Cluster randomized trials for health care quality improvement research

Communication Strategies to Improve Antibiotic Prescribing in Pediatric Urgent Care Centers

OBJECTIVE

Urgent care (UC) clinicians frequently prescribe inappropriate antibiotics for upper respiratory illnesses. In a national survey, pediatric UC clinicians reported family expectations as a primary driver for prescribing inappropriate antibiotics. Communication strategies effectively reduce unnecessary antibiotics while increasing family satisfaction. We aimed to reduce inappropriate prescribing practices in otitis media with effusion (OME), acute otitis media (AOM), and pharyngitis in pediatric UC clinics by a relative 20% within 6 months using evidence-based communication strategies.

METHODS

We recruited participants via e-mails, newsletters, and Webinars from pediatric and UC national societies. We defined antibiotic-prescribing appropriateness based on consensus guidelines. Family advisors and UC pediatricians developed script templates based on an evidence-based strategy. Participants submitted data electronically. We reported data using line graphs and shared deidentified data during monthly Webinars. We used χ 2 tests to evaluate change in appropriateness at the beginning and end of the study period.

RESULTS

The 104 participants from 14 institutions submitted 1183 encounters for analysis in the intervention cycles. Using a strict definition of inappropriateness, overall inappropriate antibiotic prescriptions for all diagnoses trended downward from 26.4% to 16.6% ( P = 0.13). Inappropriate prescriptions trended upward in OME from 30.8% to 46.7% ( P = 0.34) with clinicians' increased use of "watch and wait" for this diagnosis. Inappropriate prescribing for AOM and pharyngitis improved from 38.6% to 26.5% ( P = 0.03) and 14.5% to 8.8% ( P = 0.44), respectively.

CONCLUSIONS

Using templates to standardize communication with caregivers, a national collaborative decreased inappropriate antibiotic prescriptions for AOM and had downward trend in inappropriate antibiotic prescriptions for pharyngitis. Clinicians increased the inappropriate use of "watch and wait" antibiotics for OME. Future studies should evaluate barriers to the appropriate use of delayed antibiotic prescriptions.

A Multisite Collaborative to Decrease Inappropriate Antibiotics in Urgent Care Centers

BACKGROUND

Urgent care (UC; a convenient site to receive care for ambulatory-sensitive) centers conditions; however, UC clinicians showed the highest rate of inappropriate antibiotic prescriptions among outpatient settings according to national billing data. Antibiotic prescribing practices in pediatric-specific UC centers were not known but assumed to require improvement. The aim of this multisite quality improvement project was to reduce inappropriate antibiotic prescribing practices for 3 target diagnoses in pediatric UC centers by a relative 20% by December 1, 2019.

METHODS

The Society of Pediatric Urgent Care invited pediatric UC clinicians to participate in a multisite quality improvement study from June 2019 to December 2019. The diagnoses included acute otitis media (AOM), otitis media with effusion, and pharyngitis. Algorithms based on published guidelines were used to identify inappropriate antibiotic prescriptions according to indication, agent, and duration. Sites completed multiple intervention cycles from a menu of publicly available antibiotic stewardship materials. Participants submitted data electronically. The outcome measure was the percentage of inappropriate antibiotic prescriptions for the target diagnoses. Process measures were use of delayed antibiotics for AOM and inappropriate testing in pharyngitis.

RESULTS

From 20 UC centers, 157 providers submitted data from 3833 encounters during the intervention cycles. Overall inappropriate antibiotic prescription rates decreased by a relative 53.9%. Inappropriate antibiotic prescribing decreased from 57.0% to 36.6% for AOM, 54.6% to 48.4% for otitis media with effusion, and 66.9% to 11.7% for pharyngitis.

CONCLUSIONS

Participating pediatric UC providers decreased inappropriate antibiotic prescriptions from 60.3% to 27.8% using publicly available interventions.

Two Questions About the Design of Cluster Randomized Trials: A Tutorial

This is a short tutorial on two key questions that pertain to cluster randomized trials (CRTs): 1) Should I perform a CRT? and 2) If so, how do I derive the sample size? In summary, a CRT is the best option when you "must" (e.g., the intervention can only be administered to a group) or you "should" (e.g., because of issues such as feasibility and contamination). CRTs are less statistically efficient and usually more logistically complex than individually randomized trials, and so reviewing the rationale for their use is critical. The most straightforward approach to the sample size calculation is to first perform the calculation as if the design were randomized at the level of the patient and then to inflate this sample size by multiplying by the "design effect", which quantifies the degree to which responses within a cluster are similar to one another. Although trials with large numbers of small clusters are more statistically efficient than those with a few large clusters, trials with large clusters can be more feasible. Also, if results are to be compared across individual sites, then sufficient sample size will be required to attain adequate precision within each site. Sample size calculations should include sensitivity analyses, as inputs from the literature can lack precision. Collaborating with a statistician is essential. To illustrate these points, we describe an ongoing CRT testing a mobile-based app to systematically engage families of intensive care unit patients and help intensive care unit clinicians deliver needs-targeted palliative care.

Intent-to-treat analysis of cluster randomized trials when clusters report unidentifiable outcome proportions

Background

Cluster randomized trials are designed to evaluate interventions at the cluster or group level. When clusters are randomized but some clusters report no or non-analyzable data, intent-to-treat analysis, the gold standard for the analysis of randomized controlled trials, can be compromised. This article presents a very flexible statistical methodology for cluster randomized trials whose outcome is a cluster-level proportion (e.g. proportion from a cluster reporting an event) in the setting where clusters report non-analyzable data (which in general could be due to nonadherence, dropout, missingness, etc.). The approach is motivated by a previously published stratified randomized controlled trial called, “The Randomized Recruitment Intervention Trial (RECRUIT),” designed to examine the effectiveness of a trust-based continuous quality improvement intervention on increasing minority recruitment into clinical trials (ClinicalTrials.gov Identifier: NCT01911208).

Methods

The novel approach exploits the use of generalized estimating equations for cluster-level reports, such that all clusters randomized at baseline are able to be analyzed, and intervention effects are presented as risk ratios. Simulation studies under different outcome missingness scenarios and a variety of intra-cluster correlations are conducted. A comparative analysis of the method with imputation and per protocol approaches for RECRUIT is presented.

Results

Simulation results show the novel approach produces unbiased and efficient estimates of the intervention effect that maintain the nominal type I error rate. Application to RECRUIT shows similar effect sizes when compared to the imputation and per protocol approach.

Conclusion

The article demonstrates that an innovative bivariate generalized estimating equations framework allows one to implement an intent-to-treat analysis to obtain risk ratios or odds ratios, for a variety of cluster randomized designs.

Improving the quality of quality metrics in neonatology

This article examines approaches for improving the efficiency and effectiveness of quality metrics currently in use in neonatal care. Desirable characteristics of quality metrics are discussed, the criteria and process for their development are presented, and the uses and limitations of current neonatal outcome and process metrics are explored together with approaches for improving metric performance. Discussion includes enhancing quality metrics through optimizing improvement readiness, sustaining improvements once achieved, and use of improvement science methods to improve metric validity.

Optimal designs for group randomized trials and group administered treatments with outcomes at the subject and group level

With group randomized trials complete groups of subject are randomized to treatment conditions. Such grouping also occurs in individually randomized trials where treatment is administered in groups. Outcomes may be measured at the level of the subject, but also at the level of the group. The optimal design determines the number of groups and the number of subjects per group in the intervention and control conditions. It is found by taking a budgetary constraint into account, where costs are associated with implementing the intervention and control, and with taking measurements on subject and groups. The optimal design is found such that the effect of treatment is estimated with highest efficiency, and the total costs do not exceed the budget that is available. The design that is optimal for the outcome at the subject level is not necessarily optimal for the outcome at the group level. Multiple-objective optimal designs consider both outcomes simultaneously. Their aim is to find a design that has high efficiencies for both outcome measures. An Internet application for finding the multiple-objective optimal design is demonstrated on the basis of an example from smoking prevention in primary education, and another example on consultation time in primary care.

A review of the use and effectiveness of digital health technologies in patients with asthma

OBJECTIVE

A new generation of digital health technologies (DHT) offers the opportunity to improve adherence and asthma control. Recent literature was reviewed to summarize the use of technological aids and evaluate their impact on health outcomes in patients with asthma.

DATA SOURCES

PubMed and Embase were searched to identify articles published over the past 5 years (2013 to 2017).

STUDY SELECTIONS

All records were judged for eligibility by 2 independent reviewers; 28 articles met the inclusion criteria.

RESULTS

Interactive websites were the most frequently evaluated type of DHT (50% of all studies), followed by mobile apps in adult patient cohorts. Relatively few studies assessed electronic monitoring devices, phone calls, or text messaging. Among the 16 studies that focused on children, most interventions that used interactive websites (n = 8) showed at least some benefit, although results varied based on the specific outcome. Twelve studies focused on adults, with interventions using interactive websites (n = 6) reporting results that were generally less consistent compared with the pediatric studies. The 6 studies that assessed mobile apps with adult patients reported consistent benefits across a range of outcomes, including medication adherence and asthma control.

CONCLUSION

Most interventions reported at least some benefit, although results varied based on the specific outcome. Overall, technology that included more interactive features, such as website-based daily diary entries and apps that provided real-time feedback, was associated with increased asthma control, as was the case for multidimensional interventions that combined the use of several complementary types of DHT.