Dataset Information

Effects of external inspections on sepsis detection and treatment: a stepped-wedge study with cluster-level randomisation.

ABSTRACT:

Objective

To evaluate the effects of external inspections on (1) hospital emergency departments' clinical processes for detecting and treating sepsis and (2) length of hospital stay and 30-day mortality.

Design

Incomplete cluster-randomised stepped-wedge design using data from patient records and patient registries. We compared care processes and patient outcomes before and after the intervention using regression analysis.

Setting

Nationwide inspections of sepsis care in emergency departments in Norwegian hospitals.

Participants

7407 patients presenting to hospital emergency departments with sepsis.

Intervention

External inspections of sepsis detection and treatment led by a public supervisory institution.

Main outcome measures

Process measures for sepsis diagnostics and treatment, length of hospital stay and 30-day all-cause mortality.

Results

After the inspections, there were significant improvements in the proportions of patients examined by a physician within the time frame set in triage (OR 1.28, 95% CI 1.07 to 1.53), undergoing a complete set of vital measurements within 1 hour (OR 1.78, 95% CI 1.10 to 2.87), having lactate measured within 1 hour (OR 2.75, 95% CI 1.83 to 4.15), having an adequate observation regimen (OR 2.20, 95% CI 1.51 to 3.20) and receiving antibiotics within 1 hour (OR 2.16, 95% CI 1.83 to 2.55). There was also significant reduction in mortality and length of stay, but these findings were no longer significant when controlling for time.

Conclusions

External inspections were associated with improvement of sepsis detection and treatment. These findings suggest that policy-makers and regulatory agencies should prioritise assessing the effects of their inspections and pay attention to the mechanisms by which the inspections might contribute to improve care for patients.

Trial registration

NCT02747121.

SUBMITTER: Husabo G

PROVIDER: S-EPMC7577024 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Effects of external inspections on sepsis detection and treatment: a stepped-wedge study with cluster-level randomisation.

Husabø Gunnar G Nilsen Roy Miodini RM Solligård Erik E Flaatten Hans Kristian HK Walshe Kieran K Frich Jan C JC Bondevik Gunnar Tschudi GT Braut Geir Sverre GS Helgeland Jon J Harthug Stig S Hovlid Einar E

BMJ open 20201020 10

<h4>Objective</h4>To evaluate the effects of external inspections on (1) hospital emergency departments' clinical processes for detecting and treating sepsis and (2) length of hospital stay and 30-day mortality.<h4>Design</h4>Incomplete cluster-randomised stepped-wedge design using data from patient records and patient registries. We compared care processes and patient outcomes before and after the intervention using regression analysis.<h4>Setting</h4>Nationwide inspections of sepsis care in em ...[more]

PMID: 33082187

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Project description:IntroductionInspections are widely used in health care as a means to improve the health services delivered to patients. Despite their widespread use, there is little evidence of their effect. The mechanisms for how inspections can promote change are poorly understood. In this study, we use a national inspection campaign of sepsis detection and initial treatment in hospitals as case to: (1) Explore how inspections affect the involved organizations. (2) Evaluate what effect external inspections have on the process of delivering care to patients, measured by change in indicators reflecting how sepsis detection and treatment is carried out. (3) Evaluate whether external inspections affect patient outcomes, measured as change in the 30-day mortality rate and length of hospital stay.Methods and analysisThe intervention that we study is inspections of sepsis detection and treatment in hospitals. The intervention will be rolled out sequentially during 12 months to 24 hospitals. Our effect measures are change on indicators related to the detection and treatment of sepsis, the 30-day mortality rate and length of hospital stay. We collect data from patient records at baseline, before the inspections, and at 8 and 14 months after the inspections. We use logistic regression models and linear regression models to compare the various effect measurements between the intervention and control periods. All the models will include time as a covariate to adjust for potential secular changes in the effect measurements during the study period. We collect qualitative data before and after the inspections, and we will conduct a thematic content analysis to explore how inspections affect the involved organisations.Ethics and disseminationThe study has obtained ethical approval by the Regional Ethics Committee of Norway Nord and the Norwegian Data Protection Authority. It is registered at www.clinicaltrials.gov (Identifier: NCT02747121). Results will be reported in international peer-reviewed journals.Trial registrationNCT02747121; Pre-results.

Project description:BackgroundStepped-wedge cluster randomized trials (SWCRTs) are a type of cluster-randomized trial in which clusters are randomized to cross-over to the active intervention sequentially at regular intervals during the study period. For SWCRTs, sequential imbalances of cluster-level characteristics across the random sequence of clusters may lead to biased estimation. Our study aims to examine the effects of balancing cluster-level characteristics in SWCRTs.MethodsTo quantify the level of cluster-level imbalance, a novel imbalance index was developed based on the Spearman correlation and rank regression of the cluster-level characteristic with the cross-over timepoints. A simulation study was conducted to assess the impact of sequential cluster-level imbalances across different scenarios varying the: number of sites (clusters), sample size, number of cross-over timepoints, site-level intra-cluster correlation coefficient (ICC), and effect sizes. SWCRTs assumed either an immediate "constant" treatment effect, or a gradual "learning" treatment effect which increases over time after crossing over to the active intervention. Key performance metrics included the relative root mean square error (RRMSE) and relative mean bias.ResultsFully-balanced designs almost always had the highest efficiency, as measured by the RRMSE, regardless of the number of sites, ICC, effect size, or sample sizes at each time for SWCRTs with learning effect. A consistent decreasing trend of efficiency was observed by increasing RRMSE as imbalance increased. For example, for a 12-site study with 20 participants per site/timepoint and ICC of 0.10, between the most balanced and least balanced designs, the RRMSE efficiency loss ranged from 52.5% to 191.9%. In addition, the RRMSE was decreased for larger sample sizes, larger number of sites, smaller ICC, and larger effect sizes. The impact of pre-balancing diminished when there was no learning effect.ConclusionThe impact of pre-balancing on preventing efficiency loss was easily observed when there was a learning effect. This suggests benefit of pre-balancing with respect to impacting factors of treatment effects.

Project description:BackgroundCluster randomised trials with unequal sized clusters often have lower precision than with clusters of equal size. To allow for this, sample sizes are inflated by a modified version of the design effect for clustering. These inflation factors are valid under the assumption that randomisation is stratified by cluster size. We investigate the impact of unequal cluster size when that constraint is relaxed, with particular focus on the stepped-wedge cluster randomised trial, where this is more difficult to achieve.MethodsAssuming a multi-level mixed effect model with exchangeable correlation structure for a cross-sectional design, we use simulation methods to compare the precision for a trial with clusters of unequal size to a trial with clusters of equal size (relative efficiency). For a range of scenarios we illustrate the impact of various design features (the cluster-mean correlation - a function of the intracluster correlation and the cluster size, the number of clusters, number of randomisation sequences) on the average and distribution of the relative efficiency.ResultsSimulations confirm that the average reduction in precision, due to varying cluster sizes, is smaller in a stepped-wedge trial compared to the parallel trial. However, the variance of the distribution of the relative efficiency is large; and is larger under the stepped-wedge design compared to the parallel design. This can result in large variations in actual power, depending on the allocation of clusters to sequences. Designs with larger variations in cluster sizes, smaller number of clusters and studies with smaller cluster-mean correlations (smaller cluster sizes or smaller intra-cluster correlation) are particularly at risk.ConclusionThe actual realised power in a stepped-wedge trial might be substantially higher or lower than that estimated. This is particularly important when there are a small number of clusters or the variability in cluster sizes is large. Constraining the randomisation on cluster size, where feasible, might mitigate this effect.

Dataset Information

Effects of external inspections on sepsis detection and treatment: a stepped-wedge study with cluster-level randomisation.

Objective

Design

Setting

Participants

Intervention

Main outcome measures

Results

Conclusions

Trial registration

Publications

Effects of external inspections on sepsis detection and treatment: a stepped-wedge study with cluster-level randomisation.

Similar Datasets

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