To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a “real-world” setting.

Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a “real-world” setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY.

Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%–99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%–61.6%), but not the “real-world” setting (acceptability:32.9%–42.6%).

EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and “real-world” setting, although this was largely related to baseline patient differences favoring the “real-world” EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.

Retrospective self-report is typically used for diagnosing previous pediatric traumatic brain injury (TBI). A new semi-structured interview instrument (New Mexico Assessment of Pediatric TBI; NewMAP TBI) investigated test–retest reliability for TBI characteristics in both the TBI that qualified for study inclusion and for lifetime history of TBI.

One-hundred and eight-four mTBI (aged 8–18), 156 matched healthy controls (HC), and their parents completed the NewMAP TBI within 11 days (subacute; SA) and 4 months (early chronic; EC) of injury, with a subset returning at 1 year (late chronic; LC).

The test–retest reliability of common TBI characteristics [loss of consciousness (LOC), post-traumatic amnesia (PTA), retrograde amnesia, confusion/disorientation] and post-concussion symptoms (PCS) were examined across study visits. Aside from PTA, binary reporting (present/absent) for all TBI characteristics exhibited acceptable (≥0.60) test–retest reliability for both Qualifying and Remote TBIs across all three visits. In contrast, reliability for continuous data (exact duration) was generally unacceptable, with LOC and PCS meeting acceptable criteria at only half of the assessments. Transforming continuous self-report ratings into discrete categories based on injury severity resulted in acceptable reliability. Reliability was not strongly affected by the parent completing the NewMAP TBI.

Categorical reporting of TBI characteristics in children and adolescents can aid clinicians in retrospectively obtaining reliable estimates of TBI severity up to a year post-injury. However, test–retest reliability is strongly impacted by the initial data distribution, selected statistical methods, and potentially by patient difficulty in distinguishing among conceptually similar medical concepts (i.e., PTA vs. confusion).

Shared patient–clinician decision-making is central to choosing between medical treatments. Decision support tools can have an important role to play in these decisions. We developed a decision support tool for deciding between nonsurgical treatment and surgical total knee replacement for patients with severe knee osteoarthritis. The tool aims to provide likely outcomes of alternative treatments based on predictive models using patient-specific characteristics. To make those models relevant to patients with knee osteoarthritis and their clinicians, we involved patients, family members, patient advocates, clinicians, and researchers as stakeholders in creating the models.

Stakeholders were recruited through local arthritis research, advocacy, and clinical organizations. After being provided with brief methodological education sessions, stakeholder views were solicited through quarterly patient or clinician stakeholder panel meetings and incorporated into all aspects of the project.

Participating in each aspect of the research from determining the outcomes of interest to providing input on the design of the user interface displaying outcome predications, 86% (12/14) of stakeholders remained engaged throughout the project. Stakeholder engagement ensured that the prediction models that form the basis of the Knee Osteoarthritis Mathematical Equipoise Tool and its user interface were relevant for patient–clinician shared decision-making.

Methodological research has the opportunity to benefit from stakeholder engagement by ensuring that the perspectives of those most impacted by the results are involved in study design and conduct. While additional planning and investments in maintaining stakeholder knowledge and trust may be needed, they are offset by the valuable insights gained.

To sustainably improve cleaning of high-touch surfaces (HTSs) in acute-care hospitals using a multimodal approach to education, reduction of barriers to cleaning, and culture change for environmental services workers.

Prospective, quasi-experimental, before-and-after intervention study.

The study was conducted in 2 academic acute-care hospitals, 2 community hospitals, and an academic pediatric and women’s hospital.

Frontline environmental services workers.

A 5-module educational program, using principles of adult learning theory, was developed and presented to environmental services workers. Audience response system (ARS), videos, demonstrations, role playing, and graphics were used to illustrate concepts of and the rationale for infection prevention strategies. Topics included hand hygiene, isolation precautions, personal protective equipment (PPE), cleaning protocols, and strategies to overcome barriers. Program evaluation included ARS questions, written evaluations, and objective assessments of occupied patient room cleaning. Changes in hospital-onset C. difficile infection (CDI) and methicillin-resistant S. aureus (MRSA) bacteremia were evaluated.

On average, 357 environmental service workers participated in each module. Most (93%) rated the presentations as ‘excellent’ or ‘very good’ and agreed that they were useful (95%), reported that they were more comfortable donning/doffing PPE (91%) and performing hand hygiene (96%) and better understood the importance of disinfecting HTSs (96%) after the program. The frequency of cleaning individual HTSs in occupied rooms increased from 26% to 62% (P < .001) following the intervention. Improvement was sustained 1-year post intervention (P < .001). A significant decrease in CDI was associated with the program.

A novel program that addressed environmental services workers’ knowledge gaps, challenges, and barriers was well received and appeared to result in learning, behavior change, and sustained improvements in cleaning.

To enhance enrollment into randomized clinical trials (RCTs), we proposed electronic health record-based clinical decision support for patient–clinician shared decision-making about care and RCT enrollment, based on “mathematical equipoise.”

As an example, we created the Knee Osteoarthritis Mathematical Equipoise Tool (KOMET) to determine the presence of patient-specific equipoise between treatments for the choice between total knee replacement (TKR) and nonsurgical treatment of advanced knee osteoarthritis.

With input from patients and clinicians about important pain and physical function treatment outcomes, we created a database from non-RCT sources of knee osteoarthritis outcomes. We then developed multivariable linear regression models that predict 1-year individual-patient knee pain and physical function outcomes for TKR and for nonsurgical treatment. These predictions allowed detecting mathematical equipoise between these two options for patients eligible for TKR. Decision support software was developed to graphically illustrate, for a given patient, the degree of overlap of pain and functional outcomes between the treatments and was pilot tested for usability, responsiveness, and as support for shared decision-making.

The KOMET predictive regression model for knee pain had four patient-specific variables, and an r2 value of 0.32, and the model for physical functioning included six patient-specific variables, and an r2 of 0.34. These models were incorporated into prototype KOMET decision support software and pilot tested in clinics, and were generally well received.

Use of predictive models and mathematical equipoise may help discern patient-specific equipoise to support shared decision-making for selecting between alternative treatments and considering enrollment into an RCT.

The aim of this study was to assess the impact of a urinary tract infection (UTI) management bundle to reduce the treatment of asymptomatic bacteriuria (AB) and to improve the management of symptomatic UTIs.

Before-and-after intervention study.

Tertiary-care hospital.

Consecutive sample of inpatients with positive single or mixed-predominant urine cultures collected and reported while admitted to the hospital.

The UTI management bundle consisted of nursing and prescriber education, modification of the reporting of positive urine cultures, and pharmacists’ prospective audit and feedback. A retrospective chart review of consecutive inpatients with positive urinary cultures was performed before and after implementation of the management bundle.

Prior to the implementation of the management bundle, 276 patients were eligible criteria for chart review. Of these 276 patients, 165 (59·8%) were found to have AB; of these 165 patients with AB, 111 (67·3%) were treated with antimicrobials. Moreover, 268 patients met eligibility criteria for postintervention review. Of these 268, 133 patients (49·6%) were found to have AB; of these 133 with AB, 22 (16·5%) were treated with antimicrobials. Thus, a 75·5% reduction of AB treatment was achieved. Educational components of the bundle resulted in a substantial decrease in nonphysician-directed urine sample submission. Adherence to a UTI management algorithm improved substantially in the intervention period, with a notable decrease in fluoroquinolone prescription for empiric UTI treatment.

A UTI management bundle resulted in a dramatic improvement in the management of urinary tract infection, particularly a reduction in the treatment of AB and improved management of symptomatic UTI.