The value of care algorithms

Protocol for DRAUP: a deimplementation programme to decrease routine chest radiographs after central venous catheter insertion

Introduction

Avoiding low value medical practices is an important focus in current healthcare utilisation. Despite advantages of point-of-care ultrasound (POCUS) over chest X-ray including improved workflow and timeliness of results, POCUS-guided central venous catheter (CVC) position confirmation has slow rate of adoption. This demonstrates a gap that is ripe for the development of an intervention.

Methods

The intervention is a deimplementation programme called DRAUP (deimplementation of routine chest radiographs after adoption of ultrasound-guided insertion and confirmation of central venous catheter protocol) that will be created to address one unnecessary imaging modality in the acute care environment. We propose a three-phase approach to changing low-value practices. In phase 1, we will be guided by the Consolidated Framework for Implementation Research framework to explore barriers and facilitators of POCUS for CVC confirmation in a single centre, large tertiary, academic hospital via focus groups. The qualitative methods will inform the development and adaptation of strategies that address identified determinants of change. In phase 2, the multifaceted strategies will be conceptualised using Morgan’s framework for understanding and reducing medical overuse. In phase 3, we will locally implement these strategies and assess them using Proctor’s outcomes (adoption, deadoption, fidelity and penetration) in an observational study to demonstrate proof of concept, gaining valuable insights on the programme. Secondary outcomes will include POCUS-guided CVC confirmation efficacy measured by time and effectiveness measured by sensitivity and specificity of POCUS confirmation after CVC insertion.

With limited data available to inform interventions that use concurrent implementation and deimplementation strategies to substitute chest X-ray for POCUS using the DRAUP programme, we propose that this primary implementation and secondary effectiveness pilot study will provide novel data that will expand the knowledge of implementation approaches to replacing low value or unnecessary care in acute care environments.

Ethics and dissemination

Approval of the study by the Human Research Protection Office has been obtained. This work will be disseminated by publication of peer-reviewed manuscripts, presentation in abstract form at scientific meetings and data sharing with other investigators through academically established means.

Trial registration number

ClinicalTrials.gov Identifier, NCT04324762, registered on 27 March 2020.

Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology

In oncology, decision-making in individual situations is often very complex. To deal with such complexity, people tend to reduce it by relying on their initial intuition. The downside of this intuitive, subjective way of decision-making is that it is prone to cognitive and emotional biases such as overestimating the quality of its judgements or being influenced by one’s current mood. Hence, clinical predictions based on intuition often turn out to be wrong and to be outperformed by statistical predictions. Structuring and objectivizing oncological decision-making may thus overcome some of these issues and have advantages such as avoidance of unwarranted clinical practice variance or error-prevention. Even for uncertain situations with limited medical evidence available or controversies about the best treatment option, structured decision-making approaches like clinical algorithms could outperform intuitive decision-making. However, the idea of such algorithms is not to prescribe the clinician which decision to make nor to abolish medical judgement, but to support physicians in making decisions in a systematic and structured manner. An example for a use-case scenario where such an approach may be feasible is the selection of treatment dose in radiation oncology. In this paper, we will describe how a clinical algorithm for selection of a fractionation scheme for palliative irradiation of bone metastases can be created. We explain which steps in the creation process of a clinical algorithm for supporting decision-making need to be  performed and which challenges and limitations have to be considered.

The impact of implementation of a nutrition support algorithm on nutrition care outcomes in an intensive care unit

BACKGROUND

A nutrition support algorithm is an operational version of a guideline that is adapted to local requirements and easy to apply in clinical practice. The purpose of this study was to determine the impact of implementing a nutrition support algorithm on nutrition care outcomes in an intensive care unit (ICU) in Switzerland without a designated dietitian.

METHODS

The retrospective study included data collection on 2 cohorts of critically ill patients before (n = 56) and after (n = 56) implementation of a nutrition support algorithm based on the guidelines published by the Society of Critical Care Medicine and the American Society for Parenteral and Enteral Nutrition guidelines.

RESULTS

There were significant differences between groups for the mean delivery of total energy in the pre- vs postimplementation group (909 ± 444 vs 1097 ± 420 kcal/d; P = .023) and mean delivery of protein per day (35 ± 17.9 vs 59.1 ± 27.3 g; P < .001). For patients staying at least 7 days in the ICU, the cumulative energy deficit decreased from -5664 ± 3613 kcal in the preimplementation group to -2972 ± 2420 kcal (P = .011) in the postimplementation group. No significant differences in the route of feeding and timing of enteral nutrition initiation were found.

CONCLUSIONS

Implementation of a nutrition support algorithm resulted in improved provision of energy and protein delivery. This may be further improved with routine nutrition assessment by a dietitian or a designated nutrition support team.