A Cluster-Randomized Study of Technology-Assisted Health Coaching for Weight Management in Primary Care.

Purpose: We undertook a trial to test the efficacy of a technology-assisted health coaching intervention for weight management, called Goals for Eating and Moving (GEM), within primary care.

Methods: This cluster-randomized controlled trial enrolled 19 primary care teams with 63 clinicians; 9 teams were randomized to GEM and 10 to enhanced usual care (EUC). The GEM intervention included 1 in-person and up to 12 telephone-delivered coaching sessions.

Generalized Propensity Score Methods to Assess CKD-Associated Physiologic Factors and Risk of Kidney Failure in the Chronic Renal Insufficiency Cohort (CRIC) Study.

Epidemiologic studies have identified many biochemical risk factors for chronic kidney disease (CKD) progression that are correlates of kidney function, termed here 'CKD-associated physiologic factors'. Uncertainty remains if these factors are risk factors or risk markers accounting for aspects of kidney function not otherwise captured. We aimed to use flexible machine learning, a dynamic covariate history including kidney function informative markers, and generalized propensity score (GPS) weighting, to better control confounding for such exposures.

Rationale and Design for the BLOCK-SAH Study (Pterygopalatine Fossa Block as an Opioid-Sparing Treatment for Acute Headache in Aneurysmal Subarachnoid Hemorrhage): A Phase II, Multicenter, Randomized, Double-Blinded, Placebo-Controlled Clinical Trial with a Sequential Parallel Comparison Design.

Background: Acute post-subarachnoid hemorrhage (SAH) headaches are common and severe. Management strategies for post-SAH headaches are limited, with heavy reliance on opioids, and pain control is overall poor. Pterygopalatine fossa (PPF) nerve blocks have shown promising results in treatment of acute headache, including our preliminary and published experience with PPF-blocks for refractory post-SAH headache during hospitalization.

A Cost Comparison Between Mohs Micrographic Surgery and Conventional Excision for the Treatment of Head and Neck Melanomas In Situ and Thin Melanomas.

Background: Variation in operative setting and surgical technique exists when treating specialty site melanomas. There are limited data comparing costs among surgical modalities.

Objective: To evaluate the costs of head and neck melanoma surgery performed with Mohs micrographic surgery or conventional excision in the operating room or office-based settings.

Incidence of Timely Outpatient Follow-Up Care After Emergency Department Encounters for Acute Heart Failure.

Background: Patients who are discharged from the emergency department (ED) after an encounter for acute heart failure are at high risk for return hospitalization. These patients may benefit from timely outpatient follow-up care to reassess volume status, adjust medications, and reinforce self-care strategies. This study examines the incidence of outpatient follow-up care after ED encounters for acute heart failure and describes patient characteristics associated with obtaining timely follow-up care.

A regression framework for a probabilistic measure of cost-effectiveness.

To make informed health policy decisions regarding a treatment, we must consider both its cost and its clinical effectiveness. In past work, we introduced the net benefit separation (NBS) as a novel measure of cost-effectiveness. The NBS is a probabilistic measure that characterizes the extent to which a treated patient will be more likely to experience benefit as compared to an untreated patient.

Leveraging machine learning predictive biomarkers to augment the statistical power of clinical trials with baseline magnetic resonance imaging.

A key factor in designing randomized clinical trials is the sample size required to achieve a particular level of power to detect the benefit of a treatment. Sample size calculations depend upon the expected benefits of a treatment (effect size), the accuracy of measurement of the primary outcome, and the level of power specified by the investigators. In this study, we show that radiomic models, which leverage complex brain MRI patterns and machine learning, can be utilized in clinical trials with protocols that incorporate baseline MR imaging to significantly increase statistical power to detect treatment effects.

Changes in Supplemental Nutrition Assistance Program Policies and Diabetes Prevalence: Analysis of Behavioral Risk Factor Surveillance System Data From 2004 to 2014.

Objective: Food insecurity is associated with diabetes. The Supplemental Nutrition Assistance Program (SNAP) is the largest U.S.

Trends in Patient Volume by Hospital Type and the Association of These Trends With Time to Cancer Treatment Initiation.

Importance: Increasing demand for cancer care may be outpacing the capacity of hospitals to provide timely treatment, particularly at referral centers such as National Cancer Institute (NCI)-designated and academic centers. Whether the rate of patient volume growth has strained hospital capacity to provide timely treatment is unknown.

Objective: To evaluate trends in patient volume by hospital type and the association between a hospital's annual patient volume growth and time to treatment initiation (TTI) for patients with cancer.

Net benefit separation and the determination curve: A probabilistic framework for cost-effectiveness estimation.

Considerations regarding clinical effectiveness and cost are essential in comparing the overall value of two treatments. There has been growing interest in methodology to integrate cost and effectiveness measures in order to inform policy and promote adequate resource allocation. The net monetary benefit aggregates information on differences in mean cost and clinical outcomes; the cost-effectiveness acceptability curve was developed to characterize the extent to which the strength of evidence regarding net monetary benefit changes with fluctuations in the willingness-to-pay threshold.

Impact of Regression to the Mean on the Synthetic Control Method: Bias and Sensitivity Analysis.

To make informed policy recommendations from observational panel data, researchers must consider the effects of confounding and temporal variability in outcome variables. Difference-in-difference methods allow for estimation of treatment effects under the parallel trends assumption. To justify this assumption, methods for matching based on covariates, outcome levels, and outcome trends-such as the synthetic control approach-have been proposed.