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Alerts in electronic medical records to promote a colorectal cancer screening programme: a cluster randomised controlled trial in primary care.

ABSTRACT: Participation rates in colorectal cancer screening are below recommended European targets.To evaluate the effectiveness of an alert in primary care electronic medical records (EMRs) to increase individuals' participation in an organised, population-based colorectal cancer screening programme when compared with usual care.Cluster randomised controlled trial in primary care centres of Barcelona, Spain.Participants were males and females aged 50-69 years, who were invited to the first round of a screening programme based on the faecal immunochemical test (FIT) (n = 41 042), and their primary care professional. The randomisation unit was the physician cluster (n = 130) and patients were blinded to the study group. The control group followed usual care as per the colorectal cancer screening programme. In the intervention group, as well as usual care, an alert to health professionals (cluster level) to promote screening was introduced in the individual's primary care EMR for 1 year. The main outcome was colorectal cancer screening participation at individual participant level.In total, 67 physicians and 21 619 patients (intervention group) and 63 physicians and 19 423 patients (control group) were randomised. In the intention-to-treat analysis screening participation was 44.1% and 42.2% respectively (odds ratio 1.08, 95% confidence interval [CI] = 0.97 to 1.20, P = 0.146). However, in the per-protocol analysis screening uptake in the intervention group showed a statistically significant increase, after adjusting for potential confounders (OR, 1.11; 95% CI = 1.02 to 1.22; P = 0.018).The use of an alert in an individual's primary care EMR is associated with a statistically significant increased uptake of an organised, FIT-based colorectal cancer screening programme in patients attending primary care centres.

SUBMITTER: Guiriguet C

PROVIDER: S-EPMC4917051 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Alerts in electronic medical records to promote a colorectal cancer screening programme: a cluster randomised controlled trial in primary care.

Guiriguet Carolina C Muñoz-Ortiz Laura L Burón Andrea A Rivero Irene I Grau Jaume J Vela-Vallespín Carmen C Vilarrubí Mercedes M Torres Miquel M Hernández Cristina C Méndez-Boo Leonardo L Toràn Pere P Caballeria Llorenç L Macià Francesc F Castells Antoni A

The British journal of general practice : the journal of the Royal College of General Practitioners 20160606 648

<h4>Background</h4>Participation rates in colorectal cancer screening are below recommended European targets.<h4>Aim</h4>To evaluate the effectiveness of an alert in primary care electronic medical records (EMRs) to increase individuals' participation in an organised, population-based colorectal cancer screening programme when compared with usual care.<h4>Design and setting</h4>Cluster randomised controlled trial in primary care centres of Barcelona, Spain.<h4>Method</h4>Participants were males ...[more]

PMID: 27266861

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Project description:Colorectal cancer is an important public health problem in Spain. Over the last decade, several regions have carried out screening programmes, but population participation rates remain below recommended European goals. Reminders on electronic medical records have been identified as a low-cost and high-reach strategy to increase participation. Further knowledge is needed about their effect in a population-based screening programme. The main aim of this study is to evaluate the effectiveness of an electronic reminder to promote the participation in a population-based colorectal cancer screening programme. Secondary aims are to learn population's reasons for refusing to take part in the screening programme and to find out the health professionals' opinion about the official programme implementation and on the new computerised tool.This is a parallel randomised trial with a cross-sectional second stage.all the invited subjects to participate in the public colorectal cancer screening programme that includes men and women aged between 50-69, allocated to the eleven primary care centres of the study and all their health professionals. The randomisation unit will be the primary care physician. The intervention will consist of activating an electronic reminder, in the patient's electronic medical record, in order to promote colorectal cancer screening, during a synchronous medical appointment, throughout the year that the intervention takes place. A comparison of the screening rates will then take place, using the faecal occult blood test of the patients from the control and the intervention groups. We will also take a questionnaire to know the opinions of the health professionals. The main outcome is the screening status at the end of the study. Data will be analysed with an intention-to-treat approach.We expect that the introduction of specific reminders in electronic medical records, as a tool to facilitate and encourage direct referral by physicians and nurse practitioners to perform colorectal cancer screening will mean an increase in participation of the target population. The introduction of this new software tool will have good acceptance and increase compliance with recommendations from health professionals.Clinical Trials.gov identifier NCT01877018.

Project description:Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real-world evidence for assessing device safety and tracking device-related patient outcomes over time. However, distilling this evidence remains challenging, as information is fractured across clinical notes and structured records. Modern machine learning methods for machine reading promise to unlock increasingly complex information from text, but face barriers due to their reliance on large and expensive hand-labeled training sets. To address these challenges, we developed and validated state-of-the-art deep learning methods that identify patient outcomes from clinical notes without requiring hand-labeled training data. Using hip replacements-one of the most common implantable devices-as a test case, our methods accurately extracted implant details and reports of complications and pain from electronic health records with up to 96.3% precision, 98.5% recall, and 97.4% F1, improved classification performance by 12.8-53.9% over rule-based methods, and detected over six times as many complication events compared to using structured data alone. Using these additional events to assess complication-free survivorship of different implant systems, we found significant variation between implants, including for risk of revision surgery, which could not be detected using coded data alone. Patients with revision surgeries had more hip pain mentions in the post-hip replacement, pre-revision period compared to patients with no evidence of revision surgery (mean hip pain mentions 4.97 vs. 3.23; t?=?5.14; p?<?0.001). Some implant models were associated with higher or lower rates of hip pain mentions. Our methods complement existing surveillance mechanisms by requiring orders of magnitude less hand-labeled training data, offering a scalable solution for national medical device surveillance using electronic health records.

Dataset Information

Alerts in electronic medical records to promote a colorectal cancer screening programme: a cluster randomised controlled trial in primary care.

Publications

Alerts in electronic medical records to promote a colorectal cancer screening programme: a cluster randomised controlled trial in primary care.

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