ReviewJMIR medical informatics2018
Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review.
Review in JMIR medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled 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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Alert fatigue measurement in clinical decision support: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- The Effect of Computerized Alerts on Prescribing and Patient Outcomes: A Systematic Review.Applied clinical informatics · 2025Pooled it
- Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial.Journal of general internal medicine · 2020Trial
- Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals' Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial.Journal of medical Internet research · 2020Trial
- Medication Safety in India and Southeast Asia: A SWOT Analysis of Policies and Practices.Pharmaceutical medicine · 2026Review
- QT prolongation alerts lead to monitoring but rarely to therapeutic changes: a prospective hospital study.Frontiers in pharmacology · 2026Article
- Clinical decision support systems' effect in reducing medication errors and adverse drug events: an expanded review from Making Healthcare Safer IV.BMJ digital health & AI · 2025Review
- Pharmacogenomic augmented machine learning in electronic health record alerts: A health system-wide usability survey of clinicians.Clinical and translational science · 2024Article
- Effect of knowledgebase transition of a clinical decision support system on medication order and alert patterns in an emergency department.Scientific reports · 2023Article
- Electronic monitoring of potential adverse drug events related to lopinavir/ritonavir and hydroxychloroquine during the first wave of COVID-19.European journal of hospital pharmacy : science and practice · 2023Article
- Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review.BMC primary care · 2023Article
- Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision.Clinical pharmacology and therapeutics · 2022Review
- Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events.BMC medical informatics and decision making · 2022Article
- Creating a High-Specificity Acute Kidney Injury Detection System for Clinical and Research Applications.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2021Article
- Electronic Health Record Reminders for Chlamydia Screening in an American Indian Population.Public health reports (Washington, D.C. : 1974) · 2021Article
- Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication-Related Clinical Decision Support System: Model Development and Validation.JMIR medical informatics · 2020Article
- Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert).Journal of medical Internet research · 2020Article
- Applying population health approaches to improve safe anticoagulant use in the outpatient setting: the DOAC Dashboard multi-cohort implementation evaluation study protocol.Implementation science : IS · 2020Article
- Clinical Decision Support and Implications for the Clinician Burnout Crisis.Yearbook of medical informatics · 2020Review
- Is the Climb Worth the View? The Savings/Alert Ratio for Reducing Vitamin D Testing.Applied clinical informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundComputerized decision support systems have raised a lot of hopes and expectations in the field of order entry. Although there are numerous studies reporting positive impacts, concerns are increasingly high about alert fatigue and effective impacts of these systems. One of the root causes of fatigue alert reported is the low clinical relevance of these alerts.
objectiveThe objective of this systematic review was to assess the reported positive predictive value (PPV), as a proxy to clinical relevance, of decision support systems in computerized provider order entry (CPOE).
methodsA systematic search of the scientific literature published between February 2009 and March 2015 on CPOE, clinical decision support systems, and the predictive value associated with alert fatigue was conducted using PubMed database. Inclusion criteria were as follows: English language, full text available (free or pay for access), assessed medication, direct or indirect level of predictive value, sensitivity, or specificity. When possible with the information provided, PPV was calculated or evaluated.
resultsAdditive queries on PubMed retrieved 928 candidate papers. Of these, 376 were eligible based on abstract. Finally, 26 studies qualified for a full-text review, and 17 provided enough information for the study objectives. An additional 4 papers were added from the references of the reviewed papers. The results demonstrate massive variations in PPVs ranging from 8% to 83% according to the object of the decision support, with most results between 20% and 40%. The best results were observed when patients' characteristics, such as comorbidity or laboratory test results, were taken into account. There was also an important variation in sensitivity, ranging from 38% to 91%.
conclusionsThere is increasing reporting of alerts override in CPOE decision support. Several causes are discussed in the literature, the most important one being the clinical relevance of alerts. In this paper, we tried to assess formally the clinical relevance of alerts, using a near-strong proxy, which is the PPV of alerts, or any way to express it such as the rate of true and false positive alerts. In doing this literature review, three inferences were drawn. First, very few papers report direct or enough indirect elements that support the use or the computation of PPV, which is a gold standard for all diagnostic tools in medicine and should be systematically reported for decision support. Second, the PPV varies a lot according to the typology of decision support, so that overall rates are not useful, but must be reported by the type of alert. Finally, in general, the PPVs are below or near 50%, which can be considered as very low.
Indexed as
Identifiers
What OpenQuestion holds
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.