The Inclusion of Economic Endpoints as Outcomes in Clinical Trials Reported to ClinicalTrials.gov

Interventions and impact of pharmacist-delivered services in perioperative setting on clinically important outcomes: a systematic review and meta-analysis

Background

The perioperative arena is a unique and challenging environment that requires coordination of the complex processes and involvement of the entire care team. Pharmacists' scope of practice has been evolving to be patient-centered and to expand to variety of settings including perioperative settings.

Objectives

To critically appraise, synthesize, and present the available evidence of the characteristics and impact of pharmacist-led interventions on clinically important outcomes in the perioperative settings.

Design

A systematic review and meta-analysis.

Methods

We searched PubMed, Embase, and CINAHL from index inception to September 2023. Included studies compared the effectiveness of pharmacist-led interventions on clinically important outcomes (e.g. length of stay, readmission) compared to usual care in perioperative settings. Two independent reviewers extracted the data using the DEPICT-2 (Descriptive Elements of Pharmacist Intervention Characterization Tool) and undertook quality assessment using the Crowe Critical Appraisal (CCAT). A random-effect model was used to estimate the overall effect [odds ratio (OR) for dichotomous and standard mean difference (SMD) for continuous data] with 95% confidence intervals (CIs).

Results

Twenty-five studies were eligible, 20 (80%) had uncontrolled study design. Most interventions were multicomponent and continuous over the perioperative period. The intervention components included clinical pharmacy services (e.g. medication management/optimization, medication reconciliation, discharge counseling) and education of healthcare professionals. While some studies provided a minor description in regards to the intervention development and processes, only one study reported a theoretical underpinning to intervention development. Pooled analyses showed a significant impact of pharmacist care compared to usual care on length of stay (11 studies; SMD -0.09; 95% CI -0.49 to -0.15) and all-cause readmissions (8 studies; OR 0.60; 95% CI 0.39-0.91). The majority of included studies (n = 21; 84%) were of moderate quality.

Conclusion

Pharmacist-led interventions are effective at improving clinically important outcomes in the perioperative setting; however, most studies were of moderate quality. Studies lacked the utilization of theory to develop interventions; therefore, it is not clear whether theory-derived interventions are more effective than those without a theoretical element. Future research should prioritize the development and evaluation of multifaceted theory-informed pharmacist interventions that target the whole surgical care pathway.

Point estimation for adaptive trial designs II: Practical considerations and guidance

In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. As stated in recent FDA guidance on adaptive designs, it is desirable to report estimates of treatment effects that reduce or remove this bias. However, it may be unclear which of the available estimators are preferable, and their use remains rare in practice. This article is the second in a two-part series that studies the issue of bias in point estimation for adaptive trials. Part I provided a methodological review of approaches to remove or reduce the potential bias in point estimation for adaptive designs. In part II, we discuss how bias can affect standard estimators and assess the negative impact this can have. We review current practice for reporting point estimates and illustrate the computation of different estimators using a real adaptive trial example (including code), which we use as a basis for a simulation study. We show that while on average the values of these estimators can be similar, for a particular trial realization they can give noticeably different values for the estimated treatment effect. Finally, we propose guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design. The issue of bias should be considered throughout the whole lifecycle of an adaptive design, with the estimation strategy prespecified in the statistical analysis plan. When available, unbiased or bias-reduced estimates are to be preferred.

Practical Guide to Adjuncts to Clinical Trials in Surgery

This Guide to Statistics and Methods discusses adjunct outcome parameters that optimize patient-centered, timely, efficient, and equitable components in randomized clinical trials.