ArticleImplementation science : IS2016
Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial.
Article in Implementation science : IS, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02645357 (Effect on Professional Practice and Health Care Outcomes of Computerized Evidence-based Information System and Clinical Decision Support), which is not on this map. Cited by 9 papers.
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.
Effect on Professional Practice and Health Care Outcomes of Computerized Evidence-based Information System and Clinical Decision Support: A Randomized Controlled Trial in Orthopaedics (GR-2009-1606736)
Who cites it
9 citing papers in PubMed.
- Paediatric rare diseases: Can large language models assist off-label prescribing?British journal of clinical pharmacology · 2025Article
- Identifying Patients at Risk for Alcohol-Exposed Pregnancies: The Importance of Addressing Multiple Risk Factors.Substance use & addiction journal · 2025Article
- Feasibility study of a clinical decision support system for polymedicated patients in primary care.Healthcare technology letters · 2023Review
- Examining clinician choice to follow-up (or not) on automated notifications of medication non-adherence by clinical decision support systems.BMC medical informatics and decision making · 2023Article
- Article
- Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study.BMC medical informatics and decision making · 2019Article
- Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.Journal of diabetes science and technology · 2018Article
- What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation.Implementation science : IS · 2017Article
- The Oswestry Disability Index, confirmatory factor analysis in a sample of 35,263 verifies a one-factor structure but practicality issues remain.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundComputerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/
designThe Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle. DISCUSSION: The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care.
trial registrationClinicalTrials.gov, NCT02645357.
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.