Trial reportImplementation science : IS2017
Electronic Laboratory Medicine ordering with evidence-based Order sets in primary care (ELMO study): protocol for a cluster randomised trial.
Trial report in Implementation science : IS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02950142 (The Effect of Evidence-based Order Sets Within a CPOE System on the Quantity and Quality of Laboratory Test Ordering in Family Practice), which is not on this map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Effect of Evidence-based Order Sets Within a CPOE System on the Quantity and Quality of Laboratory Test Ordering in Family Practice: a Cluster Randomised Trial
Who cites it
5 citing papers in PubMed.
- Trial
- Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial.Implementation science : IS · 2020Trial
- Trends and Components of Thyroid Status Evaluation in Commercially Insured Adults in the United States, 2006-2020.The Journal of clinical endocrinology and metabolism · 2024Article
- Health Data for Research Through a Nationwide Privacy-Proof System in Belgium: Design and Implementation.JMIR medical informatics · 2018Article
- The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support.Implementation science : IS · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundLaboratory testing is an important clinical act with a valuable role in screening, diagnosis, management and monitoring of diseases or therapies. However, inappropriate laboratory test ordering is frequent, burdening health care spending and negatively influencing quality of care. Inappropriate tests may also result in false-positive results and potentially cause excessive downstream activities. Clinical decision support systems (CDSSs) have shown promising results to influence the test-ordering behaviour of physicians and to improve appropriateness. Order sets, a form of CDSS where a limited set of evidence-based tests are proposed for a series of indications, integrated in a computerised physician order entry (CPOE) have been shown to be effective in reducing the volume of ordered laboratory tests but convincing evidence that they influence appropriateness is lacking. The aim of this study is to evaluate the effect of order sets on the quality and quantity of laboratory test orders by physicians. We also aim to evaluate the effect of order sets on diagnostic error and explore the effect on downstream or cascade activities.
methodsWe will conduct a cluster randomised controlled trial in Belgian primary care practices. The study is powered to measure two outcomes. We will primarily measure the influence of our CDSS on the appropriateness of laboratory test ordering. Additionally, we will also measure the influence on diagnostic error. We will also explore the effects of our intervention on cascade activities due to altered results of inappropriate tests. DISCUSSION: We have designed a study that should be able to demonstrate whether the CDSS aimed at diagnostic testing is not only able to influence appropriateness but also safe with respect to diagnostic error. These findings will influence a lager, nationwide implementation of this CDSS.
trial registrationClinicalTrials.gov, NCT02950142 .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.