MDM Policy and Practice最新文献

Background. Despite the established effectiveness of expedited partner therapy (EPT) in partner treatment of bacterial sexually transmitted infections (STI), the practice is underutilized. Objective. To estimate the relative effectiveness of strategies to increase EPT uptake (numbers of partners treated for chlamydia). Methods. We developed a care cascade model of cumulative probabilities to estimate the number of partners treated under strategies to increase EPT uptake in Minnesota. The care cascade model used data from clinical trials, population-based studies, and Minnesota chlamydia surveillance as well as in-depth interviews of health providers who regularly treat STI patients and a statewide survey of health providers across Minnesota. Results. Several strategies could improve EPT uptake among providers, including facilitating treatment payment (additional 1,932 partners treated) and implementing electronic health record reminders (additional 1,755 partners treated). Addressing concerns about liability would have the greatest effect, resulting in 2,187 additional partners treated. Conclusions. Providers expressed openness to offering EPT under several scenarios, which reflect differences in knowledge about EPT, its legality, and potential risks to patients. While addressing concerns about provider liability would have the greatest effect on number of partners treated, provider education and procedural changes could make a substantial impact.

Highlights: Addressing provider concerns about expedited partner therapy (EPT) legality and its potential risks would result in the most partners treated for chlamydia.EPT alerts and electronic EPT prescriptions may also streamline partner treatment.Provider education about the legality of EPT and its potential risks and training in counseling patients on EPT could also increase uptake.

Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practical setting. We report our experiences with UCD to develop a modeling tool for cancer control planners evaluating cancer survivorship interventions. Design. Using UCD principles (described in the article), we developed a dynamic cohort model of cancer survivorship for individuals with female breast, colorectal, lung, and prostate cancer over 10 y. Parameters were obtained from the National Program of Cancer Registries and peer-reviewed literature, with model outcomes captured in quality-adjusted life-years and net monetary benefit. Prototyping and iteration were conducted with structured focus groups involving state cancer control planners and staff from the Centers for Disease Control and Prevention and the American Public Health Association. Results. Initial feedback highlighted model complexity and unclear purpose as barriers to end user uptake. Revisions addressed complexity by simplifying model input requirements, providing clear examples of input types, and reducing complex language. Wording was added to the results page to explain the interpretation of results. After these updates, feedback demonstrated that end users more clearly understood how to use and apply the model for cancer survivorship resource allocation tasks. Conclusions. A UCD approach identified challenges faced by end users in integrating a decision aid into their workflow. This approach created collaboration between modelers and end users, tailoring revisions to meet the needs of the users. Future models developed for individuals without a decision science background could leverage UCD to ensure the model meets the needs of the intended audience.

Highlights: Model complexity and unclear purpose are 2 barriers that prevent lay users from integrating decision science tools into their workflow.Modelers could integrate the user-centered design framework when developing a model for lay users to reduce complexity and ensure the model meets the needs of the users.

Introduction. Prognosis is an essential component of informed consent for medical decision making. Research shows that physicians display discrepancies in their prognostication, leading to variable, inaccurate, optimistic, or pessimistic prognosis. Factors driving these discrepancies and the supporting evidence have not been reviewed systematically. Methods. We undertook a scoping review to explore the literature on the factors leading to discrepancies in medical prognosis. We searched Medline (Ovid) and Embase (Ovid) databases for peer-reviewed articles from 1970 to 2017. We included articles that discussed prognosis variation or discrepancy and where factors influencing prognosis were evaluated. We extracted data outlining the participants, methodology, and prognosis discrepancy information and measured factors influencing prognosis. Results. Of 4,723 articles, 73 were included in the final analysis. There was significant variability in research methodologies. Most articles showed that physicians were pessimistic regarding patient outcomes, particularly in early trainees and acute care specialties. Accuracy rates were similar across all time periods. Factors influencing prognosis were clustered in 4 categories: patient-related factors (such as age, gender, race, diagnosis), physician-related factors (such as age, race, gender, specialty, training and experience, attitudes and values), clinical situation-related factors (such as physician-patient relationship, patient location, and clinical context), and environmental-related factors (such as country or hospital size). Discussion. Obtaining accurate prognostic information is one of the highest priorities for seriously ill patients. The literature shows trends toward pessimism, especially in early trainees and acute care specialties. While some factors may prove difficult to change, the physician's personality and psychology influence prognosis accuracy and could be tackled using debiasing strategies. Exposure to long-term patient outcomes and a multidisciplinary practice setting are environmental debiasing strategies that may warrant further research.

Highlights: Literature on discrepancies in physician's prognostication is heterogeneous and sparse.Literature shows that physicians are mostly pessimistic regarding patient outcomes.Literature shows that a physician's personality and psychology influence prognostic accuracy and could be improved with evidence-based debiasing strategies.Medical specialty strongly influences prognosis, with specialties exposed to acutely ill patients being more pessimistic, whereas specialties following patients longitudinally being more optimistic.Physicians early in their training were more pessimist than more experienced physicians.

Introduction. Generic preference-based instruments inadequately measure breast cancer (BrC) health-related quality-of-life preferences given advances in therapy. Our overall purpose is to develop the Breast Utility Instrument (BUI), a BrC-specific preference-based instrument. This study describes the selection of the BUI items. Methods. A total of 408 patients from diverse BrC health states completed the EORTC QLQ-C30 and BR45 (breast module). For each of 10 dimensions previously assessed with confirmatory factor analysis, we evaluated data fit to the Rasch model based on global model and item fit, including threshold ordering, item residuals, infit and outfit, differential item functioning (age), and unidimensionality. Misfitting items were removed iteratively, and the model fit was reassessed. From items fitting the Rasch model, we selected 1 item per dimension based on high patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance. Results. Global model fit was good in 7 and borderline in 3 dimensions. Separation index was acceptable in 4 dimensions. Item selection criteria were maximized for the following items: 1) physical functioning (trouble taking a long walk), 2) emotional functioning (worry), 3) social functioning (interfering with social activities), 4) pain (having pain), 5) fatigue (tired), 6) body image (dissatisfied with your body), 7) systemic therapy side effects (hair loss), 8) sexual functioning (interest in sex), 9) breast symptoms (oversensitive breast), and 10) endocrine therapy symptoms (problems with your joints). Conclusions. We propose 10 items for the BUI. Our next steps include assessing the measurement properties prior to eliciting preference weights of the BUI.

Highlights: A previous confirmatory factor analysis established 10 dimensions of the European Organisation for Research and Treatment of Cancer (EORTC) core quality of life questionnaire (QLQ-C30) and its breast module (BR45).In this study, we selected 1 item per dimension based on fit to the Rasch model, patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance.These items form the core of the future Breast Utility Instrument (BUI).The future BUI will be a novel breast cancer-specific preference-based instrument that potentially will better reflect women's preferences in clinical decision making and cost utility analyses.

Background. The novel coronavirus SARS-CoV-2 spread across the world causing many waves of COVID-19. Children were at high risk of being exposed to the disease because they were not eligible for vaccination during the first 20 mo of the pandemic in the United States. While children 5 y and older are now eligible to receive a COVID-19 vaccine in the United States, vaccination rates remain low despite most schools returning to in-person instruction. Nonpharmaceutical interventions (NPIs) are important for controlling the spread of COVID-19 in K-12 schools. US school districts used varied and layered mitigation strategies during the pandemic. The goal of this article is to analyze the impact of different NPIs on COVID-19 transmission within K-12 schools. Methods. We developed a deterministic stratified SEIR model that captures the role of social contacts between cohorts in disease transmission to estimate COVID-19 incidence under different NPIs including masks, random screening, contact reduction, school closures, and test-to-stay. We designed contact matrices to simulate the contact patterns between students and teachers within schools. We estimated the proportion of susceptible infected associated with each intervention over 1 semester under the Omicron variant. Results. We find that masks and reducing contacts can greatly reduce new infections among students. Weekly screening tests also have a positive impact on disease mitigation. While self-quarantining symptomatic infections and school closures are effective measures for decreasing semester-end infections, they increase absenteeism. Conclusion. The model provides a useful tool for evaluating the impact of a variety of NPIs on disease transmission in K-12 schools. While the model is tested under Omicron variant parameters in US K-12 schools, it can be adapted to study other populations under different disease settings.

Highlights: A stratified SEIR model was developed that captures the role of social contacts in K-12 schools to estimate COVID-19 transmission under different nonpharmaceutical interventions.While masks, random screening, contact reduction, school closures, and test-to-stay are all beneficial interventions, masks and contact reduction resulted in the greatest reduction in new infections among students from the tested scenarios.Layered interventions provide more benefits than implementing interventions independently.

Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers.

Highlights: Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.

Background. Patients with chronic limb-threatening ischemia who are facing a lower-limb amputation often require a transmetatarsal amputation (TMA) or a transtibial amputation (TTA). A TMA preserves more of the patient's limb and may provide better mobility but has a lower probability of primary wound healing relative to a TTA and may result in additional amputation surgeries. Understanding the differences in how patients and providers prioritize key outcomes may enhance the amputation decisional process. Purpose. To develop and pilot test a multiple criteria decision analysis (MCDA) tool to elicit patient values around amputation-level selection and compare those with provider perceptions of patient values. Methods. We conducted literature reviews to identify and measure the performance of criteria important to patients. Because the quantitative literature was sparse, we developed a Sheffield elicitation framework exercise to elicit criteria performance from subject matter experts. We piloted our MCDA among patients and providers to understand tool acceptability and preliminarily assess differences in patient and provider priorities. Results. Five criteria of importance were identified: ability to walk, healing after amputation surgery, rehabilitation intensity, limb length, and prosthetic/orthotic device ease. Patients and providers successfully completed the MCDA and identified challenges in doing so. We propose potential solutions to these challenges. The results of the pilot test suggest differences in patient and provider outcome priorities. Limitations. The pilot test study enrolled a small sample of providers and patients. Conclusions. We successfully implemented the pilot study to patients and providers, received helpful feedback, and identified solutions to improve the tool. Implications. Once modified, our MCDA tool will be suitable for wider rollout.

Highlights: Patients and providers have successfully completed our MCDA, and patients feel the MCDA may be useful in clinical practice.We encountered several methodologic challenges and identified approaches to ease participant burden.When data are sparse, using the Sheffield elicitation framework is helpful in creating a performance matrix, although patients relied largely on their amputation experiences to complete the exercise. Blinding the alternatives may help patients better understand the process.

Background. For men with intermediate-risk prostate cancer (IRPC), adding short-term androgen deprivation therapy (ADT) to external beam radiation therapy (EBRT) has shown efficacy, but men are often reluctant to accept it because of its impact on quality of life. Methods. We conducted time tradeoffs (score of 1 = perfect health and 0 = death) and probability tradeoffs with patients aged 51 to 78 y who had received EBRT for IRPC within the past 2 y. Of 40 patients, 20 had received 6 mo of ADT and 20 had declined. Utility assessments explored 4 ADT-related side effects: hot flashes, fatigue, loss of libido/erectile dysfunction, and weight gain. Results. The most commonly reported "worst" treatment-related complication of ADT was fatigue (50% in both cohorts) followed by reduced libido/erectile dysfunction (40% in both cohorts). The utilities for fatigue were mean = 0.71 and median = 0.92 and for reduced libido/erectile dysfunction were mean = 0.81 and median = 0.92. Utilities did not differ significantly between cohorts. Assuming a 6-mo course of ADT, men reported being willing to trade 3 mo of life expectancy to avoid fatigue due to ADT and 1.8 mo to avoid sexual side effects. Patients in the ADT cohort were willing to accept the side effects of ADT in exchange for a mean 8% absolute increase in survival, whereas patients in the no ADT cohort required a 16% increase (P < 0.001). Conclusions. When considering treatment with ADT, men with IRPC identified fatigue and sexual dysfunction as the most bothersome side effects. Patients who declined ADT expected a larger survival benefit than those who opted for treatment. Both groups expected a survival benefit exceeding that shown by recent trials, suggesting some men may be selecting treatments inconsistent with their preferences.

Highlights: This study demonstrates that prostate cancer patients receiving radiation therapy are reluctant to receive androgen deprivation therapy (ADT) most commonly due to anticipated fatigue and loss of libido/erectile dysfunction.Men who had received ADT reported they would require an average 8% absolute increase in survival to tolerate its side effects, whereas those who declined ADT would require an average 16% increase.Required thresholds are well above the estimated absolute survival benefit for ADT demonstrated in recent clinical trials, suggesting an unmet need for improved patient education regarding the risks and benefits of ADT.

Background. Problematic alcohol use is known to harm individuals surrounding the drinker. This study described the health utility of people who reported having a family member(s) whom they perceived as a "problem drinker."Methods. We conducted a secondary analysis of the US National Epidemiologic Survey of Alcohol and Related Conditions Wave 3 (NESARC-III, 2012-13) data to estimate the independent associations of a family member's problem drinking on the respondent's health utility, also known as health-related quality of life, assessed via the SF-6D. Participants included 29,159 noninstitutionalized adults, of whom 21,808 reported perceiving a family member or members as having a drinking problem at any point in that person's life. Respondent drinking was assessed via self-report and diagnostic interview. We used population-weighted multivariate regression to estimate disutility. Results. After adjusting for the respondent's own alcohol consumption, alcohol use disorder (AUD), family structure, and sociodemographic characteristics, the mean decrement in SF-6D score associated with perceiving a family member as a problem drinker ranged from 0.033 (P < 0.001) for a spouse/partner to 0.023 (P < 0.001) for a grandparent, sibling, aunt, or uncle. The mean decrement in SF-6D score from having AUD oneself was 0.039 (P < 0.001). Conclusions. Perceived problem drinking within one's family is associated with statistically significant losses in health utility, the magnitude of which is dependent on relationship type. The adverse consequences associated with problem drinking in the family may rival having AUD oneself. Implications. Family-oriented approaches to AUD interventions may confer outsize benefits, especially if focused on the spouse or partner. Economic evaluation of alcohol misuse could be made more accurate through the inclusion of family spillover effects.

Highlights: Spillover effects from problem drinking in the family vary by relationship type.One's perception of their spouse or child as having a drinking problem is associated with a utility decrement of equal magnitude to having alcohol use disorder oneself.Medical decision makers should consider the outsize effects of family spillovers in treatment decisions in the context of alcohol consumption, particularly among spouses and children of problem drinkers.Economic evaluation should consider how to incorporate family spillover effects from problem drinking in alcohol-related models.