防策略风险承受能力的变化:离散选择实验的结果
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2024-12-25 DOI: 10.1177/0272989X241302829
Brian L Egleston, Mary B Daly, Kaitlyn Lew, Lisa Bealin, Alexander D Husband, Jill E Stopfer, Pawel Przybysz, Olga Tchuvatkina, Yu-Ning Wong, Judy E Garber, Timothy R Rebbeck

Background: Prior to COVID-19, little was known about how risks associated with such a pandemic would compete with and influence patient decision making regarding cancer risk reducing medical decision making. We investigated how the pandemic affected preferences for medical risk-reducing strategies among women at elevated risk of breast or ovarian cancer.

Methods: We conducted a discrete choice experiment. Women about to undergo genetic testing and counseling at 2 medical centers participated. Enrollment occurred between 2019 and 2022, allowing us to investigate changes in preferences from before the pandemic to after the pandemic. Women chose from permuted scenarios that specified type of surgery, age of menopause, quality of menopausal symptoms, and risk of ovarian cancer, heart disease, or osteoporosis.

Results: A total of 355 women, with a median age of 36 y, participated. In 2019, women were less likely to choose prevention scenarios with higher ovarian cancer risk (odds ratio [OR] = 0.42 per 10-point increase in risk, 95% confidence interval [CI] 0.22-0.61). In June 2020, the effect of higher ovarian cancer risk scenarios on choice was attenuated (OR = 0.86, 95% CI 0.68-1.04), with the effect becoming more salient again by July 2021 (OR = 0.59, 95% CI 0.52-0.67) (P = 0.039 for test of temporal interaction). No other attribute demonstrated a temporal trend.

Conclusion: The risks associated with the COVID-19 pandemic may have attenuated the impact of risk of ovarian cancer on choice of risk-reducing prevention strategies for ovarian cancer. The maximum attenuation occurred at the beginning of the pandemic when access to risk-reducing surgery was most restricted. Our findings highlight how individuals evaluate competing health risks and adjust their uptake of cancer prevention strategies when faced with a future pandemic or similar global crisis.

Highlights: In this discrete choice experiment, women were much less likely to choose prevention scenarios that had higher ovarian cancer risk prior to the COVID-19 pandemic than after the pandemic.The attenuation of preferences may have persisted through 2022.COVID-19 may have altered the relative importance of factors that motivate women to undergo risk-reducing surgeries.

背景:在COVID-19之前,人们对与这种大流行相关的风险如何与降低癌症风险的医疗决策竞争并影响患者决策知之甚少。我们调查了大流行如何影响乳腺癌或卵巢癌高风险妇女对医疗降低风险策略的偏好。方法:进行离散选择实验。即将在两个医疗中心接受基因检测和咨询的妇女参与了这项研究。登记发生在2019年至2022年之间,使我们能够调查从大流行之前到大流行之后偏好的变化。妇女可以根据手术类型、绝经年龄、更年期症状的质量、卵巢癌、心脏病或骨质疏松症的风险等多种情况进行选择。结果:共有355名女性参与,中位年龄36岁。2019年,女性不太可能选择卵巢癌风险较高的预防方案(风险每增加10个点的优势比[OR] = 0.42, 95%置信区间[CI] 0.22-0.61)。2020年6月,高卵巢癌风险情景对选择的影响减弱(OR = 0.86, 95% CI 0.68-1.04),到2021年7月,影响再次变得更加显著(OR = 0.59, 95% CI 0.52-0.67)(时间交互作用检验P = 0.039)。没有其他属性显示出时间趋势。结论:与COVID-19大流行相关的风险可能减弱了卵巢癌风险对卵巢癌降低风险预防策略选择的影响。最大程度的衰减发生在大流行开始时,当时获得降低风险手术的机会受到最严格的限制。我们的研究结果强调了当面临未来的流行病或类似的全球危机时,个人如何评估相互竞争的健康风险并调整他们对癌症预防策略的吸收。在这个离散选择实验中,女性在COVID-19大流行之前选择卵巢癌风险较高的预防方案的可能性要比大流行之后低得多。偏好的减弱可能会持续到2022年。COVID-19可能改变了促使女性接受降低风险手术的因素的相对重要性。
{"title":"Changes in Risk Tolerance for Ovarian Cancer Prevention Strategies during the COVID-19 Pandemic: Results of a Discrete Choice Experiment.","authors":"Brian L Egleston, Mary B Daly, Kaitlyn Lew, Lisa Bealin, Alexander D Husband, Jill E Stopfer, Pawel Przybysz, Olga Tchuvatkina, Yu-Ning Wong, Judy E Garber, Timothy R Rebbeck","doi":"10.1177/0272989X241302829","DOIUrl":"10.1177/0272989X241302829","url":null,"abstract":"<p><strong>Background: </strong>Prior to COVID-19, little was known about how risks associated with such a pandemic would compete with and influence patient decision making regarding cancer risk reducing medical decision making. We investigated how the pandemic affected preferences for medical risk-reducing strategies among women at elevated risk of breast or ovarian cancer.</p><p><strong>Methods: </strong>We conducted a discrete choice experiment. Women about to undergo genetic testing and counseling at 2 medical centers participated. Enrollment occurred between 2019 and 2022, allowing us to investigate changes in preferences from before the pandemic to after the pandemic. Women chose from permuted scenarios that specified type of surgery, age of menopause, quality of menopausal symptoms, and risk of ovarian cancer, heart disease, or osteoporosis.</p><p><strong>Results: </strong>A total of 355 women, with a median age of 36 y, participated. In 2019, women were less likely to choose prevention scenarios with higher ovarian cancer risk (odds ratio [OR] = 0.42 per 10-point increase in risk, 95% confidence interval [CI] 0.22-0.61). In June 2020, the effect of higher ovarian cancer risk scenarios on choice was attenuated (OR = 0.86, 95% CI 0.68-1.04), with the effect becoming more salient again by July 2021 (OR = 0.59, 95% CI 0.52-0.67) (<i>P</i> = 0.039 for test of temporal interaction). No other attribute demonstrated a temporal trend.</p><p><strong>Conclusion: </strong>The risks associated with the COVID-19 pandemic may have attenuated the impact of risk of ovarian cancer on choice of risk-reducing prevention strategies for ovarian cancer. The maximum attenuation occurred at the beginning of the pandemic when access to risk-reducing surgery was most restricted. Our findings highlight how individuals evaluate competing health risks and adjust their uptake of cancer prevention strategies when faced with a future pandemic or similar global crisis.</p><p><strong>Highlights: </strong>In this discrete choice experiment, women were much less likely to choose prevention scenarios that had higher ovarian cancer risk prior to the COVID-19 pandemic than after the pandemic.The attenuation of preferences may have persisted through 2022.COVID-19 may have altered the relative importance of factors that motivate women to undergo risk-reducing surgeries.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"168-176"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142899970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Fast Nonparametric Sampling Method for Time to Event in Individual-Level Simulation Models. 个体水平仿真模型中时间到事件的快速非参数采样方法。
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2025-01-05 DOI: 10.1177/0272989X241308768
David U Garibay-Treviño, Hawre Jalal, Fernando Alarid-Escudero

Highlights: The nonparametric sampling method is generic and can sample times to an event from any discrete (or discretizable) hazard without requiring any parametric assumption.The method is showcased with 5 commonly used distributions in discrete-event simulation models.The method produced very similar expected times to events, as well as their probability distribution, compared with analytical results.We provide a multivariate categorical sampling function for R and Python programming languages to sample times to events from processes with different hazards simultaneously.

重点:非参数采样方法是通用的,可以从任何离散(或可离散)危险中采样到事件的时间,而不需要任何参数假设。以离散事件仿真模型中常用的5种分布为例进行了说明。与分析结果相比,该方法产生的事件预期时间及其概率分布非常相似。我们为R和Python编程语言提供了一个多变量分类抽样函数,用于同时从具有不同危险的过程中对事件进行采样时间。
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引用次数: 0
Testing an HPV Vaccine Decision Aid for 27- to 45-Year-Old Adults in the United States: A Randomized Trial. 美国27- 45岁成人HPV疫苗决策辅助测试:一项随机试验
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2024-12-24 DOI: 10.1177/0272989X241305142
Erika L Thompson, Justin Luningham, Sarah A Alkhatib, Jessica Grace, Idara N Akpan, Ellen M Daley, Gregory D Zimet, Christopher W Wheldon

Background: In the United States, human papillomavirus (HPV) vaccination among 27- to 45-y-olds (mid-adults) is recommended based on shared clinical decision making with a health care provider. We developed a patient decision aid tool to support the implementation of this mid-adult HPV vaccination guideline. The purpose of this study was to evaluate the effect of a patient decision aid tool for HPV vaccination, HPV DECIDE, compared with an information fact sheet among mid-adults who have not received the HPV vaccine.

Method: Participants were recruited between December 2023 and January 2024. We used a randomized Solomon, 4-group, pretest/posttest design with mid-adults aged 27 to 45 y who were unvaccinated for HPV and balanced based on sex (n = 612). The primary outcome was decisional conflict. Intermediate outcomes included knowledge, behavioral expectancies, self-efficacy, and perceived risk. Variables were measured using validated scales. Pretest sensitization was not present; intervention and control groups were compared. Fixed-effects inverse-variance weighting was used to pool effect estimates and determine meta-analytic statistical significance across tests with and without pretest controls.

Results: Participants in the intervention group had significantly lower total decisional conflict scores (B = -3.58, P = 0.007) compared with the control group. Compared with the control group, participants in the intervention group showed higher knowledge (B = 0.48, P = 0.020), greater intention to receive (B = 0.196, P = 0.049) and discuss the HPV vaccine (B = 0.324, P ≤ 0.001), and greater self-efficacy about HPV vaccine decision making (B = 3.28, P = 0.043). There were no statistically significant results for perceived risks of HPV infection.

Conclusions: The HPV DECIDE tool for mid-adult HPV vaccination shows promise for immediate reductions in decisional conflict and improvement in knowledge, intentions, and self-efficacy about the HPV vaccine. Future studies are warranted to evaluate the effectiveness of this patient decision aid tool in real-world settings.

Highlights: Shared clinical decision making is recommended for HPV vaccination with mid-adults.A patient decision aid for HPV vaccination reduced decisional conflict for mid-adults.The HPV vaccine patient decision aid was acceptable to mid-adults.

背景:在美国,根据与卫生保健提供者共同的临床决策,建议27至45岁(中年)的人乳头瘤病毒(HPV)疫苗接种。我们开发了一种患者决策辅助工具,以支持该成人中期HPV疫苗接种指南的实施。本研究的目的是评估HPV疫苗接种患者决策辅助工具HPV DECIDE的效果,并与未接种HPV疫苗的中年成年人的信息情况表进行比较。方法:在2023年12月至2024年1月期间招募参与者。我们采用随机所罗门,4组,测试前/测试后设计,年龄在27至45岁之间的未接种HPV疫苗的中年人,并根据性别进行平衡(n = 612)。主要的结果是决策冲突。中间结果包括知识、行为预期、自我效能和感知风险。采用有效的量表测量变量。不存在测试前致敏;干预组与对照组比较。固定效应反方差加权用于汇总效应估计,并确定有无前测控制的meta分析统计显著性。结果:干预组决策冲突总分显著低于对照组(B = -3.58, P = 0.007)。与对照组相比,干预组对HPV疫苗的知晓程度(B = 0.48, P = 0.020)、接种意向(B = 0.196, P = 0.049)和讨论意向(B = 0.324, P≤0.001)较高,对HPV疫苗决策的自我效能感(B = 3.28, P = 0.043)较高。对于HPV感染的感知风险没有统计学上的显著结果。结论:用于中期成人HPV疫苗接种的HPV决策工具有望立即减少决策冲突,并改善HPV疫苗的知识,意图和自我效能。未来的研究有必要评估这种患者决策辅助工具在现实世界中的有效性。重点:建议中年人接种HPV疫苗时共享临床决策。一项针对HPV疫苗接种的患者决策援助减少了中年人的决策冲突。人乳头瘤病毒疫苗患者决策辅助对中年人是可接受的。
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引用次数: 0
How Inclusive Are Patient Decision Aids for People with Limited Health Literacy? An Analysis of Understandability Criteria and the Communication about Options and Probabilities. 患者决策辅助工具对健康素养有限者的包容性如何?对可理解性标准以及选项和概率沟通的分析。
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2024-12-14 DOI: 10.1177/0272989X241302288
Romy Richter, Jesse Jansen, Josine van der Kraan, Wais Abbaspoor, Iris Bongaerts, Fleur Pouwels, Celine Vilters, Jany Rademakers, Trudy van der Weijden

Objective: Patient decision aids (PtDAs) can support shared decision making. We aimed to explore how inclusive PtDAs are for people with limited health literacy (LHL) by analyzing 1) the understandability of PtDAs using established criteria, 2) how options and probabilities of outcomes are communicated, and 3) the extent to which risk communication (RC) guidelines are followed.

Methods: In a descriptive document analysis, we analyzed Dutch PtDAs available in 2021 that met the International Patient Decision Aid Standards. We developed and pilot tested a data extraction form based on key RC and health literacy literature.

Results: Most PtDAs (151/198) met most of the understandability criteria on layout (7-8 out of 8 items) such as font size but not on content aspects (121/198 PtDAs scored 5-7 out of 12 items) such as defining medical terms. Only 31 of 198 PtDAs used a short and simple sentence structure. Most PtDAs presented 2 to 4 treatment options. Many followed RC recommendations such as the use of numerical RC strategies such as percentages or natural frequencies (160/198) and visual formats such as icon arrays (91/198). Only 10 used neutral framing (10/198). When presented, uncertainty was presented verbally (134/198) or in ranges (58/198). Four PtDAs were co-created together with patients with LHL and used only verbal RC or no RC.

Conclusion: Most PtDAs met most of the understandability criteria on layout, but content aspects and adherence to RC strategies can be improved. Many PtDAs used long sentences and mostly verbal RC and are therefore likely to be inappropriate for patients with LHL. Further research is needed on PtDA characteristics and RC strategies suitable for people with LHL.

Highlights: Despite meeting most criteria for understandability, many of the Dutch PtDAs use long sentences, which likely impede comprehension for patients with LHL.Most of the Dutch PtDAs follow established recommendations for risk communication, with room for improvement for some strategies such as framing and a clear reference to the time frame.Overall, more research is needed to tailor PtDAs to the needs of people with LHL.

目的:患者决策辅助工具(ptda)可支持共同决策。我们的目的是通过分析1)使用既定标准的ptda的可理解性,2)如何沟通结果的选择和概率,以及3)遵循风险沟通(RC)指南的程度,来探索ptda对健康素养有限(LHL)人群的包容性。方法:在描述性文献分析中,我们分析了2021年符合国际患者决策辅助标准的荷兰ptda。我们开发并试点测试了一种基于关键RC和健康素养文献的数据提取表。结果:大多数ptda(151/198)在排版(8项中7-8项)如字体大小等方面符合大部分可理解性标准,但在内容方面(121/198)如医学术语的定义等方面不符合可理解性标准(12项中5-7项)。198个ptda中只有31个使用了简短的句子结构。大多数ptda提供2至4种治疗方案。许多人遵循RC的建议,如使用数值RC策略,如百分比或自然频率(160/198)和视觉格式,如图标数组(91/198)。只有10个使用中性框架(10/198)。不确定度以口头形式(134/198)或范围形式(58/198)呈现。与LHL患者共同创建了4个ptda,仅使用口头RC或不使用RC。结论:大多数ptda在布局上符合大部分可理解性标准,但在内容方面和对RC策略的依从性方面有待改进。许多ptda使用长句子和大部分口头RC,因此可能不适合LHL患者。需要进一步研究适合LHL患者的PtDA特征和RC策略。尽管符合大多数可理解性标准,但许多荷兰ptda使用长句子,这可能阻碍LHL患者的理解。大多数荷兰ptda都遵循既定的风险沟通建议,但在某些策略方面仍有改进空间,例如框架和明确的时间框架。总的来说,需要更多的研究来定制ptda以满足LHL患者的需求。
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引用次数: 0
A Parsimonious Approach to Remediate Concerns about QALY-Based Discrimination. 纠正对基于质量的歧视的担忧的一种节俭的方法。
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2024-12-21 DOI: 10.1177/0272989X241305119
Ronald Scott Braithwaite

Highlights: Important barriers to the use of QALYs in the United States include concerns about disability and age discrimination.Modifications to the utility function underlying QALYs have been proposed to mitigate these concerns, but some find them challenging to consider and/or to apply.Unrelated to these concerns, QALYs have been adapted within the framework of distributional cost-effectiveness analysis to allow consideration of inequality as well as efficiency.I outline how this framework can also remediate concerns about disability and age discrimination.

重点:在美国使用质量质量指标的重要障碍包括对残疾和年龄歧视的担忧。已经提出了对qaly基础效用函数的修改,以减轻这些担忧,但是有些人发现考虑和/或应用它们具有挑战性。与这些问题无关的是,质量质量年在分配成本效益分析的框架内进行了调整,以便考虑到不平等和效率。我概述了这一框架如何也能纠正对残疾和年龄歧视的关切。
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引用次数: 0
Physician-Patient Communication about Novel Drugs and High-Risk Medical Devices. 新药与高危医疗器械的医患沟通。
IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Pub Date : 2025-02-01 Epub Date: 2024-12-21 DOI: 10.1177/0272989X241302096
Sanket S Dhruva, Aaron S Kesselheim, Steven Woloshin, Robin Z Ji, Zhigang Lu, Jonathan J Darrow, Rita F Redberg

Background: After a new drug or medical device is approved by the US Food and Drug Administration (FDA), physician-patient communication about benefits and risks is critical, including whether the product was approved through an expedited pathway based on limited evidence. In addition, physician reporting of drug- and device-related adverse events in real-world use is necessary to have a complete safety profile. We studied physician-reported communication and safety-reporting practices related to drugs and devices.

Methods: We surveyed a random national sample of American Board of Internal Medicine-certified internists, cardiologists, and oncologists between October 2021 and September 2022 about the sources of information used to prescribe a drug or medical device, details of communication with patients, and reporting of adverse events.

Results: Among 509 respondents (39% response rate), 387 (76%) reported that FDA approval influenced their decision "a lot" to prescribe a new drug or recommend use of a medical device. Half (122; 50%) of the 244 physicians randomized to receive a question about their own communication of trial endpoints reported "usually" telling patients when products were approved based on surrogate measures and 126 (52%) "usually" reported telling patients if a postapproval trial was required to evaluate safety and effectiveness. Two-thirds (165) said they were likely to report drug- or device-related adverse events to FDA.

Conclusions: Physician self-reporting of communication with patients about drugs and devices suggests that half include characteristics of the pivotal trials such as use of clinically meaningful endpoints or continued requirement for evidence generation.

Implications: More consistent discussions with patients about the quality of evidence supporting new drugs and devices and increased reporting of adverse events could ensure optimal use of these products in clinical practice.

Highlights: Among 509 board-certified internists, cardiologists, and oncologists, half reported telling patients when drugs or medical devices were approved based on surrogate measures and when there was an FDA-mandated postapproval trial to further evaluate safety and effectiveness.As drugs and medical devices are increasingly approved by the FDA through expedited pathways based on data with lingering uncertainties, discussion with patients about issues such as the nature of the endpoints assessed and existence of postapproval testing requirements can help inform patient decision making.

背景:在美国食品和药物管理局(FDA)批准一种新药或医疗器械后,医患之间关于获益和风险的沟通至关重要,包括该产品是否通过基于有限证据的加速途径获得批准。此外,医生在真实使用中报告药物和器械相关的不良事件对于获得完整的安全性档案是必要的。我们研究了与药物和器械相关的医生报告沟通和安全报告实践。方法:在2021年10月至2022年9月期间,我们随机调查了美国内科医学委员会认证的内科医生、心脏病专家和肿瘤学家的全国样本,内容包括处方药物或医疗器械的信息来源、与患者沟通的细节以及不良事件的报告。结果:在509名受访者(39%的回复率)中,387人(76%)表示FDA的批准对他们开新药或推荐使用医疗器械的决定影响“很大”。一半(122;244名医生随机接受了一个关于他们自己对试验终点的沟通的问题,其中50%的医生报告“通常”告诉患者产品何时根据替代措施获得批准,126名(52%)医生报告说:“通常”报告告诉患者是否需要进行批准后试验来评估安全性和有效性。三分之二(165人)表示他们可能会向FDA报告药物或器械相关的不良事件。结论:医生自我报告与患者关于药物和设备的沟通表明,其中一半包括关键试验的特征,如使用临床有意义的终点或继续要求证据生成。意义:与患者就支持新药和器械的证据质量进行更一致的讨论,并增加不良事件的报告,可以确保这些产品在临床实践中的最佳使用。重点:在509名委员会认证的内科医生、心脏病专家和肿瘤学家中,有一半的人报告说,他们告诉患者药物或医疗器械何时根据替代措施获得批准,以及何时有fda授权的批准后试验来进一步评估安全性和有效性。随着药物和医疗器械越来越多地通过基于数据的快速途径获得FDA的批准,这些数据具有挥之不去的不确定性,与患者讨论诸如评估终点的性质和批准后测试要求的存在等问题可以帮助患者做出决策。
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引用次数: 0
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Medical Decision Making
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