Predictors for Early Liver Cancer Survival After Ablation and Surgical Resection: A Surveillance, Epidemiology, and End Results Program-Medicare Study.

OBJECTIVE: To identify independent predictors of all-cause and cancer-specific mortality after ablation or surgical resection (SR) for small hepatocellular carcinomas (HCCs), after adjusting for key confounders. METHODS: Using Surveillance, Epidemiology, and End Results Program-Medicare, HCCs less than 5 cm treated with ablation or SR in 2009 to 2016 (n = 956) were identified. Univariate and multivariable Cox regression models for all-cause and cancer-specific mortality were performed including demographics, clinical factors (tumor size, medical comorbidities, and liver disease factors), social determinants of health, and treatment characteristics. We also determined the most influential predictors of survival using a random forest analysis. RESULTS: Larger tumor size (3-5 cm) is predictive of all-cause (hazard ratio [HR] 1.31, P = .002) and cancer-specific mortality (HR 1.59, P < .001). Furthermore, chronic kidney disease is predictive of all-cause mortality (HR 1.43, P = .013), though it is not predictive of cancer-specific death. Multiple liver disease factors are predictive of all-cause and cancer-specific mortality including portal hypertension and esophageal varices (HRs > 1, P < .05). Though Asian race is protective in univariate models, in fully adjusted, multivariable models, Asian race is not a significant protective factor. Likewise, other social determinants of health are not significantly predictive of all-cause or cancer-specific mortality. Finally, treatment with SR, in later procedure years or at high-volume centers, is protective for all-cause and cancer-specific mortality. In machine learning models, year procedure was performed, ascites, portal hypertension, and treatment choice were the most influential factors. DISCUSSION: Treatment characteristics, liver disease factors, and tumor size are more important predictors of all-cause and cancer-specific death than social determinants of health for small HCCs.

Beyond Survival: Adverse Events and Care Delivery Outcomes after Early Liver Cancer Treatment in a Nationally Representative Cohort.

PURPOSE: To compare secondary outcomes after ablation (AB), surgical resection (SR), and liver transplant (LT) for small hepatocellular carcinomas (HCCs), including resource utilization and adverse event (AE) rates. MATERIALS AND METHODS: Using Surveillance, Epidemiology, and End Results Program (SEER)-Medicare, HCCs <5 cm that were treated with AB, SR, or LT in 2009-2016 (n = 1,067) were identified using Healthcare Common Procedure Coding System codes through Medicare claims. Index procedure length of stay, need for intensive care unit (ICU) level care, readmission rates, and AE rates at 30 and 90 days were compared using chi-square tests or Fisher exact tests. Examined AEs included hemorrhage, abscess formation, biliary injury, pneumonia, sepsis, liver disease-related AEs, liver failure, and anesthesia-related AEs, identified by International Classification of Diseases, Ninth/10th Revision, codes. RESULTS: The median length of stay for initial treatment was 1 day, 6 days, and 7 days for AB, SR, and LT, respectively (P < .001). During initial hospital stay, 5.0%, 40.8%, and 63.4% of AB, SR, and LT cohorts, respectively, received ICU-level care (P < .001). By 30 and 90 days, there were significant differences among the AB, SR, and LT cohorts in the rate of postprocedural hemorrhage, abscess formation, biliary injury, pneumonia, sepsis, liver disease-related AEs, and anesthesia-related AEs (P < .05). By 90 days, the readmission rates after AB, SR, and LT were 18.6%, 28.2%, and 40.6% (P < .001), respectively. CONCLUSIONS: AB results in significantly less healthcare utilization during the initial 90 days after procedure compared with that after SR and LT due to shorter length of stay, lower intensity care, fewer readmissions, and fewer AEs.

Prioritizing Quality Measures in Acute Stroke Care : A Cost-Effectiveness Analysis.

BACKGROUND: The American Heart Association and American Stroke Association (AHA/ASA) endorsed 15 process measures for acute ischemic stroke (AIS) to improve the quality of care. Identifying the highest-value measures could reduce the administrative burden of quality measure adoption while retaining much of the value of quality improvement. OBJECTIVE: To prioritize AHA/ASA-endorsed quality measures for AIS on the basis of health impact and cost-effectiveness. DESIGN: Individual-based stroke simulation model. DATA SOURCES: Published literature. TARGET POPULATION: U.S. patients with incident AIS. TIME HORIZON: Lifetime. PERSPECTIVE: Health care sector. INTERVENTION: Current versus complete (100%) implementation at the population level of quality measures endorsed by the AHA/ASA with sufficient clinical evidence (10 of 15). OUTCOME MEASURES: Life-years, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios, and incremental net health benefits. RESULTS OF BASE-CASE ANALYSIS: Discounted life-years gained from complete implementation would range from 472 (tobacco use counseling) to 34 688 (early carotid imaging) for an annual AIS patient cohort. All AIS quality measures were cost-saving or highly cost-effective by AHA standards (<$50 000 per QALY for high-value care). Early carotid imaging and intravenous tissue plasminogen activator contributed the largest fraction of the total potential value of quality improvement (measured as incremental net health benefit), accounting for 72% of the total value. The top 5 quality measures accounted for 92% of the total potential value. RESULTS OF SENSITIVITY ANALYSIS: A web-based user interface allows for context-specific sensitivity and scenario analyses. LIMITATION: Correlations between quality measures were not incorporated. CONCLUSION: Substantial variation exists in the potential net benefit of quality improvement across AIS quality measures. Benefits were highly concentrated among 5 of 10 measures assessed. Our results can help providers and payers set priorities for quality improvement efforts and value-based payments in AIS care. PRIMARY FUNDING SOURCE: National Institute of Neurological Disorders and Stroke.

Long-Term Survival After Surgery Versus Ablation for Early Liver Cancer in a Large, Nationally Representative Cohort.

OBJECTIVE: To compare survival outcomes (all-cause, cancer-specific, and disease-free) for small hepatocellular carcinomas (HCCs), less than or equal to 5 cm, after ablation (AB) and surgical resection (SR) after adjusting for key confounders. Secondarily, to understand differential survival outcomes of liver transplant (TR) compared with SR and AB. METHODS: Using Surveillance, Epidemiology, and End Results Program-Medicare, HCCs less than 5 cm that were treated with AB, SR, or TR in 2009 to 2016 (n = 1,215) were identified using Healthcare Common Procedure Coding System codes through Medicare claims. The TR group was subdivided into two groups: TR with prior treatment and TR without prior treatment. All-cause survival, cancer-specific survival, and disease-free survival were analyzed using Kaplan-Meier curves and compared between groups using log-rank tests and Cox regression analyses. Propensity score-matched comparison of AB and SR groups was performed, with groups matched on demographics, social determinants of health, medical comorbidities, and liver disease severity prognostic indicators. RESULTS: Median study follow-up time was 2.71 years (interquartile range 1.25-3.83). Unadjusted 1-, 3-, and 5-year cancer-specific survivals were 85.9%, 67.6%, and 56.3% for the AB group; 91.7%, 82.6%, and 81.7% for the SR group; 93.5%, 88.7%, and 79.4% for TR without prior treatment group; and 96.4%, 93.2%, and 93.2% for TR with prior treatment group (P < .0001). With SR as the reference group, the propensity-matched hazard ratios for AB were 2.04 (95% confidence interval: 1.51-2.77) for all-cause mortality, 2.44 (95% confidence interval: 1.56-3.80) for cancer-specific mortality, and 2.12 (95% confidence interval: 1.61-2.78) for disease recurrence. DISCUSSION: SR is superior to AB for small HCCs in a large, nationally representative, modern cohort, and in secondary analysis TR was superior to both.

Baseline haemoglobin A1c and the risk of COVID-19 hospitalization among patients with diabetes in the INSIGHT Clinical Research Network.

AIMS: To examine the association between baseline glucose control and risk of COVID-19 hospitalization and in-hospital death among patients with diabetes. METHODS: We performed a retrospective cohort study of adult patients in the INSIGHT Clinical Research Network with a diabetes diagnosis and haemoglobin A1c (HbA1c) measurement in the year prior to an index date of March 15, 2020. Patients were divided into four exposure groups based on their most recent HbA1c measurement (in mmol/mol): 39-46 (5.7%-6.4%), 48-57 (6.5%-7.4%), 58-85 (7.5%-9.9%), and ≥86 (10%). Time to COVID-19 hospitalization was compared in the four groups in a propensity score-weighted Cox proportional hazards model adjusting for potential confounders. Patients were followed until June 15, 2020. In-hospital death was examined as a secondary outcome. RESULTS: Of 168,803 patients who met inclusion criteria; 50,016 patients had baseline HbA1c 39-46 (5.7%-6.4%); 54,729 had HbA1c 48-57 (6.5-7.4%); 47,640 had HbA1c 58-85 (7.5^%-9.9%) and 16,418 had HbA1c ≥86 (10%). Compared with patients with HbA1c 48-57 (6.5%-7.4%), the risk of hospitalization was incrementally greater for those with HbA1c 58-85 (7.5%-9.9%) (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI] 1.06-1.34) and HbA1c ≥86 (10%) (aHR 1.40, 95% CI 1.19-1.64). The risk of COVID-19 in-hospital death was increased only in patients with HbA1c 58-85 (7.5%-9.9%) (aHR 1.29, 95% CI 1.06, 1.61). CONCLUSIONS: Diabetes patients with high baseline HbA1c had a greater risk of COVID-19 hospitalization, although association between HbA1c and in-hospital death was less consistent. Preventive efforts for COVID-19 should be focused on diabetes patients with poor glucose control.

Cost-Effectiveness Study of Initial Imaging Selection in Acute Ischemic Stroke Care.

PURPOSE: National guidelines recommend prompt identification of candidates for acute ischemic stroke (AIS) treatment, requiring timely neuroimaging with CT and/or MRI. CT is often preferred because of its widespread availability and rapid acquisition. Despite higher diagnostic accuracy of MRI, it commonly involves complex workflows that could potentially cause treatment time delays. The purpose of this study was to analyze the impact on outcomes of imaging utilization before treatment decisions at comprehensive stroke centers for patients presenting with suspected AIS in the anterior circulation with last-known-well-to-arrival time 0 to 24 hours. METHODS: A decision simulation model based on the American Heart Association's recommendations for AIS care pathways was developed from a health care perspective to compare initial imaging strategies: (1) stepwise-CT: noncontrast CT (NCCT) at the time of presentation, with CT angiography (CTA) ± CT perfusion (CTP) only in select patients (initial imaging to exclude hemorrhage and extensive ischemia) for mechanical thrombectomy (MT) evaluation; (2) stepwise-hybrid: NCCT at the time of presentation, with MR angiography (MRA) ± MR perfusion (MRP) only for MT evaluation; (3) stepwise-advanced: NCCT + CTA at presentation, with MR diffusion-weighted imaging (MR DWI) + MRP only for MT evaluation; (4) comprehensive-CT: NCCT + CTA + CTP at the time of presentation; and (5) comprehensive-MR: MR DWI + MRA + MRP at the time of presentation. Model parameters were defined using evidence-based data. Cost-effectiveness and sensitivity analyses were performed. RESULTS: The cost-effectiveness analyses revealed that comprehensive-CT and comprehensive-MR yield the highest lifetime quality-adjusted life-years (QALYs) (4.81 and 4.82, respectively). However, the incremental cost-effectiveness ratio of comprehensive-MR is $233,000/QALY compared with comprehensive-CT. Stepwise-CT, stepwise-hybrid, and stepwise-advanced strategies are dominated, yielding lower QALYs and higher costs compared with comprehensive-CT. CONCLUSIONS: Performing comprehensive-CT at presentation is the most cost-effective initial imaging strategy at comprehensive stroke centers.

Can Pay-for Performance Incentive Levels be Determined Using a Cost-Effectiveness Framework?

BACKGROUND: Healthcare payers in the United States are increasingly tying provider payments to quality and value using pay-for-performance policies. Cost-effectiveness analysis quantifies value in healthcare but is not currently used to design or prioritize pay-for-performance strategies or metrics. Acute ischemic stroke care provides a useful application to demonstrate how simulation modeling can be used to determine cost-effective levels of financial incentives used in pay-for-performance policies and associated challenges with this approach. METHODS AND RESULTS: Our framework requires a simulation model that can estimate quality-adjusted life years and costs resulting from improvements in a quality metric. A monetary level of incentives can then be back-calculated using the lifetime discounted quality-adjusted life year (which includes effectiveness of quality improvement) and cost (which includes incentive payments and cost offsets from quality improvements) outputs from the model. We applied this framework to an acute ischemic stroke microsimulation model to calculate the difference in population-level net monetary benefit (willingness-to-pay of $50 000 to $150 000/quality-adjusted life year) accrued under current Medicare policy (stroke payment not adjusted for performance) compared with various hypothetical pay-for-performance policies. Performance measurement was based on time-to-thrombolytic treatment with tPA (tissue-type plasminogen activator). Compared with current payment, equivalent population-level net monetary benefit was achieved in pay-for-performance policies with 10-minute door-to-needle time reductions (5057 more acute ischemic stroke cases/y in the 0-3-hour window) incentivized by increasing tPA payment by as much as 18% to 44% depending on willingness-to-pay for health. CONCLUSIONS: Cost-effectiveness modeling can be used to determine the upper bound of financial incentives used in pay-for-performance policies, although currently, this approach is limited due to data requirements and modeling assumptions. For tPA payments in acute ischemic stroke, our model-based results suggest financial incentives leading to a 10-minute decrease in door-to-needle time should be implemented but not exceed 18% to 44% of current tPA payment. In general, the optimal level of financial incentives will depend on willingness-to-pay for health and other modeling assumptions around parameter uncertainty and the relationship between quality improvements and long-run quality-adjusted life expectancy and costs.

Overcoming barriers to the use of metformin: patient and provider perspectives.

BACKGROUND: Metformin is the first-line treatment for type 2 diabetes mellitus. Observational studies show lower rates of use than would be expected from clinical guidelines. OBJECTIVE: We undertook a qualitative study of barriers to metformin use from the patient and provider perspective. DESIGN: Patient focus group, patient individual interviews, provider interviews, and chart review. Purposive sampling of patients and providers in New York State. PARTICIPANTS: Seven one-on-one patient interviews, one focus group with 13 patients, 10 provider interviews, and manual review of 1259 charts. APPROACH: Grounded theory. RESULTS: Both providers and patients cited potential health benefits as strong reasons to take metformin and describe it as the first-line drug for diabetes. Patients and providers both cited gastrointestinal side effects as the primary barrier to metformin use. Patients described adapting to these side effects and taking metformin at a time that minimizes them. In contrast, providers emphasized dose titration and the use of extended-release formulation as tools for minimizing side effects but were uncertain about the effectiveness of these strategies. CONCLUSION: Metformin is positively viewed by patients and providers, but gastrointestinal side effects are a barrier to its use. There is some consensus on basic measures to improve its tolerability, but these measures are not consistently applied and lack evidence establishing their effectiveness. Pragmatic clinical trial research on optimal dose, formulation, and counseling for new metformin users should be considered.

Cost Effectiveness of Assessing Ultrasound Plaque Characteristics to Risk Stratify Asymptomatic Patients With Carotid Stenosis.

Background Imaging may play an important role in identifying high-risk plaques in patients who have carotid disease and who could benefit from surgical revascularization. We sought to evaluate the cost effectiveness of a decision-making rule based on the ultrasound imaging assessment of plaque echolucency in patients with asymptomatic carotid stenosis. Methods and Results We used a decision-analytic model to project lifetime quality-adjusted life years and costs for 5 stroke prevention strategies: (1) medical therapy only; (2) revascularization if both plaque echolucency and stenosis progression to >90% are present; (3) revascularization only if plaque echolucency is present; (4) revascularization only if stenosis progression >90% is present; or (5) either plaque echolucency or stenosis progression is present. Risks of clinical events, costs, and quality-of-life values were estimated based on published sources and the analysis was conducted from a healthcare system perspective for asymptomatic patients with 70% to 89% carotid stenosis at presentation. Patients who did not undergo revascularization had the highest stroke events (17.6%) and lowest life-years (8.45), while those who underwent revascularization on the basis of either presence of plaque echolucency on ultrasound or progression of carotid stenosis had the lowest stroke events (12.0%) and longest life-years (14.41). The either plaque echolucency or progression-based revascularization group had an incremental cost-effectiveness ratio of $110 000/quality-adjusted life years compared with the plaque echolucency-based strategy, which had an incremental cost-effectiveness ratio of $29 000/quality-adjusted life years compared with the joint echolucency and progression-based strategy. Conclusions Plaque echolucency on ultrasound can be a cost-effective tool to identify patients with asymptomatic carotid artery stenosis most likely to benefit from carotid endarterectomy.

Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support.

Importance: Pulmonary embolism (PE) is a life-threatening clinical problem, and computed tomographic imaging is the standard for diagnosis. Clinical decision support rules based on PE risk-scoring models have been developed to compute pretest probability but are underused and tend to underperform in practice, leading to persistent overuse of CT imaging for PE. Objective: To develop a machine learning model to generate a patient-specific risk score for PE by analyzing longitudinal clinical data as clinical decision support for patients referred for CT imaging for PE. Design, Setting, and Participants: In this diagnostic study, the proposed workflow for the machine learning model, the Pulmonary Embolism Result Forecast Model (PERFORM), transforms raw electronic medical record (EMR) data into temporal feature vectors and develops a decision analytical model targeted toward adult patients referred for CT imaging for PE. The model was tested on holdout patient EMR data from 2 large, academic medical practices. A total of 3397 annotated CT imaging examinations for PE from 3214 unique patients seen at Stanford University hospitals and clinics were used for training and validation. The models were externally validated on 240 unique patients seen at Duke University Medical Center. The comparison with clinical scoring systems was done on randomly selected 100 outpatient samples from Stanford University hospitals and clinics and 101 outpatient samples from Duke University Medical Center. Main Outcomes and Measures: Prediction performance of diagnosing acute PE was evaluated using ElasticNet, artificial neural networks, and other machine learning approaches on holdout data sets from both institutions, and performance of models was measured by area under the receiver operating characteristic curve (AUROC). Results: Of the 3214 patients included in the study, 1704 (53.0%) were women from Stanford University hospitals and clinics; mean (SD) age was 60.53 (19.43) years. The 240 patients from Duke University Medical Center used for validation included 132 women (55.0%); mean (SD) age was 70.2 (14.2) years. In the samples for clinical scoring system comparisons, the 100 outpatients from Stanford University hospitals and clinics included 67 women (67.0%); mean (SD) age was 57.74 (19.87) years, and the 101 patients from Duke University Medical Center included 59 women (58.4%); mean (SD) age was 73.06 (15.3) years. The best-performing model achieved an AUROC performance of predicting a positive PE study of 0.90 (95% CI, 0.87-0.91) on intrainstitutional holdout data with an AUROC of 0.71 (95% CI, 0.69-0.72) on an external data set from Duke University Medical Center; superior AUROC performance and cross-institutional generalization of the model of 0.81 (95% CI, 0.77-0.87) and 0.81 (95% CI, 0.73-0.82), respectively, were noted on holdout outpatient populations from both intrainstitutional and extrainstitutional data. Conclusions and Relevance: The machine learning model, PERFORM, may consider multitudes of applicable patient-specific risk factors and dependencies to arrive at a PE risk prediction that generalizes to new population distributions. This approach might be used as an automated clinical decision-support tool for patients referred for CT PE imaging to improve CT use.

Identifying prevalence and risk factors for metformin non-persistence: a retrospective cohort study using an electronic health record.

OBJECTIVES: Non-persistence may be a significant barrier to the use of metformin. Our objective was to assess reasons for metformin non-persistence, and whether initial metformin dosing or use of extended release (ER) formulations affect persistence to metformin therapy. DESIGN: Retrospective cohort study. SETTING: Electronic health record data from a network of urban academic practices. PARTICIPANTS: The cohort was restricted to individuals receiving a metformin prescription between 2009/1/1 and 2015/9/31, under care for at least 6 months before the first prescription of metformin. The cohort was further restricted to patients with no evidence of any antihyperglycaemic agent use prior to the index date, an haemoglobin A1c measured within 1 month prior to or 1 week after the index date, at least 6 months of follow-up, and with the initial metformin prescription originating in either a general medicine or endocrinology clinic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was early non-persistence, as defined by the absence of further prescriptions for metformin after the first 90 days of follow-up. RESULTS: The final cohort consisted of 1259 eligible individuals. The overall rate of early non-persistence was 20.3%. Initial use of ER and low starting dose metformin were associated with significantly lower rates of reported side effects and non-persistence, but after multivariable analysis, only use of low starting doses was independently associated with improved persistence (adjusted OR 0.54, 95% CI 0.37 to 0.76, for comparison of 500 mg daily dose or less to all higher doses). CONCLUSIONS: These data support the routine prescribing of low starting doses of metformin as a tool to improve persistence. In this study setting, many providers routinely used ER metformin as an initial treatment; while this practice may have benefits, it deserves more rigorous study to assess whether increased costs are justified.

Facilitating informed decisions about breast cancer screening: development and evaluation of a web-based decision aid for women in their 40s.

BACKGROUND: Expert groups and national guidelines recommend individualized decision making about screening mammography for women in their 40s at low-to-average risk of breast cancer. We created Breast Screening Decisions (BSD), a personalized, web-based decision aid, to help women decide when to start and how often to have routine screening mammograms. We evaluated BSD in a large, prospective pilot trial of women and their clinicians. METHODS: Women ages 40-49 were invited to use BSD before a scheduled preventive care visit. One month post-visit, users were asked about decisional conflict, knowledge, perceptions and worry about breast cancer and screening. They were also asked whether they had a screening mammogram since their visit, scheduled an appointment for a screening mammogram, or if they were planning to schedule an appointment within the next six months. Women who responded "no" to each of these successive questions were considered to have no plan for a screening mammogram within the next 6 months, unless they explicitly stated that they were unsure about screening mammography. Clinicians were surveyed regarding mammography discussions and perceived patient knowledge and anxiety. RESULTS: Of 1,100 women invited to use BSD, 253 accessed the website, and 168 were eligible to participate in the pilot study. One-fifth had a family history of breast cancer, and at least 76% had any prior mammogram. At follow-up, 88% of BSD users reported discussing mammography at their visit, and 77% said they had a screening mammogram since the visit or that they made or were planning to make a screening mammogram appointment. The average decisional conflict score was 22.5, within the threshold for implementing decisions. Decisional conflict scores were lowest in women who said that they had or planned to have a mammogram (mean 21.4, 95% CI 18.3-24.6), higher in those who did not (mean 24.8, 95% CI 19.2-30.5), and highest in those who were unsure (mean 31.5, 95% CI 13.9-49.1). Most BSD users expressed accurate perceptions of their breast cancer risk and the benefits and limitations of screening. CONCLUSIONS: A web-based decision aid may support informed, individualized decisions about screening mammography and facilitate discussions about screening between women in their 40s and their clinicians.

Do Surgeon Expectations Predict Clinically Important Improvements in WOMAC Scores After THA and TKA?

BACKGROUND: Failure of THA or TKA to meet a patient's expectations may result in patient disappointment and litigation. However, there is little evidence to suggest that surgeons can consistently anticipate which patients will benefit from those interventions. QUESTIONS/PURPOSES: To determine the ability of surgeons to identify, in advance of surgery, patients who will benefit from THA or TKA and those who will not, where 'benefit' is defined as a clinically important improvement in a validated patient-reported outcomes score. METHODS: In this prospective study, eight high-volume orthopaedic surgeons completed validated THA and TKA expectations questionnaires (score 0-100, 100 being the highest expectation) as part of preoperative assessment of all their patients scheduled for a THA or TKA and enrolled in the Hospital for Special Surgery institutional registry. Enrolled patients completed the WOMAC preoperatively and at 2 years. Successful outcomes were defined as achieving the minimum clinically important difference (MCID) in WOMAC pain and function subscales. Sensitivity, specificity, and receiver operating characteristic (ROC) curves were used to evaluate the ability of surgeons' expectation scores to identify patients likely to achieve the MCID on the WOMAC scale. Analyses were run separately for patients having THA and TKA. We enrolled 259 patients undergoing THA and 247 undergoing TKA, of whom 77% (n = 200) and 77% (n = 191) completed followup surveys 2 years after their procedures, respectively. RESULTS: Surgeons' expectation scores effectively anticipated patients who would improve after THA, but they were no better than chance in identifying patients who would achieve the MCID on the WOMAC score 2 years after TKA. For patients having THA, the areas under the ROC curve were 0.67 (95% CI, 0.53-0.82; p = 0.02) and 0.74 (95% CI, 0.63-0.85; p < 0.01) for WOMAC function and pain outcomes, respectively, indicating good accuracy. Sensitivity and specificity were maximized on WOMAC pain and function scores (sensitivity = 0.69, specificity = 0.72, both for pain and function) at an expectations score of 83 or greater of 100. Surgeons' expectations were more accurate for patients who were men, who had a BMI less than 30 kg/m2, who had more than one comorbidity, and who were older than 65 years. For patients having TKA, surgeons' expectation scores were not better than chance for identifying those who would experience a clinically important improvement on the WOMAC scale (area under ROC curve: Function = 0.51, [95% CI, 0.42-0.61], p = 0.78; Pain = 0.51, [95% CI, 0.40-0.61], p = 0.92). CONCLUSIONS: Most patients having THA and TKA achieved the MCID improvement after surgery. However, the inability of surgeons' expectation scores to discriminate accurately between patients who benefit and those who do not among patients scheduled for THA who are young, with no comorbidities, and with elevated BMIs, and among all patients scheduled for TKA, calls for surgeons to spend more time with these patients to fully understand and address their needs and expectations. Using standardized assessment tools to compare surgeons' expectations and those of their patients may help focus the surgeon-patient discussion further, and address patients' expectations more effectively. LEVEL OF EVIDENCE: Level II, therapeutic study.

Proposals to Conduct Randomized Controlled Trials Without Informed Consent: a Narrative Review.

BACKGROUND: Individual informed consent from all participants is required for most randomized clinical trials (RCTs). However, some exceptions-for example, emergency research-are widely accepted. METHODS: The literature on various approaches to randomization without consent (RWOC) has never been systematically reviewed. Our goal was to provide a survey and narrative synthesis of published proposals for RWOC. We focused on proposals to randomize at least some participants in a study without first obtaining consent to randomization. This definition included studies that omitted informed consent entirely, omitted informed consent for selected patients (e.g., the control group), obtained informed consent to research but not to randomization, or only obtained informed consent to randomization after random assignment had already occurred. It omitted oral and staged consent processes that still obtain consent to randomization from all participants before randomization occurs. RESULTS: We identified ten different proposals for RWOC: two variants of cluster randomization, two variants of the Zelen design, consent to postponed information, two-stage randomized consent, cohort multiple RCT, emergency research, prompted optional randomization trials, and low-risk pragmatic RCTs without consent. CONCLUSION: Of all designs discussed here, only cluster randomized designs and emergency research are routinely used, with the justification that informed consent is infeasible in those settings. Other designs have raised concerns that they do not appropriately respect patient autonomy. Recent proposals have emphasized the importance for RWOC of demonstrating such respect through systematic patient engagement, transparency, and accountability, potentially in the context of learning health care systems.

Designing Radiology Outcomes Studies-Essential Principles.

Health outcomes research is essential to align radiology with current standards of high-value patient care, through the assessment of end results of diagnostic tests, interventions, or policy on patient health. To bridge studies of diagnostic test accuracy and health outcomes research, key considerations include: (1) how to determine when a diagnostic test merits evaluation of impact on outcomes, (2) when study of intermediate/surrogate outcomes can be useful, (3) how to consider the possible harms as well as potential benefits of a test, and (4) how to integrate evidence of an imaging test's efficacy/effectiveness with clinical data to assess outcomes. Due to challenges in conducting studies of long-term outcomes consequent to imaging use, intermediate health outcomes may capture a test's impact on successful diagnosis and therapy, and can provide readily measurable, incremental insights into the role of imaging in health-care delivery and efficiency. In an era marked by recognition of quality and value of care, outcomes research will provide essential evidence to inform radiologists' guidance of imaging use toward improved patient care, creation of clinical guidelines, and policy decisions.