Trial reportImplementation science : IS2014
Patient-specific computer-based decision support in primary healthcare--a randomized trial.
Trial report in Implementation science : IS, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00915304 (Patient Specific Automatic Reminders in Primary Care - the EBMeDS Randomised Trial), which is not on this map. Cited by 16 papers, 3 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.
Patient Specific Automatic Reminders in Primary Care - the EBMeDS Randomised Trial
Who cites it
16 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Interventions to improve the use of EMRs in primary health care: a systematic review and meta-analysis.BMJ health & care informatics · 2019Pooled it
- What maximizes the effectiveness and implementation of technology-based interventions to support healthcare professional practice? A systematic literature review.BMC medical informatics and decision making · 2018Pooled it
- The Empirical Foundations of Telemedicine Interventions in Primary Care.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2016Pooled it
- Effectiveness of a Hospital-Based Computerized Decision Support System on Clinician Recommendations and Patient Outcomes: A Randomized Clinical Trial.JAMA network open · 2019Trial
- Electronic reminders to facilitate longitudinal care: a mixed-methods study in general practices.BMC medical informatics and decision making · 2016Trial
- Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial.Implementation science : IS · 2016Trial
- Trial
- Development of Quality Indicators for the Correct Use of Electronic Medical Records in Primary Care: Modified Delphi Study.JMIR medical informatics · 2026Article
- Integrating clinician support with intervention design as part of a programme testing stratified care for musculoskeletal pain in general practice.BMC family practice · 2021Article
- Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.JMIR research protocols · 2018Article
- Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.Journal of diabetes science and technology · 2018Article
- Computerized Childbirth Monitoring Tools for Health Care Providers Managing Labor: A Scoping Review.JMIR medical informatics · 2017Article
- Adapting a large database of point of care summarized guidelines: a process description.Journal of evaluation in clinical practice · 2017Article
- 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.Implementation science : IS · 2016Article
- Providing Doctors With High-Quality Information: An Updated Evaluation of Web-Based Point-of-Care Information Summaries.Journal of medical Internet research · 2016Review
- Point of care information services: a platform for self-directed continuing medical education for front line decision makers.Postgraduate medical journal · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundComputer-based decision support systems are a promising method for incorporating research evidence into clinical practice. However, evidence is still scant on how such information technology solutions work in primary healthcare when support is provided across many health problems. In Finland, we designed a trial where a set of evidence-based, patient-specific reminders was introduced into the local Electronic Patient Record (EPR) system. The aim was to measure the effects of such reminders on patient care. The hypothesis was that the total number of triggered reminders would decrease in the intervention group compared with the control group, indicating an improvement in patient care.
methodsFrom July 2009 to October 2010 all the patients of one health center were randomized to an intervention or a control group. The intervention consisted of patient-specific reminders concerning 59 different health conditions triggered when the healthcare professional (HCP) opened and used the EPR. In the intervention group, the triggered reminders were shown to the HCP; in the control group, the triggered reminders were not shown. The primary outcome measure was the change in the number of reminders triggered over 12 months. We developed a unique data gathering method, the Repeated Study Virtual Health Check (RSVHC), and used Generalized Estimation Equations (GEE) for analysing the incidence rate ratio, which is a measure of the relative difference in percentage change in the numbers of reminders triggered in the intervention group and the control group.
resultsIn total, 13,588 participants were randomized and included. Contrary to our expectation, the total number of reminders triggered increased in both the intervention and the control groups. The primary outcome measure did not show a significant difference between the groups. However, with the inclusion of patients followed up over only six months, the total number of reminders increased significantly less in the intervention group than in the control group when the confounding factors (age, gender, number of diagnoses and medications) were controlled for.
conclusionsComputerized, tailored reminders in primary care did not decrease during the 12 months of follow-up time after the introduction of a patient-specific decision support system.
trial registrationClinicalTrial.gov NCT00915304.
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