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Nandish Chiropractic in East Auckland has come a long way since it opened its doors in 2015.
It’s now one of the city’s largest chiropractic clinics with six chiropractors specialising in different fields.
E-Referrals to Nandish Chiropractic can be made using CareSelect.
Nandish Chiropractic has five departments: the Spinal Clinic, Headache and Migraine Clinic, Concussion Clinic, Pregnancy Clinic, and Paediatric Clinic.
Nandish Chiropractic founder and principal chiropractor Karen Singh says she loves helping people thrive by encouraging a proactive, holistic approach to healthcare.
Dr Singh has a keen interest in complex and chronic pain, spinal disc compression and stress. She also runs wellness classes teaching patients how to manage stress effectively.
“Chiropractic care is a proven and effective way to align the spine and nervous system to operate at its optimum potential,” she says.
Three-step process
Each new patient goes through a three-step process.
“They have an extensive health history check, physical assessment (postural, range of motion, orthopaedic, neurologic and spinal), and a report of findings with clinical diagnosis and a care plan tailored to the patient’s needs. We believe education and empowerment is key in the healing and recovery process,” says Dr Singh.
“We like to help people understand why things are happening and what they can do to help themselves. We also focus on stress and the effects it has on the body and functionality. The body is like a car – it won’t function as well as one that gets regularly serviced.”
Dr Singh says a common issue is device use and changes in the spinal curve due to an increased load on the neck and spinal nerves causing poor posture, headaches and premature degeneration.
“We help realign their posture, educate them about spinal ergonomics and where their screens should be to be proactive and avoid future problems.”
She says people sometimes confuse chiropractors with physiotherapists.
“Physiotherapists focus on injury rehabilitation, whereas chiropractors focus on the underlying issues with the neck, back and nervous system.”
Dr Singh says her team regularly holds workshops with health practitioners to explain what chiropractors do.
How to refer to Nandish Chiropractic:
open the patient record
select the HealthLink icon
use the CareSelect search bar, type “Nandish Chiropractic”
click “Compose Referral”.
e-Referrals for Freedom Medical Alarms go nationwide
E-Referrals for Freedom Medical Alarms can now be made for patients living outside of Wellington.
Previously, e-Referrals could only be made for patients living in the capital, but they can now be made nationwide.
Freedom Medical Alarms national manager Debbie Booth says it’s exciting for the service to be expanding.
“It means we can provide support and reassurance to a much larger number of people,” she says.
Peace of mind for everybody
Freedom Medical Alarms is a joint venture with HealthCare NZ and Wellington Free Ambulance. It’s the only medical alarm directly connected to the Central Emergency Ambulance Communication Centre.
“That means patients are directly connected to trained emergency call-takers at the push of a button.”
Debbie says it’s reassuring for patients and their family members to know that medical help is readily available.
“It provides peace of mind for everybody and freedom from worry.”
Funding available
Freedom Medical Alarms is a Work and Income accredited supplier.
“If a patient qualifies, an alarm can be funded through the Disability Allowance.”
The cost of an ambulance call out is covered for all patients, Debbie says.
Freedom Medical Alarms also has a GO pendant that can be worn out in the community but isn’t currently funded.
Landline or cellular network
Patients can choose either a neck or wrist pendant, which they press in an emergency. The alarms work via a landline or the cellular network.
A key safe can be installed as part of the set up so paramedics can easily access a patient’s home in the case of an emergency.
“The patient’s next of kin is also contacted if an ambulance is called.”
Debbie says the demand for Freedom Medical Alarms is increasing.
“We’ve seen a surge in demand since the COVID-19 pandemic because people are living alone and isolated. We also have an ageing population and people want to be able to live in their own home for longer.”
How to refer to Freedom Medical Alarms:
open the patient record
select the HealthLink icon
scroll to the “Referred Services” heading
select Freedom Medical Alarms.
System Release – RTEC, SCR 1-click, Bag labels, EPS Queues
We are delighted to share with you a detailed look at what’s included in the June system release.
Since our upgrade to HTML5, RxWeb is faster, smoother, and more reliable than ever before. The time it takes to develop and release new features to the system has also reduced significantly which means our product roadmap has become much more agile.
Because of this, we have adopted a new system release schedule meaning you will be seeing new features and functionality added to RxWeb much more regularly. And as a web-based system, all updates are rolled out remotely by our development team.
So what’s in the release?
Real-Time Exemption Checking (RTEC) – RxWeb will now confirm a patient’s exemption status by automatically checking the NHS databases. PLEASE NOTE: There will be an initial pilot phase of RTEC meaning it won’t be immediately available within the system. Once approved by the NHS, this feature will be rolled out to all customers. This pilot is expected to run for 6 weeks. We will keep you updated on progress.
Token Printing Limit Increased – The EPS token printing limit has been increased from 10 tokens to 20 tokens.
SCR 1 click integration – Allows RxWeb users to access a patient’s SCR record with a single click from the patient home screen. PLEASE NOTE: Similar to RTEC, this feature will be switched on for all customers shortly after the release pending approval from the NHS.
Increased View In EPS Queues – The ‘Additional Information’ window in the queues has now been replaced with a button to access this information, providing an increased view of the items listed in the EPS queues.
New FP34 report – A new report has been added under Report Type ‘Financial’ called FP34 Statement Data – Current + 6 Months (EPS2) This report shows all items claimed for the last 6 months and for the current month, based on claims made within the claim submission window for the respective month. This is to help reconcile the item counts with the FP34 payment.
Barcodes on Bag Labels – If you use an app for delivering prescriptions to your patients you will be able to scan a barcode on the bag label (containing the patient’s NHS number) directly into the delivery app. This will help you find your patient’s details quickly and easily.
New Filter on Dispensing Screen – To help speed up the search responses for drugs, the current filters have been updated to only return those items currently available in the DM+D or that have been discontinued in the last 18 months. A new ‘ALL+DISC’ filter has therefore been added to display all items in the DM+D, including all discontinued items listed, regardless of the date they were discontinued.
Search by NHS Number – Users can now search for a patient from the home screen using their NHS number.
nhs.uk Domain Added for Prescribers – Users can now enter email addresses for prescribers that have nhs.uk addresses, as well as nhs.net, when sending repeat requests by email.
Sort Care homes Drug Grid by Headers – You can now click the headers on the columns in the care home module to sort the data.
Colours for Care Home/MDS Patients – You can now set a colour for your care home and MDS patients so they are highlighted in the queues.
New 3rd Party Integrations
Pharmatek – A new dispensing robot entering the UK market. Further details at www.avonnex.com or by contacting amrik@avonnex.com
AviBuyer – AviBuyer is another new buying tool available to RxWeb users. Please note that you must have Avicenna membership to use this system. For further details, please click here or contact support@avicenna.org
Please Note: RxWeb will now automatically set the correct exemption and you will not be required to perform any additional actions in the following cases:
Patient is Age Exempt – we will automatically set every script as Exempt: A
ALL Items on the prescription are prescriber endorsed FS (Sexual Health Free of Charge Medication) – prescription will automatically be set as Exempt: Y
ALL Items on the prescription are prescriber endorsed CC (Free of Charge Contraceptives) – prescription will automatically be set as Exempt: X
In case of a prescription where NOT ALL Items are prescriber endorsed with either CC or FS you will still need to confirm the exemption for all other items that may require payment if the patient is Not Exempt, therefore the system will not set the exemption automatically for that script.
You can learn more about what integrations are available with RxWeb by visiting our modules page here or contact sales@rxweb.co.uk . A range of smaller items and bug fixes will also be included within the release. A full set of release notes CAN BE FOUND HERE.
We have also hosted a webinar where we ran through all the relevant updates and how they work. You can watch this webinar back down below.
We’ve been very excited to share this first major release with you all. We’ll be in touch again next week to let you know when the release has gone live
RxWeb is designed to be the digital foundation of your pharmacy. We are proud to be the UK’s only web-based Patient Medical Record (PMR) system that exceeds the needs of all pharmacy types and sizes. RxWeb is a simple and straightforward system providing users with fast and intuitive workflows to streamline the whole dispensing process and other areas of pharmacy management.
Our system beats our competitors because it enables you to manage the day-to-day operations of your pharmacy, seamlessly running clinical services, patient communications, stock management and robot integrations allowing you to focus on patient care.
If you’re not currently using RxWeb but would like to learn more about the system we recommend booking a demonstration or downloading a brochure at the links below.
While the HSE work through the impact of the recent ransomware attack on its IT systems we want to assure all customers and users that no Clanwilliam Health system has been affected by this attack. We have undertaken a thorough investigation of our system infrastructure and where necessary we have restricted access to all HSE systems while they work through their recovery and restoration processes.
In addition to these steps, we have also conducted risk assessments for all of our systems and will continue to closely monitor the situation, assisting both the HSE and all of our customers however best we can.
We will continue to notify customers directly, through email, as soon as we receive updates from the HSE that their systems are back online and safe to use.
Dictate IT Provides GP Market with AI-Powered Speech Recognition Solutions
Dictate IT, part of healthcare technology company Clanwilliam Group, today confirmed its plans to enter the UK GP and primary care market with its AI-powered speech recognition products for the first time.
With over 30,000 clinical users and almost 20 years’ experience of supplying NHS Trusts with digital dictation and transcription software, Dictate has been developing speech recognition in their AI labs since 2014. The company is the only UK supplier to have developed its own cutting-edge deep neural net based medical speech recognition engine, enabling unmatched highly-accurate speech recognition for UK medical dictation.
Already widely used in NHS Trusts, Dictate IT has been trialling two of its speech recognition products with GPs across the country for four months, with strong results. Both products are designed to save valuable time and increase efficiencies.
Dictate Swift is a workflow-based speech recognition solution designed to support existing letter production processes. Doctors securely dictate from their iOS or Android smartphone; the medical letter is then made available via the web-based application for their administrative staff for final review and completion. The software facilities remote working and is also integrated with EMIS and TPP clinical systems.
“We have been extremely satisfied with Dictate IT – the product works really well transcribing speech to text for medical letters near flawlessly. This significantly reduces secretarial typing times and allows them to focus on other tasks that are always adding to their workloads. The ability to remote dictate using smartphone app securely is wonderful; it is so intuitive and easy to use that even our most IT wary colleagues took to it easily!”
Dr Matt Best, from Yelverton Surgery
Dictate IT’s second product offering in the market is Dictate Live which provides immediate speech-to-text conversion. GPs simply place their cursor where they want the text to appear, and dictate. Their voice is picked up either from their desktop microphone or Dictate app making the process completely seamless. Dictate Live works with any 3rd party system, including EMIS Web and SystmOne. Research has found that, in general, people can speak three times faster than typing. Therefore, using Dictate Live provides enormous potential for time saving on clinical note capturing.
“Dictate Live is very quick and writes into any programme a GP might use. It saves me an hour per day.”
Dr Andrew Sharpe, from Ashley Centre Surgery
“We are unique in that our proprietary AI-based speech recognition technology was built specifically for use in the NHS. Our proposition for GPs is simple – cost effective products that deliver immediate benefit, will little or no implementation effort required. Our products don’t require any voice training or hardware and cover a wide range of accents found across the country. We are providing a three-month trial to allow users to see for themselves how accurate our speech engine behind Dictate Swift and Dictate Live really is.
Additionally, we continue to expand our provision of speech recognition into secondary care settings, therefore we expect to soon have multiple regions where we provide end-to-end digital clinical correspondence services. The resultant integrated approach will radically expand the scope of benefits that we will be able to bring to our NHS customer base.”
Rob Hadley, Commercial Director of Dictate IT said
Dictate IT is offering GPs
Dictate IT is offering GPs a free three-month trial of Dictate Swift and Dictate Live, with no installation cost. To find more and book a free trial
Bluespier Theatres went live on 22nd March 2021 across all theatres at the Trust replacing the Trust’s previous Theatre Management System, Galaxy DXC. Bluespier Theatres is fully integrated with the Trust’s EPR, Careflow, ensuring a seamless user experience. Elective and emergency theatre bookings can be scheduled and managed directly from within System C’s Patient Administration System. The wider theatre record can also be accessed directly from within Careflow, which allows for end-to-end management of the theatre journey.
Along with other recent implementations the project was delivered through a difficult period for the NHS, with the Trust in the mist of a second covid wave. This however did not affect the scheduled go live date and the determination and collaborative working between Bluespier and the Trust ensured a positive go live.
Following the install of the core Theatre system, we are looking forward to working with the Trust to further embed more functionality and help the Trust reap the benefits as an organisation.
Paul Chadwick, Head of IT for Southport and Ormskirk Hospital NHS Trust, said: “To deliver the best care for our patients, it is vital that our Theatre and clinical teams have access to all the information they need at the point of care. Through its direct integration into the Trust EPR, Bluespier provides this. The implementation has been a great success through a collaborative effort. We look forward to building on this going forward and continuing to provide high quality care for our patients.”
Stuart van Rooyen, Managing Director of Bluespier, said: “The implementation of Bluespier Theatres into Southport and Ormskirk Hospital NHS Trust has been a huge success due to the vast efforts and hard work of Trust and Bluespier staff. I’m delighted the Trust are looking to further utilise other Bluespier modules including our new mobile application, Bluespier Mobile. We look forward to a long and successful partnership working collaboratively with the Trust and System C improving both efficiency and patient care through utilising fit for purpose technology.”
In this, our first DGL Practice Manager Lunch and Learn Webinar, our Service Delivery Leader, David West brought attendees through all of the reporting functionality within DGL. We looked at areas around patients, billing and accounts while also showing users where to find reports and how the key ones work e.g. filtering/adding columns.
Please feel free to share this with your wider team and colleagues if you think it will be of use.
DGL Go, Speech Recognition And Video Consultations On Your Mobile Device
Speech Recognition is a technology that has fascinated and disappointed doctors for more than 25 years. Dictate IT has been developing Speech Recognition solutions in our AI labs since 2014 and outlined here is a brief history of the science behind the technology and a reflection on why it might be the right time to give it a second look.
The ability for machines to recognise and respond to human speech has been a desire since the outset of computing. Early computer scientists wished they could interact with their creations as they did with their colleagues – by talking.
The Post War Period – The birth of the Computer Age
The first machine capable of recognizing human speech was invented in 1952 and named ‘Audrey’ by Bell Labs in the US. She could recognise spoken numbers from 1 to 9. Ten years later, IBM released ‘Shoebox’ which had the ability to recognise simple calculations and input them into a calculator. In the UK, scientists worked to improve recognition using statistical information concerning allowable phonemes in English, and in the USSR they pioneered dynamic time warping to cope with variations in speaking speed. Ask typists in your surgery about the variations in the speed of speech patterns and you will understand the significance of this.
Progress Slows after a promising start
By the 1970s progress had slowed, hampered by the idea that to improve recognition, machines would need to ‘understand’ speech, something that turned out to be unnecessary for the task of recognition and something which still eludes us today.
The late 70s and early 80s saw the introduction of two key new approaches: n-gram language models and Hidden Markov Models (HMMs).
N-gram language models describe the probability of a sequence of words, and are often contextual dependant. For example in the medical dictation domain, the tri-gram “This charming gentleman” is more likely than “This charming pineapple”. This probability allows speech recognition to go beyond just the phonetic information in the audio.
Hidden Markov model
Hidden Markov Models are variants of techniques developed in the 1960s to aid prediction in the US defence industry, in turn based on maths outlined by the Russian Andrey Markov in the middle of the 20th century. Markov models aim to simplify prediction of a future state by only using the current state, rather than needing to use many prior states. Adoption of HMMs for speech recognition, coupled with the increases in computer power needed to feasibly run them produced huge leaps in accuracy and vocabulary size. HMMs continued to dominate speech recognition approaches for the next 25 years.
During the 90s and 00s, the PC enabled HMM-based speech recognition to become more widely available to consumers. Accuracy continued to improve, though began to plateau in the early 00s and still required a degree of per user training and manual correction, based on a speaker-dependent individual profile. Thus speech recognition acquired a slightly jaded reputation as being ‘not quite good enough’ for normal usage. When you last tried speech recognition on your PC to dictate a medical report you probably used a system that used an HMM acoustic model. The results would have been interesting –but not good enough and you probably concluded that it was not for your practice.
Enter the Neural Network and Machine Learning
Artificial Neural Networks (ANNs) were first described in the 1940s, and are networks of nodes and connections inspired by the workings of biological neurons. As with real neurons, as the network ‘learns’ some connections between nodes become stronger, some weaker. The difference from classic computer programming was that ANNs ‘learn’ by themselves rather than being driven entirely from hand-crafted rules given to them by their human programmers. It wasn’t until the 1980s that computing power was sufficient to realise the theoretical technique and interest in neural networks surged with hopes of (strong) Artificial Intelligence based on this biological model. The concept was applied to tasks like speech recognition, but without much success compared to the dominant HMMs. General interest in ANNs declined.
However, in the early 00s, a specific kind of ANN method called Deep Learning began to emerge as a potentially superior alternative. In particular, a collaboration between researchers at Google, Microsoft, IBM, and the University of Toronto showed how Deep Learning techniques could bring significant improvements to many areas including speech, image, and handwriting recognition.
Deep Learning uses Neural Networks that are ‘deep’ by virtue of having multiple layers of nodes between their input and output layers. In speech recognition the input being a segment of audio and the output a piece of text. Each layer ‘learns’ to transform the input to the output in a slightly different way. In 2009 a researcher at Google realised that by using Graphics Processing Units they could massively speed up the training of Deep Neural Networks (DNNs), dramatically shortening the time taken to experiment with new models. By 2012 it was clear that DNNs were outperforming old approaches in multiple fields and this kicked off the huge industry interest and public awareness about the use of ‘AI’.
DNNs are now used by all the major consumer speech recognition products you may be familiar with: Siri, Alexa, Cortana, Google Home/Nest, etc.
Dictate IT Neural Net Stack
Dictate IT began developing its own Deep Neural Network-based speech recognition in 2014. We have always focused on UK medical report recognition. The state of the art is changing constantly, but we currently use two kinds of neural networks:
An acoustic model based on a factorised Time-Delay Neural Network (TDNN-F)
An AWD-LTSM language model (aka an ASGD Weight-dropped Long Short Term Memory model
This allows us to provide unmatched highly-accurate speech recognition for UK medical dictation, with no training period required, while covering a wide range of the accents found in the NHS. If you’ve not used medical speech recognition in the last few years, we think you will be impressed by the improvements in the field.
