Evidence map›Paper›PMID 24218045›Full record

SynthesisThe Cochrane database of systematic reviews2013

Computerized advice on drug dosage to improve prescribing practice.

Florence Gillaizeau, Ellis Chan, Ludovic Trinquart, Isabelle Colombet, R T Walton, Myriam Rège-Walther, Bernard Burnand, Pierre Durieux

Registry-linked trialAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03537638 (Effectiveness and Cost-effectiveness of a Multicomponent Strategy to Implement a Clinical Practice Guideline and Improve Health Outcomes in People With Systemic Lupus Erythematosus), which is not on this map. Cited by 41 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT03537638 nacompletednot on this mapstarted 2018, after this paper: background citation

Effectiveness and Cost-effectiveness of a Multicomponent Strategy to Implement a Clinical Practice Guideline and Improve Health Outcomes in People With Systemic Lupus Erythematosus

TypeinterventionalSponsorServicio Canario de SaludRan2018 to 2020Enrolled237ConditionsSystemic Lupus ErythematosusArmsMulticomponent intervention
3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  7. Impact of Complex Quality-Interventions on Patient Outcome: A Systematic Overview of Systematic Reviews.Inquiry : a journal of medical care organization, provision and financing
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  19. Golden opportunities for clinical decision support in an era of team-based healthcare.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Florence GillaizeauFrench Cochrane Center, Hôpital Hôtel-Dieu, 1 place du Parvis Notre-Dame, Paris, France, 75004.
Ellis Chan
Ludovic Trinquart
Isabelle Colombet
R T Walton
Myriam Rège-Walther
Bernard Burnand
Pierre Durieux

Funding

Department of Health RP-PG-0609-10181
6 · The paper itself

Abstract

backgroundMaintaining therapeutic concentrations of drugs with a narrow therapeutic window is a complex task. Several computer systems have been designed to help doctors determine optimum drug dosage. Significant improvements in health care could be achieved if computer advice improved health outcomes and could be implemented in routine practice in a cost-effective fashion. This is an updated version of an earlier Cochrane systematic review, first published in 2001 and updated in 2008.

objectivesTo assess whether computerized advice on drug dosage has beneficial effects on patient outcomes compared with routine care (empiric dosing without computer assistance). SEARCH

methodsThe following databases were searched from 1996 to January 2012: EPOC Group Specialized Register, Reference Manager; Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Ovid; EMBASE, Ovid; and CINAHL, EbscoHost. A "top up" search was conducted for the period January 2012 to January 2013; these results were screened by the authors and potentially relevant studies are listed in Studies Awaiting Classification. The review authors also searched reference lists of relevant studies and related reviews. SELECTION CRITERIA: We included randomized controlled trials, non-randomized controlled trials, controlled before-and-after studies and interrupted time series analyses of computerized advice on drug dosage. The participants were healthcare professionals responsible for patient care. The outcomes were any objectively measured change in the health of patients resulting from computerized advice (such as therapeutic drug control, clinical improvement, adverse reactions). DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed study quality. We grouped the results from the included studies by drug used and the effect aimed at for aminoglycoside antibiotics, amitriptyline, anaesthetics, insulin, anticoagulants, ovarian stimulation, anti-rejection drugs and theophylline. We combined the effect sizes to give an overall effect for each subgroup of studies, using a random-effects model. We further grouped studies by type of outcome when appropriate (i.e. no evidence of heterogeneity). MAIN

resultsForty-six comparisons (from 42 trials) were included (as compared with 26 comparisons in the last update) including a wide range of drugs in inpatient and outpatient settings. All were randomized controlled trials except two studies. Interventions usually targeted doctors, although some studies attempted to influence prescriptions by pharmacists and nurses. Drugs evaluated were anticoagulants, insulin, aminoglycoside antibiotics, theophylline, anti-rejection drugs, anaesthetic agents, antidepressants and gonadotropins. Although all studies used reliable outcome measures, their quality was generally low.This update found similar results to the previous update and managed to identify specific therapeutic areas where the computerized advice on drug dosage was beneficial compared with routine care:1. it increased target peak serum concentrations (standardized mean difference (SMD) 0.79, 95% CI 0.46 to 1.13) and the proportion of people with plasma drug concentrations within the therapeutic range after two days (pooled risk ratio (RR) 4.44, 95% CI 1.94 to 10.13) for aminoglycoside antibiotics;2. it led to a physiological parameter more often within the desired range for oral anticoagulants (SMD for percentage of time spent in target international normalized ratio +0.19, 95% CI 0.06 to 0.33) and insulin (SMD for percentage of time in target glucose range: +1.27, 95% CI 0.56 to 1.98);3. it decreased the time to achieve stabilization for oral anticoagulants (SMD -0.56, 95% CI -1.07 to -0.04);4. it decreased the thromboembolism events (rate ratio 0.68, 95% CI 0.49 to 0.94) and tended to decrease bleeding events for anticoagulants although the difference was not significant (rate ratio 0.81, 95% CI 0.60 to 1.08). It tended to decrease unwanted effects for aminoglycoside antibiotics (nephrotoxicity: RR 0.67, 95% CI 0.42 to 1.06) and anti-rejection drugs (cytomegalovirus infections: RR 0.90, 95% CI 0.58 to 1.40);5. it tended to reduce the length of time spent in the hospital although the difference was not significant (SMD -0.15, 95% CI -0.33 to 0.02) and to achieve comparable or better cost-effectiveness ratios than usual care;6. there was no evidence of differences in mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, anti-rejection drugs and antidepressants.For all outcomes, statistical heterogeneity quantified by I(2) statistics was moderate to high. AUTHORS'

conclusionsThis review update suggests that computerized advice for drug dosage has some benefits: it increases the serum concentrations for aminoglycoside antibiotics and improves the proportion of people for which the plasma drug is within the therapeutic range for aminoglycoside antibiotics.It leads to a physiological parameter more often within the desired range for oral anticoagulants and insulin. It decreases the time to achieve stabilization for oral anticoagulants. It tends to decrease unwanted effects for aminoglycoside antibiotics and anti-rejection drugs, and it significantly decreases thromboembolism events for anticoagulants. It tends to reduce the length of hospital stay compared with routine care while comparable or better cost-effectiveness ratios were achieved.However, there was no evidence that decision support had an effect on mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, anti-rejection drugs and antidepressants. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimize the effect of computerized advice.Taking into account the high risk of bias of, and high heterogeneity between, studies, these results must be interpreted with caution.

Indexed as

Drug Therapy, Computer-AssistedPractice Patterns, Physicians'Dosage FormsHumansMedication ErrorsRandomized Controlled Trials as TopicDosage Forms

Identifiers

PMID24218045
PMCPMC11393523

What OpenQuestion holds

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Registered trials

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.