Industry news in brief

  • 7 May 2021
Industry news in brief
Digital Health's weekly round-up of healthcare IT news

The latest Digital Health News industry news round-up features news that e-clinic has launched a booking app and a data tracker for lung health is improving understanding of respiratory conditions.

e-clinic launches healthcare booking app

Patient and clinic management software provider e-clinic has launched a new patient-focused booking app called BookmyClinic.

The new platform will enable patients to search for relevant clinics, book their treatments and appointments, and manage payments and follow up appointments.

For clinics, it enables them to reach more patients, more efficiently, through a location-based search tool which allows users to find clinics in their vicinity for more efficient conversion and engendering of loyalty and the support of local businesses.

BookmyClinic will also deliver unique analytics to clinic managers to support their growth and development. Anonymised data will be made available based on patient preferences and usage of the app, enabling more tailored services and even greater efficiencies.

Mark Lainchbury, product director at e-clinic, said: “The launch of the new app comes as the world is emerging from the pandemic and businesses plan for reopening.

“Ahead of an easing of lockdown and a return to relative normality, there is an expectation that aesthetic treatments will see a boom post Lockdown, and medical surgeries will be managing an increased number of patient bookings. We feel it is an opportune time for clinics to prepare for this.”

Lung Health Data Tracker aims to improve data on respiratory health

The Taskforce for Lung Health, a collaboration of more than 30 different charities, organisations and patients with lung conditions trying to improve lung health in England, is raising awareness of its Lung Health Data Tracker, which aims to provide statistical evidence on the nation’s lung health.

The Lung Health Data Tracker was created to address the fact that data on respiratory health is patchy, lagging far behind other diseases. Although there are 12 million people living with a history of lung disease in the UK, before the creation of the Lung Health Data Tracker, there was no public facing resource or ‘one stop shop’ which could inform researchers, healthcare professionals and the public about lung health across the country.

Since the launch of the Lung Health Data Tracker in December 2019, the Taskforce has been able to highlight that nearly one million people in England have missed out on opportunities to quit smoking due to service cuts, work out that there are at least 450,000 people living with occupational lung disease (existing records only show 144,000), and highlight the need for increased uptake of the flu jab among healthcare workers.

Dr Alison Cook, chair of the Taskforce for Lung Health, said: “The Lung Health Data Tracker was developed to address the huge gaps that exist when it comes to information about lung health.

“The data that does exist is often patchy, difficult to understand and hidden behind closed doors unavailable to the public. It is difficult to support people living with lung conditions when there are glaring knowledge gaps about how many people live with certain conditions, how easily they are able to access treatment, and how they are affected by lung health issues across the country.

“By launching and developing the Lung Health Data Tracker, the Taskforce is creating a one stop shop where anyone can access and more importantly understand, all of the available information we have about lung health in one place for the first time.”

AI tool may improve diagnosis of cancers

An artificial intelligence (AI) tool could improve the diagnosis of metastatic cancer, according to new research.

In 1 to 2 percent of cancer cases, the primary site of tumor origin cannot be determined and patients often have to undergo extensive diagnostic procedures, which can delay treatment.

To improve diagnosis for patients with complex metastatic cancers, especially those in low-resource settings, researchers from the Mahmood Lab at the Brigham and Women’s Hospital developed an artificial intelligence (AI) system that uses routinely acquired histology slides to accurately find the origins of metastatic tumors while generating a “differential diagnosis,” for CUP (cancer of unknown primary) patients.

Faisal Mahmood, PhD, of the Division of Computational Pathology at the  Brigham and an assistant professor at Harvard Medical School, said: “Almost every patient that has a cancer diagnosis has a histology slide, which has been the diagnostic standard for over a hundred years.

“Our work provides a way to leverage universally acquired data and the power of artificial intelligence to improve diagnosis for these complicated cases that typically require extensive diagnostic work-ups.”

The deep-learning-based algorithm developed by the researchers, called Tumor Origin Assessment via Deep Learning (TOAD), simultaneously identifies the tumor as primary or metastatic and predicts its site of origin.

The researchers trained their model with gigapixel pathology whole-slide images of tumors from more than 22,000 cancer cases, and then tested TOAD in about 6,500 cases with known primaries and analysed increasingly complicated metastatic cancers to establish utility of the AI model on CUPs.

For tumors with known primary origins, the model correctly identified the cancer 83% of the time and listed the diagnosis among its top three predictions 96% of the time.

Researchers then tested the model on 317 CUP cases for which a differential diagnosis was assigned, finding that TOAD’s diagnosis agreed with pathologists’ reports 61 percent of the time and top-three agreement in 82 percent of cases.

The findings were published in the journal Nature.

Rotherham-based medical device company takes home award for innovation

A Rotherham-based medical device company has been awarded a Queen’s Award for Enterprise in Innovation.

The award was secured by Marsden in recognition of the work the company has undertaken in developing a unique Patient Transfer Scale, which is used to provide accurate weight measurements when a patient is admitted to hospital.

Launched in 2018, the Marsden Patient Transfer Scale is now used in 65% of all NHS trusts across the UK and also sold worldwide.

The innovative product was developed when nurse Gillian Taylor witnessed first-hand the discomfort and delays to treatment caused when medical staff attempted to weigh immobile patients using traditional hoists.

When a patient suffers a stroke or is diagnosed with sepsis it is vital for medication to be administered as quickly as possible. However, before treatment can begin a patient must be weighed to identify the correct dosage required.

But cumbersome hoists could lead to delays in the time taken for a patient to receive treatment. Now, the Patient Transfer Scale can weigh patients up to 250kg (39 stone) and provides accurate readings up to 500g.

Gillian Taylor, inventor of the Patient Transfer Scale, said: “When patients are admitted to hospital, getting accurate weight measurements is vital because it determines the amount of medication needed.

“I looked at my kitchen scales and had something of a lightbulb moment. During my research, I began to realise the invention could have other practical uses within a hospital and after developing a prototype we approached Marsden, to see whether they could help transform the idea into a product capable of saving lives.”

Subscribe to our newsletter

Subscribe To Our Newsletter

Subscribe To Our Newsletter

Sign up

Related News

AI software improves odds of good maternity care by 69%, say researchers

AI software improves odds of good maternity care by 69%, say researchers

Women are more likely to receive good care during pregnancy when AI and other clinical software tools are used, researchers have found.
NHS to trial AI tool that predicts health risks and early death

NHS to trial AI tool that predicts health risks and early death

The NHS in England is to trial an AI tool that can predict patients’ risk of heart disease and early death using an electrocardiogram (ECG).
NICE recommends use of AI to detect broken bones on X-rays

NICE recommends use of AI to detect broken bones on X-rays

NICE has recommended the use of four AI technologies to help detect broken bones on X-rays, in addition to a trained healthcare professional.