iPLATO Research Concludes: Patients Are (Mostly) Good

iPLATORecent research from Imperial College London suggests that almost six million patients a year are turning to A&E because they cannot get an appointment with their GP. At the same time, iPLATO Research published a report concluded that 180,000 people used the iPLATO system to cancel their appointment during the 2013/14 financial year.

Cancelling appointments via text is attractive for both patients and practices. Patients do not have to call up the practice switchboard and wait to talk to someone - they simply reply with the word 'cancel' as a response to an appointment reminder. Similar to when patients book and cancel appointments on-line, practices have the capability to systematically free up appointments through iPLATO's new 'Auto Cancellation' feature. The obvious advantage of text messaging over password restricted web-services, of course, is the broad usage of text messaging and the immediacy of the mobile channel.

Appointment cancellation timing is key for improving access to GP services and avoiding A&E.

To better understand the process of using digital communication to systematically free up urgent GP appointments, iPLATO Research recently studied the anonymised transaction flow of some practices that use ‘Auto Cancellations’ combined with 'iPLATO best practice' of reminding patients about upcoming appointment three days before the event. In this research we sought to evaluate how quickly patients cancel along with the ability of the practice to offer the cancelled appointment to another patient. We define an urgent GP appointment as the ability to see a GP within 48 hours or less from the initial request. A 'green' cancellation frees up the appointment 72 to 48 hours before the event. This is the ideal scenario as it is highly likely (80% or above) that the appointment can be reused by another patient. An 'amber' cancelation frees up the appointment between 48 and 24 hours before and a ‘red’ cancellation frees up the appointment less than 24 hours before the event.

From the studies iPLATO Research concluded that 71% of all cancellations were green, 10% were amber and 19% red, meaning that a significant majority of patients who use text messaging to cancel their appointment do so in time to free up an urgent GP appointment. Indeed, over 6 in 10 patients cancelled within twelve hours after receiving the reminder. This research also largely dispels the myth of the cheeky patient who cancels in the very last moment as only 5% of all text cancellations arrived less than 1 hour before the appointment.

Related news articles:

About iPLATO
iPLATO Healthcare is British innovation company dedicated to mHealth and Analytics since 2006.

iPLATO's evidence based mobile health solutions have proven to improve patient access to healthcare, to enable powerful health promotion targeted at people at risk and to support people with long term conditions.

Serving millions of patients and thousands of healthcare professionals every day iPLATO has emerged as the leader in mobile health. Across this network the company is running campaigns to promote smoking cessation, weight loss, childhood immunisation and pandemic awareness as well as mobile disease management services for people with diabetes, hypertension, epilepsy and HIV.

iPLATO Healthcare's mission is to, in partnership with clinicians, help healthcare commissioners transform patient care through cloud based mHealth and Analytics.

Most Popular Now

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...

Does AI Improve Doctors' Diagnoses?

With hospitals already deploying artificial intelligence to improve patient care, a new study has found that using Chat GPT Plus does not significantly improve the accuracy of doctors' diagnoses when...

AI Analysis of PET/CT Images can Predict…

Dr. Watanabe and his teams from Niigata University have revealed that PET/CT image analysis using artificial intelligence (AI) can predict the occurrence of interstitial lung disease, known as a serious...